factors that affect people’s health DUE TOMORROW

Chapter 4
Descriptive Epidemiology: Person, Place, Time

Learning Objectives
State primary objectives of descriptive epidemiology
Provide examples of descriptive studies
List characteristics of person, place, and time
Characterize the differences between descriptive and analytic epidemiology

Descriptive vs. Analytic Epidemiology
Descriptive studies–used to identify a health problem that may exist. Characterize the amount and distribution of disease
Analytic studies–follow descriptive studies, and are used to identify the cause of the health problem

2

Objectives of Descriptive Epidemiology
To evaluate and compare trends in health and disease
To provide a basis for planning, provision, and evaluation of health services
To identify problems for analytic studies (creation of hypotheses)

3

Descriptive Studies and Epidemiologic Hypotheses
Hypotheses–theories tested by gathering facts that lead to their acceptance or rejection
Three types:
Positive declaration (research hypothesis)
Negative declaration (null hypothesis)
Implicit question (e.g., to study association between infant mortality and region)

4

Mill’s Canons of Inductive Reasoning
The method of difference–all the factors in two or more places are the same except for a single factor.
The method of agreement–a single factor is common to a variety of settings. Example: air pollution.

5

Mill’s Canons (cont’d)
The method of concomitant variation–the frequency of disease varies according to the potency of a factor.
The method of residues–involves subtracting potential causal factors to determine which factor(s) has the greatest impact.

6

Method of Analogy
(MacMahon and Pugh)
The mode of transmission and symptoms of a disease of unknown etiology bear a pattern similar to that of a known disease.
This information suggests similar etiologies for both diseases.

Three Approaches to Descriptive Epidemiology
Case reports–simplest category of descriptive epidemiology
Case series
Cross-sectional studies

Case Reports and Case Series
Case reports–astute clinical observations of unusual cases of disease
Example: a single occurrence of methylene chloride poisoning
Case series–a summary of the characteristics of a consecutive listing of patients from one or more major clinical
Example: five cases of hantavirus pulmonary syndrome

7

Cross-sectional Studies
Surveys of the population to estimate the prevalence of a disease or exposure
Example: National Health Interview Survey

Characteristics of Persons Covered in Chapter 4
Age
Sex
Marital Status
Race and ethnicity
Nativity and migration
Religion
Socioeconomic status

Age
One of the most important factors to consider when describing the occurrence of any disease or illness

8

Trends by Age Subgroup
Childhood to early adolescence
Leading cause of death, ages 1-14 years—unintentional injuries
Infants—mortality from developmental problems, e.g., congenital birth defects
Childhood—occurrence of infectious diseases such as meningococcal disease

Trends by Age Subgroup (cont’d)
Teenage years
Leading causes of death—unintentional injuries, homicide, and suicide
Other issues—unplanned pregnancy, tobacco use, substance abuse

Trends by Age Subgroup (cont’d)
Adults—leading causes of death
Unintentional injuries
Cancer
Heart disease
Older adults—deaths from chronic diseases (e.g., cancer and heart disease) dominate.
Elderly—deaths from chronic diseases and limitations in activities of daily living

Age Trends in Cancer Incidence
Age-specific rates of cancer incidence increase with age with apparent declines late in life.

Reasons for Age Associations
Validity of diagnoses across the life span
Multimodality of trends
Latency effects
Action of the “human biologic clock”
Life cycle and behavioral phenomena

Validity of Diagnoses
Classification errors
Age-specific incidence rates among older groups
Exact cause of death can be inaccurate due multiple sources of morbidity that affect elderly.

Age-Specific Distributions of Disease Incidence
Age-specific distributions of disease incidence can be linear or multimodal.
Linear trend—incidence of cancer
Multimodal (having several peaks in incidence)
Tuberculosis—peaks at ages 0 to 4 and ages 20-29
Meningococcal disease—peaks among infants younger than age 1 year and teenagers about 18 years old

Latency Effects
Age effects on mortality may reflect the long latency period between environmental exposures and subsequent development of disease.

Biologic Clock Phenomenon
Waning of the immune system may result in increased susceptibility to disease, or aging may trigger appearance of conditions believed to have genetic basis.
Example: Alzheimer’s disease

9

Sex Differences: Males
All-cause age-specific mortality rates is higher for men than for women.
May be due to social factors
May have biological basis
Men often develop severe forms of chronic disease.
Generally, death rates for both sexes are declining.

