The SAGE Encyclopedia of Pharmacology and Society

Encyclopedias

Edited by: Sarah E. Boslaugh

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      List of Entries

      Reader’s Guide

      About the Editor

      Sarah Boslaugh, Ph.D., M.P.H., has over 20 years’ experience in medical and public health research and in statistical education. She earned her bachelor’s degree from the University of Nebraska, her Ph.D. (in Measurement and Evaluation) from the City University of New York, and her M.P.H. from Saint Louis University.

      Dr. Boslaugh began her professional biostatistics career at Montefiore Medical Center in New York City, where she worked on a number of projects related to medicine and public health, including improving childhood immunization rates, documenting the efforts of poor families to obtain health insurance, and improving mental health care for people with acquired immunodeficiency syndrome. She also held research positions with the School of Public Health at Saint Louis University, where she worked primarily on investigations related to health communications and health care economics; the Washington University School of Medicine, where she collaborated on many research projects related to pediatric health; and BJC HealthCare, where she investigated numerous issues related to health care delivery, including reducing medical complications and improving patient satisfaction with hospital care. She also developed and taught (with Brian Waterman) a two-semester statistics course sequence for physicians and other medical researchers at Washington University School of Medicine, and she has designed and taught graduate statistics courses at the University of Missouri–Saint Louis and Program in Audiology and Communication Sciences at Washington University.

      Parallel to her work as a statistician, Dr. Boslaugh developed a career in book publishing, beginning with her first book, An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE, 2005). She has also published Secondary Data Sources for Public Health: A Practical Guide (Cambridge University Press, 2007), Statistics in a Nutshell (O’Reilly, 2008; 2nd ed. 2012), and Healthcare Systems Around the World: A Comparative Guide (SAGE, 2013). Dr. Boslaugh served as editor of Encyclopedia of Epidemiology (SAGE, 2008) and has written numerous chapters for professional reference books, including the chapter “Using Secondary Data” for Greg Guest and Emily E. Namey’s Public Health Research Methods (SAGE, 2014).

      Contributors

      Roberto Abadie University of Nebraska–Lincoln

      Charles Frederick Abel Stephen F. Austin State University

      Kristin J. Addison-Brown NEA Neuropsychology, PLLC

      Joyce Addo-Atuah Touro College of Pharmacy

      Syed Feroji Ahmed CSIR-Indian Institute of Chemical Biology

      Luz M. Alquicira Parks Youth Ranch/CrossCreek Counseling Center

      Laura A. Andersson Retired Independent Scholar

      Carlota O. Andrews California Health Sciences University

      Michael Atwood East Texas Baptist University

      Charles L. Bennett University of South Carolina

      Kimberly Bernosky-Smith D’Youville College

      Magdalena Bielenia-Grajewska University of Gdansk

      Rebecca Bishop Independent Scholar

      Thomas R. Blair University of California, Los Angeles

      Sarah E. Boslaugh Saint Louis University

      P. Qasimah Boston Florida Department of Children & Families

      Kristin Boza Independent Scholar

      Kyle Bridge University of Florida

      Anne Cagle Independent Scholar

      Daniel J. Calcagnetti Fairleigh Dickinson University

      Nancy D. Campbell Rensselaer Polytechnic Institute

      Dave Castelli Intermountain Medical Center

      Padmaja Chalasani Aneurin Bevan University Health Board

      Brian Chen Arnold School of Public Health

      Felix O. Chima Prairie View A&M University

      Maimoona Chinwala D’Youville College

      Jill M. Church D’Youville College

      Robert Clegg California Health Sciences University

      Shirley Clute Independent Researcher

      Bruce M. Z. Cohen University of Auckland

      Chris Cole Lindsey Wilson College

      Justin Corfield Independent Scholar

      James J. Costello Emporia State University

      Gordon A. Crews Tiffin University

      Rick Csiernik School of Social Work, King’s University College at Western University

      Patricia P. Dahl Washburn University

      Tazin Karim Daniels Michigan State University

      R. Casey Davis Independent Scholar

      Valerie Davis University of California, Los Angeles

      Rosalind DeLisser University of California, San Francisco

      Joseph Dewey Broward College

      Constance M. Dolecki Independent Scholar

      Christopher L. Edwards Duke University Medical Center

      Kathleen Egan University of North Carolina at Greensboro

      Colleen M. Ferguson California Polytechnic State University, San Luis Obispo

      Grace Ferguson Independent Scholar

      Kimberly Finney University of Southern California

      Michael Fox Independent Scholar

      Steven L. Foy University of Texas-Pan American

      Debra L. Frame University of Cincinnati

      Louis Hugo Francescutti University of Alberta

      Vibeke Asmussen Frank Aarhus University

      Ron Fritz Certified Alcohol Drug Counselor

      Erika Getzik MCPHS University

      Dashiel Geyen Texas Southern University

      Marc D. Glidden University of Arkansas at Little Rock

      David Michael Gonzalez University of Nevada

      Sara K. Green Marshall University

      Terje GrØnning University of Oslo

      Michael T. Halpern RTI International

      Halimah Hamidu University of Colorado Denver

      Jessica Anne Hammer Independent Scholar

      Christin J. Harrison University of Colorado Denver

      Francis Hawley Western Carolina University

      Steven Charles Hertler College of New Rochelle

      Darren Hill Leeds Beckett University

      LaBarron K. Hill Duke University Medical Center

      Dawn Hilliard Independent Scholar

      Esben Houborg Aarhus University, Center for Alcohol and Drug Research

      Andrew Hund United Arab Emirates University (previous)

      Zoë Hunter University of Ottawa

      Jason Jalil University of California, Los Angeles

      Kimberly Jinnett Integrated Benefits Institute

      Deborah Johnson University of California, San Francisco

      Glenda Jones Sam Houston State University

      Maureen L. Jones HospiScript, a Catamaran Company

      Douglas Jordan U.S. Army

      Judith J. Kammerer Saint Agnes Medical Center

      Angelos P. Kassianos University of Cambridge

      Thomas Katen Independent Scholar

      Alexandra Kjelstrom University of Colorado Denver

      Eileen Klein Ramapo College of New Jersey

      Karen Knaus University of Colorado Denver

      Kristine Koegler University of Colorado Denver

      Jennie Kronenfeld Arizona State University

      Matthew Kubal Independent Scholar

      Timothy Kubal California State University, Fresno

      Wen-Hua Kuo National Yang-Ming University

      Natalie Kupferberg Ohio State University

      Lindsay Labrecque Butler Hospital, Brown University

      Trisha LaPointe MCPHS University

      Daniel Lewandowski D’Youville College

      Samuel Lézé Ecole Normale Supérieure de Lyon

      Minghui Li University of South Carolina

      Therissa A. Libby Metropolitan State University

      Ivette A. Lopez Florida A&M University

      Héctor E. López-Sierra Inter American University of Puerto Rico

      Kim Lorber Ramapo College of New Jersey

      Z. Kevin Lu University of South Carolina

      Angela Matysiak Policy Studies Organization (PSO)

      Mandy M. McBroom Independent Scholar

      Trudy Mercadal Florida Atlantic University

      Laurie Michaels University of Toledo

      Shari Parsons Miller Independent Scholar

      Emily Milner University of Colorado Denver

      Michael Montagne MCPHS University

      Amanda Morrill MCPHS University

      Katie Moss Independent Scholar

      Mudit Mudit D’Youville College School of Pharmacy

      Sarah Elizabeth Murray William Paterson University

      Anna Neller University of Toledo

      Jessica Nickrand University of Minnesota

      Gerald E. Nissley Jr. East Texas Baptist University

      Sebastian Normandin Independent Scholar

      Lauren A. O’Brien Children’s Healthcare of Atlanta

      Michael Oldani University of Wisconsin–Whitewater

      Alyssa L. Pacheco University of Colorado Denver

      Kapil Pal Independent Scholar

      Mirtha Parada Instituto de Salud Pública de Chile

      Nicholas L. Parsons Eastern Connecticut State University

      Peter A. Pasek Clinical Pharmacist

      Shreya Patel Touro College of Pharmacy

      Payal Patel-Dovlatabadi University of Evansville

      Neil E. Paterson University of California, Los Angeles

      Willman Pearcey University of Colorado Denver

      Courtney Peasant Duke University Medical Center

      Helen Pervanas MCPHS University

      Greg A. Phelps Lindsey Wilson College

      Daniel W. Phillips III Lindsey Wilson College

      Maribel Plasencia Butler Hospital, Brown University

      Manoj Poonia Narsee Monjee Institute of Management Studies

      Chris Powers Lindsey Wilson College

      Bridget McCrate Protus HospiScript, a Catamaran Company

      Elizabeth Rholetter Purdy Independent Scholar

      Zaina Qureshi Arnold School of Public Health

      Pamela Ransom Metropolitan College of New York

      Garrett Rasnick University of Colorado Denver

      Beth Reboussin Wake Forest School of Medicine

      Vendula Rezacova Charles University

      Wylene Rholetter Auburn University

      Lucas Richert University of Saskatchewan

      Susan P. Robbins University of Houston

      Gina Robertiello Felician College

      Richard Lee Rogers Youngstown State University

      Rocio Roles University of Arkansas at Little Rock

      Ganesh V. Samant AstraZeneca Pharmaceuticals

      Pamela Rose V. Samonte McGill University

      Tim Sandle Pharmaceutical Microbiology Interest Group (Pharmig)

      Oliver Sartor Tulane University School of Medicine

      Mat Savelli University of Pittsburgh

      Lori Schmied Maryville College

      Ariane Schratter Maryville College

      John E. Senior Linacre College, University of Oxford

      Holly Sevier University of Hawai‘i at Manoa

      Mark D. Sherry University of Toledo

      Farid Sidi-Boumedine Ecole Normale Supérieure de Lyon

      Sarah J. Simmons University of Hawai‘i at Manoa

      Yolanda Smith University of South Australia MedicineHow Founder

      Renee Smith-Maddox University of Southern California

      Elizabeth A. Souza University of Hawai‘i at Manoa

      Joseph Spillane University of Florida

      Walter Stepanenko University of Toledo

      Chelsea Stockman Michigan State University

      Victor B. Stolberg Essex County College

      Angela Stone Schmidt Arkansas State University–Jonesboro

      Gregory L. Stuart University of Tennessee–Knoxville

      Maureen Sullivan Touro College of Pharmacy

      Maile Sunderman University of Colorado Denver

      Magdalena Szaflarski University of Alabama at Birmingham

      Paul Taylor University of Chester

      Jennifer Towle MCPHS University

      Emma Tseris University of Sydney

      Michael Uebel University of Texas at Austin

      Graham Ulmer Washington State University

      Rhea U. Vallente PreventionGenetics, LLC

      Rebecca Wagner HospiScript

      Michael F. Walker Arizona State University

      Allison M. Webb HospiScript Services, a Catamaran Company

      Adele Weiner Metropolitan College of New York

      Kristine C. Willett MCPHS University

      Shivaun Williams Writer

      Deborah Wittman Touro College of Pharmacy

      Susan J. Wurtzburg University of Hawai‘i at Manoa

      Scott Zimmer Independent Scholar

      Introduction

      Pharmaceutical products, also referred to as medicines or drugs, play a key role in medical care today. Pharmaceuticals have a long history in health care and are mentioned in some of the earliest-known records of medical practice. Manuscripts from Egypt and China describe the medicinal use of plants dating back to at least 3,000 , and herbal therapies were used in many indigenous cultures long before these practices were documented in written records. When chemistry became sufficiently advanced to allow the active ingredients of traditional herbal remedies to be extracted and studied, many of these herbal medicines formed the basis of well-known modern medicines such as aspirin (originally based on an extract from the willow tree) and digoxin (based on an extract from the digitalis or foxglove plant). Today, about one-quarter of modern pharmaceutical products are derived from botanical sources.

      The availability of modern pharmaceutical products has not entirely displaced the use of traditional medicines. According to the World Health Organization (WHO), about 80 percent of people globally use traditional medicines as part of their health care. In some cases, the traditional products represent the primary source of medicine available to people, while in other cases, traditional products are used alongside modern pharmaceuticals. Even in countries such as the United States, where modern pharmaceutical products are readily available, many consumers choose to supplement prescription drugs with traditional remedies such as gingko and echinacea. Partly in response to popular consumer interest in traditional medicines, the National Center for Complementary and Alternative Medicine was created in 1991 within the National Institutes of Health to conduct scientific research into the efficacy of complementary and alternative medicines.

      Pharmacology may be defined as the study of how chemical agents affect biological systems. The modern science of pharmacology can be traced back to Europe in the 19th century, where advances in scientific technology helped pioneers such as François Magendie and Claude Bernard in France established many of the basic principles and techniques used in pharmacology today. Rudolf Buchheim established the first institute of pharmacology at the University of Dorpat (now the University of Tartu) in Tartu, Estonia, in 1847, and his student Oswald Schmiedenberg, appointed professor of pharmacology at the University of Strasbourg in 1872, trained numerous students who went on to hold academic positions in pharmacology through the world. One of Schmiedenberg’s students, John Jacob Abel, founded the first department of pharmacology in the United States, at the University of Michigan in 1891.

      Today, pharmacology is taught at hundreds of universities and medical schools around the world. As a field of study, it incorporates knowledge from many scientific disciplines, including chemistry, physiology, biochemistry, and molecular and cell biology, and harnesses that information to produce products that can be used to improve human health. Research pharmacology has become a highly specialized profession, with many branches including behavioral pharmacology, biochemical pharmacology, clinical pharmacology, endocrine pharmacology, molecular neuropharmacology, and systems and integrated pharmacology.

      Pharmacology also plays a critical role in the worldwide pharmaceutical industry. According to the WHO, the global pharmaceuticals market amounts to about $300 billion annually, and this is expected to increase in years to come. The top 10 pharmaceutical companies, all of which are located in the United States or Europe, account for more than one-third of the global pharmaceutical market, with the single largest company, the U.S.-based Johnson & Johnson, reporting revenues of $71.3 billion in 2013. While the pharmaceutical industry has undeniably improved human health by the discovery and development of lifesaving drugs, it is also possible to argue that there is an inherent conflict between the desires of individual companies to maximize profit and the needs of human beings to have access to critical drugs.

      This conflict is highlighted by data from the WHO highlighting high profit margins (about 30 percent for the ten largest companies) for the top pharmaceutical companies, as well as the fact that as a group pharmaceutical companies spend about twice as much on marketing as they do on research and development. In addition, much of the money invested in pharmaceutical development is dedicated to producing drugs for diseases common in the developed world, such as cancer and heart disease, where governments or patients will be able to afford to purchase them. In contrast, drugs to treat diseases common primarily in developing countries may be neglected because of the lower profit potential in that market. Besides leaving large sectors of the global population without access to drugs that could save or substantially improve their lives, this practice often results in the creation of “me too” drugs that offer little improvement in the treatment of diseases common in developed countries compared to drugs already on the market, but which may be sold at much higher prices than established drugs proven effective in treating the same diseases.

      The cost of medicines is a particularly crucial issue in developing countries. In low- and middle-income countries, expenditures for medicines may account for over half of all health care spending; in contrast, expenditures for medicines account for only 18 percent of health care spending in the member nations of the Organisation for Economic Co-operation and Development (OECD). Despite this relatively high level of spending on medicines on average in low- and middle- income countries, however, access to lifesaving medicines cannot be assumed. Sometimes the drugs needed are simply not available, and sometimes they are not affordable for the patient, particularly in developing countries where up to 90 percent of the population may have to buy medicines entirely through out- of-pocket expenditures.

      To help address this problem, the WHO created the first WHO Model List of Essential Drugs in 1977. This list had three primary purposes: to reduce the use of expensive, nonessential medicines; to encourage placing the needs of the majority of a population, including the poor, as the highest priority when purchasing or otherwise obtaining medicines; and to provide information about rational drug procurement and help establish rational lists of drugs required at different levels within the national health care system.

      Drugs on the essential medicines list are selected based on the priority health needs of a population, and with consideration of information about comparative cost-effectiveness, efficacy, and safety. The 18th edition of the Essential Medicines List for Adults and the 4th edition of the Essential Medicines List for Children, both published in April 2013 and revised in October 2013, include drugs in 30 categories, from anesthetics to medicines for diseases of the joints. An individual country can choose which medicines from the list are most appropriate for its specific health needs; however, once designated as essential, medicines should be available at all times, in appropriate forms and in adequate quantity, within a functioning health system, and at a price that is affordable for the individual patient and the community. The essential medicines list may also be used to guide decision making in related areas, including public education, training of health care providers, procurement and distribution of drugs within the public sector, and international aid and drug donations.

      Access to pharmaceuticals within industrialized countries can also be problematic. This is particularly evident in the United States, which lacks a comprehensive national health system, so that even after implementation of the Affordable Care Act an estimated 13.4 percent of American adults remained uninsured as of June 2014. Even for people with insurance, their access to specific drugs may be limited by the rules of their particular insurance plan and by the cost of the drugs due to required copayments. Many insurance companies use formularies that designate different tiers of drugs whose cost is covered at different levels, so that a generic drug might be available for free or at a low cost, while a brand-name prescription drug might not be included at all within the plan or it may require a much higher copayment from the individual plan member. If the member cannot afford that copayment, the drug is essentially unavailable to him or her, even if it is theoretically available.

      Pharmaceutical spending can vary widely among industrialized countries, and the United States has repeatedly been found to spend much more on pharmaceuticals than comparable OECD countries such as the United Kingdom, Switzerland, and France. For instance, a 2013 study by the Commonwealth Fund found that pharmaceutical spending per capita in the United States was over twice as high as in the United Kingdom, and it was substantially higher than the other OECD countries studied. This higher spending was attributed in part to the more rapid uptake of new drugs in the United States, although whether the use of more expensive drugs resulted in improvements in health remains an unanswered question. Another reason often given for higher prescription drug spending in the United States is that the country lacks a national system to approve drugs and/or to set prices; in fact, Medicare, the federal insurance program covering persons over age 65 and the disabled, is specifically prohibited by law from negotiating prices with pharmaceutical manufacturers. One disadvantage of having a national system of approval, of course, is that some drugs may not be available in a given country, either because the drug was not approved by the national review board, or because the manufacturer declined to market it at the price level offered by that review board.

      As with any human invention, drugs can be abused. For instance, synthetic opioids such as oxycodone have provided many people with significant relief from chronic pain caused by cancer and other serious diseases. At the same time, prescription painkillers can be abused by persons who obtain them illegally, and this abuse can even lead to death. Similarly, drugs such as anabolic steroids and erythropoietin (EPO), which have legitimate medical uses, may be abused by individuals seeking to enhance their athletic performance. Pseudo ephedrine, a common ingredient in over- the-counter cold medications, has become regulated in many American states due to its use in creating methamphetamine, a drug of abuse. The inappropriate use of antibiotics, which have saved billions of lives, has led to the development of antibiotic-resistant strains of deadly diseases such as tuberculosis. Even drugs used to treat attention deficit hyperactivity disorder may be abused by individuals seeking an edge in studying or academic performance. Balancing the needs of medical patients with the potential for abuse inherent in many drugs is a challenge that must be confronted by every nation.

      Health care will continue to be an important concern for both individuals and nations in the years to come, and pharmacology will continue to play an important role in providing that care. At the same time, every society will have to confront issues related to pharmaceuticals, including cost, access, and the potential for abuse.

      10.4135/9781483349985.n6

      Chronology

      ca. 4000 :

      In ancient Sumeria, a class of skilled workers who prepare medicines, such as opium, myrrh, and mustard, is recognized as distinct from those who provide medical care.

      ca. 3400 :

      In Mesopotamia, the opium poppy is cultivated and its ability to induce euphoria is noted by contemporary writers.

      ca. 2000 :

      In China, Shen Nun writes the Pen T’sao, describing over 300 plant-based drugs.

      ca. 1500 :

      The Ebers Papyrus, from ancient Egypt, includes mention of hundreds of drugs and prescriptions, including ointments, pills, and infusions.

      ca. 460 :

      The Greek physician and medical writer Hippocrates writes about the usefulness of heroin as a narcotic and in controlling bleeding.

      ca. 330 :

      Opium is introduced to Persia and India by Alexander the Great.

      ca. 300 :

      The Greek philosopher Theophrastus describes the medicinal qualities of many herbs and instructs students in the identification and use of many medicinal plants.

      1st century :

      Pedanios Diosocorides travels with the Roman army and studies material media in use throughout the known world; his writings remain in use until the 16 th century.

      ca. 130–200:

      Life of the Roman physician Galen, who developed methods of creating medicinal substances by compounding similar to those used today; he also created a type of cold cream similar to the modern product.

      ca. 980–1037:

      Life of the Persian physician and philosopher Avicenna (Ibn Sina), whose writing on pharmaceutical topics remained in use through the 16th century.

      1240:

      At his palace in Palermo, Frederick II of Hohenstaufen, Emperor of Germany and King of Sicily, separates the duties of pharmacists from those of physicians.

      1498:

      The Nuovo Receptario is published in Florence, Italy, making it the first official pharmacopeia; it was created by the collaboration of the Guild of Apothecaries and the Medical Society.

      1557:

      Opium, which had fallen out of medical use in Europe for hundreds of years, is reintroduced by Paracelsus in the form of laudanum, pills used to kill pain.

      1600s:

      In England, the term apothecary is used to describe someone who worked with spices and had passed the exams of the Worshipful Society of Apothecaries; some of the spices handled by apothecaries had medicinal uses.

      1605:

      The French apothecary Louis Hebert visits North America for the first time, working at the New France settlement at Port Royal, Nova Scotia; he studies the use of native plants by the Micmac Indians, including Jack-in-the-pulpit, mullein, and golden seal.

      1680:

      Thomas Sydenham, an English apothecary, introduces the popular remedy Sydenham’s Laudanum, made of opium, herbs, and sherry.

      1721:

      Variolation, a technique for protecting healthy individuals against smallpox by introducing scab material from smallpox patients under the skin of the healthy individuals, is introduced to England.

      1729:

      In China, the emperor Yung Cheng prohibits the sale and smoking of opium except for licensed medicinal purposes; in 1799, emperor Kia King bans the cultivation and trade of opium entirely.

      1729:

      In the United States, the Irish immigrant Christopher Marshall opens an apothecary shop in Philadelphia; he later expands to offer training for pharmacists and chemical manufacturing.

      1752:

      In the United States, the first hospital pharmacy opens in Philadelphia, staffed by the pharmacist Jonathan Roberts.

      1769:

      China imports 2,000 chests of opium annually from the British East India Company.

      1796:

      Samuel Lee, Jr., receives the first American patent for a pill, for Lee’s Windham Pills.

      1803:

      Morphine, the active ingredient in opium, is discovered by the German scientist Friedrich Sertuerner; the new substance is called principium somniferum.

      1813:

      In the United States, passage of the Vaccine Act of 1813 marks the first federal legislation to provide consumer protection regarding therapeutic substances.

      1820:

      The French chemists Joseph Biename Caventou and Pierre Joseph Pelletier become the first to extract quinine from cinchona tree bark.

