Future directions in residential segregation and health research: a multilevel approach

Neighborhood disorder and smoking: findings of a European urban survey

Using the Large Analysis and Review of European housing and health Status (LARES) survey, this paper investigates the influence of neighborhood physical disorder on smoking behaviors, and the extent to which it is mediated by perceptions of safety. Indicators of physical disorder: litter, graffiti, and the absence of vegetation on facades, balconies or windows, were directly observed by surveyors. The paper also considers whether the place effects on smoking are similar across the 7 European cities in the study. Results indicate that the odds of smoking are 64% higher for those living in an area rated high on neighborhood disorder compared to low. The effect is substantially greater for men than for women with men in areas rated high on disorder showing odds of smoking that are twice as high as those living in areas rated low. The association does not vary by city of residence. Only a small part of the effect of neighborhood disorder is mediated by perceptions of safety. The finding of a substantial neighborhood physical disorder effect on smoking across a range of cities in Europe adds to the evidence suggesting that environmental interventions are worth pursuing in conjunction with other approaches to smoking prevention.

Race, segregation, and physicians' participation in medicaid

Many studies have explored the extent to which physicians' characteristics and Medicaid program factors influence physicians' decisions to accept Medicaid patients. In this article, we turn to patient race/ethnicity and residential segregation as potential influences. Using the 2000/2001 Community Tracking Study and other sources we show that physicians are significantly less likely to participate in Medicaid in areas where the poor are nonwhite and in areas that are racially segregated. Surprisingly-and contrary to the prevailing Medicaid participation theory--we find no link between poverty segregation and Medicaid participation when controlling for these racial factors. Accordingly, this study contributes to an accumulating body of circumstantial evidence that patient race influences physicians' choices, which in turn may contribute to racial disparities in access to health care.

Racial Segregation and Health Disparities Between Black and White Older Adults

OBJECTIVES

In this study, we examined whether racial segregation is associated with poorer self-rated health among older adults, and whether racial segregation helps explain race disparities in self-rated health between Black and White older adults.

METHODS

We used multilevel data at the individual, neighborhood (tract), and county levels, from two national surveys-the Americans' Changing Lives (ACL) survey and the National Survey of Families and Households (NSFH). We used hierarchical linear models in order to regress self-rated health on county-, neighborhood-, and individual-level racial and socioeconomic variables.

RESULTS

In the NSFH, there was an association between county racial segregation and poorer self-rated health among White but not Black older adults (net of county percent Black and percent poverty). In the ACL, there was no statistically significant association between racial segregation and self-rated health. In the NSFH, there was some indication that Black older adults had better self-rated health when living in neighborhoods with a higher percentage of Black residents than the county percentage.

DISCUSSION

Although aggregate-level studies demonstrate associations between racial segregation and mortality rates, our multilevel analyses with two national data sets suggest only weak associations between racial segregation and self-rated health. However, socioeconomic status at multiple levels contributes to race disparities in health.

Is there a "school effect" on pupil outcomes? A review of multilevel studies

STUDY OBJECTIVE

The school environment is of importance for child outcomes. Multilevel analyses can separate determinants operating at an individual level from those operating at a contextual level. This paper aims to systematically review multilevel studies of school contextual effects on pupil outcomes.

DESIGN

Key word searching of five databases yielded 17 cross sectional or longitudinal studies meeting the inclusion criteria. Results are summarised with reference to type of school contextual determinant.

MAIN RESULTS

Four main school effects on pupil outcomes were identified. Having a health policy or antismoking policy, a good school climate, high average socioeconomic status, and urban location had a positive effect on pupil outcomes. Outcomes under study were smoking habits, wellbeing, problem behaviour, and school achievement.

CONCLUSIONS

Despite the different pupil outcomes and the variety of determinants used in the included papers, a school effect was evident. However, to improve our understanding of school effects, presentations of results from multilevel studies need to be standardised. Intraclass correlation and explained between school variance give relevant information on factors in the school environment influencing pupil outcomes, and should be included in all multilevel studies. Inclusion of pupil level predictors in the multilevel models should be based on theoretical considerations of how schools and communities are interconnected and how pupils and their families are influenced by school contextual factors.

Discrimination, symptoms of depression, and self-rated health among african american women in detroit: results from a longitudinal analysis

OBJECTIVES

Our understanding of the relationships between perceived discrimination and health was limited by the cross-sectional design of most previous studies. We examined the longitudinal association of self-reported everyday discrimination with depressive symptoms and self-rated general health.

METHODS

Data came from 2 waves (1996 and 2001) of the Eastside Village Health Worker Partnership survey, a community-based participatory survey of African American women living on Detroit's east side (n=343). We use longitudinal models to test the hypothesis that a change in everyday discrimination over time is associated with a change in self-reported symptoms of depression (positive) and on self-reported general health status (negative).