10

Sex Differences: Female Paradox
Reports from the 1970s indicated female age-standardized morbidity rates for many acute and chronic conditions were higher than rates for males, even though mortality was higher among males.
Higher female rates for:
Pain
Asthma
Some lung difficulties

Cancer
Cancer of the lung and bronchus is leading cause of cancer death for both men and women in the U.S.
Increases among women are related to changes in lifestyle and risk behavior, e.g., smoking.

CHD among Women
Coronary heart disease (CHD) is the leading cause of mortality among women (and also men).
Women may not be alert for symptoms of CHD and fail to seek needed treatment.

Minority Women in Economically Disadvantaged U.S. Areas
In Los Angeles County, some have higher rates of diabetes and hypertension than men.
A large percentage are physically inactive.
High rates of obesity among Latinas and African Americans.

Marital Status
Categories
Single or non-married (e.g., never married, divorced, widowed)
Married
Living with a partner

Marital Status (cont’d)
In general, married people tend to have lower rates of morbidity and mortality.
Examples: chronic and infectious diseases, suicides, and accidents.
Never married adults (especially men) less likely to be overweight

11

Marital Status (cont’d)
Marriage may operate as a protective or selective factor.
Protective hypothesis: marriage provides an environment conducive to health.
Selective hypothesis: people who marry are healthier than people who never marry.

Marital Status (cont’d)
Widowed persons
Suicide rates
Elevated among young white males who were widowed
Depression
Elevated rates among widowed persons

General Comments About Race
U.S. is becoming increasingly more diverse.
Race is an ambiguous concept that overlaps with other dimensions.
Some scientists propose that race is primarily a social and cultural construct.

Measurement of Race
Census 2000 changed the race category by allowing respondents to choose one or more race categories.
Census 2000 used five categories of race.
Census 2010 continued with this classification scheme (Refer to Exhibit 4-1 in text).

Exhibit 4.0.E01B: Overview of Race and Hispanic Origin, Census 2011, continued

Reproduced from U.S. Census Bureau. Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-02.pdf accessed: March 5, 2012

Exhibit 4.0.E01F: Overview of Race and Hispanic Origin, Census 2011, continued

Reproduced from U.S. Census Bureau. Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-02.pdf accessed: March 5, 2016

Race/Ethnicity Categories Discussed in Chapter 4
African American
American Indian
Asian
Hispanic/Latino

Figure 4.0.F10: Human immunodeficiency virus diagnoses. Percentage of diagnosed cases, by race/ethnicity–United States, 2009.

Reproduced from Centers for Disease Control and Prevention, Summary of notifiable diseases–United States, 2007, MMWR. Vol 58, No 53, p. 63, 2011.

African Americans
In a classic study of differential mortality in U.S., they had the highest rate of mortality of all groups studied.
Higher blood pressure levels
Possible influence of stress or diet.
Higher rates of hypertensive heart disease.
In 2007, age-adjusted death rate for African Americans was 1.3 times rate for whites.
Differences in life expectancy

12

American Indians/Alaska Natives
High rates of chronic diseases, adverse birth outcomes, and some infectious diseases
Pima Indians (1975-1984 data):
High mortality, e.g., male death rate (ages 25 to 34) was 6.6 times that for all races in U.S.
Infectious diseases were the 10th leading cause of death.

13

Asians
Japanese Americans have lower mortality rates than whites.
Lower rates of CHD and cancer.
Low CHD rates attributed to low-fat diet and institutionalized stress-reducing strategies.
Some Asian groups, e.g., Cambodian Americans, have high smoking rates.
TB rates are highest among Asian/Pacific Islander group.

14

Figure 4.0.F12: Tuberculosis. Incidence,* by race/ethnicity: United States, 1995–2009.

Reproduced from Centers for Disease Control and Prevention, Summary of notifiable diseases–United States, 2011, MMWR. Vol 58, No 53, p. 78, 2011.

Acculturation
Defined as modifications that individuals or groups undergo when they come in contact with another country
Provides evidence of the influence of environmental and behavioral factors on chronic disease
Example: Japanese migrants experience a shift in rates of chronic disease toward those of the host country.