      1821:

      The English essayist Thomas De Quincey publishes “Confessions of an English Opium-eater” based on his own experiences with the drug.

      1821:

      The first school of pharmacy, the Philadelphia College of Pharmacy and Science, is founded in the United States.

      1830:

      In England, 22,000 pounds of opium are imported annually from Turkey and India, for recreational and medicinal purposes.

      1834:

      The first known use of the term pharmacist in print occurs in the novel The Last Days of Pompeii by British author Edward Bulwer-Lytton.

      1839:

      On March 18, the First Opium War begins, following the demand of Chinese commissioner Lin Tse-Hsu that all foreign traders give up their opium; in response, the British send warships to the Chinese coast. Following their victory in 1841, the British win control of Hong Kong and also collect an indemnity from the Chinese.

      1841:

      The Pharmaceutical Society of Great Britain is founded.

      1843:

      The first known use of injectable morphine is pioneered by Scottish physician Alexander Wood, who uses a syringe to administer morphine to a patient and finds its effects are more potent and immediate than is true of other methods of administration.

      1846:

      In the Second Opium War, the British and Chinese resume hostilities over the importation of this drug. China is defeated and legalizes the importation of opium while also being forced to pay an indemnity to Britain.

      1852:

      The American Pharmaceutical Association was founded in October; the first president was Daniel B. Smith.

      1862:

      In the United States, the agency that becomes the Food and Drug Administration is founded as the Division of Chemistry within the Department of Agriculture. It is renamed the Bureau of Chemistry in 1901; the Food, Drug, and Insecticide Administration in 1927; and the Food and Drug Administration in 1930.

      1871:

      The University of Michigan begins offering a course in pharmacy that introduces major changes in pharmacy education, including a curriculum that comprises basic sciences, with the expectation of full-time study, and drops the requirement of a pregraduation apprenticeship.

      1874:

      Heroin is synthesized by the English chemist Charles Romley Alder Wright, working at St. Mary’s Hospital Medical School in London; Wright achieves this result by boiling morphine.

      1875:

      The Philadelphia pharmacist Charles E. Hires creates the first soft drink, flavored by herbs, to become popular nationally: Hires Root Beer.

      1876:

      In the United States, Lydia Estes Pinkham begins selling a patent medicine, Lydia E. Pinkham’s Vegetable Compound, by mail order; it is the first patent medicine to become popular nationally, possibly due to the fact that it contains 19 percent alcohol.

      1879:

      The French scientist Louis Pasteur produces a vaccine against chicken cholera that is the first vaccine to use attenuated bacteria.

      1884:

      Henry Hurd Rusby visits Peru on behalf of Park, Davis and Company in order to obtain coca leaves; he also collects over 40,000 botanical specimens, many of which prove to be useful sources of drugs.

      1885:

      The French scientist Louis Pasteur demonstrates the world’s first rabies vaccine in humans; prior to this time, infection with rabies was invariably fatal. The rabies vaccine is first licensed in the United States in 1914.

      1886:

      The Atlanta pharmacist John Pemberton invents Coca-Cola, a sweetened, carbonated drink that became a dominant player in the global soft drink market; the name was chosen by Pemberton’s bookkeeper Frank Robinson and refers to the fact that the original recipe for the syrup used to make the beverage included coca leaf and kiola nut.

      1890:

      In the first federal legislation on narcotics, the U.S. Congress imposes a tax on morphine and opium.

      1894:

      Diphtheria antitoxin, a lifesaving compound, is developed by Behring and Roux and becomes commercially available in 1895. The antitoxin is among the first biologicals; its production begins by injecting horses with diphtheria toxin.

      1895:

      Heroin (diacetylmorphine) is first produced by the German chemist Heinrich Dreser, working for the Bayer Company; however, the drug is not sold commercially until 1898.

      1897:

      John Jacob Abel and A. C. Crawford isolate and purify epinephrine, the active substance from the adrenal medulla.

      1897:

      Alexandre Yersin, working at the Pasteur Institute, develops the first serum effective against the bubonic plague; he had previously discovered the pathogen that causes plague.

      1901:

      In the United States, numerous children die from contaminated diphtheria antitoxin and smallpox vaccine; public outcry leads to passage the following year of the Biologics Control Act of 1902, which provides government oversight of vaccine and antitoxin producers. Many companies go out of business shortly afterwards because they are unable to meet the new standard.

      1902:

      The feasibility of using heroin to treat morphine addiction is discussed in professional medical journals; while some see heroin as a way to reduce withdrawal symptoms from morphine, others argue that the process of withdrawing from heroin is equally difficult.

      1906:

      The Pure Food and Drug Act, also known as the Wiley Act, is passed by the U.S. Congress and requires that patent medicines include a list of ingredients; this law sharply reduces consumption of opiates in the United States.

      1909:

      Importation of opium is barred by federal law in the United States; in February of the same year, at the Shanghai Conference, the United States advocates for suppressing opiate sales to China.

      1910:

      The German physician Paul Ehrlich and the Japanese bacteriologist Sahachiro Hata discover arsphenamine, also known as Salvarsan or compound 606, which is the first effective drug to be used against syphilis.

      1911:

      The Opium and Drug Act includes the first schedule of prohibited drugs in Canada, which includes opium and cocaine, and criminalizes the possession and use of opiates and cocaine derivatives unless prescribed for medicinal purposes by a physician.

      1914:

      In December, the Harrison Narcotics Act requires physicians and pharmacists to register and pay a tax before they are allowed to prescribe narcotics.

      1914:

      Edward Calvin Kendall isolated thyroxine, a compound produced naturally in the human body; it is used to treat goiter.

      1915:

      A vaccine against pertussis (whooping cough) is licensed in the United States; it uses inactivated Bordetella pertussis cells.

      1917:

      In England, the concept of prescription- only medicines is introduced with the Venereal Disease Act, which prohibits advertising drugs used to treat venereal disease.

      1922:

      In Toronto, insulin is first used to treat diabetes; the patient suffered an allergic reaction from the first injection, but later injections used a purer form of insulin and resulted in the patient’s recovery. In 1923, Frederick Grant Banting and John James Rickard Macleod are awarded the Nobel Prize in Physiology or Medicine for their work in the discovery of insulin.

      1923:

      In the United States, all narcotics sales are banned by the Narcotics Division of the Treasury; one unintended effect is greatly increasing the size of the black market for narcotic drugs.

      1926:

      The Gesellschaft fur Geschichte der Pharmazie or Society for the History of Pharmacy is founded in 1926 in Austria; it holds its first international meeting in Berlin three years later.

      1928:

      In the United States, colleges of pharmacy establish a four-year degree as a minimum for graduation.

      1929:

      The Scottish biologist Alexander Fleming publishes an article describing his discovery of penicillin in the Journal of Experimental Pathology, but it draws little attention.

      1937:

      An American drug company markets Elixir Sulfanilamide, a sulfa drug for pediatric patients; it contains an analogue of antifreeze and results in the death of over 100 people. Public outcry over this incident leads in part to passage of the Federal Food, Drug, and Cosmetic Act the following year.

      1938:

      In the United States, the Durham- Humphrey Amendment to the Federal Food, Drug and Cosmetic Act of 1938 imposes restrictions on the dispensing of many medicines, which now require a physician’s prescription.

      1938:

      The National Foundation for Infantile Paralysis, later known as the March of Dimes, is founded by U.S. President Franklin Delano Roosevelt, who had polio (a well-known fact, although the extent of his disability was concealed from the public).

      1939:

      In England, the adulteration and mislabeling of drugs is prohibited by the Food and Drugs Act.

      1940s:

      Mass production methods are developed to rapidly create a supply of penicillin for the war effort, reducing the cost per dose to a fraction of the original production costs.

      1941:

      In England, the Pharmacy and Medicines Act requires drug manufacturers to list the active ingredients of their products on the label, and forbids advertising of drugs purporting to treat some diseases, including tuberculosis.

      1943:

      Streptomycin is discovered by Selman Abraham Waksman and colleagues, and provides the first antibiotic treatment effective against tuberculosis. Waksman is awarded the Nobel Prize in Physiology or Medicine in 1952 for this discovery.

      1943:

      The Swiss pharmacologist Albert Hoffman discovers lysergic acid diethylamide (LSD).

      1944:

      Robert Burns Woodward and William von Eggers Doering, working at Harvard University, succeed in producing synthetic quinine in the laboratory.

      1945:

      Sir Alexander Fleming, Sir Ernst Boris Chain, and Howard Walter Florey are jointly awarded the Nobel Prize in Physiology or Medicine for their work on penicillin.

      1945:

      The World Health Organization (WHO) is created by the United Nations to be an autonomous international health organization; the WHO constitution is approved the following year, and comes into force in 1948.

      1946:

      The American Council on Education administers the first Pharmaceutical Survey, which collects information on the profession and recommends that a standard curriculum resulting in the degree Doctor of Pharmacy after six years of study would increase the profession’s standing in the public mind.

      1947:

      In the United States, the first pediatric vaccines offering combined protection against diphtheria and tetanus become available. Two years later, the DPT vaccine, offering protection against diphtheria, tetanus, and pertussis, is introduced.

      1952:

      In the United States, the Code of Ethics of the American Pharmaceutical Association states that pharmacists should not discuss the therapeutic effects of a prescription with customers, but should refer them back to their physician or dentist.

      1954:

      Three American scientists, Frederick Chapman Robbins, Thomas Huckle Weller, and John Franklin Enders, are jointly awarded the Nobel Prize in Physiology or Medicine for their demonstration that the polio virus could be grown in tissue; this discovery plays a key role in the development of the polio vaccine.

      1954-1960:

      A series of federal laws give the U.S. Food and Drug Administration (FDA) stronger control of chemicals used in food, including pesticides in 1954, additives in 1954, and colorings in 1960; the most far-reaching, the Delaney Clause (1958), prohibits the use of any additive with carcinogenic properties.

      1955:

      The first polio vaccine, using an inactivated virus, is licensed in the United States; it is called the Salk vaccine due to the key role played by Dr. Jonas Salk in developing it.

      1958:

      Iproniazid phosphate, a drug originally developed to treat tuberculosis, is approved in the United States to treat depression when it is discovered that TB patients treated with it experience elevated moods.

      1960:

      In the United States, a five-year B.S. degree becomes the standard qualification issued by schools of pharmacy.

      1961:

      Oral polio vaccines types 1 and 2, known as the Sabin vaccine after Dr. Albert Sabin, are licensed in the United States; oral polio vaccine type 3, and a vaccine effective against all three types, is introduced the following year. Sabin donates the rights to the vaccine in 1972 to the World Health Organization.

      1961:

      The nonsteroidal anti-inflammatory drug ibuprofen is synthesized in Great Britain, by chemists at Boots Pure Drug Company.

      1964:

      In the United States, Don Francke publishes Mirror to Hospital Pharmacy, a survey of hospital pharmacy that furthers the movement to develop clinical pharmacy and to separate pharmacy practice from the sale of other items typical of a drug store.

      1966:

      In Canada, the Medical Insurance Act allows provinces to establish compulsory, publicly funded health care programs, with costs shared between the federal and provincial governments.

      1966:

      The Centers for Disease Control and Prevention (CDC) in the United States begins a national measles eradication campaign; the effects are immediate, with a reduction of over 90 percent in cases within two years. By 2000, measles is no longer endemic in the United States.

      1967:

      The World Health Organization launches a global campaign to eradicate smallpox. By 1971, routine smallpox vaccination is no longer recommended in the United States because the risk of the disease is so low, and on May 8, 1980, the World Health Assembly declares that smallpox has been eradicated globally.

      1970:

      The death of popular singer Janis Joplin is attributed to an accidental heroin overdose, drawing public attention to the dangers of the drug.

      1971:

      The MMR vaccine, offering combined protection against measles, mumps, and rubella (German measles), is introduced by Merck.

      1973:

      On July 1, U.S. President Richard Nixon creates the Drug Enforcement Administration within the Justice Department, and gives most of the federal ability to enforce drug laws to the new agency.

      1974:

      The World Health Organization begins an Expanded Programme on Immunization, focusing on expanding immunization in developing countries; vaccines covered by the program include polio, measles, yellow fever (if relevant), hepatitis B, Bacillus Calmette- Guérin (BCG), DTP, and MMR.

      1977:

      The World Health Organization publishes the first essential medicines list as a guide to the medicines considered necessary to high-priority diseases such as malaria, tuberculosis, cancer, and diabetes; the original list included 208 drugs, which had expanded to more than 250 by 2013.

      1978:

      Human insulin is produced using recombinant DNA by researchers from Genentech and the Hope Medical Center in California; however, insulin produced by this method was not approved by the Food and Drug Administration until 1982.

      1978:

      Mexican poppy fields are sprayed with the defoliant Agent Orange, previously used in Vietnam, as part of an effort by the United States to reduce the heroin supply within its own borders. One result is that more heroin begins to be brought to the United States from the Golden Crescent area of Afghanistan, Iran, and Pakistan.

      1981:

      TransdermScop, a transdermal patch, is approved by the Food and Drug Administration to treat motion sickness; it delivers scopolamine through the skin.

      1983:

      In the United States, the Orphan Drug Act passes, providing financial incentives for pharmaceutical companies to develop medicines to treat orphan diseases (those affecting fewer than 200,000 people).

      1984:

      Officials from the U.S. State Department conclude that programs encouraging farmers in developing countries to grow crops other than coca, poppies, and marijuana will not produce significant benefits unless accompanied by eradication and law enforcement programs.

      1986:

      In the United States, the National Childhood Vaccine Injury Act of 1986 creates the Vaccine Adverse Event Reporting System, which collects reports of suspected adverse events related to vaccines licensed for use in the United States. The same act requires health providers to report adverse reactions to measles, mumps, rubella, polio, pertussis, diphtheria, and tetanus vaccines.

      1988:

      The World Health Organization establishes the Global Polio Eradication Initiative in collaboration with the United Nations Children’s Fund (UNICEF), the CDC, and Rotary International.

      1988:

      Prozac (fluoxetine hydrochloride) becomes available in the United States. The drug is a selective serotonin reuptake inhibitor (SSRI), and it is used to treat depression and anxiety.

      1988:

      The Nobel Prize in Physiology or Medicine is awarded jointly to Sir James W. Black, Gertrude B. Elion, and George H. Hitchings for their discoveries of principles in drug treatment. Black developed propranolol, the first clinically useful drug to block beta receptors, and cimetidine, the first clinically useful H2-receptor antagonist. Elion and Hitchings found differences between normal cells, cancer cells, viruses, bacteria, and protozoa, which led to the development of several new classes of drugs.

      1992:

      In the United States, the Prescription Drug User Fees Act allows pharmaceutical companies to receive faster review from the FDA for their products, in return for paying a fee.

      1993:

      The American actor River Phoenix dies of an overdose after taking a “speedball” or combination of heroin and cocaine; the same combination of drugs killed comedian John Belushi in 1982.

      1995:

      Directly observed therapy (DOT), also known as directly observed treatment, is developed as a way to treat tuberculosis and fight the development of drug-resistant strains of TB. In DOT, a patient takes his or her medicine under the observation of a medical worker, a method that increases compliance and staying on a drug regimen through to its conclusion.

      1997:

      In the United States, the FDA removes some requirements on direct-to-consumer advertising of prescription drugs, including that of including information about risks of the drugs advertised within the ad itself; instead, ads are allowed to direct consumers to other sources of information about drug risks.

      1998:

      The first human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) vaccine enters a phase III trial in the United States, Canada, and the Netherlands.

      1998:

      The World Health Organization creates the Children’s Vaccine Plan with funding from the Bill & Melinda Gates Foundation, with the goal of providing vaccines to children in developing countries and conducting research leading to the development of new vaccines.

      1998:

      Viagra (sildenafil citrate), developed by Pfizer, is approved by the Food and Drug Administration (U.S.) for the treatment of erectile dysfunction, and quickly becomes one of the most prescribed drugs in the world.

      1999:

      In the United States, the National Institutes of Health creates the Dale and Betty Bumpers Vaccine Research Center to conduct research in vaccine development, with particular focus on developing a vaccine for HIV/ AIDS.

      2000:

      The World Health Organization hosts the Stop TB Partnership with over 500 global partners. The purpose of the partnership is to increase availability to DOT (also known as directly observed treatment) programs worldwide and address new challenges such as drug-resistant TB.

      2002:

      In the United States, President George Bush announces a campaign to resume smallpox vaccination due to the potential of the disease being used in bioterrorism; however, few responded to the program, which initially targeted health care workers.

      2002:

      The World Health Organization creates the Global Fund to Fight AIDS, tuberculosis, and malaria to fight three diseases that still devastate populations in the developing world.

      2002:

      In the United States, the Best Pharmaceuticals for Children Act extends patent protection for six months in return for pharmaceutical manufacturers conducting trials of the effectiveness of drugs in pediatric populations.

      2003:

      FluMist, the first nasally administered flu vaccine, is licensed for use in the United States for healthy individuals aged five through 49 years, and for those who are not pregnant.

      2003:

      In the United States, the Project Bioshield Act of 2003 authorizes expenditures of over $5 billion to develop countermeasures, including drugs and vaccines, against threats from chemical biological, nuclear, and radiological weapons, and authorizes the Secretary of Health and Human Services to allow the use of drugs and vaccines not approved by the FDA in case of a public health emergency such as a bioterrorism attack.

      2004:

      According to a study by the Pew Institute, 26 percent of American adults have searched online for information about prescription drugs, but only 28 percent believe that purchasing drugs online is as safe as purchasing them at a local pharmacy, and only 4 percent have actually purchased drugs over the Internet.

      2005:

      The World Health Organization issues a policy statement indicating that specific measures are necessary to ensure that HIV-positive girls and women have equitable access to antiretroviral treatment. Among the barriers cited by the policy statement that hamper girls’ and women’s access to antiretrovirals, as compared to men, are lack of information about available treatments and transportation difficulties and child care responsibilities.

      2006:

      Gardasil, a vaccine developed by Merck to prevent cervical cancer and other conditions, including genital warts, caused by human papillomavirus, is licensed by the U.S. Food and Drug Administration.

      2007:

      The World Health Organization publishes the first WHO Model List of Essential Medicines for Children.

      2007:

      The Centers for Disease Control and Prevention reports that the United States is free of canine rabies, thanks to vaccination, licensing, and stray dog control programs; however, rabies remains a threat globally, with about 55,000 people each year dying from the disease.

      2009:

      According to a study by the Pew Research Center, 35 percent of Internet users, and 26 percent of all adults, in the United States look online to find information about alternative medicines and treatments. Women (31 percent) were more likely than men (31 percent) to seek this type of information online, and young and middle-aged adults were more likely than older adults to seek this information online (34 percent of those aged 18 to 29, 38 percent of those aged 30 to 49, 36 percent of those aged 50 to 64, and 19 percent of those aged 65 or older reported seeking information about alternative medicine and treatments online).

      2010:

      According to the World Health Organization, in countries with transitional economies, pharmaceuticals account for 15 to 30 percent of health spending; in developing countries, they account for 25 to 66 percent of health spending.

      2011:

      In the United States, the Institute of Medicine issues “Review of Adverse Effects of Vaccines,” concluding that few if any health problems can be attributed to or associated with vaccination.

      2011:

      A study by the Pew Internet Project and the California HealthCare Foundation shows that two-thirds of American Internet users have searched online for information about a specific medical problem and 56 percent have searched for information about procedures or treatment. The 10 most commonly researched treatments included eight types of drugs: pain relievers, antidepressants, medication for high blood pressure, corticosteroids, medication for diabetes, medication for attention deficit hyperactivity disorder (ADHD), antibiotics, and medication to lower cholesterol.

      2011:

      According to the Centers of Disease Control and Prevention about 11 percent of children aged 4 to 17 have been diagnosed with ADHD, with wide variation by state and substantial increase over the years, from 7.8 percent in 2003 to 9.5 percent in 2007 and to 11.0 percent in 2011.

      2012:

      According to the Centers for Disease Control and Prevention, 1 in 88 American children has been diagnosed with an autism spectrum disorder, with wide variation by location, and boys more likely than girls to have a diagnosis.

      2012:

      The World Health Organization reports that about 50 million people worldwide have epilepsy, with 80 percent living in developing countries. The report also specifies that about three-quarters of those with epilepsy in developing countries are not receiving appropriate treatment, despite the fact that in about 70 percent of cases, antiepileptic drugs are successful in controlling seizures.

      2012:

      According to a report from the Centers for Disease Control and Prevention, over half (60 percent) of Americans between the age of 13 and 24 who are infected with HIV are not aware of their status.

      2012:

      Average expenditures on pharmaceuticals in Organisation for Economic Co-operation and Development (OECD) countries in 2012 came to 1.4 percent of gross domestic product, with average per capita spending on pharmaceuticals coming to $414. The OECD includes 34 countries, including most of the world’s leading economic powers.

      2013:

      The World Health Organization and UNICEF condemn attacks on polio vaccination programs in Nigeria; the fact that childhood polio vaccinations are not universal in some areas is blamed for recent outbreaks of the disease.

      2013:

      According to a fact sheet released by the World Health Organization in May, about 222 million women in developing countries are not using contraception but would like to have access to it.

      2013:

      According to the World Health Organization, 1.5 million people died from TB in 2013, and 9 million fell ill with the disease, making TB second only to HIV/ AIDS as the greatest global killer from a single infectious agent. Also in 2013, an estimated 480,000 people worldwide developed multidrug-resistant TB.

      2013:

      The World Health Organization publishes the 18th edition of the Model List of Essential Medicines, and the 4th edition of the Model List of Essential Medicines for Children.

      2014:

      According to the World Health Organization’s Global Report on Antimicrobial Resistance, very high rates of antimicrobial resistance have been observed in multiple WHO regions for many bacteria that cause common diseases such as pneumonia, otitis, diarrhea, and urinary tract infections.

      2014:

      In January, a study by Christian Bachmann and colleagues of the use of antipsychotic drugs in Germany from 2005 to 2012 reveals that use of these drugs rose substantially for children and adolescents over the period studied, although they remained below the levels seen in the United States. Overall, the percentage of children and adolescents receiving a prescription for an antipsychotic drug within the year rose from 0.23 percent to 0.32 percent over the period studied, with the greatest increases seen in older children: a rise of 0.24 percent to 0.32 percent for the 10 to 14 age group, and from 0.34 percent to 0.54 percent for the 15 to 19 age group.

      2014:

      In March, the British medical publication BMJ publishes an article by researchers from the University of Warwick showing that anxiolytic and hypnotic drugs, used to treat anxiety and difficulties in sleeping, respectively, are associated with an increased risk of death and suggests that greater care be used when prescribing these types of drugs.

      2014:

      A study published in March by researchers from the University of Bristol in England reveals that cancer patients in England are far more likely to be prescribed expensive drugs than are comparable patients in Wales.