RESULTS

We found that a change over time in discrimination was significantly associated with a change over time in depressive symptoms (positive) (b=0.125; P<.001) and self-rated general health (negative) (b=-0.163; P<.05) independent of age, education, or income.

CONCLUSIONS

The results reported here are consistent with the hypothesis that everyday encounters with discrimination are causally associated with poor mental and physical health outcomes. In this sample of African American women, this association holds above and beyond the effects of income and education.

Residential segregation and Latino, black and white mortality in New York City

Although racial segregation is associated with health status, few studies have examined this relationship among Latinos. We examined the effect of race/ethnic group concentration of Latinos, blacks and whites on all-cause mortality rates within a highly segregated metropolitan area, New York City (NYC). We linked NYC mortality records from 1999 and 2000 with the 2000 U.S. Census data by zip code area. Age-adjusted mortality rates by race/ethnic concentration were calculated. Linear regression was used to determine the association between population characteristics and mortality. Blacks living in predominantly black areas had lower all-cause mortality rates than blacks living in other areas regardless of gender (1616/100,000 vs. 2014/100,000 for men; 1032/100,000 vs. 1362/100,000 for women). Amongst whites, those living in predominantly white areas had the lowest mortality rates. Latinos living in predominantly Latino areas had lower mortality rates than those in predominantly black areas (1187/100,000 vs.1950/100,000 for men; 760/100,000 vs. 779/100,000 for women). After adjustment for socioeconomic conditions, whites, older blacks, and young Latino men experienced decreasing mortality rates when living in areas with increasing similar race/ethnic concentrations. Increasing residential concentration of blacks is independently associated with lower mortality in older blacks; similarly, increasing residential concentration of Latinos and whites is associated with lower mortality in young Latino men and whites, respectively.

Separate and unequal: residential segregation and estimated cancer risks associated with ambient air toxics in U.S. metropolitan areas

This study examines links between racial residential segregation and estimated ambient air toxics exposures and their associated cancer risks using modeled concentration estimates from the U.S. Environmental Protection Agency's National Air Toxics Assessment. We combined pollutant concentration estimates with potencies to calculate cancer risks by census tract for 309 metropolitan areas in the United States. This information was combined with socioeconomic status (SES) measures from the 1990 Census. Estimated cancer risks associated with ambient air toxics were highest in tracts located in metropolitan areas that were highly segregated. Disparities between racial/ethnic groups were also wider in more segregated metropolitan areas. Multivariate modeling showed that, after controlling for tract-level SES measures, increasing segregation amplified the cancer risks associated with ambient air toxics for all racial groups combined [highly segregated areas: relative cancer risk (RCR) = 1.04; 95% confidence interval (CI), 1.01-107; extremely segregated areas: RCR = 1.32; 95% CI, 1.28-1.36]. This segregation effect was strongest for Hispanics (highly segregated areas: RCR = 1.09; 95% CI, 1.01-1.17; extremely segregated areas: RCR = 1.74; 95% CI, 1.61-1.88) and weaker among whites (highly segregated areas: RCR = 1.04; 95% CI, 1.01-1.08; extremely segregated areas: RCR = 1.28; 95% CI, 1.24-1.33), African Americans (highly segregated areas: RCR = 1.09; 95% CI, 0.98-1.21; extremely segregated areas: RCR = 1.38; 95% CI, 1.24-1.53), and Asians (highly segregated areas: RCR = 1.10; 95% CI, 0.97-1.24; extremely segregated areas: RCR = 1.32; 95% CI, 1.16-1.51). Results suggest that disparities associated with ambient air toxics are affected by segregation and that these exposures may have health significance for populations across racial lines.

Racial residential segregation and geographic heterogeneity in black/white disparity in poor self-rated health in the US: a multilevel statistical analysis

Existing evidence demonstrating a relationship between racial residential segregation and health has been based on aggregate analysis. Using a multilevel analytical framework, we assess the extent of geographic variation in black/white disparities in self-rated health across US metropolitan areas, and whether racial residential segregation accounts for such variation. We estimated multilevel regression models of poor self-rated health among 51,316 non-Hispanic white and non-Hispanic black adults nested within 207 metropolitan areas to assess the multilevel relationship between segregation and racial disparities in health. We found statistically significant variation in the black/white disparity in poor self-rated health across metropolitan areas, after controlling for individual level factors (age, sex, marital status, education and income) and residential segregation. High black isolation was associated with increased odds of reporting poor health among blacks (p<0.05). While a similar pattern was observed for white/black dissimilarity and white isolation, they were not statistically significant. Our multilevel analysis only partially supports the previously reported aggregate findings linking segregation to health. Additional multilevel statistical investigations across different health outcomes are required to draw firmer conclusions regarding the adverse effects of segregation on health.

