[Skip to Content]
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
From the Centers for Disease Control and Prevention
July 5, 2000

Heat-Related Illnesses, Deaths, and Risk Factors—Cincinnati and Dayton, Ohio, 1999, and United States, 1979-1997

JAMA. 2000;284(1):34-35. doi:10.1001/jama.284.1.34
Heat-Related Illnesses, Deaths, and Risk Factors—Cincinnati and Dayton, Ohio, 1999, and United States, 1979-1997

MMWR. 2000;49:470-473

1 figure omitted

During the summer of 1999, a heat wave* occurred in the midwestern and eastern United States. This period of hot and humid weather persisted from July 12 through August 1, 1999, and caused or contributed to 22 deaths among persons residing in Cincinnati (18 deaths) and Dayton (four deaths). A CDC survey of 24 U.S. metropolitan areas indicated that Ohio recorded some of the highest rates for heat-related deaths during the 1999 heat wave, with Cincinnati reporting 21 per million and Dayton reporting seven per million (CDC, unpublished data, 1999). This report describes four heat-related deaths representative of those that occurred in Cincinnati or Dayton during the 1999 heat wave, summarizes heat-related deaths in the United States during 1979-1997, describes risk factors associated with heat-related illness and death, and recommends preventive measures.

Case Reports

Case 1. In July 1999, a 34-year-old woman with schizophrenia was found dead in a group home in Cincinnati at 9 a.m. A caretaker discovered the decedent lying on the couch of a second-floor living room; two windows were open and fans were blowing. The decedent was last seen alive around noon the previous day. She had a medical history of hypertensive heart disease, asthma, and swelling of the ankles for which she had been taking a diuretic, furosemide. The temperature inside the home at the time of her death was unknown; however, the ambient temperature was 92.1 F (33.4 C) when the decedent was found. Her liver core temperature was 106.2 F (41.2 C). The Hamilton County Coroner's Office attributed the death to heatstroke.

Case 2. In July 1999, an 84-year-old man was found dead in his Dayton residence. He lived alone and was found lying in bed, supine and nude. The doors to his home were locked and all the windows were shut. When the body was discovered, the temperature inside the home was approximately 86 F (30 C). A fan was blowing air toward the ceiling, an air conditioner was present but not running, and the thermostat was set in the heat mode. The temperature in Dayton that day reached greater than 90 F (greater than 32 C) with high humidity. An autopsy report indicated the decedent suffered from arteriosclerosis and hypertensive cardiovascular disease. The Montgomery County Coroner's Office attributed the death to exposure to excessive environmental heat.

Case 3. In July 1999, a 65-year-old man was found in his residence by a neighbor, unresponsive and having seizures. Following transport to the emergency department of a local hospital by the Cincinnati Fire Division, the patient had a rectal temperature of 108 F (42.2 C) and subsequently died. The decedent had a history of chronic alcoholism and hypertensive cardiovascular disease. He lived alone in an attic apartment without air conditioning. The Hamilton County Coroner's Office attributed the death to hypoxic encephalopathy following resuscitation for heatstroke.

Case 4. In August 1999, a 24-year-old man was found lying face down on the living room floor of his Dayton apartment in an early stage of decomposition. The room temperature was 99 F (37.2 C), and the apartment had no air conditioning. The decedent lived alone and was last seen alive 3 days earlier at his home by a neighbor. The decedent had a history of mental illness and depression and had been taking benztropine. The Montgomery County Coroner's report listed the probable cause of death as cardiac arrhythmia caused by hyperthermia resulting from exposure to high environmental temperature.

United States

During 1979-1997, the most recent years for which data are available, an annual average of 371 deaths in the United States1 were attributable to "excessive heat exposure"† (median: 249; range: 148 in 1979 to 1700 in 1980).5 This translates into a mean annual death rate of 1.5 per million and a median annual death rate of one per million. Because of a record heat wave, the heat-related death rate for 1980 was more than three times higher than that for any other year during the 19-year period. The median annual death rate for hyperthermia in persons aged greater than or equal to 65 years was three per million. During 1979-1997, 7046 deaths were attributable to excessive heat exposure: 3010 (43%) were "due to weather conditions," 351 (5%) to heat "of manmade origin," and 3683 (52%) "of unspecified origin." Of the 2954 persons whose deaths were caused by weather conditions and for whom age data were available, persons aged greater than or equal to 65 years accounted for 1783 (44%) deaths, and persons aged less than or equal to 14 years accounted for 127 (4%) deaths. Except children aged less than or equal to 14 years, the average annual rate of heat-related deaths increased with each age group, particularly for persons aged greater than or equal to 65 years. During 1979-1997, among persons of all ages, the annual death rate "due to weather conditions" was two times higher for men (0.8 per million) than for women (0.4 per million), and more than three times higher for blacks (1.6 per million) than for whites (0.5 per million). Arizona and Missouri (four per million) and Arkansas and Kansas (three per million) had the highest annual age-adjusted rates for heat-related deaths "due to weather conditions."1