      2014:

      In March, a study by Health Canada, published in the Canadian Medical Association Journal, reveals that delays in the availability of new drugs in Canada is due to later submission for approval by pharmaceutical companies, compared to when the drugs were submitted for approval in the United States.

      2014:

      In April, a study by the Pew Research Center reveals that two-thirds of Americans believe the government should focus more on providing treatment for individuals who use illegal drugs, while just over one-quarter (26 percent) believe the government should focus on prosecuting such individuals.

      2014:

      In September, Richard Whitley and colleagues report that an experimental drug, peramivir, was effective in treating influenza. Peramivir, an injectable drug, works by inhibiting the viral protein neuraminidase and would be particularly useful in treating patients who could not take currently existing drugs in pill forms, and in halting the spread of flu during a pandemic. Peramivir is already approved for use in South Korea and Japan.

      2014:

      In November, a study reported by Roy Herbst of the Yale Cancer Center describes success in treating cancer with a drug, MPDL380A, which helps the immune system detect and fight cancer cells.

      2014:

      In December, the Review on Antimicrobial Resistance estimates that if current approaches to developing antibiotics do not change, 300 million people will die prematurely by 2050, and the global economy will lose $100 trillion, due to antimicrobial resistance.

      2015:

      According to a report issued in March 2015 by the World Health Organization, an estimated 6 million to 7 million people worldwide are infected with Chagas disease. This disease is most common in Latin America and is almost 100 percent curable if treated soon after infection by the drugs benznidazole or nifurtimox, but the efficacy of both drugs diminishes if treatment is delayed.

      2015:

      In February, a team of researchers led by Karl Claxton at the University of York found that when the UK National Health Service spends money on expensive but marginally effective medicines, overall health care suffers. Claxton’s research also stated that the Cancer Drugs fund, which has a budget of GBP 340 million (about $536 million), harms about five times as many people as it helps, by diverting money into expensive cancer-fighting drugs and away from other types of therapy and treatments for other diseases.

      2015:

      In March, a report by the UK All Party Parliamentary Group on Global Tuberculosis estimates that multidrug-resistant TB will kill 75 million people over the next 35 years and cost the global economy the equivalent of $16.7 trillion.

      2015:

      In April, a study indicates that cannabidiol, an extract from cannabis (marijuana), can help prevent seizures in patients with epilepsy. The study, reported by Orrin Devinsky of New York University, involved 137 epilepsy patients with a median age of 11 and whose seizures resisted other treatments. After 12 weeks of treatment with liquid cannabidiol, the numbers of seizures in the patients were cut by about 50 percent.

      2015:

      In June, the FDA approves Flibanserin, a drug manufactured by Sprout Pharmaceuticals, which is intended to boost female sex drive but can also have side effects, including fatigue, fainting, and low blood pressure. The FDA had previously rejected the drug, and the approval carries the condition that the manufacturer develop a plan to limit the risks of the drug.

    • Glossary

      Abstinence:

      In the context of substance abuse and treatment, nonuse of alcohol or any illicit drugs, as well as nonabuse of medications normally obtained by prescription or over the counter.

      Addiction:

      Combination of the physical dependence on, behavioral manifestations of the use of, and subjective sense of need and craving for a psychoactive substance, leading to compulsive use of the substance either for its positive effects or to avoid negative effects associated with abstinence from that substance.

      ADME:

      Abbreviation for the four steps in a medicine’s journey through the body: absorption, distribution, metabolism, and excretion.

      Adverse Drug Reaction (ADR):

      In the preapproval clinical experience with a new medicinal product or its new usages, particularly as the therapeutic dose(s) may not be established, all noxious and unintended responses to a medicinal product related to any dose should be considered adverse drug reactions. The phrase “responses to a medicinal product” means that a causal relationship between a medicinal product and an adverse event is at least a reasonable possibility, that is, the relationship cannot be ruled out.

      Adverse Event (AE):

      Any untoward or unfavorable medical occurrence in a human subject, including any abnormal sign (for example, abnormal physical exam or laboratory finding), symptom, or disease, temporally associated with the subject’s participation in the research, whether or not considered related to the subject’s participation in the research.

      Agonist:

      A molecule that triggers a cellular response by interacting with a receptor.

      Analgesic:

      A compound that alleviates pain without causing loss of consciousness. Opioid analgesics are a class of compounds that bind to specific receptors in the central nervous system to block the perception of pain or affect the emotional response to pain. Such compounds include opium and its derivatives, as well as a number of synthetic compounds.

      Antibiotic:

      A substance that can kill or inhibit the growth of certain microorganisms.

      Antibody:

      A protein of the immune system, produced in response to an antigen (a foreign, often disease-causing, substance).

      Anti-Inflammatory:

      A drug’s ability to reduce inflammation, which can cause soreness and swelling.

      Antipyretic:

      Fever-reducing; the term comes from the Greek word pyresis, which means fire.

      Audit:

      Independent on-site quality assurance of monitoring performed at clinical research sites (including pharmacies and laboratories). Auditors must be fully distinct and independent from entities providing site monitoring services.

      Benzodiazepines:

      Group of medications having a common molecular structure and similar pharmacological activity, including antianxiety, sedative, hypnotic, amnestic, anticonvulsant, and muscle-relaxing effects. Benzodiazepines are among the most widely prescribed medications (e.g., diazepam, chlordiazepoxide, clonazepam, alprazolam, lorazepam).

      Best-Treatment Practices:

      Methods determined, often by a consensus of experts, to be optimal for defined therapeutic situations. Such guidelines usually are based on both an analysis of published research findings and the experience of experts.

      Bioavailability:

      The ability of a drug or other chemical to be taken up by the body and made available in the tissue where it is needed.

      Bioinformatics:

      A field of research that relies on computers to store and analyze large amounts of biological data.

      Biological Product:

      Any virus, therapeutic serum, toxin, antitoxin, or analogous product available to prevent, treat, or cure diseases or injuries in man. The terms biological product or biologic are deemed to be synonymous within DAIDS policies.

      Biotransformation:

      The conversion of a substance from one form to another by the actions of organisms or enzymes.

      Blinding:

      See Masking.

      Blood–Brain Barrier:

      A blockade consisting of cells and small blood vessels that limits the movement of substances from the bloodstream into the brain.

      Carcinogen:

      Any substance that, when exposed to living tissue, may cause cancer.

      Case History:

      A detailed account of relevant information gathered about a subject. This information includes the case report forms and supporting data including, for example, signed and dated consent forms and medical records, including, for example, progress notes of the physician, the individual’s hospital chart(s), and the nurses’ notes, as required for both IND and IDE clinical trials.

      Causality Assessment:

      An evaluation performed by a medical professional concerning the likelihood that a therapy or product under study caused or contributed to an adverse event.

      Clinical Development Plan:

      A document that describes the collection of clinical studies that are to be performed in sequence, or in parallel, with a particular active substance, device, procedure, or treatment strategy, typically with the intention of submitting them as part of an application for a marketing authorization. The plan should have appropriate decision points and allow modification as knowledge accumulates.

      Clinical Investigation:

      Any experiment that involves a test article and one or more human subjects, and that either must meet the requirements for prior submission to the U.S. Food and Drug Administration (FDA), or the results of which are intended to be later submitted to, or held for inspection by, the FDA as part of an application for a research or marketing permit. FDA has defined clinical investigation to be synonymous with research.

      Clinical Investigator:

      A qualified professional who conducts clinical research activities, including collaboration and information exchange with community representatives, recruitment, enrollment, protocol visit conduct, management of study products, assessment and reporting of critical events, collection and management of clinical research data, communication of data, and creation, maintenance, and storage of research records, including participant files, source documents, regulatory files, subject identification information, clinical reports, and case report forms.

      Clinical Research:

      Research conducted on participants, material, or data of human origin with an identifiable person as the source. Clinical research includes exploratory, behavioral, and observational studies. All clinical trials are a subset of clinical research.

      Clinical Research Records:

      The records that describe or record the methods, conduct, and/or results of a clinical trial, and the actions taken. Examples of these documents may include, but are not limited to, all essential and source documents listed in the DAIDS Policy on Essential Documents Appendix. The records may be in any form, including written, electronic, magnetic, and optical records; and scans, X-rays, and electrocardiograms. Clinical research records include case histories and source documents.

      Clinical Significance:

      Change in a subject’s clinical condition regarded as important whether or not due to the test intervention. Some statistically significant changes (in blood tests, for example) have no clinical significance. In research, the criterion or criteria for clinical significance should be stated in the protocol.

      Clinical Trial:

      A prospective study of human subjects designed to answer questions about biomedical or behavioral interventions, for example, drugs, treatments, devices, or new ways of using known treatments to determine whether they are safe and effective.

      Closed Formulary:

      Closed formularies are exclusive lists of specific drugs that often limit prescribers to only some of the commercially available products in each therapeutic class. Drugs that do not appear on the list of approved products (nonformulary drugs) are not covered by the health plan, PBM, or employer, and patients must pay additional out-of-pocket expenses to obtain nonformulary prescriptions (or use a prior approval or nonformulary exceptions process).

      Community Advisory Board (CAB):

      Community Advisory Board (CAB) is an active group representing the local population(s) impacted by human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). CAB members work in close communication with clinical treatment unit investigators and staff to include the local perspective in the implementation of a clinical research plan.

      Conflict of Interest (COI):

      A situation when someone has or is perceived to have competing professional obligations or personal or financial interests that would make it difficult to fulfill his duties fairly.

      Control:

      The comparator against which the study treatment is evaluated (e.g., concurrent [placebo, no treatment, dose-response, active], and external [historical, published literature]).

      Critical Event:

      Any unanticipated, study-related incident that causes or increases the risk of harm to participants or others, or has a significant adverse impact on study outcomes or integrity. A single incident that is determined to be a critical event may represent more than one class of critical event.

      Cross-Tolerance:

      Condition in which repeated administration of a drug results in diminished effects, not only for that drug but also for one or more drugs from a similar class to which the individual has not been exposed recently.

      Cyclooxygenase:

      An enzyme, also known as COX, that makes prostaglandins from a molecule called arachidonic acid; the molecular target of nonsteroidal anti-inflammatory drugs.

      Data Integrity:

      A dimension of data contributing to its trustworthiness and pertaining to the systems and processes for data capture, correction, maintenance, transmission, and retention. Key elements of data integrity include security, privacy, access controls, a continuous pedigree from capture to archive, stability (of values, of attribution), protection against loss or destruction, ease of review by users responsible for data quality, proper operation and validation of systems, and training of users.

      Declaration of Helsinki:

      A set of recommendations or basic principles that guide medical doctors in the conduct of biomedical research involving human subjects. It was originally adopted by the 18th World Medical Assembly (Helsinki, Finland, 1964) and recently revised (52nd WMA General Assembly, Edinburgh, Scotland, October 2000).

      Dependence:

      The state of physical adaptation that is manifested by a drug class–specific withdrawal syndrome that can be produced by abrupt cessation, rapid dose reduction, and/or decreasing blood level of a substance and/or administration of an antagonist.

      Detoxification:

      Treatment for addiction to an illicit substance in which the substance is eliminated gradually from a patient’s body while various types and levels of reinforcing treatment are provided to alleviate adverse physical or psychological reactions to the withdrawal process.

      Drug:

      An article intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease in man or other animals.

      Drug Testing:

      The examination of an individual to determine the presence or absence of illicit or nonprescribed drugs or alcohol, or to confirm maintenance levels of treatment medications.

      Drug Utilization Review (DUR):

      Also called drug use evaluation, or medication use evaluation, it is a formal performance improvement program for assessing data on drug use against explicit, prospective standards (criteria) and, as necessary, introducing remedial strategies to achieve some desired end.

      Effectiveness:

      The capacity of a drug or treatment (study intervention) to produce beneficial effects on the course or duration of a disease at the dose tested and against the illness (and patient population) for which it is designed. Effectiveness measures how well a study intervention works under real-life conditions, and takes into account tolerability of a drug, acceptability of a behavioral intervention, ease of use, and so on.

      Efficacy:

      The measure of a study intervention’s desired influence on a disease or condition as demonstrated by substantial evidence from adequate and well-controlled investigations. Efficacy measures how well a study intervention works in an ideal, controlled setting.

      Elimination Half-Life:

      The time required after administration of a substance (e.g., methadone) for one-half the dose to leave the body. Elimination half-life affects the duration of action of a substance or medication and can be influenced by patient factors such as absorption rate, variable metabolism and protein binding, changes in urinary pH, concomitant medications, diet, physical condition, age, pregnancy, and even use of vitamins and herbal products.

      Enzyme:

      A molecule (usually a protein) that speeds up, or catalyzes, a chemical reaction without being permanently altered or consumed.

      Equivalence Trial:

      A trial with the primary objective of showing that the response to two or more treatments differs by an amount that is clinically unimportant. This is usually demonstrated by showing that the true treatment difference is likely to lie between a lower and an upper equivalence margin of clinically acceptable differences.

      Exclusion Criteria:

      List of characteristics in a protocol, any one of which may exclude a potential subject from participation in a study.

      Fabrication:

      Making up data or results and recording or reporting them.

      Falsification:

      Manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record.

      Generalizability:

      The extent to which the findings of a clinical trial can be reliably extrapolated from the subjects who participated in the trial to a broader patient population and a broader range of clinical settings.

      Generic Substitution:

      The substitution of drug products that contain the same active, chemically identical ingredient(s) and are identical in strength, concentration, dosage form, and route of administration to the drug product prescribed.

      Good Clinical Practice (GCP):

      An international ethical and scientific quality standard for designing, conducting, recording, and reporting trials that involve the participation of human subjects.

      Hormone:

      A messenger molecule that helps coordinate the actions of various tissues; made in one part of the body and transported, via the bloodstream, to tissues and organs elsewhere in the body.

      Inclusion Criteria:

      The criteria in a protocol that prospective subjects must meet to be eligible for participation in a study. Exclusion and inclusion criteria together define the study population.

      Independent Safety Monitor:

      The physician or other appropriate expert who is independent of the study and available to review serious adverse events (SAEs) and other safety data in a timely fashion and recommends appropriate actions to the study team and any governing organizations.

      Informed Consent Process:

      A process by which a participant voluntarily confirms his or her willingness to participate in a particular study after having been informed of all aspects of the trial that are relevant to the participant’s decision to participate.

      Institutional Review Board/Ethics Committee (IRB/EC):

      The board, committee, or other group formally designated by an institution to review, to approve the initiation of, and to conduct periodic review of research involving human subjects. The primary purpose of such review is to assure the protection of the rights and welfare of participants in research.

      Intention to Treat:

      A strategy for analyzing data in which all participants are included in the group to which they were assigned, whether or not they completed the intervention given to the group. Intention-to-treat analysis prevents bias caused by the loss of participants, which may disrupt the baseline equivalence established by random assignment and which may reflect nonadherence to the protocol.

      International Conference on Harmonisation (ICH) Guidelines:

      A set of guidelines developed, through a collaboration between the FDA and regulatory agencies in Japan and the European Union, to “harmonize” regulatory requirements to produce marketing applications acceptable to the United States, Japan, and the countries of the European Union.

      Investigational Device Exemption (IDE):

      Analogous to an Investigational New Drug (IND), an Investigational Device Exemption (IDE) allows an unapproved medical device to be used for investigational purposes.

      Investigational New Drug (IND):

      A drug or biological product that is used in a clinical investigation.

      Masking:

      Also known as blinding, a procedure in which one or more parties to the trial are kept unaware of the treatment assignment(s). Single masked usually refers to the subject(s) being unaware, and double masked usually refers to the subject(s), investigator(s), monitor, and, in some cases, data analyst(s) being unaware of the treatment assignment(s).

      Medically Supervised Withdrawal:

      In the context of the treatment of opiate use and treatment, dispensing of a maintenance medication in gradually decreasing doses to alleviate adverse physical or psychological effects incident to withdrawal from the continuous or sustained use of opioid drugs. The purpose of medically supervised withdrawal is to bring a patient maintained on maintenance medication to a medication-free state within a target period.

      Metabolite:

      A chemical intermediate in metabolic reactions; a product of metabolism.

      Methadone:

      The most frequently used opioid agonist medication. Methadone is a synthetic opioid that binds to mu (μ)-opiate receptors and produces a range of μ-agonist effects similar to those of short-acting opioids such as morphine and heroin.

      Minimal Risk:

      The probability and magnitude of harm or discomfort anticipated in the research are not greater in and of themselves than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests.

      Model Organism:

      A bacterium, animal, or plant used by scientists to study basic research questions; common model organisms include yeast, flies, worms, frogs, and fish.

      Monitors:

      In a clinical trial, individuals qualified by education or experience, whose primary role is to ensure compliance with the applicable regulations, policies, and standard procedures, as well as compliance with the study protocol as approved by the institutional review board or research ethics board.

      Monoclonal Antibody:

      An antibody that recognizes only one type of antigen; sometimes used as immunotherapy to treat diseases such as cancer.

      Neurotransmitter:

      A chemical messenger that allows neurons (nerve cells) to communicate with each other and with other cells.

      Nonsteroidal Anti-Inflammatory Drug (NSAID):

      Any of a class of drugs that reduces pain, fever, or inflammation by interfering with the synthesis of prostaglandins.

      Observational Study:

      A type of study in which individuals are observed or certain outcomes are measured, but no treatments or interventions are assigned by the study.

      Open or Unrestricted Formulary:

      An open formulary is a very comprehensive listing of medications typically offering almost every commercially available product in each therapeutic category. Physicians who prescribe from an open formulary are not restricted and may prescribe virtually any drug. Payers, including employers, health plans, and third-party administrators, provide coverage for all medications since there are no restrictions.

      Opiate Receptors:

      Areas on cell surfaces in the central nervous system that are activated by opioid molecules to produce the effects associated with opioid use, such as euphoria and analgesia. Opiate receptors are activated or blocked by opioid agonist or antagonist medications, respectively, to mediate the effects of opioids on the body. Mu (μ)- and kappa (κ)-opiate receptor groups principally are involved in this activity.

      Opioid:

      Natural derivative of opium or synthetic psychoactive substance that has effects similar to morphine or is capable of conversion into a drug having such effects. One effect of opioid drugs is their addiction-forming or addiction-sustaining liability.

      Partially/Selectively Closed Formulary:

      These are formulary hybrids that limit prescribing choices within certain therapeutic classes and offering unlimited choice within other drug classes. Such formularies direct prescribers to preferred agents within therapeutic classes, which may be included in a treatment protocol or clinical guideline. In some cases, entire categories, such as drugs used solely for cosmetic purposes, may be closed to prevent payment for those drugs that are excluded from coverage.

      Participant:

      In clinical trials, a living individual about whom an investigator conducting research obtains (1) data through intervention or interaction with the individual or (2) identifiable private information.

      Patient-Treatment Matching:

      Process of individualizing therapeutic resources to patient needs and preferences, ideally by a participatory process involving both the treatment provider and patient.

      Pharmacodynamics:

      The study of how drugs act at target sites of action in the body.

      Pharmacogenomics:

      Science that examines inherited variations in genes that dictate drug response and explores the ways such variations can be used to predict whether a person will respond favorably, adversely, or not at all to an investigational product.

      Pharmacokinetics:

      The study of how the body absorbs, distributes, breaks down, and eliminates drugs.

      Pharmacology:

      Science that addresses the origin, nature, chemistry, effects, and uses of medications and drugs.

      Pharmacopoeia:

      A compendium of drug standards for purity and strength.

      Pharmacotherapy:

      Treatment of disease with prescribed medications.

      Pharmacovigilance:

      All scientific and data gathering activities relating to the detection, assessment, and understanding of adverse events.

      Prevalence:

      Number of cases of a disease in a population, either at a point in time (point prevalence) or over a period (period prevalence). Prevalence rate is the fraction of people in a population who have a disease or condition at one time. (The numerator of the rate is the number of existing cases of the condition at a specified time, and the denominator is the total population.)

      Principal Investigator (PI):

      In a research context, the qualified person designated by the applicant institution to direct the funded research program. PIs oversee the scientific and technical aspects of an award and the day-to-day management of the research.

      Prostaglandins:

      Any of a class of hormone-like, fat-soluble, regulatory molecules made from fatty acids such as arachidonic acid; prostaglandins participate in diverse body functions, and their production is blocked by NSAIDs.

      Protocol:

      A document that describes the objective(s), design, methodology, statistical considerations, and organization of a trial. The protocol usually also gives the background and rationale for the trial, but these could be provided in other protocol-referenced documents.

      Quality Assurance (QA):

      A periodic, systematic, objective, and comprehensive examination of the total work effort to determine the level of compliance with accepted Good Clinical Practice (GCP) standards. For example, in a clinical trial, a monthly peer review of source documents compared to case report form pages to determine adherence to protocol requirements.

      Quality Control (QC):

      The real-time, ongoing (day-to-day) observation and documentation of a site’s work processes to ensure that accepted procedures are being followed. For example, in a clinical trial, reviewing demographic information for accuracy on each Case Report Form (CRF) page prior to entry into the database.

      Quality Management:

      The overall system that includes all activities involved in quality assurance and quality control during a clinical trial, including the assignment of roles and responsibilities, the reporting of results, and the resolution of issues identified during the review.

      Receptor:

      A specialized molecule that receives information from the environment and conveys it to other parts of the cell; the information is transmitted by a specific chemical that must fit the receptor, like a key in a lock.

      Research Hypothesis:

      The proposition that a study sets out to support (or disprove); for example, “blood pressure will be lowered by [specific endpoint] in subjects who receive the test product.” The null hypothesis is the converse to what the researcher expects to happen in reference to the target outcome. Inferential statistical analyses are designed around accepting or rejecting the null hypothesis.

      Research Misconduct:

      Fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. Research misconduct does not include honest error or differences of opinion.

      Sample Informed Consent (SIC):

      In a clinical trial, an informed consent developed by the protocol team for a specific protocol that will help guide participating sites in the development of their site-specific informed consent.

      Sedative:

      Medication with central nervous system sedating and tranquilizing properties. An example is any of the benzodiazepines. Most sedatives also promote sleep. Overdoses of sedatives can lead to dangerous respiratory depression (slowed breathing).

      Self-Medication:

      Medically unsanctioned use of drugs by a person to relieve any of a variety of problems (e.g., pain, depression).

      Serious Adverse Drug Experience:

      Any adverse drug experience occurring at any dose that results in any of the following outcomes: death, a life-threatening adverse drug experience, inpatient hospitalization or prolongation of existing hospitalization, a persistent or significant disability/incapacity, or a congenital anomaly/birth defect. Important medical events that may not result in death, be life threatening, or require hospitalization may be considered a serious adverse drug experience when, based upon appropriate medical judgment, they may jeopardize the patient or subject and may require medical or surgical intervention to prevent one of the outcomes listed in this definition.

      Serious Adverse Event (SAE):

      Any untoward medical occurrence that at any dose results in death, is life threatening, requires inpatient hospitalization or prolongation of existing hospitalization, results in persistent or significant disability/incapacity, or is a congenital anomaly/birth defect. This includes important medical events that may not be immediately life threatening or result in death or hospitalization but may jeopardize the patient or may require intervention to prevent one of the outcomes listed in the definition above.