Urban health: evidence, challenges, and directions

Urbanization is one of the most important demographic shifts worldwide during the past century and represents a substantial change from how most of the world's population has lived for the past several thousand years. The study of urban health considers how characteristics of the urban environment may affect population health. This paper reviews the empirical research assessing urban living's impact on population health and our rationale for considering the study of urban health as a distinct field of inquiry. The key factors affecting health in cities can be considered within three broad themes: the physical environment, the social environment, and access to health and social services. The methodologic and conceptual challenges facing the study of urban health, arising both from the limitations of the research to date and from the complexities inherent in assessing the relations among complex urban systems, disease causation, and health are discussed.

Cities and population health

A majority of the world's population will live in urban areas by 2007 and cities are exerting growing influence on the health of both urban and non-urban residents. Although there long has been substantial interest in the associations between city living and health, relatively little work has tried to understand how and why cities affect population health. This reflects both the number and complexity of determinants and of the absence of a unified framework that integrates the multiple factors that influence the health of urban populations. This paper presents a conceptual framework for studying how urban living affects population health. The framework rests on the assumption that urban populations are defined by size, density, diversity, and complexity, and that health in urban populations is a function of living conditions that are in turn shaped by municipal determinants and global and national trends. The framework builds on previous urban health research and incorporates multiple determinants at different levels. It is intended to serve as a model to guide public health research and intervention.

Identifying environmental risk factors for asthma emergency care" a multilevel approach for ecological study

This ongoing empirical study suggests a model for evaluating a combination of environmental risk factors to explain neighborhood differences in adult use of Harlem Hospital's Asthma Emergency Department services. A multilevel or "nested" model incorporates methods for hypothesis testing using geographic information systems (GIS) and existing data from Harlem Hospital Center, city agencies, and other sources to measure variables on both building and street segment levels. Selection of the best geographic scale by which to measure housing conditions, neighborhood physical quality, income indicators, and access to healthcare is an important strategy toward identifying neighborhood socioenvironmental patterns contributing to geographic clustering of asthma emergencies. Specific community interventions may then be defined to improve the health outcomes of residents with asthma.

Perceptions of neighborhood environment for physical activity: is it "who you are" or "where you live"?

Lack of physical activity among American adults is a serious public health concern. Many factors influence activity levels, and most research has focused on either individual factors, such as race and income, or on characteristics of the physical environment, such as the availability of parks. Our study used a cross-sectional multilevel design to examine the influences of individual- and neighborhood-level characteristics on participant's perceptions of their neighborhood as an appropriate venue for physical activity. Study participants were 1,073 African American and white adults living in the St. Louis, Missouri, metropolitan area. Individual-level information was gathered from self-administered questionnaires; neighborhood-level data for these same individuals were obtained from the 2000 US Census. We found that both individual and neighborhood characteristics were significant predictors of how individuals perceived physical activity opportunities in their neighborhood, and that African Americans perceived their neighborhoods as less safe and less pleasant for physical activity than did whites, regardless of the racial composition of the neighborhood. We suggest that any evaluation of opportunities for physical activity within a neighborhood should include consideration of resident's perceptions of the safety and pleasantness of using them, and that the role of perceived and actual neighborhood conditions in explaining disparities in physical activity between African American and other populations should be examined further.

Environmental health disparities: a framework integrating psychosocial and environmental concepts

Although it is often acknowledged that social and environmental factors interact to produce racial and ethnic environmental health disparities, it is still unclear how this occurs. Despite continued controversy, the environmental justice movement has provided some insight by suggesting that disadvantaged communities face greater likelihood of exposure to ambient hazards. The exposure-disease paradigm has long suggested that differential "vulnerability" may modify the effects of toxicants on biological systems. However, relatively little work has been done to specify whether racial and ethnic minorities may have greater vulnerability than do majority populations and, further, what these vulnerabilities may be. We suggest that psychosocial stress may be the vulnerability factor that links social conditions with environmental hazards. Psychosocial stress can lead to acute and chronic changes in the functioning of body systems (e.g., immune) and also lead directly to illness. In this article we present a multidisciplinary framework integrating these ideas. We also argue that residential segregation leads to differential experiences of community stress, exposure to pollutants, and access to community resources. When not counterbalanced by resources, stressors may lead to heightened vulnerability to environmental hazards.