Reported by:

MP Adcock, PhD, City of Cincinnati. WH Bines, MS, Montgomery County; FW Smith, MD, State Epidemiologist, Ohio Dept of Health. Health Studies Br, Div of Environmental Hazards and Health Effects, National Center for Environmental Health; and an EIS Officer, CDC.

CDC Editorial Note:

Behavioral and environmental precautions are essential to preventing illness and death‡ associated with heat waves or sustained periods of hot weather (daytime heat index§ of greater than or equal to 105 F [greater than or equal to 40.6 C] and a nighttime minimum temperature of 80 F [26.7 C] persisting for at least 48 hours).6

Illnesses associated with high environmental temperatures include heatstroke (hyperthermia), heat exhaustion, heat syncope, and heat cramps.2 Heatstroke is a medical emergency characterized by the rapid onset and increase (within minutes) of the core body temperature to greater than or equal to 105 F (greater than or equal to 40.6 C), lethargy, disorientation, delirium, and coma.2 Heatstroke is often fatal despite rapidly lowering the body temperature (e.g., ice baths), because frequently irreparable neurologic damage has occurred.2 Heat exhaustion is characterized by dizziness, weakness, or fatigue often following several days of sustained exposure to hot temperatures, and results from dehydration or electrolyte imbalance2; treatment includes replacing fluids and electrolytes and may require hospitalization.2 Physical exertion during hot weather increases the likelihood of heat syncope and heat cramps caused by peripheral vasodilation.2 Persons who lose consciousness because of heat syncope should be placed in a recumbent position with feet elevated and given fluid and electrolyte replacement.2 For heat cramps, physical exertion should be discontinued and fluids and electrolytes replaced.2,7

All persons are at risk for hyperthermia when exposed to a sustained period of excessive heat2; however, factors that increase the risk for hyperthermia and heat-related death include age (e.g., the elderly), chronic health conditions (e.g., cardiovascular disease or respiratory diseases), mental illness (e.g., schizophrenia), social circumstances (e.g., living alone), and other conditions that might interfere with the ability to care for oneself.2,3 Other risk factors are alcohol consumption, which may cause dehydration, previous heatstroke, physical exertion in exceptionally hot environments, the use of medications that interfere with the body's heat regulatory system, such as neuroleptics (e.g., antipsychotics and major tranquilizers), and medications with anticholinergic effects (e.g., tricyclic antidepressants, antihistamines, some antiparkinsonian agents, and some over-the-counter sleep medication).24 Persons working in hot indoor or outdoor environments should take 10-14 days to acclimate to high temperatures.

Although adequate salt intake is important, salt tablets are not recommended and can be hazardous to some persons.2 Although the use of fans may increase comfort at temperatures less than 90 F (less than 32.2 C), fans are not protective against heatstroke when temperatures reach greater than or equal to 90 F (greater than or equal to 32.2 C) and humidity exceeds 35%.2,4

Measures for preventing heat-related illness and death during a heat wave include spending time in air conditioned environments, increasing nonalcoholic fluid intake, exercising only during cooler parts of the day, and taking cool baths.2 Elderly persons should be encouraged to take advantage of air conditioned environments (e.g., shopping malls, senior centers, and public libraries), even for part of the day.24 Public health information about exceptionally high temperatures should be directed toward persons aged greater than or equal to 65 years and less than 5 years. Parents should be educated about the heat sensitivity of children aged less than 5 years,2 and should never leave them unattended, especially in motor vehicles. When a heat wave is predicted, friends, relatives, neighbors, and caretakers should check frequently on elderly, disabled, mentally ill, chronically ill, and home-bound persons, and during periods of high temperatures, prevention messages should be disseminated to the public as early and often as possible.