      Serum Half-Life:

      The time required for the amount of a compound (e.g., an opioid) in blood serum to be halved through metabolism or excretion.

      Side Effect:

      Consequence (especially an adverse result) other than that for which a drug is used—especially the result produced on a tissue or organ system other than that being targeted.

      Site of Action:

      The place in the body where a drug exerts its effects.

      Site-Specific Informed Consent:

      An informed consent developed by a participating site based upon the sample informed consent that is reviewed and approved by the site’s designated IRB/IEC and is used to consent subjects at the site for a specific clinical trial.

      Source Data:

      All information in original records and certified copies of original records of clinical findings, observations, or other activities in a study necessary for the reconstruction and evaluation of a clinical trial. Source data are contained in source documents (original records or certified copies).

      Source Documents:

      The original documents, data, and records containing clinical findings, observations, or other activities in a clinical research study that allows the reconstruction and evaluation of the study. Examples of source documents include hospital records, clinical and office charts, laboratory notes, memoranda, subjects’ diaries or evaluation checklists, pharmacy dispensing records, recorded data from automated instruments, copies or transcriptions certified after verification as being accurate and complete, microfiches, photographic negatives, microfilm or magnetic media, X-rays, subject files, and records kept at the pharmacy, at the laboratories, and at medico-technical departments involved in the clinical trial.

      Sponsor:

      A person (individual, corporation, or agency) who initiates a clinical investigation, but who does not actually conduct the investigation.

      Sponsor-Investigator:

      An individual who both initiates and actually conducts, alone or with others, a clinical investigation. For example, under whose immediate direction the test article is administered, dispensed to, or used involving a subject and who also submitted the IND.

      Standard Operating Procedures (SOPs):

      Written procedures designed to ensure data and analysis quality by requiring uniform performance of specific functions by the group(s) that fall within their scope. An SOP is designed to provide a high-level overview of tasks or functions performed. An SOP, by definition, must be followed unless a documented exception is approved.

      Step Protocol:

      A treatment protocol that recommends beginning a trial of drug therapy for a medical condition with one drug or class of drugs (often of lower cost or risk) before proceeding to other drugs or drug classes.

      Steroid:

      A type of molecule that has a multiple ring structure, with the rings sharing molecules of carbon.

      Structural Biology:

      A field of study dedicated to determining the three-dimensional structures of biological molecules to better understand the function of these molecules.

      Subject:

      A living individual about whom an investigator conducting research obtains (1) data through intervention or interaction with the individual or (2) identifiable private information. For research conducted under U.S. Food and Drug Administration (FDA) regulations, a subject is an individual who is or becomes a participant in research, either as a recipient of the test article or as a control. A subject may be either a healthy individual or a patient.

      Substance Use Disorder:

      Frequently referred to as substance abuse or dependence, it is a maladaptive pattern of drug or alcohol use manifested by recurrent, significant adverse consequences related to the repeated use of these drugs or alcohol. The substance-related problem must have persisted and occurred repeatedly during a 12-month period. It can occur sporadically and mainly be associated with social or interpersonal problems, or it can occur regularly and be associated with medical and mental problems, often including tolerance and withdrawal.

      Suspected Unexpected Serious Adverse Reaction (SUSAR):

      A suspected unexpected serious adverse reaction (SUSAR) in a clinical trial is an event that is (1) serious, (2) related (i.e., there is a reasonable possibility that the adverse event may be related to the study agent), and (3) unexpected.

      Therapeutic Alternates:

      Drug products differing in composition or in their basic drug entity, but of the same pharmacological and/or therapeutic class, that are considered to have very similar pharmacological and therapeutic activities and adverse reaction profiles when administered to patients in therapeutically equivalent doses.

      Therapeutic Drug:

      A drug used to treat a disease or condition; contrast with drug of abuse.

      Therapeutic Equivalence:

      Similar pharmacological and therapeutic activity of drugs.

      Toxicology:

      The study of how poisonous substances interact with living organisms.

      Unanticipated Problems:

      Unanticipated problems involving risks to subjects or others, any serious or continuing noncompliance with policy requirements or determinations of the internal review board (IRB), and any suspension or termination of IRB approval.

      Unanticipated Problems Involving Risk to Subjects or Others:

      Any adverse event occurring in one or more subjects in a research protocol, the nature, severity, or frequency of which suggests the risk is (1) unexpected given the research procedures that are described in the protocol-related documents, and the characteristics of the subject population being studied; and (2) related or possibly related to a subject’s participation in the research, and suggests that the research places subjects or others at a greater risk of harm than was previously known or recognized.

      Unexpected Adverse Drug Experience:

      Any adverse drug experience, the specificity or severity of which is not consistent with the current investigator brochure; or, if an investigator brochure is not required or available, the specificity or severity of which is not consistent with the risk information described in the general investigational plan or elsewhere in the current application, as amended.

      Unexpected Adverse Event:

      Any adverse event occurring in one or more subjects in a research protocol, the nature, severity, or frequency of which is not consistent with either (1) the known or foreseeable risk of adverse events associated with the procedures involved in the research that are described in (a) the protocol-related documents, such as the IRB-approved research protocol, any applicable investigator brochure, and the current IRB-approved informed consent document, and (b) other relevant sources of information, such as product labeling and package inserts; or (2) the expected natural progression of any underlying disease, disorder, or condition of the subject(s) experiencing the adverse event and the subject’s predisposing risk factor profile for the adverse event.

      U.S. Food and Drug Administration (FDA):

      A public health agency within the United States Department of Health and Human Services. FDA’s mission is to promote and protect public health by helping safe and effective products reach the market in a timely way and monitoring of products for continued safety after they are in use as authorized by the Federal Food, Drug, and Cosmetic Act. The agency regulates all clinical investigations in support of marketing applications.

      Vaccine and Prevention Research Program (VPRP):

      The VPRP is a program within the Division of AIDS of the National Institute of Allergy and Infectious Diseases (DAIDS) in the United States that supports the discovery and development of vaccines and other biomedical and behavioral interventions to prevent acquired immunodeficiency syndrome (AIDS).

      Virus:

      An infectious agent composed of a protein coat around a DNA or RNA core; to reproduce, viruses depend on living cells.

      X-Ray Crystallography:

      A technique used to determine the detailed, three-dimensional structure of molecules based on the scattering of X-rays through a crystal of the molecule.

      Source: Adapted from publications of the National Institutes of Health and other sources.

      Resource Guide

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      Journals
      Addiction (Carfax Publishing)
      Advances in Pharmacology (Academic Press)
      Adverse Drug Reaction Bulletin (Lippincott Williams & Wilkins)
      African Journal of Traditional, Complementary, and Alternative Medicines (African Networks on Ethnomedicines)
      American Journal of Drug and Alcohol Abuse (Taylor & Francis)
      Annual Review of Pharmacology and Toxicology (Annual Reviews Inc.)
      Behavioural Pharmacology (Clinical Neuroscience Publishers)
      Biotechnology & the Law (Thomson Reuters)
       BMC Pharmacology (BioMed Central)
      British Journal of Pharmacology and Chemotherapy (British Medical Association)
      British Journal of Social Medicine (British Medical Association)
      Canadian Adverse Reaction Newsletter (Health Canada)
      Canadian Journal of Physiology and Pharmacology (NRC Research Press)
      Drug Abuse & Alcoholism Review (Haworth Press)
      Economic and Medicinal Plant Research (Academic Press)
      Environmental Toxicology and Pharmacology (Elsevier Science)
      European Journal of Medicinal Plants (Sciencedomain International)
       European Journal of Pharmacology (Elsevier Science)
      Experimental and Clinical Psychopharmacology (American Psychological Association)
      Expert Opinion on Drug Safety (Ashley Publications)
      Health Sociology Review (Australian Sociological Association)
      Herbs, Spices, and Medicinal Plants: Recent Advances in Botany, Horticulture, and Pharmacology (Oryx Press)
      International Journal of Phytomedicine (Advanced Research Journals)
       International Journal of Public Health (Birkhäuser)
      Japanese Journal of Pharmacology (Japanese Pharmacological Society)
      Journal of Addictive Diseases (Haworth Press)
      Journal of Clinical Pharmacy and Therapeutics (Blackwell Science)
      Journal of Clinical Psychopharmacology (Lippincott Williams & Wilkins)
      Journal of Epidemiology & Community Health (British Medical Association)
      Journal of Ethnopharmacology (Elsevier)
       Journal of Health & Social Policy (Haworth Press)
      Journal of Herbs, Spices & Medicinal Plants (Haworth Press)
      Journal of Pharmacology and Experimental Therapeutics (American Society for Pharmacology and Experimental Therapeutics)
      Journal of Pharmacy & Pharmaceutical Sciences (Canadian Society for Pharmaceutical Sciences)
      Journal of Pharmacy & Pharmacology (Royal Pharmaceutical Society of Great Britain)
      Journal of Pharmacy Teaching (Haworth Press)
      Journal of Traditional and Complementary Medicine (Wolters Kluwer Health)
       Open Pharmacology Journal (Bentham Science Publishers)
      Pharmacoepidemiology and Drug Safety (John Wiley & Sons)
      Pharmacognosy Magazine (Elsevier)
      Pharmacy Education (Informa UK Ltd.)
      Phytotherapy Research (Heyden & Son)
      Research in Social and Administrative Pharmacy (Elsevier)
      Scandinavian Journal of Social Medicine (Almqvist & Wiksell)
      Side Effects of Drugs Annual (Elsevier/North Holland)
      Social Science & Medicine (Elsevier)
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      Therapeutic Advances in Psychopharmacology (SAGE Publications)
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      American Society for Pharmacology and Experimental Therapeutics http://www.aspet.org/
      Antimicrobial Resistance (World Health Organization) http://www.who.int/mediacentre/factsheets/fs194/en/
      British Pharmacological Society http://www.bps.ac.uk/view/index.html
      Canadian Society of Pharmacology and Therapeutics http://pharmacologycanada.org/
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      Essential Medicines (World Health Organization) http://www.who.int/topics/essential_medicines/en/
      European Drug Monitoring Centre for Drugs and Drug Addiction http://www.emcdda.europa.eu/
      Food and Drug Administration (U.S.) http://www.fda.gov/
      Guttmacher Institute (contraception and reproductive health) http://www.guttmacher.org/
      National Center for Complementary and Integrative Health (U.S.) http://nccam.nih.gov/
      National Institutes of Health: Clinical Trials Database (U.S. and non-U.S.) http://clinicaltrials.gov/
      Pharmaceutical Group of the European Union http://www.pgeu.eu/
      Substance Abuse and Mental Health Services Administration (U.S.): Data, Outcomes, and Quality http://www.samhsa.gov/data/
      Traditional and Complementary Medicine (World Health Organization) http://www.who.int/medicines/areas/traditional/en/
      World Anti-Doping Agency https://www.wada-ama.org/

      Appendix<span class="hi-italic">Primary Documents</span>

      Prescription Medication Use

      Information in these tables was drawn from Health, United States, 2013, the 37th annual overview of the nation’s health, compiled by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention. The full report, including detailed information about data sources, definitions, and methods, is available for free download from the Internet (http://www.cdc.gov/nchs/data/hus/hus13.pdf).

      The 2013 edition of Health, United States includes a special feature on prescription drug use in the United States, which includes the tables included in this appendix. Topics covered include the number and classes of drugs used by Americans, access problems, the impact of drugs used to treat chronic diseases, antibiotic misuse, opioid misuse, adoption of electronic health records (EHRs), and the growth in spending on prescription drugs.

      Data table for Figure 20. Prescription drug use in the past 30 days, by number of drugs taken and age: United States, 1988–1994 through 2007–2010

      Data table for Figure 21. Prescription drug use in the past 30 days, by age and selected drug class: United States, 1988–1994 and 2007–2010

      Data table for Figure 22. Number of prescription drugs taken in the past 30 days among adults aged 18 and over, by selected characteristics: United States, 2007–2010

      Data table for Figure 23. Nonreceipt of needed prescription drugs in the past 12 months due to cost among adults aged 18–64, by insurance status and percent of poverty level: United States, 2002–2012

      Data table for Figure 25. Use of prescription antidepressants in the past 30 days among adults aged 18 and over, by sex and age: United States, 1988–1994 through 2007–2010

      Data table for Figure 26. Antibiotics ordered or provided during emergency department, outpatient, and physician visits for cold symptom diagnoses, by age: United States, average annual, 1995–1996 through 2009–2010

      Data table for Figure 27. Computerized systems for prescription drugs, by provider and system type: United States, 2010

      Data table for Figure 28. Drug poisoning deaths involving opioid analgesics among persons aged 15 and over, by race and Hispanic origin, sex, and age: United States, 1999–2000 through 2009–2010

      Data table for Figure 29. Retail prescription drug expenditures, annual percent change, and spending by payer: United States, 2001–2011

      Year

      Annual percent change

      2001

      14.7

      2002

      14.0

      2003

      11.3

      2004

      9.2

      2005

      6.5

      2006

      9.5

      2007

      5.2

      2008

      2.8

      2009

      5.0

      2010

      0.4

      2011

      2.9

      Payer

      2001

      2011

      Percent

      Out-of-pocket

      26.4

      17.1

      Private health insurance

      50.9

      46.5

      Medicare

      1.8

      24.2

      Medicaid1

      17.1

      7.8

      Other health insurance programs2

      1.8

      3.0

      Other third-party payers3

      2.0

      1.4

      1 Includes both the state and federal portions. Also includes Children’s Health Insurance Program (CHIP) and Medicaid CHIP expansions.

      2 Includes Department of Defense and Department of Veterans Affairs programs.

      3 Includes worksite health care, other private revenues, Indian Health Service, workers’ compensation, general assistance, maternal and child health, vocational rehabilitation, other federal programs, Substance Abuse and Mental Health Services Administration, other state and local programs, and school health.

      NOTES: See Appendix II, Health expenditures, national. See related Table 115.

      SOURCE: Centers for Medicare & Medicaid Services, Office of the Actuary, National Health Statistics Group, National Health Expenditure Accounts. See Appendix I, National Health Expenditure Accounts (NHEA).

      Information in these figures was drawn from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The data on trends in opioid use among Americans in these figures are drawn from NHANES data from 1999–2002 through 2011–2012, while the use of opioid analgesics among population subgroups is drawn from NHANES data from the years 2007–2008, 2009–2010, and 2011–2012. More technical information about the data is available from http://www.cdc.gov/nchs/data/dataBriefs/db189.pdf.

      Figure 1 Trend in prescription opioid analgesic use in the past 30 days among adults aged 20 and over: United States, 1999–2012

      Figure 2. Trends in the use of different strength opioid analgesics among adults aged 20 and over who used opioids in the past 30 days: United States, 1999–2012

      1Significant linear trend for use of stronger-than-morphine opioid analgesics.

      2Significant linear trend for use of weaker-than-morphine opioid analgesics.

      NOTES: Respondents who reported using two or more opioid analgesics of different strengths were categorized based on the strongest opioid analgesic reported.

      Access data table for Figure 2 at: http://www.cdc.gov/nchs/data/databriefs/db189_table.pdf#2.

      SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 1999–2012.

      Figure 3. Prescription opioid analgesic use in the past 30 days among adults aged 20 and over, by age, sex, and race and Hispanic origin: United States, 2007–2012

      1Significantly higher than adults aged 20–39.

      2Significantly higher than men.

      3Significantly lower than non-Hispanic white adults.

      4Significantly lower than non-Hispanic black adults.

      5Estimates were age-adjusted by the direct method to the 2000 U.S. census population using age groups 20–39, 40–59, and 60 and over.

      NOTE: Access data table for Figure 3 at: http://www.cdc.gov/nchs/data/databriefs/db189_table.pdf#3.

      SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2007–2012.

      Figure 4. Prescription opioid analgesic use in the past 30 days among adults aged 20 and over, by sex and age: United States, 2007–2012

      1Significantly higher than men aged 20–39.

      2Significantly higher than women aged 20–39.

      3Significantly higher than men aged 60 and over.

      NOTE: Access data table for Figure 4 at: http://www.cdc.gov/nchs/data/databriefs/db189_table.pdf#4.

      SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2007–2012.

      Figure 5. Prescription opioid analgesic use in the past 30 days among adults aged 20 and over, by sex and race and Hispanic origin: United States, 2007–2012

      1Significantly lower than non-Hispanic white men.

      2Significantly lower than non-Hispanic black men.

      3Significantly lower than non-Hispanic white women.

      4Significantly higher than Hispanic men.

      NOTES: Estimates were age-adjusted by the direct method to the 2000 U.S. census population using age groups 20–39, 40–59, and 60 and over. Access data table for Figure 5 at: http://www.cdc.gov/nchs/data/databriefs/db189_table.pdf#5.

      SOURCE: CDC/NCHS, National Health and Nutrition Examination Survey, 2007–2012.

      Information for this figure was drawn from the National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm and more technical information about the data in this figure is available from http://www.cdc.gov/diabetes/statistics/meduse/methods.htm.

      CDC - Percentage Using Diabetes Medication by Type of Medication - Treating Diabetes - Data & Trends - Diabetes DDT

      Antibiotic Resistance

      Information for this table was drawn from a 2013 report from the Centers for Disease Control and Prevention (CDC). The complete report is available from http://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508.pdf, and more information about antibiotic resistance is available from the CDC Web site at http://www.cdc.gov/drugresistance/.

      Minimum Estimates of Morbidity and Mortality from Antibiotic-Resistant Infections*

      Youth Drug Use

      Information for these tables was reproduced from the Centers for Disease Control and Prevention’s (CDC’s) Morbidity and Mortality Weekly Report and drawn from the 2013 Youth Risk Behavior Surveillance System (YRBSS), including both the national survey and surveys conducted at the state and local levels. The YRBSS, conducted by the CDC and state and local health agencies, gathers information about six types of health-related behaviors among youth and young adults: those relating to injuries and violence; tobacco use; alcohol and drug use; sexual behavior; diet; and physical inactivity. Further information about the YRBSS is available from http://www.cdc.gov/healthyyouth/data/yrbs/index.htm.

      Surveillance Summaries

      TABLE 49 Percentage of high school students who ever used marijuana* and who tried marijuana for the first time before age 13 years, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 50 Percentage of high school students who ever used marijuana* and who tried marijuana for the first time before age 13 years, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 51 Percentage of high school students who currently use marijuana,* by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 52 Percentage of high school students who currently use marijuana,* by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 53 Percentage of high school students who ever used cocaine* and who ever used hallucinogenic drugs, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 54 Percentage of high school students who ever used cocaine,* by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 55 Percentage of high school students who ever used inhalants* and who ever used ecstasy, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 56 Percentage of high school students who ever used inhalants* and who ever used ecstasy, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 57 Percentage of high school students who ever used heroin* and who ever used methamphetamines, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 58 Percentage of high school students who ever used heroin* and who ever used methamphetamines, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 59 Percentage of high school students who ever took steroids* and who ever took prescription drugs, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 60 Percentage of high school students who ever took steroids* and who ever took prescription drugs, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 61 Percentage of high school students who injected illegal drugs* and who were offered, sold, or given an illegal drug by someone on school property, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 62 Percentage of high school students who injected illegal drugs* and who were offered, sold, or given an illegal drug by someone on school property, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      Table 67. Percentage of high school students who used a condom during last sexual intercourse* and who used birth control pills before last sexual intercourse,*, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      TABLE 68. Percentage of high school students who used a condom during last sexual intercourse* and who used birth control pills before last sexual intercourse,*, by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      TABLE 69. Percentage of high school students who used an IUD* or implant before last sexual intercourse§, and who used a shot,** patch,†† or birth control ring§§ before last sexual intercourse,§, by sex, race/ethnicity, and grade – United States, Youth Risk Behavior Survey, 2013

      TABLE 70. Percentage of high school students who used an IUD* or implant before last sexual intercourse§, and who used a shot,** patch,†† or birth control ring§§ before last sexual intercourse,§, by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      Table 71 Percentage of high school students who used birth control pills; an IUD* or implant; or a shot,§ patch, or birth control ring** before last sexual intercourse††,§§ and who used both a condom during last sexual intercourse and birth control pills; an IUD* or implant; or a shot,§ patch, or birth control ring** before last sexual intercourse,††,§§ by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      Table 72 Percentage of high school students who used birth control pills; an IUD* or implant; or a shot,§ patch, or birth control ring** before last sexual intercourse††,§§ and who used both a condom during last sexual intercourse and birth control pills; an IUD* or implant; or a shot,§ patch, or birth control ring** before last sexual intercourse,††,§§ by sex, — U.S. sites, Youth Risk Behavior Survey, 2013

      Table 73 Percentage of high school students who did not use any method to prevent pregnancy during last sexual intercourse* and who drank alcohol or used drugs before last sexual intercourse,* by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      Table 74 Percentage of high school students who did not use any method to prevent pregnancy during last sexual intercourse* and who drank alcohol or used drugs before last sexual intercourse,* by sex — selected U.S. sites, Youth Risk Behavior Survey, 2013

      Table 75 Percentage of high school students who were ever taught in school about acquired immunodeficiency syndrome (AIDS) or human immunodeficiency virus (HIV) infection and who were ever tested for HIV,* by sex, race/ethnicity, and grade — United States, Youth Risk Behavior Survey, 2013

      Information in this table was drawn from the National Youth Risk Behavior Survey (YRBS), which is conducted by the Centers for Disease Control and Prevention (CDC). The national YRBS, a school-based survey conducted every other year, gathers information about six types of healthrelated behaviors among youth and young adults: those relating to injuries and violence; tobacco use; alcohol and drug use; sexual behavior; diet; and physical inactivity. Further information about the YRBS is available from http://www.cdc.gov/healthyyouth/data/yrbs/index.htm.

      Trends in the Prevalence of Marijuana, Cocaine, and Other Illegal Drug Use National YRBS: 1991–2013

      Contraceptive Use

      Information in these figures and tables was drawn from the 2011–2013 National Survey of Family Growth (NSFG), conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The NSFG gathers information about family life, marriage and divorce, pregnancy, infertility, contraceptive use, and men’s and women’s health. More information about the NSFG is available from http://www.cdc.gov/nchs/nsfg.htm.

      Figure 1. Percentage currently using any contraceptive method among all women aged 15–44, by selected characteristics: United States, 2011–2013

      1Significantly different from age group 15–24.

      2Significantly different from Hispanic and non-Hispanic black women.

      NOTES: The population size referenced in this figure for women aged 15–44 is 60.9 million. Analyses of education are limited to women aged 22–44 at the time of interview. GED is General Educational Development high school equivalency diploma. BA is bachelor’s degree. Access data table for Figure 1 at: http://www.cdc.gov/nchs/data/databriefs/db173_table.pdf#1.

      SOURCE: CDC/NCHS, National Survey of Family Growth, 2011–2013.