15

Hispanics/Latinos
Hispanic Health and Nutrition Examination Survey (HHANES).
Examined health and nutrition status of major Hispanic/Latino populations in the U.S.
San Antonio Heart Study
Found high rates of obesity and diabetes among Mexican Americans
Hispanic mortality paradox (text box)

16

Figure 4.0.F14: Prevalence of obesity*among public school children in grades K-8 s, by school year and selected characteristics–New York City, 2006-07 to 2010-11.

Data from Centers for Disease Control and Prevention, Obesity in K-8 students–New York City, 2006-07 to 2010-11 school years. MMWR. Vol 60, No 49, p. 1675, 2011.

Nativity and Migration
Nativity–Place of origin of the individual
Categories are foreign born and native born.
Nativity and migration are related.

17

Impact of Migration
Importation of “Third World” disease by immigrants from developing countries
Leprosy during 1980s
Programmatic needs resulting from migration:
Specialized screening programs (tuberculosis and nutrition)
Familiarization with formerly uncommon (in U.S.) tropical diseases

Figure 4.0.F16: Hansen’s disease (leprosy). Number of reported cases, by year: United States, 1970–2006.

Reproduced from Centers for Disease Control and Prevention, Summary of notifiable diseases–United States, 2005, MMWR. Vol 54, No 53, p. 55, 2007.

Healthy Migrant Effect
Observation that healthier, younger persons usually form the majority of migrants
Often difficult to separate environmental influences in the host country from selective factors operative among those who choose to migrate

Religion
Certain religions prescribe lifestyles that may influence rates of morbidity and mortality.
Example: Seventh Day Adventists
Follow vegetarian diet and abstain from alcohol and tobacco use
Have lower rates of CHD, reduced cancer risk, and lower blood pressure
Similar findings for Mormons

18

Socioeconomic Status
Low social class is related to excess mortality, morbidity, and disability rates.
Factors include:
Poor housing
Crowded conditions
Racial disadvantage
Low income
Poor education
Unemployment

19

Measurement of Social Class
Variables include:
Prestige of occupation or social position
Educational attainment
Income
Combined indices of two or more of the above variables

20

Figure 4.0.F17A: Age-adjusted percent distributions of health status among persons aged 18 years and over by education (Part A): United States, 2010.

Reproduced from Schiller JS, Lucas JW, Ward BW, Peregoy JA. Summary health statistics for US adults: National Health Interview Survey, 2010. National Center for Health Statistics. Vital Health Stat 10 (252). 2012.

Figure 4.0.F17B: Age-adjusted percent distributions of health status among persons aged 18 years and over by education and income (Part B): United States, 2010.

Reproduced from Schiller JS, Lucas JW, Ward BW, Peregoy JA. Summary health statistics for US adults: National Health Interview Survey, 2010. National Center for Health Statistics. Vital Health Stat 10 (252). 2012.

Hollingshead and Redlich
Studied association of socioeconomic status and mental illness
Classified New Haven, Connecticut, into five social classes based on occupational prestige, education, and address

23

Hollingshead and Redlich Findings
Strong inverse association between social class and likelihood of being a mental patient under treatment.
As social class increased, severity of mental illness decreased.
Type of treatment varied by social class.

24

Mental Health and Social Class
In the U.S., the highest incidence of severe mental illness occurs among the lowest social classes.

Mental Health and Social Class: Two Hypotheses
Social causation explanation (breeder hypothesis)—conditions associated with lower social class produce mental illness.
Downward drift hypothesis—Persons with severe mental dis s move to impoverished areas.

21

Other Correlates of Low Social Class
Higher rate of infectious disease
Higher infant mortality rate and overall mortality rates
Lower life expectancy
Larger proportion of cancers with poor prognosis
May be due to delay in seeking health care
Low self-perceived health status

22

Characteristics of Place
Types of place comparisons:
International
Geographic (within-country) variations
Urban/rural differences
Localized occurrence of disease

25

International Comparisons of Disease Frequency
World Health Organization (WHO) tracks international variations in rates of disease.
Infectious and chronic diseases show great variation across countries.
Variations are attributable to climate, cultural factors, dietary habits, and health care access.
The U.S. fell in the bottom half of OECD countries for both male and female life expectancy; Japan was highest.

26

Figure 4.0.F18: Life expectancy Ranking* at birth,† by sex in selected countries and territories, 2004.§¶

Reproduced from Centers for Disease Control and Prevention, MMWR. Vol 57, No 13, p. 346, 2008.

