Pamela D. Waterman

Race/Ethnicity, Gender, and Monitoring Socioeconomic Gradients in Health: A Comparison of Area-Based Socioeconomic Measures—The Public Health Disparities Geocoding Project

Use of multilevel frameworks and area-based socioeconomic measures (ABSMs) for public health monitoring can potentially overcome the absence of socioeconomic data in most US public health surveillance systems. To assess whether ABSMs can meaningfully be used for diverse race/ethnicity-gender groups, we geocoded and linked public health surveillance data from Massachusetts and Rhode Island to 1990 block group, tract, and zip code ABSMs. Outcomes comprised death, birth, cancer incidence, tuberculosis, sexually transmitted infections, childhood lead poisoning, and nonfatal weapons-related injuries. Among White, Black, and Hispanic women and men, measures of economic deprivation (e.g., percentage below poverty) were most sensitive to expected socioeconomic gradients in health, with the most consistent results and maximal geocoding linkage evident for tract-level analyses.

Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: The Public Health Disparities Geocoding Project (US)

Study objectives: To determine which area based socioeconomic measures can meaningfully be used, at which level of geography, to monitor socioeconomic inequalities in childhood health in the US. Design: Cross sectional analysis of birth certificate and childhood lead poisoning registry data, geocoded and linked to diverse area based socioeconomic measures that were generated at three geographical levels: census tract, block group, and ZIP code. Setting: Two US states: Massachusetts (1990 population=6 016 425) and Rhode Island (1990 population=1 003 464). Participants: All births born to mothers ages 15 to 55 years old who were residents of either Massachusetts (1989–1991; n=267 311) or Rhode Island (1987–1993; n=96 138), and all children ages 1 to 5 years residing in Rhode Island who were screened for lead levels between 1994 and 1996 (n=62 514 children, restricted to first test during the study period). Main results: Analyses of both the birth weight and lead data indicated that: (a) block group and tract socioeconomic measures performed similarly within and across both states, while ZIP code level measures tended to detect smaller effects; (b) measures pertaining to economic poverty detected stronger gradients than measures of education, occupation, and wealth; (c) results were similar for categories generated by quintiles and by a priori categorical cut off points; and (d) the area based socioeconomic measures yielded estimates of effect equal to or augmenting those detected, respectively, by individual level educational data for birth outcomes and by the area based housing measure recommended by the US government for monitoring childhood lead poisoning. Conclusions: Census tract or block group area based socioeconomic measures of economic deprivation could be meaningfully used in conjunction with US public health surveillance systems to enable or enhance monitoring of social inequalities in health in the United States.

Painting a Truer Picture of US Socioeconomic and Racial/Ethnic Health Inequalities: The Public Health Disparities Geocoding Project

OBJECTIVES We describe a method to facilitate routine monitoring of socioeconomic health disparities in the United States. METHODS We analyzed geocoded public health surveillance data including events from birth to death (c. 1990) linked to 1990 census tract (CT) poverty data for Massachusetts and Rhode Island. RESULTS For virtually all outcomes, risk increased with CT poverty, and when we adjusted for CT poverty racial/ethnic disparities were substantially reduced. For half the outcomes, more than 50% of cases would not have occurred if population rates equaled those of persons in the least impoverished CTs. In the early 1990s, persons in the least impoverished CT were the only group meeting Healthy People 2000 objectives a decade ahead. CONCLUSIONS Geocoding and use of the CT poverty measure permit routine monitoring of US socioeconomic inequalities in health, using a common and accessible metric.