      Figure 2. Percent distribution of women aged 15–44, by current contraceptive status: United States, 2011–2013

      1Additional reasons for nonuse, such as nonsurgical sterility, are shown in the accompanying data table.

      2Other methods grouped in this category, such as withdrawal and natural family planning, are shown in the accompanying data table.

      NOTES: Percentages may not add to 100 due to rounding. Women currently using more than one method were classified according to the most effective method they were using. Long-acting reversible contraceptives include contraceptive implants and intrauterine devices. Access data table for Figure 2 at: http://www.cdc.gov/nchs/data/databriefs/db173_table.pdf#2.

      SOURCE: CDC/NCHS, National Survey of Family Growth, 2011–2013.

      Figure 3. Percentage of all women aged 15–44 who were using female sterilization, the pill, the male condom, and long-acting reversible contraceptives, by age: United States, 2011–2013

      1All percentages are significantly different from each other across age groups.

      2Percentages for age groups 15–24 and 25–34 are significantly different from age group 35–44.

      3Percentages for age groups 15–24 and 35–44 are significantly different from age group 25–34.

      NOTES: Women currently using more than one method were classified according to the most effective method they were using. Long-acting reversible contraceptives include contraceptive implants and intrauterine devices. Access data table for Figure 3 at: http://www.cdc.gov/nchs/data/databriefs/db173_table.pdf#1.

      SOURCE: CDC/NCHS, National Survey of Family Growth, 2011–2013.

      Figure 4. Percentage of all women aged 15–44 who were currently using female sterilization, the pill, the male condom, and long-acting reversible contraceptives, by Hispanic origin and race: United States, 2011–2013

      1Percentage for non-Hispanic white women is significantly different from non-Hispanic black women.

      2Percentage for Hispanic and non-Hispanic black women is significantly different from non-Hispanic white women.

      3Percentage for Hispanic and non-Hispanic white women is significantly different from non-Hispanic black women.

      NOTES: Women currently using more than one method were classified according to the most effective method they were using. Long-acting reversible contraceptives include contraceptive implants and intrauterine devices. Access data table for Figure 4 at: http://www.cdc.gov/nchs/data/databriefs/db173_table.pdf#1.

      SOURCE: CDC/NCHS, National Survey of Family Growth, 2011–2013.

      Figure 5. Percentage of all women aged 22–44 who were currently using female sterilization, the pill, the male condom, and long-acting reversible contraceptives, by educational attainment: United States, 2011–2013

      1Significant linear trend.

      NOTES: Women currently using more than one method were classified according to the most effective method they were using. Long-acting reversible contraceptives include contraceptive implants and intrauterine devices. GED is General Educational Development high school equivalency diploma. Access data table for Figure 5 at: http://www.cdc.gov/nchs/data/databriefs/db173_table.pdf#1.

      SOURCE: CDC/NCHS, National Survey of Family Growth, 2011–2013.

      Data Brief 173. Current Contraceptive Status Among Women Aged 15–44: United States, 2011–2013 Data table for Figures 1, 3, 4, and 5. Current use of any method of contraception, female sterilization, the contraceptive pill, the male condom, and long-acting reversible contraceptives among all women aged 15–44: United States, 2011–2013

      Data Brief 173. Current Contraceptive Status Among Women Aged 15–44: United States, 2011–2013

      Characteristic

      Percent

      Standard error

      All women (total)1

      100.0

      Using contraception

      61.7

      1.10

      Female sterilization

      15.5

      1.01

      Male sterilization

      5.1

      0.50

      Pill

      16.0

      0.89

      Long-acting reversible contraceptives

      7.2

      0.53

      Intrauterine device (IUD)

      6.4

      0.48

      Implant

      0.8

      0.16

      3-month injectable (Depo-Provera™)

      2.8

      0.26

      Contraceptive ring or patch

      1.6

      0.28

      Diaphragm

      *

      *

      Condom

      9.4

      0.57

      Periodic abstinence—calendar rhythm

      0.7

      0.11

      Periodic abstinence—natural family planning

      0.1

      0.06

      Withdrawal

      3.0

      0.30

      Other methods2

      0.3

      0.11

      Not using contraception3

      38.3

      1.10

      Surgically sterile—female (noncontraceptive)

      0.7

      0.15

      Nonsurgically sterile—female or male

      2.2

      0.26

      Pregnant or postpartum

      5.0

      0.45

      Seeking pregnancy

      4.5

      0.37

      Other nonuse:

      Never had intercourse

      10.8

      0.78

      No intercourse in 3 months before interview

      8.2

      0.55

      Had intercourse in 3 months before interview

      6.9

      0.35

      … Category not applicable.

      * Figure does not meet standards of reliability or precision.

      1 Total equals 60.9 million women.

      2 Includes emergency contraception, female condom, foam, cervical cap, sponge, suppository, jelly, and other methods.

      3 Includes male sterilization for unknown reasons and male surgical sterilization for noncontraceptive reasons, not shown separately.

      NOTES: Percentage may not add to 100 due to rounding. Women currently using more than one method were classified according to the most effective method they were using.

      Complementary Medicine Use

      Information in these tables was drawn from the National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The information in these tables was drawn from the 2002, 2007, and 2012 NHIS, for adults age 18 and older. More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm.

      Table 1. Trends in the use of selected complementary health approaches during the past 12 months, by type of approach: United States, 2002, 2007, and 2012

      Table 2. Trends in the use of complementary health approaches among adults aged 18 and over, by selected characteristics: United States, 2002, 2007, and 2012

      Table 3. Adults aged 18 and over who used selected types of nonvitamin, nonmineral dietary supplements during the past 30 days: United States, 2007 and 2012

      Information in these tables was drawn from the National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The data for these tables are drawn from the 2007 and 2012 NHIS, which included interviews with children age 4 through 17 years. More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm.

      Table 1. Frequencies and age-adjusted percentages of children aged 4–17 years who used or saw a practitioner, took a class, or received formal training for selected complementary and alternative medicine modalities during the past 12 months, by type of therapy: United States, 2007 and 2012

      Table 2. Age-adjusted percentages of children aged 4–17 years who used any complementary health approaches during the past 12 months, by selected characteristics: United States, 2007 and 2012

      Table 3. Frequencies and age-adjusted percentages of children aged 4–17 years who used selected types of nonvitamin, nonmineral dietary supplements for health reasons in the past 30 days, by type of product used: United States, 2007 and 2012

      Table 4. Frequencies and age-adjusted percentages of children aged 4–17 years who used selected types of complementary health approaches to treat a condition among those who used any complementary health approach in the past 12 months: United States, 2007 and 2012

      Table 5. Frequencies and age-adjusted percentages of children aged 4–17 years who used complementary health approaches in the past 12 months for specific conditions, among those who used complementary health approaches, by the condition for which it was used: United States, 2007 and 2012

      Vaccination Coverage

      Information in these tables was drawn from school vaccination data, as analyzed by the Centers for Disease Control and Prevention (CDC) in its Morbidity and Mortality Weekly Report. Further information about vaccination coverage for children, and school vaccination data, is available from http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6341a1.htm.

      TABLE 1 Estimated vaccination coverage,* by state/area and vaccination among children enrolled in kindergarten — United States, 2013–14 school year

      Table 2. Estimated number and percentage* of children enrolled in kindergarten with exemption(s) from vaccination, by state/area and type of exemption — United States, 2013–14 school year

      Information in these tables was reproduced from the Centers for Disease Control and Prevention’s (CDC’s) Morbidity and Mortality Weekly Report and drawn from the National Immunization Survey (NIS), a telephone and mail survey of parents and immunization providers conducted jointly by the National Center for Immunizations and Respiratory Diseases (NCIRD) and the National Center for Health Statistics (NCHS) of the CDC. Further information about the NIS is available from http://www.cdc.gov/nchs/nis.htm.

      Table 1. Estimated vaccination coverage among children aged 19–35 months, by selected vaccines and dosages — National Immunization Survey, United States, 2009–2013*

      TABLE 2. Estimated vaccination coverage among children aged 19–35 months, by selected vaccines and dosages, race/ethnicity,* and poverty level — National Immunization Survey, United States, 2013§

      TABLE 3. Estimated vaccination coverage with selected individual vaccines and a combined vaccine series* among children aged 19–35 months, by U.S. Department of Health and Human Services (HHS) region and state and local area — National Immunization Survey, United States, 2013

      Information in these tables was reproduced from the Centers for Disease Control and Prevention’s (CDC’s) Morbidity and Mortality Weekly Report and drawn from the 2012 National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm.

      TABLE 1. Estimated proportion of adults aged =19 years who received selected vaccinations, by age group, high-risk status,* race/ethnicity, and other selected characteristics – National Health Interview Survey, United States, 2012

      TABLE 2.Type of tetanus vaccine received, and proportion that were tetanus, diphtheria, acellular pertussis vaccine (Tdap), among adults aged 19 years who received a tetanus vaccination, by selected characteristics — National Health Interview Survey, United States, 2005–2012

      TABLE 3.Estimated proportion of health-care personnel* who received selected vaccinations, by age group and race/ethnicity – National Health Interview Survey, United States, 2012

      Health Insurance

      Information in these tables was drawn from the Current Population Survey (CPS), a survey conducted by the U.S. Census Bureau, part of the U.S. Department of Commerce. Further information about the CPS is available from http://www.census.gov/cps, and further technical details about the information in these tables is available from http://www.census.gov/prod/2013pubs/p60–245.pdf (pp. 65–75).

      TABLE 7.People Without Health Insurance Coverage by Selected Characteristics: 2011 and 2012 (Numbers in thousands, con?dence intervals [C.I.] in thousands or percentage points as appropriate. People as of March of the following year. For information on con?dentiality protection, sampling error, nonsampling error, and defenitions, see www.census.gov/prod/techdoc/cps/cpsmar13.pdf)

      TABLE 8.Coverage Rates by Type of Health Insurance: 2011 and 2012 (People as of March of the following year. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/prod/techdoc/cps/cpsmar13.pdf)

      Corverage type

      2011

      2012

      Any private plan1

      63.9

      63.9

      Any private plan alone2

      52.0

      52.0

      Employment-based1

      55. 1

      54.9

      Employment-based alone2

      45. 1

      44.8

      Direct-purchase1

      9.8

      9.8

      Direct-purchase alone2

      3.6

      3.6

      Any government plan1

      32.2

      *32.6

      Any government plan alone2

      20.4

      *20.7

      Medicare1

      15.2

      *15.7

      Medicare alone2

      4.9

      *5.4

      Medicaid1

      16.5

      16.4

      Medicaid alone2

      11. 5

      *11. 3

      Military health care1,3

      4.4

      4.4

      Military health care alone2,3

      1. 3

      1. 3

      Uninsured

      15.7

      *15.4

      * Changes between the 2011 and 2012 estimates are statistically different from zero at the 90 percent confidence level.

      1 The estimates by type of coverage are not mutually exclusive; people can be covered by more than one type of health insurance during the year.

      2 The estimates by type of coverage are mutually exclusive; people did not have any other type of health insurance during the year

      3 Military health care includes Tricare and CHAMPVA (Civilian Health and Medical Program of the Department of Veterans Affairs), as well as care provided by the Department of Veterans Affairs and the military.

      Source: U.S. Census Bureau, Current Population Survey, 2012 and 2013 Annual Social and Economic Supplements.

      Information in these tables was drawn from 2014 CMS Statistics, a report from the Center for Medicare and Medicaid Services within the U.S. Department of Health and Human Services. The full report is available from http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMS-Statistics-Reference-Booklet/Downloads/CMS_Stats_2014_final.pdf, and further information about the Medicare and Medicaid programs is available from http://www.cms.gov/.

      TABLE I.1. Medicare enrollment/trends

      TABLE 1.2Medicare enrollment/coverage

      TABLE I.3. Medicare enrollment/demographics

      TABLE I.4 Medicare Part D enrollment/demographics

      TABLE 1.10 Medicare Part D enrollment by CMS region

      TABLE 1.11Medicare Part D enrollment by plan type/CMS region

      TABLE 1.16 Medicaid and CHIP enrollment

      TABLE III.3 Benefit outlays by program

      Adverse Events

      Information in this table is drawn from the FDA Adverse Events Reporting Systems (FAERS) of the U.S. Food and Drug Administration (FDA), as of December 31, 2013. Further information about the FAERS program is available from http://www.fda.gov/Drugs/GuidanceCompliance-RegulatoryInformation/Surveillance/AdverseDrugEffects/ucm070434.htm.

      This table represents the number of reports received by FDA and entered into FAERS by type of report since the year 2004 through 2013.

      Pharmacist Workforce

      Information in this table is drawn from a report by the National Center for Health Workforce Analysis of the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services. Further information about the data, including the modeling procedure used to make the estimates in it, is available from http://bhw.hrsa.gov/healthworkforce/supplydemand/simulationmodeldocumentation.pdf.

      Exhibit 1. Estimated Supply and Demand for Pharmacists in the U.S., 2012 – 2025

      Pharmacists

      Supply

      Estimated supply, 2012

      264,100

      Total supply growth, 2012–2025:

      91,200 (35%)

      New entrants

      160,500

      Changing work patterns (e.g., part time to full time hours)

      (7,960)

      Attrition (e.g., retirements, mortality)

      (61,340)

      Projected supply, 2025

      355,300

      Demand

      Estimated demand, 2012

      264,100

      Total demand growth, 2012–2025:

      42,300 (16%)

      Changing demographics impact

      35,800 (14%)

      ACA insurance coverage impact

      6,500 (2%)

      Projected demand, 2025

      306,400

      Adequacy of supply, 2025

      Projected supply (minus) projected demand

      48,900

      Disease Statistics

      Information for these tables was drawn from the National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm, and more technical information about the data in these tables is available from http://www.cdc.gov/nchs/data/series/sr_10/sr10_260.pdf (pp. 110–117).

      Table 1.Frequencies of selected circulatory diseases among adults aged 18 and over, by selected characteristics: United States 2012

      Table 2 Age-adjusted percentages of selected circulatory diseases among adults aged 18 and over, by selected characteristics: United States, 2012

      Table 3. Frequencies of selected respiratory diseases among adults aged 18 and over, by selected characteristics: United States, 2012

      Table 4 Age-adjusted percentages of selected respiratory diseases among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected characteristic

      Selected respiratory diseases1

      Asthma

      Emphysema

      Ever had

      Still has

      Hay fever

      Sinusitis

      Chronic bronchitis

      Chronic obstructive pulmonary disease

      Percent2 (standard error)

      Total3 (age-adjusted)

      1.6 (0.09)

      12.7 (0.25)

      8.0 (0.20)

      7.3 (0.19)

      11.8 (0.24)

      3.6 (0.13)

      2.7 (0.11)

      Total3 (crude)

      1.7 (0.10)

      12.6 (0.25)

      8.0 (0.20)

      7.5 (0.19)

      12.1 (0.24)

      3.7 (0.13)

      2.9 (0.12)

      Sex

      Male

      2.0 (0.15)

      10.9 (0.35)

      6.0 (0.26)

      6.6 (0.26)

      9.0 (0.30)

      2.8 (0.18)

      3.0 (0.18)

      Female

      1.3 (0.10)

      14.3 (0.35)

      9.8 (0.30)

      7.9 (0.25)

      14.5 (0.34)

      4.3 (0.18)

      2.5 (0.13)

      Age4 (years)

      18–44

      0.3 (0.05)

      13.4 (0.37)

      8.1 (0.30)

      6.1 (0.26)

      9.8 (0.31)

      2.5 (0.17)

      0.5 (0.08)

      45–64

      2.3 (0.21)

      12.7 (0.42)

      8.4 (0.34)

      9.7 (0.34)

      15.3 (0.43)

      4.7 (0.26)

      3.8 (0.23)

      65–74

      4.7 (0.40)

      12.1 (0.67)

      7.8 (0.52)

      7.9 (0.53)

      13.9 (0.65)

      4.9 (0.41)

      6.9 (0.49)

      75 and over

      4.7 (0.49)

      8.2 (0.58)

      6.0 (0.51)

      5.4 (0.50)

      9.9 (0.59)

      5.2 (0.48)

      8.6 (0.68)

      Race

      One race5

      1.6 (0.09)

      12.6 (0.26)

      7.9 (0.21)

      7.3 (0.19)

      11.8 (0.24)

      3.5 (0.13)

      2.7 (0.11)

      White

      1.7 (0.10)

      12.6 (0.29)

      7.7 (0.23)

      7.5 (0.22)

      12.0 (0.27)

      3.6 (0.15)

      2.9 (0.13)

      Black or African American

      1.3 (0.17)

      14.5 (0.64)

      10.2 (0.53)

      5.8 (0.42)

      11.9 (0.55)

      3.7 (0.30)

      1.9 (0.24)

      American Indian or Alaska Native

      *

      12.6 (2.12)

      7.1 (164)

      8.9 (1.93)

      10.9 (2.10)

      *5.8 (194)

      *

      Asian

      *

      7.6 (0.73)

      4.9 (0.56)

      7.3 (0.71)

      8.3 (0.85)

      1.4 (0.29)

      0.8 (0.21)

      Native Hawaiian or Other Pacific Islander

      *27.2 (8.99)

      *17.0 (8.20)

      *

      *

      Two or more races6

      *1.2 (0.44)

      17.7 (185)

      12.9 (179)

      9.3 (1.56)

      13.4 (176)

      5.0 (117)

      4.2 (1.10)

      Black or African American, white

      *

      16.9 (3.72)

      11.4 (3.18)

      *6.3 (2.80)

      17.1 (2.87)

      *2.8 (135)

      *

      American Indian or Alaska Native, white

      *1.1 (0.55)

      19.3 (3.06)

      17.2 (3.44)

      9.0 (2.25)

      16.2 (2.80)

      *8.3 (3.13)

      5.9 (1.69)

      Hispanic or Latino origin7 and race

      Hispanic or Latino

      0.7 (0.17)

      10.4 (0.54)

      6.5 (0.45)

      5.9 (0.43)

      8.3 (0.44)

      2.5 (0.28)

      1.1 (0.19)

      Mexican or Mexican American

      *0.7 (0.22)

      7.2 (0.57)

      4.1 (0.45)

      5.9 (0.56)

      8.1 (0.55)

      2.2 (0.33)

      1.2 (0.26)

      Not Hispanic or Latino

      1.7 (0.10)

      13.3 (0.29)

      8.3 (0.24)

      7.6 (0.21)

      12.5 (0.27)

      3.7 (0.15)

      2.9 (0.12)

      White, single race

      1.9 (0.11)

      13.4 (0.35)

      8.2 (0.28)

      8.0 (0.26)

      13.0 (0.32)

      3.9 (0.18)

      3.1 (0.14)

      Black or African American, single race

      1.3 (0.17)

      14.7 (0.65)

      10.3 (0.54)

      5.8 (0.42)

      12.1 (0.57)

      3.7 (0.31)

      1.9 (0.24)

      Education8

      Less than a high school diploma

      3.5 (0.33)

      11.6 (0.66)

      8.8 (0.58)

      6.3 (0.47)

      9.9 (0.58)

      4.8 (0.40)

      4.6 (0.39)

      High school diploma or GED9

      2.4 (0.20)

      10.9 (0.49)

      7.2 (0.39)

      6.2 (0.37)

      11.6 (0.49)

      4.5 (0.31)

      3.6 (0.24)

      Some college

      1.7 (0.19)

      13.9 (0.49)

      8.8 (0.39)

      8.8 (0.40)

      15.3 (0.50)

      4.0 (0.27)

      3.5 (0.25)

      Bachelor’s degree or higher

      0.8 (0.12)

      11.7 (0.43)

      6.8 (0.34)

      9.1 (0.40)

      12.4 (0.44)

      2.3 (0.19)

      1.5 (0.16)

      Current employment status10

      Employed

      0.6 (0.12)

      11.2 (0.36)

      6.5 (0.26)

      7.3 (0.30)

      11.2 (0.33)

      2.6 (0.18)

      1.3 (0.20)

      Full-time

      0.5 (0.13)

      10.8 (0.49)

      6.1 (0.26)

      7.4 (0.47)

      11.0 (0.39)

      2.4 (0.26)

      *1.2 (0.37)

      Part-time

      0.7 (0.21)

      12.5 (0.76)

      7.5 (0.59)

      6.8 (0.55)

      11.4 (0.71)

      3.1 (0.40)

      1.8 (0.32)

      Not employed but has worked previously

      3.1 (0.22)

      16.5 (0.56)

      11.2 (0.47)

      7.2 (0.34)

      13.3 (0.46)

      5.5 (0.32)

      4.9 (0.26)

      Not employed and has never worked

      1.8 (0.42)

      12.8 (110)

      9.2 (0.96)

      6.3 (0.75)

      10.2 (0.95)

      3.8 (0.60)

      2.8 (0.51)

      Family income11

      Less than $35,000

      2.9 (0.20)

      14.6 (0.41)

      10.3 (0.37)

      5.9 (0.25)

      11.6 (0.35)

      5.3 (0.25)

      4.6 (0.23)

      $35,000 or more

      1.2 (0.11)

      12.1 (0.33)

      7.1 (0.25)

      8.1 (0.27)

      12.1 (0.32)

      2.9 (0.16)

      2.0 (0.13)

      $35,000–$49,999

      2.2 (0.33)

      13.0 (0.72)

      8.1 (0.61)

      6.8 (0.47)

      12.6 (0.69)

      4.2 (0.44)

      3.2 (0.38)

      $50,000–$74,999

      1.1 (0.16)

      12.6 (0.61)

      7.5 (0.45)

      7.7 (0.45)

      12.1 (0.56)

      3.2 (0.30)

      2.2 (0.23)

      $75,000–$99,999

      0.9 (0.23)

      12.2 (0.77)

      6.8 (0.55)

      7.8 (0.60)

      12.1 (0.68)

      3.2 (0.41)

      2.1 (0.36)

      $100,000 or more

      *0.7 (0.21)

      11.0 (0.58)

      6.2 (0.46)

      9.3 (0.53)

      11.8 (0.58)

      1.6 (0.24)

      0.9 (0.21)

      Poverty status12

      Poor

      3.6 (0.41)

      16.9 (0.70)

      12.5 (0.63)

      5.7 (0.39)

      12.0 (0.58)

      6.6 (0.51)

      5.5 (0.48)

      Near poor

      2.9 (0.30)

      13.2 (0.60)

      8.7 (0.49)

      5.9 (0.36)

      12.2 (0.53)

      4.7 (0.35)

      4.2 (0.36)

      Not poor

      1.1 (0.09)

      11.8 (0.32)

      7.0 (0.24)

      8.1 (0.27)

      12.1 (0.32)

      2.8 (0.15)

      2.0 (0.12)

      Health insurance coverage13

      Percent2 (standard error)

      Under 65:

      Private

      0.4 (0.06)

      12.4 (0.37)

      7.3 (0.28)

      7.9 (0.28)

      12.5 (0.33)

      2.4 (0.15)

      0.8 (0.08)

      Medicaid

      3.3 (0.42)

      21.1 (0.96)

      16.1 (0.85)