National Center for Health Statistics.  Compressed mortality file . Atlanta, Georgia: US Department of Health and Human Services, CDC, 2000.
Kilbourne EM. Heat waves and hot environments. In: Noji EK, ed. The public health consequences of disasters . New York: Oxford University Press, 1997:245-69.
Kilbourne EM, Choi K, Jones TS, Thacker SB.Field Investigation Team.  Risk factors for heat-stroke: a case-control study.  JAMA.1982;247:3332-6.
Lee DH. Seventy-five years of searching for a heat index.  Environ Res.1980;22:331-56.
Donoghue ER, Graham MA, Jentzen JM.  et al.  Criteria for the diagnosis of heat-related deaths: National Association of Medical Examiners.  Am J Forensic Med Pathol.1997;18:11-4.
Semenza JC, Rubin CH, Falter KH.  et al.  Risk factors for heat-related mortality during the July 1995 heat wave in Chicago.  N Engl J Med.1996;35:84-90.
Huston CS. Heat cramps. In: Berkow R, ed. The Merck manual . Seventh ed. Rahaway, New Jersey: Merck & Company, Inc., 1992:2511.

*Three or more consecutive days of air temperatures greater than or equal to 90 F (greater than or equal to 32.2 C).

†The National Association of Medical Examiners' (NAME) definition for heat-related death includes exposure to high ambient temperature either causing the death or as substantially contributing to it, cases where the body temperature at time of collapse was greater than or equal to 105 F (greater than or equal to 40.6 C), and a history of exposure to high ambient temperature and the reasonable exclusion of other causes of hyperthermia.1 Because death rates from other causes (e.g., cardiovascular and respiratory disease) increase during heat waves24 (defined by the National Weather Service as greater than or equal to 3 consecutive days of temperature greater than 90 F [greater than or equal to 32.2 C]), deaths classified as caused by hyperthermia represent only a portion of heat-related death.

‡Underlying cause of death attributed to "excessive heat exposure," classified according to the International Classification of Diseases, Ninth Revision (ICD-9), code E900.0, "due to weather conditions" (deaths); code E900.1, "of manmade origin" (deaths); or code E900.9, "of unspecified origin" (deaths). Data were obtained from the Compressed Mortality File of CDC's National Center for Health Statistics, which contains information from death certificates filed in 50 states and the District of Columbia. All rates were age-standardized to the 1990 U.S. population.

§Heat index is a measure of the effect of combined elements (e.g., heat and humidity) on the body.

Prevalence of Selected Cardiovascular Disease Risk Factors Among American Indians and Alaska Natives—United States, 1997

MMWR. 2000;49:461-465

1 table omitted

Heart disease and stroke, the principal causes of cardiovascular disease (CVD), are the first and fifth leading causes of death among American Indians and Alaska Natives (AI/AN).1,2 Risk factors for CVD frequently cluster, which may increase CVD risk multiplicatively.3 To characterize the prevalence of risk factors for CVD (i.e., hypertension, current cigarette smoking, high cholesterol, obesity, and diabetes) among AI/AN, CDC analyzed data from the 1997 Behavioral Risk Factor Surveillance System (BRFSS). This report summarizes the results of that analysis, which indicated that 63.7% of AI/AN men and 61.4% of AI/AN women who participated in the survey had one or more CVD risk factors.

BRFSS is an ongoing state-based, random-digit-dialed telephone survey of the U.S., noninstitutionalized civilian population. Self-reported data were analyzed for the 1820 AI/AN aged greater than or equal to 18 years who participated in the 1997 BRFSS in 50 states and the District of Columbia (DC). Identification of race as AI/AN was based on response to the question, "What is your race?" Awareness of hypertension, high cholesterol, and diabetes was determined by the response to, "Have you even been told by a doctor or other health professional that you have (hypertension, high cholesterol, diabetes)?" Current smoking status was defined as having smoked at least 100 cigarettes during one's lifetime and still smoking at the time of the survey. Self-reported data on height and weight were used to calculate body mass index (BMI). Obesity was defined as a BMI greater than or equal to 30 kg/m2. Persons defined as employed were either employed for wages or self-employed, regardless of the number of hours spent on the job. The 50 states and DC were grouped into the four geographic regions defined by the U.S. Bureau of the Census.1 Sample estimates were weighted by sex, age, and race to reflect the state's noninstitutionalized civilian population. To account for the complex sampling design, SUDAAN was used for data analysis.4