The Fall and Rise of US Inequities in Premature Mortality: 1960–2002

Background Debates exist as to whether, as overall population health improves, the absolute and relative magnitude of income- and race/ethnicity-related health disparities necessarily increase—or derease. We accordingly decided to test the hypothesis that health inequities widen—or shrink—in a context of declining mortality rates, by examining annual US mortality data over a 42 year period. Methods and Findings Using US county mortality data from 1960–2002 and county median family income data from the 1960–2000 decennial censuses, we analyzed the rates of premature mortality (deaths among persons under age 65) and infant death (deaths among persons under age 1) by quintiles of county median family income weighted by county population size. Between 1960 and 2002, as US premature mortality and infant death rates declined in all county income quintiles, socioeconomic and racial/ethnic inequities in premature mortality and infant death (both relative and absolute) shrank between 1966 and 1980, especially for US populations of color; thereafter, the relative health inequities widened and the absolute differences barely changed in magnitude. Had all persons experienced the same yearly age-specific premature mortality rates as the white population living in the highest income quintile, between 1960 and 2002, 14% of the white premature deaths and 30% of the premature deaths among populations of color would not have occurred. Conclusions The observed trends refute arguments that health inequities inevitably widen—or shrink—as population health improves. Instead, the magnitude of health inequalities can fall or rise; it is our job to understand why.

Racial Discrimination, Psychological Distress, and Self-Rated Health Among US-Born and Foreign-Born Black Americans

OBJECTIVES We investigated associations among racial discrimination, psychological distress, and self-rated health among US-born and immigrant Black Americans. METHODS We conducted a cross-sectional analysis of a cohort of employed working-class Black Americans (193 US-born, 275 foreign-born). RESULTS Both US-born and foreign-born Black participants had high levels of exposure to poverty (51% and 57%, respectively) and racial discrimination (76% and 60%) and reported high levels of severe psychological distress (14% and 16% had a Kessler 6 [K6] score of 13 or greater); 17% and 7% reported fair or poor health. After controlling for relevant covariates, their risk parameters for racial discrimination (high vs no exposure) were 4.0 (95% confidence interval [CI] = 2.3, 5.6) and 3.3 (95% CI = 2.1, 4.5), respectively, for continuous K6 score; corresponding odds ratios for severe psychological distress were 6.9 (95% CI = 1.4, 35.7) and 6.8 (95% CI = 2.5, 18.3). No associations existed between racial discrimination and self-reported health, suggesting that an underlying propensity to report adversity does not account for our psychological distress findings. CONCLUSIONS Our results attest to the salience of racial discrimination, nativity, and socioeconomic position in understanding the experiences and psychological health of Black Americans.

Combining Explicit and Implicit Measures of Racial Discrimination in Health Research

OBJECTIVES To improve measurement of discrimination for health research, we sought to address the concern that explicit self-reports of racial discrimination may not capture unconscious cognition. METHODS We used 2 assessment tools in our Web-based study: a new application of the Implicit Association Test, a computer-based reaction-time test that measures the strength of association between an individuals self or group and being a victim or perpetrator of racial discrimination, and a validated explicit self-report measure of racial discrimination. RESULTS Among the 442 US-born non-Hispanic Black participants, the explicit and implicit measures, as hypothesized, were weakly correlated and tended to be independently associated with risk of hypertension among persons with less than a college degree. Adjustments for both measures eliminated the significantly greater risk for Blacks than for Whites (odds ratio = 1.4), reducing it to 1.1 (95% confidence interval = 0.7, 1.7). CONCLUSIONS Our results suggest that the scientific rigor of research on racism and health will be improved by investigating how both unconscious and conscious mental awareness of having experienced discrimination matter for somatic and mental health.

Monitoring Socioeconomic Disparities in Death: Comparing Individual-Level Education and Area-Based Socioeconomic Measures

We compared all-cause mortality rates stratified by individual-level education and by census tract area-based socioeconomic measures for Massachusetts (1999-2001). Among persons aged 25 and older, the age-adjusted relative index of inequality was slightly higher for the census tract than for the individual education measures (1.5 vs 1.2, respectively). Only the census tract socioeconomic measures could provide a relative index of inequality (2-3) for deaths before age 25 or detect expected socioeconomic disparities for deaths among persons 65 and older (relative index of inequality= approximately 1.2 vs 0.8 for census tract measures and individual education, respectively).