Person and place: the compounding effects of race/ethnicity and rurality on health

Rural racial/ethnic minorities constitute a forgotten population. The limited research addressing rural Black, Hispanic, and American Indian/Alaska Native populations suggests that disparities in health and in health care access found among rural racial/ethnic minority populations are generally more severe than those among urban racial/ethnic minorities. We suggest that disparities must be understood as both collective and contextual phenomena. Rural racial/ethnic minority disparities in part stem from the aggregation of disadvantaged individuals in rural areas. Disparities also emerge from a context of limited educational and economic opportunity. Linking public health planning to the education and economic development sectors will reduce racial/ethnic minority disparities while increasing overall well-being in rural communities.

A multilevel analysis of socioeconomic (small area) differences in household food purchasing behaviour

STUDY OBJECTIVE

To examine the association between area and individual level socioeconomic status (SES) and food purchasing behaviour.

DESIGN

The sample comprised 1000 households and 50 small areas. Data were collected by face to face interview (66.4% response rate). SES was measured using a composite area index of disadvantage (mean 1026.8, SD = 95.2) and household income. Purchasing behaviour was scored as continuous indices ranging from 0 to 100 for three food types: fruits (mean 50.5, SD = 17.8), vegetables (61.8, 15.2), and grocery items (51.4, 17.6), with higher scores indicating purchasing patterns more consistent with dietary guideline recommendations.

SETTING

Brisbane, Australia, 2000.

PARTICIPANTS

Persons responsible for their household's food purchasing.

MAIN RESULTS

Controlling for age, gender, and household income, a two standard deviation increase on the area SES measure was associated with a 2.01 unit increase on the fruit purchasing index (95% CI -0.49 to 4.50). The corresponding associations for vegetables and grocery foods were 0.60 (-1.36 to 2.56) and 0.94 (-1.35 to 3.23). Before controlling for household income, significant area level differences were found for each food, suggesting that clustering of household income within areas (a composition effect) accounted for the purchasing variability between them.

CONCLUSIONS

Living in a socioeconomically advantaged area was associated with a tendency to purchase healthier food, however, the association was small in magnitude and the 95% CI for area SES included the null. Although urban areas in Brisbane are differentiated on the basis of their socioeconomic characteristics, it seems unlikely that where you live shapes your procurement of food over and above your personal characteristics.

Confronting the challenges in reconnecting urban planning and public health

Although public health and urban planning emerged with the common goal of preventing urban outbreaks of infectious disease, there is little overlap between the fields today. The separation of the fields has contributed to uncoordinated efforts to address the health of urban populations and a general failure to recognize the links between, for example, the built environment and health disparities facing low-income populations and people of color. I review the historic connections and lack thereof between urban planning and public health, highlight some challenges facing efforts to recouple the fields, and suggest that insights from ecosocial theory and environmental justice offer a preliminary framework for reconnecting the fields around a social justice agenda.

Statistical and Substantive Inferences in Public Health: Issues in the Application of Multilevel Models

Multilevel statistical models have become increasingly popular among public health researchers over the past decade. Yet the enthusiasm with which these models are being adopted may obscure rather than solve some problems of statistical and substantive inference. We discuss the three most common applications of multilevel models in public health: (a) cluster-randomized trials, (b) observational studies of the multilevel etiology of health and disease, and (c) assessments of health care provider performance. In each area of investigation, we describe how multilevel models are being applied, comment on the validity of the statistical and substantive inferences being drawn, and suggest ways in which the strengths of multilevel models might be more fully exploited. We conclude with a call for more careful thinking about multilevel causal inference.

The association between state income inequality and worse health is not confounded by race

BACKGROUND

The relationship between income inequality and health across US states has been challenged recently on grounds that this relationship may be confounded by the effect of racial composition, measured as the proportion of the state's population who are black.

METHODS

Using multilevel statistical models, we examined the association between state income inequality and poor self-rated health. The analysis was based on the pooled 1995 and 1997 Current Population Surveys, comprising 201 221 adults nested within 50 US states.

RESULTS

Controlling for the individual effects of age, sex, race, marital status, education, income, health insurance coverage, and employment status, we found a significant effect of state income inequality on poor self-rated health. For every 0.05-increase in the Gini coefficient, the odds ratio (OR) of reporting poor health increased by 1.39 (95% CI: 1.26, 1.51). Additionally controlling for the proportion of the state population who are black did not explain away the effect of income inequality (OR = 1.30; 95% CI: 1.15, 1.45). While being black at the individual level was associated with poorer self-rated health, no significant relationship was found between poor self-rated health and the proportion of black residents in a state.

CONCLUSION

Our finding demonstrates that neither race, at the individual level, nor racial composition, as measured at the state level, explain away the previously reported association between income inequality and poorer health status in the US.