Of the 1820 AI/AN BRFSS participants, 46.3% were women; 63.3% were aged 18-44 years, 25.6% were 45-64 years, and 11.1% were ≥ 65 years (mean: 42.4 years; standard deviation=16.2); 15.9% were college graduates; 60.2% were employed; and 49.8% ranked their health status as excellent or very good. The largest percentage of AI/AN participants in the BRFSS lived in the West (47.4%), followed by the South (25.9%), the Midwest (17.4%) and the Northeast (9.3%).*

Approximately 22% of participants reported being told by a health professional that they had hypertension (women=23.0%, men=21.0%). Thirty-one percent reported they were current smokers (men=32.8%; women=28.8%). Approximately 16% were told by a health professional that they had high cholesterol, and 7% were told they had diabetes. Awareness of high cholesterol and diabetes was higher among women (17.6% and 9.1%, respectively) than men (13.8% and 5.5%, respectively). Nearly one fourth (23.6%) of men and nearly one fifth (19.1%) of women were categorized as obese (21.5% of all AI/AN).

Among AI/AN men, 36.3% reported having none of the selected CVD risk factors, 41.4% reported having one risk factor, and 22.3% reported having ≥ 2 risk factors. Among AI/AN women, 38.6% reported having no CVD risk factors, 37.7% reported having one risk factor, and 23.7% reported having ≥ 2 risk factors.

The prevalence of having one or more CVD risk factors increased with increasing age. The prevalence of having ≥ 2 risk factors was highest among respondents aged ≥ 65 years. The prevalence of having ≥ 2 CVD risk factors varied inversely with level of education. Approximately 25% of AI/AN men with less than a high school education reported having ≥ 2 CVD risk factors, compared with approximately 15% of AI/AN men who were college graduates. AI/AN women with less than a high school education were almost three times more likely to report having ≥ 2 risk factors than were AI/AN women who had graduated from college. The percentage of having ≥ 2 risk factors was almost three times higher among unemployed women than employed women.

Half of the respondents who reported their health status as fair or poor reported having ≥ 2 CVD risk factors (women=51.8%; men=50.0%) compared with approximately one eighth of respondents who reported their health status as excellent or very good (women=13.3%; men=13.2%).

The number of reported CVD risk factors varied by geographic region. For men, the prevalence of having ≥ 2 risk factors was highest in the Midwest (26.1%) and lowest in the Northeast (13.8%). Less geographic variation was observed among women. The prevalence of having ≥ 2 risk factors was highest in the Northeast (28.0%) and lowest in the West (20.0%).

Reported by:

The following BRFSS coordinators: S Reese, MPH, Alabama; P Owen, Alaska; B Bender, MBA, Arizona; G Potts, MBA, Arkansas; B Davis, PhD, California; M Leff, MSPH, Colorado; M Adams, MPH, Connecticut; F Breukelman, Delaware; I Bullo, District of Columbia;'s Hoecherl, Florida; L Martin, MS, Georgia; F Reyes-Salvail, MS, Hawaii; J Aydelotte, MA, Idaho; B Steiner, MS, Illinois; L Stemnock, Indiana; K MacIntyre, Iowa; C Hunt, Kansas; T Sparks, Kentucky; B Bates, MSPH, Louisiana; D Maines, Maine; A Weinstein, MA, Maryland; D Brooks, MPH, Massachusetts; H McGee, MPH, Michigan; N Salem, PhD, Minnesota; D Johnson, MS, Mississippi; J Jackson-Thompson, PhD, Missouri; P Feigley, PhD, Montana; L Andelt, PhD, Nebraska; E DeJan, MPH, Nevada; L Powers, MA, New Hampshire; G Boeselager, MS, New Jersey; W Honey, MPH, New Mexico; C Baker, New York; P Buescher, PhD, North Carolina; L Shireley, MPH, North Dakota; P Pullen, Ohio; K Baker, MPH, Oklahoma; J Grant-Worley, MS, Oregon; L Mann, Pennsylvania; J Hesser, PhD, Rhode Island; M Wu, MD, South Carolina; M Gildemaster, South Dakota; D Ridings, Tennessee; K Condon, Texas; K Marti, Utah; C Roe, MS, Vermont; K Carswell, MPH, Virginia; K Wynkoop Simmons, PhD, Washington; F King, West Virginia; P Imm, MS, Wisconsin; M Futa, MA, Wyoming. Div of Applied Public Health Training, Epidemiology Program Office; Cardiovascular Health Br, Div of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion; and an EIS Officer, CDC.