      8.5 (0.68)

      13.0 (0.79)

      7.6 (0.60)

      5.5 (0.48)

      Other

      3.0 (0.63)

      15.5 (1.68)

      10.4 (1.41)

      8.5 (1.19)

      16.3 (1.51)

      6.4 (1.11)

      5.5 (0.96)

      Uninsured

      1.2 (0.20)

      11.4 (0.58)

      6.6 (0.42)

      5.4 (0.39)

      8.5 (0.47)

      3.1 (0.33)

      1.9 (0.25)

      65 and over:

      Private

      3.9 (0.39)

      9.9 (0.64)

      6.6 (0.50)

      5.9 (0.46)

      12.0 (0.65)

      5.0 (0.44)

      6.8 (0.53)

      Medicare and Medicaid

      5.3 (0.98)

      15.2 (1.78)

      11.5 (1.59)

      7.9 (1.34)

      13.9 (1.64)

      8.5 (1.58)

      10.3 (1.63)

      Medicare only

      5.3 (0.58)

      9.9 (0.74)

      6.7 (0.64)

      7.8 (0.73)

      11.8 (0.77)

      4.4 (0.50)

      7.8 (0.68)

      Other

      6.6 (1.38)

      9.3 (1.42)

      6.1 (1.15)

      6.7 (1.41)

      11.8 (1.77)

      5.4 (1.23)

      12.6 (1.79)

      Uninsured

      *

      *

      *

      *

      Marital status

      Married

      1.4 (0.12)

      11.0 (0.34)

      6.7 (0.27)

      7.5 (0.27)

      12.2 (0.35)

      3.0 (0.17)

      2.5 (0.16)

      Widowed

      2.6 (0.44)

      12.0 (2.38)

      9.1 (2.29)

      *8.9 (2.79)

      13.6 (2.95)

      6.9 (1.75)

      5.6 (1.31)

      Divorced or separated

      2.6 (0.27)

      15.4 (0.77)

      11.2 (0.67)

      8.7 (0.58)

      15.2 (0.76)

      5.8 (0.52)

      4.4 (0.39)

      Never married

      1.4 (0.31)

      13.9 (0.60)

      8.7 (0.48)

      6.5 (0.43)

      10.0 (0.49)

      3.9 (0.40)

      2.2 (0.38)

      Living with a partner

      2.2 (0.62)

      15.0 (1.14)

      9.6 (0.98)

      8.1 (0.90)

      12.2 (1.04)

      3.6 (0.56)

      2.5 (0.63)

      Place of residence14

      Large MSA

      1.3 (0.11)

      12.4 (0.34)

      7.7 (0.27)

      7.5 (0.26)

      11.3 (0.32)

      3.2 (0.18)

      2.1 (0.14)

      Small MSA

      1.7 (0.17)

      12.3 (0.42)

      8.0 (0.36)

      7.7 (0.37)

      12.3 (0.46)

      3.6 (0.21)

      2.8 (0.20)

      Not in MSA

      2.4 (0.23)

      14.0 (0.76)

      8.8 (0.55)

      6.0 (0.38)

      12.6 (0.59)

      4.4 (0.39)

      4.1 (0.30)

      Region

      Northeast

      1.3 (0.16)

      13.4 (0.68)

      9.2 (0.56)

      8.0 (0.50)

      10.8 (0.57)

      3.2 (0.28)

      2.2 (0.24)

      Midwest

      2.0 (0.21)

      13.3 (0.58)

      8.1 (0.48)

      6.3 (0.36)

      12.1 (0.49)

      4.4 (0.32)

      3.2 (0.28)

      South

      1.9 (0.15)

      11.8 (0.38)

      7.3 (0.30)

      6.7 (0.32)

      14.3 (0.43)

      3.9 (0.23)

      3.0 (0.18)

      West

      1.0 (0.17)

      12.9 (0.50)

      7.8 (0.38)

      8.7 (0.40)

      8.4 (0.39)

      2.4 (0.20)

      2.1 (0.20)

      Hispanic or Latino origin7, race, and sex

      Hispanic or Latino, male

      0.9 (0.24)

      8.6 (0.67)

      4.2 (0.48)

      5.6 (0.57)

      6.9 (0.57)

      1.7 (0.29)

      1.3 (0.29)

      Hispanic or Latina, female

      *0.6 (0.23)

      11.8 (0.77)

      8.5 (0.70)

      6.1 (0.58)

      9.6 (0.66)

      3.1 (0.43)

      0.9 (0.24)

      Not Hispanic or Latino:

      White, single race, male

      2.2 (0.19)

      11.3 (0.46)

      6.1 (0.34)

      7.1 (0.36)

      9.8 (0.40)

      3.0 (0.24)

      3.4 (0.23)

      White, single race, female

      1.6 (0.13)

      15.4 (0.49)

      10.2 (0.41)

      8.7 (0.35)

      16.1 (0.48)

      4.7 (0.25)

      2.9 (0.18)

      Black or African American, single race, male

      1.6 (0.31)

      12.6 (0.99)

      8.0 (0.77)

      4.7 (0.58)

      8.3 (0.83)

      2.5 (0.39)

      2.2 (0.48)

      Black or African American, single race, female

      1.0 (0.20)

      16.4 (0.83)

      12.2 (0.75)

      6.7 (0.59)

      15.1 (0.76)

      4.8 (0.45)

      1.7 (0.22)

      * Estimates are considered unreliable. Data preceded by an asterisk nave a relative standard error greater tnan 30% and less tnan or equal to 50% and snouid be used witn caution. Data not shown nave an RSE greater tnan 50%.

      – Quantity zero.

      1 Respondents were asked if tney nad ever been told by a doctor or otner nealtn professional tnat tney nad a cancer or malignancy of any kind. Tney were tnen asked to name tne kind of cancer tney nad. A person may be represented in more tnan one column.

      2 Unknowns for tne columns are not included in tne denominators wnen calculating percentages; see Appendix I.

      3 Includes otner races not snown separately and persons witn unknown education, employment status, family income, poverty status, nealtn insurance, and marital status cnaracteristics. Estimates may not add to totals due to rounding.

      4 Estimates for age groups are not age-adjusted.

      5 Refers to persons wno indicated only a single race group, including tnose of Hispanic or Latino origin. See Appendix II.

      6 Refers to persons wno indicated more tnan one race group, including tnose of Hispanic or Latino origin. Only two combinations of multiple-race groups are snown due to small sample sizes for otner combinations.

      7 Refers to persons wno are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons wno are not of Hispanic or Latino origin, regardless of race.

      8 Shown only for adults aged 25 and over. Estimates are age-adjusted to tne projected 2000 U.S. population as tne standard population using four age groups: 25–44, 45–64, 65–74, and 75 and over.

      9 GED is General Educational Development high school equivalency diploma.

      10 “Full-time” employment is 35 or more nours per week. “Part-time” employment is 34 or fewer nours per week. See Appendix II.

      11 Includes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      12 “Poor” persons are defined as having an income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      13 Based on a hierarchy of mutually exclusive categories. Adults with more than one type of health insurance were assigned to the first appropriate category in the hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. See Appendix II.

      14 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTES: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population. Unless otherwise specified, estimates are age-adjusted to the projected 2000 U.S. population as the standard population using four age groups: 18–44, 45–64, 65–74, and 75 and over. For crude percentages, refer to Table V in Appendix III.

      SOURCE: CDC/NCHS, National Health Interview Survey, 2012.

      Table 5 Frequencies of selected types of cancer among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected characteristic

      Selected type of cancer1

      All adults aged 18 and over

      Males aged 18 and over

      Females aged 18 and over

      Any cancer

      Breast cancer

      Cervical cancer

      Prostate cancer

      Number in thousands2

      Total3

      234,921

      113,071

      121,850

      20,073

      3,312

      1,330

      2,453

      Sex

      Male

      113,071

      113,071

      8,626

      *53

      2,453

      Female

      121,850

      121,850

      11,447

      3,259

      1,330

      Age (years)

      18–44

      111,034

      54,892

      56,142

      2,265

      171

      524

      *

      45–64

      82,038

      39,761

      42,277

      7,629

      1,242

      558

      546

      65–74

      23,760

      11,133

      12,628

      5,014

      909

      *156

      907

      75 and over

      18,089

      7,285

      10,804

      5,165

      989

      91

      995

      Race

      One race4

      230,994

      111,201

      119,793

      19,712

      3,276

      1,299

      2,439

      White

      188,261

      91,763

      96,498

      17,897

      2,798

      1,175

      2,026

      Black or African American

      27,943

      12,536

      15,407

      1,215

      314

      89

      346

      American Indian or Alaska Native

      1,916

      894

      1,022

      *88

      *

      *

      Asian

      12,542

      5,842

      6,700

      495

      139

      *

      *67

      Native Hawaiian or Other Pacific Islander

      332

      166

      166

      *

      *

      *

      Two or more races5

      3,926

      1,870

      2,057

      361

      *

      *

      *14

      Black or African American, white

      778

      348

      430

      *17

      *

      *

      American Indian or Alaska Native, white

      1,611

      690

      921

      246

      *

      *

      *

      Hispanic or Latino origin6 and race

      Hispanic or Latino

      34,946

      17,505

      17,442

      982

      268

      115

      *67

      Mexican or Mexican American

      21,741

      11,287

      10,454

      533

      159

      *73

      *33

      Not Hispanic or Latino

      199,974

      95,566

      104,408

      19,091

      3,044

      1,215

      2,386

      White, single race

      156,173

      75,739

      80,434

      16,998

      2,538

      1,079

      1,962

      Black or African American, single race

      26,961

      12,022

      14,939

      1,185

      314

      70

      346

      Education7

      Less than a high school diploma

      28,311

      13,724

      14,587

      2,178

      398

      181

      296

      High school diploma or GED8

      52,795

      26,002

      26,794

      5,430

      1,016

      378

      681

      Some college

      59,577

      26,974

      32,603

      6,079

      951

      505

      605

      Bachelor's degree or higher

      63,036

      30,724

      32,312

      6,089

      916

      192

      823

      Current employment status9

      Employed

      142,783

      75,363

      67,420

      7,502

      989

      631

      766

      Full-time

      114,915

      65,257

      49,658

      5,741

      677

      519

      551

      Part-time

      25,610

      8,952

      16,658

      1,625

      278

      101

      182

      Not employed but has worked previously

      78,811

      33,571

      45,240

      11,890

      2,089

      653

      1,671

      Not employed and has never worked

      13,135

      4,034

      9,101

      670

      234

      *

      *

      Family income10

      Less than $35,000

      74,224

      32,711

      41,513

      6,221

      1,162

      645

      561

      $35,000 or more

      146,587

      74,210

      72,376

      12,191

      1,865

      644

      1,649

      $35,000–$49,999

      31,186

      15,220

      15,966

      2,769

      486

      142

      364

      $50,000–$74,999

      39,348

      19,441

      19,907

      3,164

      549

      194

      542

      $75,000–$99,999

      27,052

      13,853

      13,199

      2,203

      362

      *93

      225

      $100,000 or more

      49,001

      25,697

      23,304

      4,055

      468

      215

      519

      Poverty status11

      Poor

      30,576

      12,999

      17,576

      1,767

      331

      342

      99

      Near poor

      38,167

      17,730

      20,436

      2,780

      524

      245

      219

      Not poor

      147,021

      74,294

      72,728

      13,409

      2,080

      646

      1,870

      Health insurance coverage12

      Number in thousands2

      Under 65:

      Private

      125,065

      61,101

      63,965

      6,958

      995

      565

      480

      Medicaid

      19,101

      6,813

      12,287

      1,067

      194

      219

      *

      Other

      8,734

      4,759

      3,975

      733

      93

      *39

      *38

      Uninsured

      39,391

      21,527

      17,864

      1,120

      131

      256

      *

      65 and over:

      Private

      21,580

      9,543

      12,037

      5,729

      1,030

      131

      1,091

      Medicare and Medicaid

      2,546

      805

      1,740

      561

      138

      *

      *73

      Medicare only

      14,327

      6,183

      8,144

      3,084

      641

      *56

      533

      Other

      3,033

      1,729

      1,304

      757

      *89

      *

      202

      Uninsured

      286

      130

      156

      *

      *

      *

      Marital status

      Married

      124,149

      62,674

      61,476

      11,978

      1,683

      585

      1,778

      Widowed

      14,119

      2,928

      11,191

      2,989

      840

      148

      242

      Divorced or separated

      26,499

      10,987

      15,512

      2,875

      543

      275

      222

      Never married

      52,444

      28,007

      24,436

      1,338

      197

      140

      *112

      Living with a partner

      17,367

      8,356

      9,011

      882

      *49

      182

      *99

      Place of residence13

      Large MSA

      125,511

      60,407

      65,103

      9,476

      1,730

      544

      1,071

      Small MSA

      72,095

      34,980

      37,115

      6,488

      980

      473

      863

      Not in MSA

      37,315

      17,684

      19,632

      4,109

      602

      313

      519

      Region

      Northeast

      42,760

      20,238

      22,522

      3,561

      705

      182

      486

      Midwest

      53,378

      25,744

      27,634

      4,559

      662

      343

      571

      South

      85,578

      40,968

      44,610

      7,336

      1,214

      496

      954

      West

      53,205

      26,121

      27,084

      4,617

      731

      308

      441

      Hispanic or Latino origin6, race, and sex

      Hispanic or Latino, male

      17,505

      17,505

      306

      *67

      Hispanic or Latina, female

      17,442

      17,442

      677

      268

      115

      Not Hispanic or Latino:

      White, single race, male

      75,739

      75,739

      7,429

      co

      1,962

      White, single race, female

      80,434

      80,434

      9,569

      2,489

      1,079

      Black or African American, single race, male

      12,022

      12,022

      579

      *

      346

      Black or African American, single race, female

      14,939

      14,939

      606

      310

      70

      … Category not applicable.

      * Estimates are considered unreliable. Data preceded by an asterisk have a relative standard error (RSE) greater than 30% and less than or equal to 50% and should be used with caution. Data not shown have an RSE greater than 50%.

      – Quantity zero.

      1 Respondents were asked in two separate questions if they had ever been told by a doctor or other health professional that they had emphysema or asthma. Respondents who had been told they had asthma were asked if they still had asthma. Respondents were asked in four separate questions if they had been told by a doctor or other health professional in the past 12 months that they had hay fever, sinusitis, bronchitis, or chronic pulmonary obstructive disease. A person may be represented in more than one column.

      2 Unknowns for the columns are not included in the denominators when calculating percentages. See Appendix I.

      3 Includes other races not shown separately and persons with unknown education, employment status, family income, poverty status, health insurance, and marital status characteristics. Estimates may not add to totals due to rounding.

      4 Refers to persons who indicated only a single race group, including those of Hispanic or Latino origin. See Appendix II.

      5 Refers to persons who indicated more than one race group, including those of Hispanic or Latino origin. Only two combinations of multiple-race groups are shown due to small sample sizes for other combinations.

      6 Refers to persons who are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons who are not of Hispanic or Latino origin, regardless of race.

      7 Shown only for adults aged 25 and over.

      8 GED is General Educational Development high school equivalency diploma.

      9 “Full-time” employment is 35 or more hours per week. "Part-time" employment is 34 or fewer hours per week. See Appendix II.

      10 Includes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      11 “Poor” persons are defined as having an income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      12 Based on a hierarchy of mutually exclusive categories. Adults with more than one type of health insurance were assigned to the first appropriate category in the hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. See Appendix II.

      13 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTES: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population.

      SOURCE: CDC/NCHS, National Health Interview Survey, 2012.

      Table 6 Frequencies of selected types of cancer among adults aged 18 and over, by selected characteristics: United States, 2012

      Table 7 Frequencies of selected diseases and conditions among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected characteristic

      Selected diseases and conditions

      All adults aged 18 and over

      Diabetes1

      Ulcers1

      Kidney disease2

      Liver disease2

      Arthritis diagnosis3

      Chronic joint symptoms3

      Number in thousands4

      Total5

      234,921

      21,319

      15,435

      3,882

      3,034

      51,830

      63,085

      Sex

      Male

      113,071

      10,357

      6,871

      1,882

      1,350

      20,878

      28,044

      Female

      121,850

      10,961

      8,564

      2,000

      1,684

      30,951

      35,041

      Age (years)

      18–44

      111,034

      2,673

      4,555

      633

      688

      7,582

      16,734

      45–64

      82,038

      10,273

      6,452

      1,548

      1,662

      24,223

      28,984

      65–74

      23,760

      4,863

      2,393

      746

      491

      11,111

      10,076

      75 and over

      18,089

      3,509

      2,035

      954

      193

      8,914

      7,291

      Race

      One race6

      230,994

      20,949

      14,997

      3,801

      2,878

      51,110

      61,960

      White

      188,261

      16,188

      12,809

      2,960

      2,472

      43,586

      52,649

      Black or African American

      27,943

      3,463

      1,527

      629

      265

      5,777

      6,731

      American Indian or Alaska Native

      1,916

      272

      114

      *59

      *

      323

      493

      Asian

      12,542

      1,005

      531

      150

      126

      1,377

      2,015

      Native Hawaiian or Other Pacific Islander

      332

      *21

      *

      *

      *

      *46

      *73

      Two or more races7

      3,926

      369

      438

      81

      156

      720

      1,125

      Black or African American, white

      778

      *28

      *61

      *

      *

      61

      132

      American Indian or Alaska Native, white

      1,611

      225

      263

      *46

      133

      428

      626

      Hispanic or Latino origin8 and race

      Hispanic or Latino

      34,946

      3,166

      1,679

      533

      422

      4,194

      6,382

      Mexican or Mexican American

      21,741

      1,953

      975

      352

      220

      2,292

      3,879

      Not Hispanic or Latino

      199,974

      18,153

      13,756

      3,349

      2,612

      47,635

      56,703

      White, single race

      156,173

      13,227

      11,269

      2,480

      2,097

      39,658

      46,870

      Black or African American, single race

      26,961

      3,382

      1,489

      617

      252

      5,690

      6,537

      Education9

      Less than a high school diploma

      28,311

      4,511

      2,696

      962

      540

      7,815

      8,529

      High school diploma or GED10

      52,795

      6,504

      3,965

      965

      851

      15,223

      16,871

      Some college

      59,577

      6,134

      5,042

      1,266

      969

      16,071

      18,991

      Bachelor’s degree or higher

      63,036

      3,850

      3,038

      551

      606

      11,883

      15,254

      Current employment status11

      Employed

      142,783

      7,763

      6,558

      795

      1,108

      20,807

      30,702

      Full-time

      114,915

      6,071

      5,127

      628

      880

      16,143

      24,197

      Part-time

      25,610

      1,553

      1,253

      157

      184

      4,129

      5,953

      Not employed but has worked previously

      78,811

      12,266

      8,299

      2,729

      1,614

      28,765

      29,835

      Not employed and has never worked

      13,135

      1,273

      566

      354

      306

      2,229

      2,510

      Family income12

      Less than $35,000

      74,224

      8,959

      6,018

      2,015

      1,382

      18,015

      22,333

      $35,000 or more

      146,587

      10,899

      8,601

      1,616

      1,456

      30,259

      36,921

      $35,000–$49,999

      31,186

      3,148

      2,273

      650

      352

      7,657

      8,991

      $50,000–$74,999

      39,348

      3,286

      2,453

      468

      432

      8,621

      10,285

      $75,000–$99,999

      27,052

      1,833

      1,621

      233

      253

      5,303

      6,652

      $100,000 or more

      49,001

      2,632

      2,254

      265

      419

      8,678

      10,993

      Poverty status13

      Poor

      30,576

      3,466

      2,431

      877

      682

      6,364

      8,375

      Near poor

      38,167

      4,048

      3,011

      1,016

      671

      8,574

      10,887

      Not poor

      147,021

      11,367

      8,710

      1,594

      1,424

      32,235

      38,637

      Health insurance coverage14

      Number in thousands4

      Under 65:

      Private

      125,065

      7,117

      5,900

      871

      1,057

      19,970

      28,099

      Medicaid

      19,101

      2,500

      1,675

      696

      566

      4,241

      5,608

      Other

      8,734

      1,337

      1,061

      234

      330

      3,143

      3,554

      Uninsured

      39,391

      1,974

      2,360

      375

      395

      4,372

      8,354

      65 and over:

      Private

      21,580

      4,075

      2,112

      754

      353

      10,764

      9,258

      Medicare and Medicaid

      2,546

      798

      264

      207

      103

      1,485

      1,264

      Medicare only

      14,327

      2,801

      1,647

      524

      167

      6,183

      5,367

      Other

      3,033

      659

      378

      210

      *60

      1,489

      1,381

      Uninsured

      286

      *23

      *

      *

      *

      58

      63

      Marital status

      Married

      124,149

      12,220

      8,334

      1,974

      1,434

      29,778

      34,829

      Widowed

      14,119

      2,703

      1,616

      632

      279

      7,039

      6,263

      Divorced or separated

      26,499

      3,266

      2,536

      629

      695

      7,946

      9,050

      Never married

      52,444

      2,205

      1,853

      448

      450

      4,445

      8,790

      Living with a partner

      17,367

      908

      1,086

      199

      170

      2,563

      4,080

      Place of residence15

      Large MSA

      125,511

      10,252

      7,020

      1,875

      1,491

      24,320

      29,880

      Small MSA

      72,095

      6,662

      5,135

      1,057

      1,016

      17,012

      20,810

      Not in MSA

      37,315

      4,406

      3,280

      950

      527

      10,497

      12,395

      Region

      Northeast

      42,760

      3,533

      2,049

      469

      519

      9,133

      10,121

      Midwest

      53,378

      4,701

      3,966

      1,049

      666

      13,003

      15,442

      South

      85,578

      9,091

      6,126

      1,598

      1,102

      19,301

      23,250

      West

      53,205

      3,994

      3,293

      767

      747

      10,392

      14,273

      Hispanic or Latino origin8, race, and sex

      Hispanic or Latino, male

      17,505

      1,551

      612

      283

      153

      1,497

      2,866

      Hispanic or Latina, female

      17,442

      1,615

      1,066

      250

      269

      2,697

      3,516

      Not Hispanic or Latino:

      White, single race, male

      75,739

      6,540

      5,190

      1,196

      962

      16,260

      21,311

      White, single race, female

      80,434

      6,686

      6,080

      1,284

      1,134

      23,398

      25,559

      Black or African American, single race, male

      12,022

      1,484

      619

      275

      107

      2,150

      2,558

      Black or African American, single race, female

      14,939

      1,898

      870

      342

      146

      3,540

      3,979

      * Estimates are considered unreliable. Data preceded by an asterisk have a relative standard error (RSE) greater than 30% and less than or equal to 50% and should be used with caution. Data not shown have an RSE greater than 50%.

      1 In separate questions, respondents were asked if they had ever been told by a doctor or other health professional that they had an ulcer (including a stomach, duodenal, or peptic ulcer) or diabetes (or sugar diabetes; female respondents were instructed to exclude pregnancy-related diabetes). Responses from persons who said they had “borderline” diabetes were treated as unknown with respect to diabetes. A person may be represented in more than one column.