Within-Country Variations in Rates of Disease
Due to variations in climate, geology, latitude, pollution, and ethnic and racial concentrations
In U.S., comparisons can be made by region, state, and/or county.
Examples include: higher rates of leukemia in Midwest; state by state variations in infectious, vector-borne, parasitic diseases

27

Table 4.0.T02: Representative Applications of Geographic Information Systems (GIS)

Author created

Urban/Rural Differences in Disease Rates
Urban
Diseases and mortality associated with crowding, pollution, and poverty
Example: lead poisoning in inner cities
Homicide in central cities
Rural
Mortality (among all age groups) increases with decreasing urbanization.
Health risk behaviors higher in rural South

28

Standard Metropolitan Statistical Areas (SMSAs)
Established by the U.S. Bureau of the Census to make regional and urban/rural comparisons in disease rates

Metropolitan Statistical Areas (MSAs)
Provide a distinction between metropolitan and nonmetropolitan areas by type of residence, industrial concentration, and population concentration

35

Definition of MSA
Used to distinguish between metropolitan and nonmetropolitan areas
Metropolitan area—large population nucleus together with adjacent communities
Six urban-classification levels used by the National Center for Health Statistics (refer to text.)

Census Tracts
Small geographic subdivisions of cities, counties, and adjacent areas
Each tract contains about 4,000 residents.
Are designed to provide a degree of uniformity of population economic status and living conditions in each tract

36

Localized Place Comparisons
Disease patterns are due to unique environmental or social conditions found in particular area of interest. Examples include:
Fluorosis: associated with naturally occurring fluoride deposits in water.
Goiter: iodine deficiency formerly found in land-locked areas of U.S.

29

Geographic Information Systems (GIS)
A method to provide a spatial perspective on the geographic distribution of health conditions
A GIS produces a choroplath map that shows variations in disease rates by different degrees of shading.

Figure 4.0.F20: GIS Map of infant mortality rates in Idaho, United States.

Reproduced from Idaho Department of Health and Welfare, Bureau of Vital Statistics. Available at: http://inside.uidaho.edu/data/statewide/esri/idtm/atlas/infamr98_id_esri.gif Accessed: March 31, 2003.

Reasons for Place Variation in Disease
Gene/environment interaction
Examples: sickle-cell gene; Tay-Sachs disease.
Influence of climate
Examples: yaws, Hansen’s disease
Environmental factors
Example: chemical agents linked to cancer

30

Characteristics of Time
Cyclic fluctuations
Point epidemics
Secular time trends
Clustering
Temporal
Spatial

31

Cyclic Fluctuations
Periodic changes in the frequency of diseases and health conditions over time
Examples:
Birth rates
Higher heart disease mortality in winter
Influenza
Unintentional injuries
Meningococcal disease
Rotavirus infections

Cyclic Fluctuations (cont’d)
Related to changes in lifestyle of the host, seasonal climatic changes, and virulence of the infectious agent

Common Source Epidemic
Outbreak due to exposure of a group of persons to a noxious influence that is common to the individuals in the group
Types: point epidemic; continuous common source epidemic
Refer to Figure 4-22 for an example an influenza outbreak in a residential facility.

Point Epidemics
The response of a group of people circumscribed in place and time to a common source of infection, contamination, or other etiologic factor to which they were exposed almost simultaneously.
Examples: foodborne illness; responses to toxic substances; infectious diseases.

32

Influenza-Related Illness at a Residential Facility

Secular Time Trends
Refer to gradual changes in the frequency of a disease over long time periods.
Example is the decline of heart disease mortality in the U.S.
May reflect impact of public health programs, dietary improvements, better treatment, or unknown factors.

33

Figure 4.0.F23: Age-adjusted total U.S. mortality rates for breast cancer, all ages, females for 1995–2004 by ‘Expanded’ race age-adjusted to the 2000 U.S. std population.

Data from, Surveillence, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Mortality–All COD, Public-Use with State, Total U.S. (1990-2004), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2007, Underlying mortality data provided by NCHS (www.cdc.gov/nchs)

Clustering
Case clustering–refers to an unusual aggregation of health events grouped together in space and time
Temporal clustering: e.g., post-vaccination reactions, postpartum depression
Spatial clustering: concentration of disease in a specific geographic area, e.g., Hodgkin’s disease

35