CDC Editorial Note:

The findings in this report document the prevalence of selected CVD risk factors among AI/AN by sociodemographic characteristics and are consistent with previous findings that CVD risk factors and death rates are not uniformly distributed across regions among AI/AN.2,5 Higher CVD death rates have been reported among AI/AN residing in the Midwest2; data from this study indicate that AI/AN men residing in the Midwest were most likely to report having ≥ 2 CVD risk factors. Geographic variation in risk factors and death rates may reflect differences in cultural backgrounds, historical circumstances, and socioeconomic conditions. Prevalence estimates probably are influenced by sociodemographic factors (i.e., age distribution, educational attainment, employment status, and poverty), lifestyle (i.e., physical inactivity), aspects of the social environment (i.e., educational and economic opportunities), and factors affecting the health-care system (i.e., access to health care, cost, and availability of screening for diseases and risk factors). Higher prevalences of multiple CVD risk factors among AI/AN participants who were either unemployed or had completed less than a high school education corroborate the well-documented influence of low socioeconomic status on CVD risk factors.

The findings in this report are subject to at least five limitations. First, estimates of CVD risk factors are based on self-reported data and are subject to the biases associated with self-reported data. Second, these results probably underestimate the prevalence of CVD risk factors because the data are dependent on the respondent being aware of his risk factor profile. Third, data on physical inactivity, a risk factor for CVD, was not collected in the 1997 BRFSS survey. If data on physical activity levels had been included, the prevalence of CVD risk factors among AI/AN probably would have been higher. Fourth, approximately 23% of AI/AN households do not have a telephone6; these findings could underestimate the prevalence of CVD risk factors among AI/AN because persons without telephones are more likely to be of lower socioeconomic status and to have higher risk for disease.7 Finally, BRFSS does not collect information on reservation residency or tribal affiliation. Aggregating the AI/AN participants into relatively large geographic regions may mask important differences among the tribes.

The percentages of AI/AN with multiple CVD risk factors highlight the importance of enhancing primary prevention activities among communities of AI/AN. Through CDC's Racial and Ethnic Approaches to Community Health (REACH 2010) Project,8 two AI/AN communities are developing effective and sustainable programs designed to eliminate racial/ethnic disparities in CVD and diabetes. Another activity is the Inter-Tribal Heart Project, a collaboration between CDC, the Indian Health Service, and three tribal communities to determine the prevalence of risk factors for heart disease and to implement community-based heart disease prevention programs.9 Reducing the prevalence of CVD risk factors among AI/AN requires an understanding of the diversity of cultural values and practices among AI/AN, and historical circumstances that contributed to the current socioeconomic conditions. Therefore, tribal-specific assessments of CVD risk factor profiles and CVD morbidity and mortality profiles are needed to develop culturally relevant CVD prevention programs and policies that support heart-healthy living and working conditions for AI/AN.

US Department of Health and Human Services.  Health, United States, 1998, with socioeconomic status and health chartbook . Hyattsville, Maryland: US Department of Health and Human Services, CDC, 1998.
US Department of Health and Human Services.  Regional differences in Indian health, 1998-1999 . Rockville, Maryland: US Department of Health and Human Services, Indian Health Service, Office of Public Health, 2000.
Yusuf HR, Giles WH, Croft JB, Anda RF, Casper ML. Impact of multiple risk factor profiles on determining cardiovascular disease risk.  Prev Med.1998;27:1-9.
Shah BV, Barnwell BG, Bieler GS. SUDAAN: software for the statistical analysis of correlated data; user's manual, release 7.5 . Research Triangle Park, North Carolina: Research Triangle Institute, 1997.
CDC.  Prevalence of selected risk factors for chronic disease and injury among American Indians and Alaska Natives—United States, 1995-1998.  MMWR.2000;49:79-82,91.
US Department of Commerce, Economics and Statistics Administration.  Statistical brief: phoneless in America . Washington, DC: US Department of Commerce, 1994. Publication no. SB/94-16.
Pearson D, Cheadle A, Wagner E, Tonsberg R, Psaty BM. Differences in sociodemographic health status, and lifestyle characteristics among American Indians by telephone coverage.  Prev Med.1994;23:461-4.
CDC.  FY 2001 performance plan, final FY 2000 performance plan, FY 1999 performance report: January 2000 . Atlanta, Georgia: US Department of Health and Human Services, CDC, 2000.
CDC.  Inter-Tribal Heart Project: results from the cardiovascular heart survey . Atlanta, Georgia: US Department of Health and Human Services, CDC, 1996.