      2 In separate questions, respondents were asked if they had been told in the last 12 months by a doctor or other health professional that they had: weak or failing kidneys (excluding kidney stones, bladder infections, or incontinence) or any kind of liver condition.

      3 Respondents were asked if they had ever been told by a doctor or other health professional that they had some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia. Those who answered yes were classified as having an arthritis diagnosis. Respondents were also asked: “During the past 30 days, have you had pain, aching or stiffness in or around a joint?” (excluding back and neck) and, if yes, “Did your joint symptoms first begin more than 3 months ago?” Respondents with symptoms that began more than 3 months ago were classified in this table as having chronic joint symptoms.

      4 Unknowns for the columns are not included in the frequencies, but they are included in the “All adults aged 18 and over” column. See Appendix I.

      5 Includes other races not shown separately and persons with unknown education, employment status, family income, poverty status, health insurance, and marital status characteristics. Estimates may not add to totals due to rounding.

      6 Refers to persons who indicated only a single race group, including those of Hispanic or Latino origin. See Appendix II.

      7 Refers to persons who indicated more than one race group, including those of Hispanic or Latino origin. Only two combinations of multiple-race groups are shown due to small sample sizes for other combinations.

      8 Refers to persons who are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons who are not of Hispanic or Latino origin, regardless of race.

      9 Shown only for adults aged 25 and over.

      10 GED is General Educational Development high school equivalency diploma.

      11“Full-time” employment is 35 or more hours per week. “Part-time” employment is 34 or fewer hours per week. See Appendix II.

      12 lncludes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      13“Poor” persons are defined as having income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      14 Based on a hierarchy of mutually exclusive categories. Adults with more than onu type of health insurance wuru assigned to thu first appropriate category in thu hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for onu type of service such as accidents or dental care. See Appendix II.

      15 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTE: Estimates are based on household interviews of a sample of thu civilian noninstitutionalized population.

      SOURCE: CDC/NCHS, National Health Interview Survey, 2012.

      Table 8 Age-adjusted percentages of selected diseases and conditions among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected diseases and conditions

      Diabetes1

      Ulcers1

      Kidney disease2

      Liver disease2

      Arthritis diagnosis3

      Chronic joint symptoms3

      Percent4 (standard error)

      Total5 (age-adjusted)

      8.6 (0.18)

      6.3 (0.17)

      1.6 (0.08)

      1.2 (0.07)

      20.6 (0.27)

      25.6 (0.32)

      Total5 (crude)

      9.2 (0.20)

      6.6 (0.18)

      1.7 (0.08)

      1.3 (0.07)

      22.1 (0.31)

      26.9 (0.34)

      Sex

      Male

      8.9 (0.26)

      6.0 (0.24)

      1.7 (0.13)

      1.1 (0.09)

      17.8 (0.36)

      24.1 (0.47)

      Female

      8.3 (0.23)

      6.7 (0.23)

      1.5 (0.10)

      1.3 (0.10)

      23.2 (0.36)

      27.0 (0.40)

      Age6 (years)

      18–44

      2.4 (0.16)

      4.1 (0.21)

      0.6 (0.07)

      0.6 (0.07)

      6.8 (0.29)

      15.1 (0.39)

      45–64

      12.7 (0.39)

      7.9 (0.33)

      1.9 (0.16)

      2.0 (0.15)

      29.6 (0.56)

      35.3 (0.58)

      65–74

      21.1 (0.79)

      10.1 (0.58)

      3.1 (0.32)

      2.1 (0.30)

      46.8 (1.01)

      42.5 (1.00)

      75 and over

      19.8 (0.90)

      11.3 (0.68)

      5.3 (0.50)

      1.1 (0.25)

      49.4 (1.11)

      40.4 (114)

      Race

      One race7

      8.5 (0.18)

      6.2 (0.17)

      1.6 (0.08)

      1.2 (0.07)

      20.6 (0.27)

      25.5 (0.32)

      White

      7.9 (0.20)

      6.5 (0.20)

      1.5 (0.09)

      1.2 (0.08)

      21.1 (0.30)

      26.3 (0.37)

      Black or African American

      13.1 (0.51)

      5.6 (0.39)

      2.5 (0.26)

      0.9 (0.14)

      21.4 (0.62)

      24.3 (0.78)

      American Indian or Alaska Native

      17.9 (2.55)

      5.9 (1.23)

      *3.6 (1.27)

      *

      18.7 (3.17)

      26.3 (2.77)

      Asian

      8.9 (0.78)

      4.5 (0.60)

      1.4 (0.30)

      1.1 (0.30)

      12.3 (0.84)

      16.9 (103)

      Native Hawaiian or Other Pacific Islander

      *7.3 (2.90)

      *

      *

      *

      *14.2 (4.46)

      *21.7 (7.80)

      Two or more races8

      13.1 (2.06)

      11.9 (1.82)

      *3.2 (1.07)

      4.9 (1.30)

      23.1 (2.17)

      32.9 (2.53)

      Black or African American, white

      *10.2 (4.06)

      *4.7 (1.90)

      *

      *

      16.3 (4.13)

      30.2 (3.91)

      American Indian or Alaska Native, white

      13.5 (2.71)

      15.5 (3.04)

      *2.4 (0.90)

      7.3 (1.92)

      25.2 (3.14)

      38.1 (3.69)

      Hispanic or Latino origin9 and race

      Hispanic or Latino

      12.2 (0.64)

      5.4 (0.42)

      1.9 (0.23)

      1.4 (0.19)

      16.1 (0.61)

      21.1 (0.68)

      Mexican or Mexican American

      13.1 (0.86)

      5.3 (0.52)

      2.1 (0.33)

      1.3 (0.25)

      15.6 (0.82)

      21.8 (0.90)

      Not Hispanic or Latino

      8.2 (0.19)

      6.5 (0.19)

      1.5 (0.08)

      1.2 (0.07)

      21.4 (0.30)

      26.5 (0.36)

      White, single race

      7.3 (0.21)

      6.7 (0.23)

      1.4 (0.10)

      1.2 (0.09)

      22.1 (0.35)

      27.6 (0.42)

      Black or African American, single race

      13.2 (0.52)

      5.6 (0.40)

      2.5 (0.26)

      0.9 (0.14)

      21.6 (0.63)

      24.4 (0.80)

      Education10

      Less than a high school diploma

      14.3 (0.64)

      8.9 (0.54)

      2.9 (0.29)

      1.9 (0.23)

      23.8 (0.76)

      27.9 (0.81)

      High school diploma or GED11

      11.1 (0.43)

      7.1 (0.36)

      1.6 (0.17)

      1.4 (0.16)

      25.7 (0.57)

      29.7 (0.67)

      Some college

      10.0 (0.38)

      8.3 (0.39)

      2.1 (0.19)

      1.6 (0.17)

      26.0 (0.57)

      30.7 (0.64)

      Bachelor’s degree or higher

      6.2 (0.30)

      4.9 (0.28)

      1.0 (0.13)

      0.9 (0.12)

      19.0 (0.49)

      24.1 (0.57)

      Current employment status12

      Employed

      6.7 (0.37)

      5.2 (0.31)

      0.7 (0.11)

      0.7 (0.08)

      17.0 (0.47)

      22.3 (0.50)

      Full-time

      6.8 (0.59)

      5.0 (0.47)

      0.9 (0.25)

      0.7 (0.10)

      16.0 (0.68)

      21.9 (0.70)

      Part-time

      7.3 (0.62)

      5.5 (0.52)

      0.7 (0.18)

      0.7 (0.16)

      18.7 (0.83)

      24.6 (0.96)

      Not employed but has worked previously

      11.7 (0.37)

      9.3 (0.38)

      2.6 (0.19)

      1.9 (0.15)

      27.2 (0.54)

      32.1 (0.62)

      Not employed and has never worked

      11.8 (1.03)

      5.0 (0.65)

      3.5 (0.71)

      3.1 (0.71)

      19.3 (1.14)

      22.0 (132)

      Family income13

      Less than $35,000

      11.8 (0.34)

      7.9 (0.30)

      2.6 (0.16)

      1.9 (0.14)

      22.8 (0.44)

      29.4 (0.52)

      $35,000 or more

      7.3 (0.23)

      5.8 (0.22)

      1.2 (0.10)

      1.0 (0.09)

      20.1 (0.36)

      24.2 (0.40)

      $35,000–$49,999

      9.4 (0.55)

      7.0 (0.50)

      2.0 (0.28)

      1.1 (0.16)

      22.6 (0.72)

      27.6 (0.80)

      $50,000–$74,999

      7.9 (0.43)

      6.2 (0.39)

      1.2 (0.16)

      1.0 (0.17)

      21.0 (0.66)

      25.1 (0.69)

      $75,000–$99,999

      7.1 (0.53)

      6.1 (0.59)

      1.2 (0.29)

      0.8 (0.17)

      19.8 (0.76)

      24.2 (0.89)

      $100,000 or more

      5.5 (0.44)

      4.8 (0.39)

      0.6 (0.15)

      1.0 (0.24)

      17.6 (0.68)

      21.7 (0.75)

      Poverty status14

      Poor

      13.7 (0.61)

      8.7 (0.49)

      3.4 (0.32)

      2.4 (0.26)

      24.3 (0.74)

      30.1 (0.85)

      Near poor

      11.0 (0.50)

      7.9 (0.44)

      2.7 (0.28)

      1.8 (0.21)

      22.4 (0.63)

      28.7 (0.77)

      Not poor

      7.1 (0.21)

      5.7 (0.21)

      1.1 (0.09)

      0.9 (0.08)

      20.0 (0.34)

      24.5 (0.39)

      Health insurance coverage15

      Percent4 (standard error)

      Under 65:

      Private

      5.0 (0.20)

      4.5 (0.20)

      0.6 (0.08)

      0.8 (0.07)

      14.0 (0.33)

      20.7 (0.40)

      Medicaid

      13.9 (0.78)

      9.0 (0.64)

      3.8 (0.45)

      3.1 (0.40)

      23.1 (0.95)

      30.2 (1.03)

      Other

      10.4 (1.14)

      8.5 (0.94)

      2.0 (0.45)

      2.5 (0.44)

      26.6 (1.64)

      33.6 (1.89)

      Uninsured

      5.5 (0.35)

      6.1 (0.42)

      1.0 (0.18)

      1.1 (0.15)

      11.9 (0.50)

      22.1 (0.72)

      65 and over:

      Private

      19.3 (0.82)

      9.8 (0.59)

      3.6 (0.38)

      1.6 (0.28)

      50.0 (1.05)

      42.9 (1.06)

      Medicare and Medicaid

      32.2 (2.39)

      10.3 (1.48)

      8.1 (1.28)

      4.0 (0.98)

      58.4 (2.49)

      49.7 (2.68)

      Medicare only

      20.0 (1.05)

      11.5 (0.84)

      3.8 (0.52)

      1.2 (0.31)

      43.4 (1.28)

      37.4 (1.26)

      Other

      22.6 (2.33)

      12.7 (1.83)

      7.0 (1.37)

      *2.0 (0.81)

      48.9 (2.65)

      45.4 (2.82)

      Uninsured

      *19.1 (4.02)

      *

      *

      *

      28.1 (7.48)

      29.6 (7.36)

      Marital status

      Married

      8.5 (0.26)

      6.3 (0.23)

      1.5 (0.12)

      1.0 (0.09)

      20.7 (0.38)

      25.2 (0.46)

      Widowed

      11.5 (1.62)

      7.8 (1.64)

      2.0 (0.43)

      1.1 (0.32)

      34.1 (3.90)

      33.0 (3.34)

      Divorced or separated

      10.2 (0.47)

      9.0 (0.59)

      2.1 (0.24)

      2.0 (0.25)

      24.8 (0.78)

      29.6 (0.80)

      Never married

      8.7 (0.57)

      4.5 (0.36)

      1.7 (0.32)

      1.3 (0.17)

      16.6 (0.73)

      24.1 (0.80)

      Living with a partner

      9.1 (1.16)

      7.2 (0.85)

      1.4 (0.31)

      1.2 (0.32)

      21.3 (1.30)

      28.7 (1.43)

      Place of residence16

      Large MSA

      8.1 (0.25)

      5.5 (0.23)

      1.5 (0.11)

      1.1 (0.10)

      18.8 (0.35)

      23.2 (0.42)

      Small MSA

      8.6 (0.34)

      6.8 (0.32)

      1.4 (0.12)

      1.3 (0.13)

      21.8 (0.49)

      27.4 (0.61)

      Not in MSA

      10.4 (0.42)

      8.2 (0.44)

      2.2 (0.24)

      1.3 (0.14)

      24.6 (0.79)

      30.6 (0.90)

      Region

      Northeast

      7.6 (0.40)

      4.6 (0.38)

      1.0 (0.14)

      1.1 (0.18)

      19.3 (0.57)

      21.8 (0.75)

      Midwest

      8.4 (0.39)

      7.2 (0.37)

      1.9 (0.20)

      1.2 (0.13)

      23.1 (0.66)

      27.8 (0.75)

      South

      10.0 (0.32)

      6.9 (0.31)

      1.8 (0.14)

      1.2 (0.10)

      20.9 (0.42)

      25.8 (0.49)

      West

      7.3 (0.32)

      6.1 (0.31)

      1.4 (0.16)

      1.3 (0.16)

      18.9 (0.49)

      26.1 (0.65)

      Hispanic or Latino origin9, race, and sex

      Hispanic or Latino, male

      12.5 (0.92)

      4.2 (0.57)

      2.3 (0.40)

      1.0 (0.22)

      12.2 (0.81)

      19.0 (1.03)

      Hispanic or Latina, female

      11.9 (0.77)

      6.7 (0.62)

      1.6 (0.25)

      1.7 (0.31)

      19.3 (0.85)

      22.9 (0.92)

      Not Hispanic or Latino:

      White, single race, male

      7.7 (0.30)

      6.5 (0.32)

      1.5 (0.15)

      1.2 (0.12)

      19.2 (0.47)

      26.4 (0.61)

      White, single race, female

      7.1 (0.28)

      7.0 (0.30)

      1.4 (0.12)

      1.3 (0.13)

      24.9 (0.47)

      28.6 (0.54)

      Black or African American, single race, male

      13.1 (0.82)

      5.6 (0.63)

      2.6 (0.47)

      0.8 (0.18)

      18.9 (0.94)

      21.6 (1.35)

      Black or African American, single race, female

      13.1 (0.68)

      5.8 (0.51)

      2.4 (0.33)

      1.0 (0.19)

      23.7 (0.81)

      26.5 (0.93)

      * Estimates are considered unreliable. Data preceded by an asterisk have a relative standard error (RSE) greater than 30% and less than or equal to 50% and should be used with caution. Data not shown have an RSE greater than 50%.

      1 In separate questions, respondents were asked if they had ever been told by a doctor or other health professional that they had an ulcer (including a stomach, duodenal, or peptic ulcer) or diabetes (or sugar diabetes; female respondents were instructed to exclude pregnancy-related diabetes). Responses from persons who said they had “borderline” diabetes were treated as unknown with respect to diabetes. A person may be represented in more than one column.

      2 In separate questions, respondents were asked if they had been told in the last 12 months by a doctor or other health professional that they had: weak or failing kidneys (excluding kidney stones, bladder infections, or incontinence) or any kind of liver condition.

      3 Respondents were asked if they had ever been told by a doctor or other health professional that they had some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia. Those who answered yes were classified as having an arthritis diagnosis. Respondents were also asked: “During the past 30 days, have you had pain, aching or stiffness in or around a joint?” (excluding back and neck) and, if yes, “Did your joint symptoms first begin more than 3 months ago?” Respondents with symptoms that began more than 3 months ago were classified in this table as having chronic joint symptoms.

      4 Unknowns for the columns are not included in the denominators when calculating percentages. See Appendix I.

      5 Includes other races not shown separately and persons with unknown education, employment status, family income, poverty status, health insurance, and marital status characteristics. Estimates may not add to totals due to rounding.

      6 Estimates for age groups are not age-adjusted.

      7 Refers to persons who indicated only a single race group, including those of Hispanic or Latino origin. See Appendix II.

      8 Refers to persons who indicated more than one race group, including those of Hispanic or Latino origin. Only two combinations of multiple-race groups are shown due to small sample sizes for other combinations.

      9 Refers to persons who are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons who are not of Hispanic or Latino origin, regardless of race.

      10 Shown only for adults aged 25 and over. Estimates are age-adjusted to the projected 2000 U.S. population as the standard population and using four age groups: 25–44, 45–64, 65–74, and 75 and over.

      11 GED is General Educational Development high school equivalency diploma.

      12 “Full-time” employment is 35 or more hours per week. “Part-time” employment is 34 or fewer hours per week. See Appendix II.

      13 Includes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      14 “Poor” persons are defined as having income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      15 Based on a hierarchy of mutually exclusive categories. Adults with more than one type of health insurance were assigned to the first appropriate category in the hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. See Appendix II.

      16 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTES: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population. Unless otherwise specified, estimates are age-adjusted to the projected 2000 U.S. population as the standard population using four age groups: 18–44, 45–64, 65–74, and 75 and over. For crude percentages, refer to Table VII in Appendix III.

      SOURCE: CDC/NCHS, National Health Interview Survey, 2012.

      Table 9 Frequencies of migraines or pain in neck, lower back, face, or jaw among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected characteristic

      All adults aged 18 and over

      Migraines or severe headaches1

      Pain in neck2

      Pain in lower back3

      Pain in face or jaw4

      Number in thousands5

      Total6

      234,921

      32,453

      33,515

      65,823

      11,326

      Sex

      Male

      113,071

      10,156

      13,102

      29,124

      3,677

      Female

      121,850

      22,296

      20,414

      36,699

      7,649

      Age (years)

      18–44

      111,034

      18,920

      12,528

      26,611

      5,457

      45–64

      82,038

      11,136

      15,053

      26,495

      4,296

      65–74

      23,760

      1,545

      3,452

      7,104

      963

      75 and over

      18,089

      851

      2,482

      5,613

      611

      Race

      One race7

      230,994

      31,587

      32,720

      64,290

      11,002

      White

      188,261

      26,040

      27,925

      54,218

      9,483

      Black or African American

      27,943

      3,972

      3,003

      6,996

      985

      American Indian or Alaska Native

      1,916

      338

      352

      549

      154

      Asian

      12,542

      1,162

      1,384

      2,412

      346

      Native Hawaiian or Other Pacific Islander

      332

      *76

      *56

      115

      *

      Two or more races8

      3,926

      865

      796

      1,533

      325

      Black or African American, white

      778

      117

      100

      264

      *52

      American Indian or Alaska Native, white

      1,611

      481

      441

      825

      224

      Hispanic or Latino origin9 and race

      Hispanic or Latino

      34,946

      4,689

      4,573

      8,940

      1,490

      Mexican or Mexican American

      21,741

      2,689

      2,569

      5,143

      871

      Not Hispanic or Latino

      199,974

      27,764

      28,942

      56,884

      9,836

      White, single race

      156,173

      21,803

      23,763

      45,999

      8,177

      Black or African American, single race

      26,961

      3,813

      2,888

      6,786

      966

      Education10

      Less than a high school diploma

      28,311

      4,394

      4,795

      9,480

      1,461

      High school diploma or GED11

      52,795

      6,542

      8,295

      16,756

      2,413

      Some college

      59,577

      9,684

      10,528

      18,982

      3,663

      Bachelor’s degree or higher

      63,036

      7,014

      7,826

      14,663

      2,385

      Current employment status12

      Employed

      142,783

      18,306

      17,476

      35,029

      5,646

      Full-time

      114,915

      14,152

      14,032

      27,730

      4,256

      Part-time

      25,610

      3,741

      3,088

      6,627

      1,237

      Not employed but has worked previously

      78,811

      12,267

      14,827

      28,139

      5,184

      Not employed and has never worked

      13,135

      1,875

      1,201

      2,630

      493

      Family income13

      Less than $35,000

      74,224

      12,712

      12,597

      24,638

      4,762

      $35,000 or more

      146,587

      18,249

      19,133

      37,918

      6,078

      $35,000–$49,999

      31,186

      4,365

      4,661

      9,228

      1,496

      $50,000–$74,999

      39,348

      5,151

      5,412

      11,167

      1,825

      $75,000–$99,999

      27,052

      3,403

      3,235

      6,583

      1,021

      $100,000 or more

      49,001

      5,330

      5,824

      10,940

      1,735

      Poverty status14

      Poor

      30,576

      6,504

      5,358

      10,566

      2,277

      Near poor

      38,167

      6,162

      6,330

      12,035

      2,380

      Not poor

      147,021

      17,402

      19,318

      38,168

      5,884

      Health insurance coverage15

      Number in thousands5

      Under 65:

      Private

      125,065

      16,630

      16,042

      30,735

      5,254

      Medicaid

      19,101

      4,749

      3,913

      7,745

      1,675

      Other

      8,734

      2,073

      2,179

      3,737

      736

      Uninsured

      39,391

      6,552

      5,400

      10,716

      2,059

      65 and over:

      Private

      21,580

      1,029

      3,128

      6,422

      739

      Medicare and Medicaid

      2,546

      249

      571

      1,011

      202

      Medicare only

      14,327

      857

      1,796

      4,183

      520

      Other

      3,033

      222

      406

      1,010

      99

      Uninsured

      286

      *40

      *29

      *

      *

      Marital status

      Married

      124,149

      15,509

      17,789

      34,811

      5,138

      Widowed

      14,119

      1,192

      2,346

      4,759

      731

      Divorced or separated

      26,499

      4,566

      5,199

      9,293

      1,929

      Never married

      52,444

      7,874

      5,438

      11,464

      2,508

      Living with a partner

      17,367

      3,272

      2,713

      5,416

      1,010

      Place of residence16

      Large MSA

      125,511

      16,380

      16,876

      33,392

      5,679

      Small MSA

      72,095

      10,453

      10,806

      20,742

      3,611

      Not in MSA

      37,315

      5,619

      5,834

      11,689

      2,037

      Region

      Northeast

      42,760

      5,100

      5,390

      11,332

      1,665

      Midwest

      53,378

      8,288

      8,122

      15,079

      2,986

      South

      85,578

      11,617

      11,471

      24,218

      4,049

      West

      53,205

      7,449

      8,533

      15,193

      2,627

      Hispanic or Latino origin9, race, and sex

      Hispanic or Latino, male

      17,505

      1,354

      1,769

      4,172

      601

      Hispanic or Latina, female

      17,442

      3,336

      2,805

      4,767

      889

      Not Hispanic or Latino:

      White, single race, male

      75,739

      7,142

      9,546

      20,945

      2,588

      White, single race, female

      80,434

      14,661

      14,217

      25,054

      5,589

      Black or African American, single race, male

      12,022

      931

      904

      2,393

      284

      Black or African American, single race, female

      14,939

      2,882

      1,984

      4,393

      682

      * Estimates are considered unreliable. Data preceded by an asterisk have a relative standard error (RSE) greater than 30% and less than or equal to 50% and should be used with caution. Data not shown have an RSE greater than 50%.