Mapping and Measuring Social Disparities in Premature Mortality: The Impact of Census Tract Poverty within and across Boston Neighborhoods, 1999–2001

The identification and documentation of health disparities are important functions of public health surveillance. These disparities, typically falling along lines defined by gender, race/ethnicity, and social class, are often made visible in urban settings as geographic disparities in health between neighborhoods. Recognizing that premature mortality is a powerful indicator of disparities in both health status and access to health care that can readily be monitored using routinely available public health surveillance data, we undertook a systematic analysis of spatial variation in premature mortality in Boston (1999–2001) across neighborhoods and sub-neighborhoods in relation to census tract (CT) poverty. Using a multilevel model based framework, we estimated that the incidence of premature mortality was 1.39 times higher (95% credible interval 1.09–1.78) among persons living in the most economically deprived CTs (≥20% below poverty) compared to those in the least impoverished tracts (<5% below poverty). We present maps of model-based standardized mortality ratios that show substantial within-neighborhood variation in premature mortality and a sizeable decrease in spatial variation after adjustment for CT poverty. Additionally, we present maps of model-based direct standardized rates that can more readily be compared to externally published rates and targets, as well as maps of the population attributable fraction that show that in some of Boston’s poorest neighborhoods, the proportion of excess deaths associated with CT poverty reaches 25–30%. We recommend that these methods be incorporated into routine analyses of public health surveillance data to highlight continuing social disparities in premature mortality.

Race/Ethnicity and Changing US Socioeconomic Gradients in Breast Cancer Incidence: California and Massachusetts, 1978–2002 (United States)

Objective We tested the hypothesis that the US socioeconomic gradient in breast cancer incidence is declining, with the decline most pronounced among racial/ethnic groups with the highest incidence rates.Methods We geocoded the invasive incident breast cancer cases for three US population-based cancer registries covering: Los Angeles County, CA (1978–1982, 1988–1992, 1998–2002; n = 68,762 cases), the San Francisco Bay Area, CA (1978–1982, 1988–1992, 1998–2002; n = 37,210 cases) and Massachusetts (1988–1992, 1998–2002; n = 48,111 cases), linked the records to census tract area-based socioeconomic measures, and, for each socioeconomic stratum, computed average annual breast cancer incidence rates for the 5-year period straddling the 1980, 1990, and 2000 census, overall and by race/ethnicity and gender.Results Our findings indicate that the socioeconomic gradient in breast cancer incidence is: (a) relatively small (at most 1.2) and stable among US white non-Hispanic and black women; (b) sharper and generally increasing among Hispanic and Asian and Pacific Islander American women; and (c) cannot be meaningfully analyzed without considering effect modification by race/ethnicity and immigration.Conclusion Our results indicate that secular changes in US socioeconomic gradients in breast cancer incidence exist and vary by race/ethnicity.

Decline in US breast cancer rates after the women's health initiative: socioeconomic and racial/ethnic differentials.

OBJECTIVES We investigated whether there were socioeconomic and racial/ethnic disparities in recent reported declines in overall US breast cancer incidence rates attributed to post-2002 declines in hormone therapy use following publication of the Womens Health Initiative study. METHODS We analyzed 1992-2005 US breast cancer incidence data from the US Surveillance, Epidemiology and End Result (SEER) 13 Registries Database, stratified by race/ethnicity, county income level, age, and estrogen receptor (ER) status. RESULTS As we hypothesized, between 1992 and 2005, the temporal pattern of rising and then falling US breast cancer incidence rates occurred only among White non-Hispanic women who lived in high-income counties, were aged 50 years and older, and had ER-positive tumors. No such trends were evident--regardless of county income level, ER status, or age--among Black non-Hispanic, Asian/Pacific Islander, Hispanic, or-where numbers were sufficient to conduct meaningful analyses-American Indian/Alaska Native women. CONCLUSIONS The recent decline in US breast cancer incidence was not equally beneficial to all women, but instead mirrored the social patterning of hormone therapy use. Joint information on socioeconomic resources and race/ethnicity is vital for correctly understanding disease distribution, including that of breast cancer.