*Northeast=Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont; Midwest=Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin; South=Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia; and West=Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

CDC Launches Internet Site in Spanish

MMWR. 2000;49:305 .

CDC has launched its Spanish language web site, CDC En Espanol, on the World-Wide Web at http://www.cdc.gov/spanish/. It is also accessible from the left navigation side bar of the CDC home page.

CDC En Espanol is not a translation of the English language web site but is a site tailored to Hispanic/Latino populations. It provides health-related information to the Hispanic/Latino professional and to the Spanish-speaking community. The site also includes information directed at special groups, such as adolescents, students, teachers, patients, health-care providers, women, and men.

Included is information from the CDC and Agency for Toxic Substances and Disease Registry (ATSDR) centers, institutes, and offices and appropriate links to other key federal agency web sites that are important to the Hispanic/Latino community. CDC En Espanol provides an opportunity for CDC/ATSDR and its national and international partners to access common information and discuss issues. Questions related to CDC En Espanol can be sent by e-mail to spanish@cdc.gov.

Revision of Acute Hepatitis Panel

MMWR. 2000;49:424

Current Procedural Terminology (CPT) codes are standardized codes developed and maintained by the American Medical Association (AMA) for the classification and reporting of medical services. The Health Care Financing Administration (HCFA) requires the use of these codes for reporting services to Medicare and Medicaid for reimbursement. On January 1, 1998, the components of the test panel for acute viral hepatitis (CPT#80059) were changed to exclude the tests for IgM antibody to hepatitis A virus (IgM anti-HAV) and IgM antibody to hepatitis B core antigen (IgM anti-HBc), the tests that specifically identify recent infection with hepatitis A virus (HAV) and hepatitis B virus (HBV).

Effective January 1, 2000 (CPT 2000), the acute hepatitis panel has been revised (CPT#80074) to re-include the tests for IgM anti-HAV and IgM anti-HBc. This revised panel, which also includes tests for hepatitis B surface antigen (HBsAg) and antibody to hepatitis C virus (anti-HCV), should be used to diagnose any patient presenting with signs and/or symptoms of acute viral hepatitis. Additional information on CPT codes is available at the AMA World-Wide Web site, http://www.ama-assn.org/med-sci/cpt/coding.htm.*

*References to sites of non-CDC organizations on the World-Wide Web are provided as a service to MMWR readers and do not constitute or imply endorsement of these organizations or their programs by CDC or the U.S. Department of Health and Human Services. CDC is not responsible for the content of pages found at these sites.

New Web-Based Training on Hepatitis C for Health Professionals

MMWR. 2000;49:425

On May 15, 2000, CDC posted on its World-Wide Web site an interactive web-based training program titled "Hepatitis C: What Clinicians and Other Health Professionals Need to Know." The program is at http://www.cdc.gov/hepatitis.

This program provides users with up-to-date information on the epidemiology, diagnosis, and management of hepatitis C virus (HCV) infection and HCV-related chronic disease. Users also can test their knowledge of the material through study questions at the end of each section and case studies at the end of the program. Continuing medical and nursing education credits are available free from CDC on completion of the training. The American Academy of Family Physicians also will grant the academy's education credits on completion of training and filing with the academy.

Erratum: Vol 49, No. 19 (JAMA. 2000;283:3195-3196)

MMWR. 2000;49:474

In the article "Cause-Specific Adult Mortality: Evidence From Community-Based Surveillance-Selected Sites, Tanzania, 1992-1998," the district location of Dar es Salaam was misidentified. The first sentence of the second paragraph should read: The AMMP surveillance project was conducted in a low-income and in a middle-income section of the city of Dar es Salaam, in part of a region ranked by the Tanzanian government as being among the 50% most deprived in Tanzania (i.e., Morogoro Rural District in Morogoro Region), and in part of a region ranked as one of the 15% least deprived (i.e., Hai District in Kilimanjaro Region).1