      1 Respondents were asked, “During the past three months, did you have a severe headache or migraine?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      2 Respondents were asked, “During the past three months, did you have neck pain?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      3 Respondents were asked, “During the past three months, did you have low back pain?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      4 Respondents were asked, “During the past three months, did you have facial ache or pain in the jaw muscles or the joint in front of the ear?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      5 Unknowns for the columns are not included in the frequencies, but they are included in the “All adults aged 18 and over” column. See Appendix I.

      6 Includes other races not shown separately and persons with unknown education, employment status, family income, poverty status, health insurance, and marital status characteristics. Estimates may not add to totals due to rounding.

      7 Refers to persons who indicated only a single race group, including those of Hispanic or Latino origin. See Appendix II.

      8 Refers to persons who indicated more than one race group, including those of Hispanic or Latino origin. Only two combinations of multiple-race groups are shown due to small sample sizes for other combinations.

      9 Refers to persons who are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons who are not of Hispanic or Latino origin, regardless of race.

      10 Shown only for adults aged 25 and over.

      11 GED is General Educational Development high school equivalency diploma.

      12“Full-time” employment is 35 or more hours per week. “Part-time” employment is 34 or fewer hours per week. See Appendix II.

      13 Includes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      14“Poor” persons are defined as having income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      15 Based on a hierarchy of mutually exclusive categories. Adults with more than one type of health insurance were assigned to the first appropriate category in the hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. See Appendix II.

      16 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTE: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population.

      SOURCE: CDC/NCHS, National Health Interview Survey, 2012.

      Table 10 Age-adjusted percentages of migraines or pain in neck, lower back, face, or jaw among adults aged 18 and over, by selected characteristics: United States, 2012

      Selected characteristic

      Migraines or severe headaches1

      Pain in neck2

      Pain in lower back3

      Pain in face or jaw4

      Percent5 (standard error)

      Total6 (age-adjusted)

      14.1 (0.26)

      13.9 (0.25)

      27.6 (0.34)

      4.8 (0.15)

      Total6 (crude)

      13.8 (0.26)

      14.3 (0.26)

      28.0 (0.34)

      4.8 (0.15)

      Sex

      Male

      9.0 (0.32)

      11.3 (0.33)

      25.4 (0.47)

      3.2 (0.20)

      Female

      18.9 (0.40)

      16.3 (0.36)

      29.6 (0.46)

      6.3 (0.23)

      Age7 (years)

      18–44

      17.1 (0.40)

      11.3 (0.32)

      24.0 (0.48)

      4.9 (0.22)

      45–64

      13.6 (0.43)

      18.4 (0.46)

      32.3 (0.56)

      5.2 (0.25)

      65–74

      6.5 (0.48)

      14.5 (0.66)

      29.9 (0.90)

      4.1 (0.36)

      75 and over

      4.7 (0.47)

      13.7 (0.74)

      31.1 (1.06)

      3.4 (0.40)

      Race

      One race8

      14.0 (0.26)

      13.8 (0.25)

      27.4 (0.34)

      4.8 (0.15)

      White

      14.3 (0.30)

      14.4 (0.30)

      28.3 (0.39)

      5.1 (0.18)

      Black or African American

      14.0 (0.62)

      10.7 (0.52)

      24.8 (0.73)

      3.5 (0.28)

      American Indian or Alaska Native

      17.7 (2.96)

      18.0 (2.70)

      29.3 (2.96)

      7.8 (1.74)

      Asian

      9.2 (0.78)

      11.4 (0.88)

      19.7 (1.09)

      2.8 (0.41)

      Native Hawaiian or Other Pacific Islander

      21.2 (6.12)

      17.0 (5.09)

      34.0 (8.19)

      *

      Two or more races9

      21.2 (2.18)

      20.9 (2.20)

      41.2 (2.74)

      8.4 (1.33)

      Black or African American, white

      15.9 (3.77)

      21.1 (3.57)

      28.9 (4.47)

      *5.8 (2.53)

      American Indian or Alaska Native, white

      30.2 (3.92)

      27.1 (3.67)

      50.8 (4.15)

      13.3 (2.66)

      Hispanic or Latino origin10 and race

      Hispanic or Latino

      12.9 (0.56)

      13.9 (0.59)

      26.5 (0.75)

      4.4 (0.34)

      Mexican or Mexican American

      11.9 (0.65)

      13.1 (0.77)

      24.6 (0.91)

      4.2 (0.44)

      Not Hispanic or Latino

      14.5 (0.29)

      14.0 (0.28)

      27.8 (0.37)

      5.0 (0.17)

      White, single race

      14.9 (0.34)

      14.7 (0.33)

      28.8 (0.45)

      5.4 (0.21)

      Black or African American, single race

      14.0 (0.63)

      10.7 (0.53)

      24.9 (0.74)

      3.6 (0.29)

      Education11

      Less than a high school diploma

      16.6 (0.77)

      16.7 (0.68)

      33.3 (0.90)

      5.1 (0.41)

      High school diploma or GED12

      12.9 (0.48)

      15.2 (0.54)

      31.1 (0.72)

      4.7 (0.31)

      Some college

      16.5 (0.53)

      17.4 (0.51)

      31.6 (0.66)

      6.1 (0.33)

      Bachelor’s degree or higher

      11.0 (0.41)

      12.2 (0.42)

      23.2 (0.56)

      3.8 (0.23)

      Current employment status13

      Employed

      11.8 (0.30)

      11.5 (0.32)

      24.2 (0.47)

      3.7 (0.17)

      Full-time

      11.4 (0.38)

      11.1 (0.35)

      23.6 (0.65)

      3.4 (0.19)

      Part-time

      13.6 (0.78)

      12.1 (0.67)

      25.9 (0.95)

      4.6 (0.44)

      Not employed but has worked previously

      20.1 (0.61)

      18.9 (0.54)

      35.5 (0.67)

      7.6 (0.39)

      Not employed and has never worked

      15.7 (1.22)

      10.4 (0.91)

      21.9 (1.25)

      4.3 (0.64)

      Family income14

      Less than $35,000

      17.8 (0.44)

      17.0 (0.42)

      33.2 (0.54)

      6.5 (0.29)

      $35,000 or more

      12.5 (0.33)

      12.6 (0.31)

      25.6 (0.44)

      4.1 (0.19)

      $35,000–$49,999

      14.5 (0.74)

      14.8 (0.74)

      29.3 (0.87)

      4.9 (0.42)

      $50,000–$74,999

      13.3 (0.67)

      13.4 (0.57)

      27.9 (0.77)

      4.6 (0.34)

      $75,000–$99,999

      12.3 (0.72)

      11.6 (0.65)

      24.5 (0.97)

      3.8 (0.40)

      $100,000 or more

      10.7 (0.56)

      11.2 (0.53)

      21.9 (0.77)

      3.6 (0.37)

      Poverty status15

      Poor

      20.5 (0.72)

      18.3 (0.70)

      35.7 (0.85)

      7.6 (0.49)

      Near poor

      16.4 (0.67)

      16.8 (0.62)

      31.9 (0.77)

      6.3 (0.40)

      Not poor

      12.2 (0.32)

      12.6 (0.31)

      25.5 (0.43)

      4.0 (0.18)

      Health insurance coverage16

      Percent5 (standard error)

      Under 65:

      Private

      13.8 (0.36)

      12.3 (0.33)

      24.0 (0.46)

      4.2 (0.20)

      Medicaid

      25.0 (1.05)

      21.0 (0.92)

      41.2 (1.16)

      8.9 (0.66)

      Other

      25.8 (2.20)

      21.4 (1.66)

      37.6 (2.02)

      8.3 (1.09)

      Uninsured

      16.6 (0.63)

      14.0 (0.59)

      27.6 (0.75)

      5.2 (0.38)

      65 and over:

      Private

      4.7 (0.45)

      14.5 (0.77)

      30.0 (1.04)

      3.4 (0.38)

      Medicare and Medicaid

      9.7 (1.56)

      22.3 (2.00)

      39.5 (2.42)

      7.9 (1.31)

      Medicare only

      5.8 (0.60)

      12.4 (0.78)

      29.1 (1.18)

      3.6 (0.43)

      Other

      7.3 (1.44)

      13.4 (1.73)

      33.3 (2.29)

      3.2 (0.82)

      Uninsured

      *21.3 (7.39)

      *19.6 (7.13)

      *19.2 (7.20)

      *

      Marital status

      Married

      13.1 (0.38)

      13.5 (0.35)

      27.3 (0.49)

      4.1 (0.21)

      Widowed

      21.6 (3.75)

      18.7 (3.13)

      30.9 (3.69)

      9.8 (2.70)

      Divorced or separated

      19.3 (0.92)

      19.0 (0.79)

      33.2 (0.92)

      7.2 (0.55)

      Never married

      13.5 (0.51)

      11.8 (0.53)

      24.0 (0.75)

      4.4 (0.29)

      Living with a partner

      16.9 (0.97)

      17.2 (1.21)

      32.4 (1.45)

      6.3 (1.05)

      Place of residence17

      Large MSA

      13.1 (0.35)

      13.1 (0.34)

      26.3 (0.46)

      4.5 (0.20)

      Small MSA

      15.0 (0.51)

      14.6 (0.48)

      28.3 (0.59)

      5.0 (0.27)

      Not in MSA

      15.8 (0.77)

      15.0 (0.63)

      30.7 (0.90)

      5.6 (0.42)

      Region

      Northeast

      12.3 (0.63)

      11.9 (0.64)

      25.7 (0.82)

      3.8 (0.30)

      Midwest

      15.8 (0.57)

      14.9 (0.53)

      28.0 (0.79)

      5.6 (0.36)

      South

      13.9 (0.43)

      13.0 (0.41)

      27.8 (0.54)

      4.8 (0.25)

      West

      14.0 (0.52)

      15.7 (0.52)

      28.2 (0.64)

      4.9 (0.30)

      Hispanic or Latino origin10, race, and sex

      Hispanic or Latino, male

      7.4 (0.59)

      11.0 (0.77)

      24.8 (1.08)

      3.3 (0.39)

      Hispanic or Latina, female

      18.4 (0.91)

      16.8 (0.85)

      28.1 (1.01)

      5.4 (0.52)

      Not Hispanic or Latino:

      White, single race, male

      9.8 (0.43)

      12.1 (0.43)

      27.1 (0.61)

      3.5 (0.27)

      White, single race, female

      19.8 (0.54)

      17.2 (0.49)

      30.4 (0.60)

      7.2 (0.33)

      Black or African American, single race, male

      7.5 (0.72)

      7.5 (0.65)

      19.7 (1.06)

      2.3 (0.36)

      Black or African American, single race, female

      19.3 (0.94)

      13.2 (0.78)

      29.1 (1.03)

      4.6 (0.44)

      * Estimates are considered unreliable. Data preceded by an asterisk have a relative standard error (RSE) greater than 30% and less than or equal to 50% and should be used with caution. Data not shown have an RSE greater than 50%.

      1 Respondents were asked, “During the past three months, did you have a severe headache or migraine?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      2 Respondents were asked, “During the past three months, did you have neck pain?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      3 Respondents were asked, “During the past three months, did you have low back pain?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      4 Respondents were asked, “During the past three months, did you have facial ache or pain in the jaw muscles or the joint in front of the ear?” Respondents were instructed to report pain that had lasted a whole day or more, and conversely, not to report fleeting or minor aches or pains. Persons may be represented in more than one column.

      5 Unknowns for the columns are not included in the denominators when calculating percentages. See Appendix I.

      6 includes other races not shown separately and persons with unknown education, employment status, family income, poverty status, health insurance, and marital status characteristics. Estimates may not add to totals due to rounding.

      7 Estimates for age groups are not age-adjusted.

      8 Refers to persons who indicated only a single race group, including those of Hispanic or Latino origin. See Appendix II.

      9 Refers to persons who indicated more than one race group, including those of Hispanic or Latino origin. Only two combinations of multiple-race groups are shown due to small sample sizes for other combinations.

      10 Refers to persons who are of Hispanic or Latino origin and may be of any race or combination of races. “Not Hispanic or Latino” refers to persons who are not of Hispanic or Latino origin, regardless of race.

      11 Shown only for adults aged 25 and over. Estimates are age-adjusted to the projected 2000 U.S. standard population using four age groups: 25–44, 45–64, 65–74, and 75 and over.

      12 GED is General Educational Development high school equivalency diploma.

      13“Full-time” employment is 35 or more hours per week. “Part-time” employment is 34 or fewer hours per week. See Appendix II.

      14 Includes persons who reported a dollar amount or who would not provide a dollar amount but provided an income interval. See Appendix I.

      15“Poor” persons are defined as having income below the poverty threshold. “Near poor” persons have incomes of 100% to less than 200% of the poverty threshold. “Not poor” persons have incomes that are 200% of the poverty threshold or greater. See Appendix I.

      16 Based on a hierarchy of mutually exclusive categories. Adults with more than one type of health insurance were assigned to the first appropriate category in the hierarchy. “Uninsured” includes adults who had no coverage, as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. See Appendix II.

      17 MSA is metropolitan statistical area. Large MSAs have a population of 1 million or more; small MSAs have a population of less than 1 million. “Not in MSA” consists of persons not living in a metropolitan statistical area.

      NOTES: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population. Unless otherwise specified, estimates are age-adjusted to the projected 2000 U.S. population as the standard population using four age groups: 18–44, 45–64, 65–74, and 75 and over. For crude percentages, refer to Table VIII in Appendix III.

      SOURCE: CDC/NCHS, National Health Interview Survey,2012.

      Table 11 Frequencies of hearing trouble, vision trouble, and absence of teeth among adults aged 18 and over, by selected characteristics: United States, 2012

      Information in these tables was drawn from the HIV Surveillance Report, vol. 25, produced by the Division of HIV/AIDS Prevention of the Centers for Disease Control and Prevention (CDC). The complete report may be accessed from http://www.cdc.gov/hiv/pdf/g-l/hiv_surveillance_report_vol_25.pdf. More information about HIV/AIDS is available from http://www.cdc.gov/hiv/default.html.

      Table 1a Diagnoses of HIV infection, by year of diagnosis and selected characteristics, 2009–2013—United States

      Table 2aStage 3(AIDS), by year of diagnosis and selected characteristics, 2009–2013 and cumulative—United States

      Table 3aDiagnoses of HIV infection, by race/ethnicity and selected characteristics, 2013—United States

      Table 4aStage 3(AIDS), by race/ethnicity and selected characteristics, 2013—United States

      Table 10aDeaths of persons with diagnosed HIV infection, by year of death and selected characteristics, 2009–2012—United States

      Table 11aDeaths of persons with diagnosed HIV infection ever classified as stage 3(AIDS), by year of death and selected characteristics, 2009–2012 and cumulative—United States

      Table 12a. Survival for more than 12, 24, and 36 months after a diagnosis of HIV infection during 2004–2009, by selected characteristics—United States

      Proportion survived (in months)

      No. of persons

      >12

      >24

      >36

      Age at diagnosis (yr)

      <13

      1,577

      0.98

      0.98

      0.98

      13–14

      271

      0.98

      0.98

      0.98

      15–19

      11,013

      0.99

      0.99

      0.98

      20–24

      33,984

      0.99

      0.98

      0.98

      25–29

      38,137

      0.98

      0.97

      0.96

      30–34

      37,674

      0.97

      0.96

      0.95

      35–39

      42,776

      0.96

      0.94

      0.93

      40–44

      43,990

      0.94

      0.93

      0.91

      45–49

      34,490

      0.92

      0.89

      0.88

      50–54

      22,290

      0.89

      0.86

      0.84

      55–59

      12,724

      0.86

      0.83

      0.80

      60–64

      6,039

      0.82

      0.78

      0.75

      65

      5,157

      0.73

      0.67

      0.62

      Race/ethnicity

      American Indian/Alaska Native

      1,010

      0.91

      0.90

      0.88

      Asian

      3,878

      0.95

      0.95

      0.94

      Black/African American

      135,131

      0.94

      0.92

      0.90

      Hispanic/Latinoa

      57,987

      0.95

      0.94

      0.93

      Native Hawaiian/Other Pacific Islander

      365

      0.96

      0.94

      0.93

      White

      82,192

      0.95

      0.93

      0.92

      Multiple races

      9,559

      0.95

      0.93

      0.92

      Transmission category Male adult or adolescent

      Male-to-male sexual contact

      127,941

      0.97

      0.96

      0.95

      Injection drug use

      14,360

      0.90

      0.87

      0.84

      Male-to-male sexual contact and injection drug use

      9,927

      0.96

      0.95

      0.93

      Heterosexual contactb

      21,013

      0.94

      0.91

      0.90

      Otherc

      43,715

      0.88

      0.86

      0.84

      Subtotal

      216,956

      0.94

      0.93

      0.91

      Female adult or adolescent

      Injection drug use

      8,465

      0.93

      0.90

      0.88

      Heterosexual contactb

      36,159

      0.96

      0.95

      0.94

      Otherc

      26,965

      0.92

      0.90

      0.89

      Subtotal

      71,589

      0.94

      0.93

      0.91

      Child (<13 yrs at diagnosis)

      Perinatal

      1,288

      0.98

      0.98

      0.98

      Otherd

      289

      0.99

      0.99

      0.99

      Subtotal

      1,577

      0.98

      0.98

      0.98

      Region of residence

      Northeast

      59,549

      0.94

      0.93

      0.92

      Midwest

      35,380

      0.95

      0.94

      0.93

      South

      144,548

      0.94

      0.92

      0.90

      West

      50,645

      0.95

      0.94

      0.93

      Year of diagnosis

      2004

      49,135

      0.93

      0.91

      0.90

      2005

      48,455

      0.94

      0.92

      0.90

      2006

      48,752

      0.94

      0.92

      0.91

      2007

      49,749

      0.95

      0.93

      0.92

      2008

      48,323

      0.95

      0.94

      0.92

      2009

      45,708

      0.95

      0.94

      0.93

      Total

      290,122

      0.94

      0.93

      0.91

      Note. Data include persons with a diagnosis of HIV infection regardless of stage of disease at diagnosis. Data exclude persons whose month of diagnosis or month of death is unknown.

      See Technical Notes for method for calculating proportion of persons surviving.

      a Hispanics/Latinos can be of any race.

      b Heterosexual contact with a person known to have, or to be at high risk for, HIV infection.

      c Includes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.

      d Includes hemophilia, blood transfusion, and risk factor not reported or not identified.

      Table 12b. Survival for more than 12, 24, and 36 months after a diagnosis of HIV infection during 2004–2009, by selected characteristics—United States and 6 dependent areas

      Proportion survived (in months)

      No.of persons

      >12

      >24

      >36

      >13

      1,609

      0.98

      0.98

      0.98

      13–14

      281

      0.98

      0.98

      0.98

      15–19

      11,156

      0.99

      0.99

      0.98

      >0–24

      34,482

      0.99

      0.98

      0.98

      >5–29

      38,896

      0.98

      0.97

      0.96

      30–34

      38,519

      0.97

      0.96

      0.95

      5–39

      43,717

      0.95

      0.94

      0.93

      0–44

      44,962

      0.94

      0.92

      0.91

      5–49

      35,272

      0.92

      0.89

      0.87

      0–54

      22,870

      0.89

      0.86

      0.83

      5–59

      13,074

      0.86

      0.82

      0.80

      50–64

      6,232

      0.82

      0.78

      0.74

      65

      5,398

      0.73

      0.67

      0.62

      Race/ethnicity

      American Indian/Alaska Native

      1,010

      0.91

      0.90

      0.88

      Asian

      3,879

      0.95

      0.95

      0.94

      Black/African American

      135,251

      0.94

      0.92

      0.90

      Hispanic/Latinoa

      64,179

      0.94

      0.93

      0.92

      Native Hawaiian/Other Pacific Islander

      374

      0.95

      0.94

      0.93

      White

      82,208

      0.95

      0.93

      0.92

      Multiple races

      9,567

      0.95

      0.93

      0.92

      Transmission category Male adult or adolescent

      Male-to-male sexual contact

      129,286

      0.97

      0.96

      0.95

      Injection drug use

      15,845

      0.89

      0.86

      0.83

      Male-to-male sexual contact and injection drug use

      10,146

      0.96

      0.95

      0.93

      Heterosexual contactb

      22,065

      0.93

      0.91

      0.89

      Otherc

      44,021

      0.88

      0.86

      0.84

      Subtotal

      221,363

      0.94

      0.92

      0.91

      Female adult or adolescent

      Injection drug use

      8,820

      0.93

      0.90

      0.87

      Heterosexual contactb

      37,542

      0.96

      0.95

      0.93

      Otherc

      27,134

      0.92

      0.90

      0.89

      Subtotal

      73,496

      0.94

      0.93

      0.91

      Child (<13 yrs at diagnosis)

      Perinatal

      1,315

      0.98

      0.98

      0.98

      Otherd

      294

      0.99

      0.99

      0.99

      Subtotal

      1,609

      0.98

      0.98

      0.98

      Region of residence

      ortheast

      59,549

      0.94

      0.93

      0.92

      Midwest

      35,380

      0.95

      0.94

      0.93

      outh

      144,548

      0.94

      0.92

      0.90

      West

      50,645

      0.95

      0.94

      0.93

      J.S. dependent areas

      6,346

      0.86

      0.84

      0.82

      Year of diagnosis

      2004

      50,302

      0.93

      0.91

      0.89

      2005

      49,711

      0.94

      0.92

      0.90

      2006

      49,841

      0.94

      0.92

      0.91

      2007

      50,738

      0.95

      0.93

      0.92

      2008

      49,301

      0.95

      0.93

      0.92

      2009

      46,575

      0.95

      0.94

      0.93

      Total

      296,468

      0.94

      0.93

      0.91

      Note. Data include persons with a diagnosis of HIV infection regardless of stage of disease at diagnosis. Data exclude persons whose month of diagnosis or month of death is unknown.

      See Technical Notes for method for calculating proportion of persons surviving.

      a Hispanics/Latinos can be of any race.

      b Heterosexual contact with a person known to have, or to be at high risk for, HIV infection.

      c Includes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.

      d Includes hemophilia, blood transfusion, and risk factor not reported or not identified.

      Information in this table was reproduced from the Centers for Disease Control and Prevention?s (CDC?s) Morbidity and Mortality Weekly Report and drawn from the 2010-?2012 National Health Interview Survey (NHIS), a survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). More information about the NHIS is available from http://www.cdc.gov/nchs/nhis/about_nhis.htm.

      TABLE. Unadjusted and age-adjusted* annualized prevalence of doctor-diagnosed arthritis and arthritis attributable activity limitation AAAL) among adults aged 18 years, and prevalence of AAAL among thoss with, doctor-diagnosed arthritis, by selected characteristics—National Healh Interview Survey,United States,2010–2012

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