American journal of public health

OBJECTIVES: Recent studies have demonstrated that income inequality is related to mortality rates. It was hypothesized, in this study, that income inequality is related to reduction in social cohesion and that disinvestment in social capital is in turn associated with increased mortality. METHODS: In this cross-sectional ecologic study based on data from 39 states, social capital was measured by weighted responses to two items from the General Social Survey: per capita density of membership in voluntary groups in each state and level of social trust, as gauged by the proportion of residents in each state who believed that people could be trusted. Age-standardized total and cause-specific mortality rates in 1990 were obtained for each state. RESULTS: Income inequality was strongly correlated with both per capita group membership (r = -.46) and lack of social trust (r = .76). In turn, both social trust and group membership were associated with total mortality, as well as rates of death from coronary heart disease, malignant neoplasms, and infant mortality. CONCLUSIONS: These data support the notion that income inequality leads to increased mortality via disinvestment in social capital.

This paper provides an overview of problems in multivariate modeling of epidemiologic data, and examines some proposed solutions. Special attention is given to the task of model selection, which involves selection of the model form, selection of the variables to enter the model, and selection of the form of these variables in the model. Several conclusions are drawn, among them: a) model and variable forms should be selected based on regression diagnostic procedures, in addition to goodness-of-fit tests; b) variable-selection algorithms in current packaged programs, such as conventional stepwise regression, can easily lead to invalid estimates and tests of effect; and c) variable selection is better approached by direct estimation of the degree of confounding produced by each variable than by significance-testing algorithms. As a general rule, before using a model to estimate effects, one should evaluate the assumptions implied by the model against both the data and prior information.

Bodies of research pertaining to specific stigmatized statuses have typically developed in separate domains and have focused on single outcomes at 1 level of analysis, thereby obscuring the full significance of stigma as a fundamental driver of population health. Here we provide illustrative evidence on the health consequences of stigma and present a conceptual framework describing the psychological and structural pathways through which stigma influences health. Because of its pervasiveness, its disruption of multiple life domains (e.g., resources, social relationships, and coping behaviors), and its corrosive impact on the health of populations, stigma should be considered alongside the other major organizing concepts for research on social determinants of population health.

Objectives. We considered whether US Blacks experience early health deterioration, as measured across biological indicators of repeated exposure and adaptation to stressors.

Methods. Using National Health and Nutrition Examination Survey data, we examined allostatic load scores for adults aged 18–64 years. We estimated probability of a high score by age, race, gender, and poverty status and Blacks’ odds of having a high score relative to Whites’ odds.

Results. Blacks had higher scores than did Whites and had a greater probability of a high score at all ages, particularly at 35–64 years. Racial differences were not explained by poverty. Poor and nonpoor Black women had the highest and second highest probability of high allostatic load scores, respectively, and the highest excess scores compared with their male or White counterparts.

Conclusions. We found evidence that racial inequalities in health exist across a range of biological systems among adults and are not explained by racial differences in poverty. The weathering effects of living in a race-conscious society may be greatest among those Blacks most likely to engage in high-effort coping.

BACKGROUND. Socioeconomic status (SES) is usually measured by determining education, income, occupation, or a composite of these dimensions. Although education is the most commonly used measure of SES in epidemiological studies, no investigators in the United States have conducted an empirical analysis quantifying the relative impact of each separate dimension of SES on risk factors for disease. METHODS. Using data on 2380 participants from the Stanford Five-City Project (85% White, non-Hispanic), we examined the independent contribution of education, income, and occupation to a set of cardiovascular disease risk factors (cigarette smoking, systolic and diastolic blood pressure, and total and high-density lipoprotein cholesterol). RESULTS. The relationship between these SES measures and risk factors was strongest and most consistent for education, showing higher risk associated with lower levels of education. Using a forward selection model that allowed for inclusion of all three SES measures after adjustment for age and time of survey, education was the only measure that was significantly associated with the risk factors (P less than .05). CONCLUSION. If economics or time dictate that a single parameter of SES be chosen and if the research hypothesis does not dictate otherwise, higher education may be the best SES predictor of good health.

The gap between research and practice is well documented. We address one of the underlying reasons for this gap: the assumption that effectiveness research naturally and logically follows from successful efficacy research. These 2 research traditions have evolved different methods and values; consequently, there are inherent differences between the characteristics of a successful efficacy intervention versus those of an effectiveness one. Moderating factors that limit robustness across settings, populations, and intervention staff need to be addressed in efficacy studies, as well as in effectiveness trials. Greater attention needs to be paid to documenting intervention reach, adoption, implementation, and maintenance. Recommendations are offered to help close the gap between efficacy and effectiveness research and to guide evaluation and possible adoption of new programs.

The past few years have witnessed an explosion of interest in neighborhood or area effects on health. Several types of empiric studies have been used to examine possible area or neighborhood effects, including ecologic studies relating area characteristics to morbidity and mortality rates, contextual and multilevel analyses relating area socioeconomic context to health outcomes, and studies comparing small numbers of well-defined neighborhoods.

Strengthening inferences regarding the presence and magnitude of neighborhood effects will require addressing a series of conceptual and methodological issues. Many of these issues relate to the need to develop theory and specific hypotheses on the processes through which neighborhood and individual factors may jointly influence specific health outcomes. Important challenges include defining neighborhoods or relevant geographic areas, identifying significant area or neighborhood characteristics, specifying the role of individual-level variables, incorporating life-course and longitudinal dimensions, combining a variety of research designs, and avoiding reductionism in the way in which “neighborhood” factors are incorporated into models of disease causation and quantitative analyses.analyses.

OBJECTIVES. The purpose of this study was to identify associations between specific medical conditions in the elderly and limitations in functional tasks; to compare risks of disability across medical conditions, controlling for age, sex, and comorbidity; and to determine the proportion of disability attributable to each condition. METHODS. The subjects were 709 noninstitutionalized men and 1060 women of the Framingham Study cohort (mean age 73.7 +/- 6.3 years). Ten medical conditions were identified for study: knee osteoarthritis, hip fracture, diabetes, stroke, heart disease, intermittent claudication, congestive heart failure, chronic obstructive pulmonary disease, depressive symptomatology, and cognitive impairment. Adjusted odds ratios were calculated for dependence on human assistance in seven functional activities. RESULTS. Stroke was significantly associated with functional limitations in all seven tasks; depressive symptomatology and hip fracture were associated with limitations in five tasks; and knee osteoarthritis, heart disease, congestive heart failure, and chronic obstructive pulmonary disease, were associated with limitations in four tasks each. CONCLUSIONS. In general, stroke, depressive symptomatology, hip fracture, knee osteoarthritis, and heart disease account for more physical disability in noninstitutionalized elderly men and women than other diseases.

OBJECTIVES. A major assumption underlying youth health promotion has been that physiological risk factors track from childhood into adulthood. However, few studies have systematically examined how behaviors change during adolescence. This paper describes longitudinal tracking of adolescent health behaviors in two Minnesota Heart Health Program communities. METHODS. Beginning in sixth grade (1983), seven annual waves of behavioral measurements were taken from both communities (baseline n = 2376). Self-reported data included smoking behavior, physical activity, and food preferences. RESULTS. A progressive increase in the change to weekly smoking status was observed across the smoking status categories. As students began to experiment with smoking, they were more likely to either begin to be or remain regular smokers. Tracking of physical activity and food choice variables was also apparent. In nearly all the follow-up periods, the students identified at baseline as measuring high remained high, and those measuring low remained low. CONCLUSIONS. These results indicate that there is evidence of early consolidation and tracking of physical activity, food preference, and smoking behavior. The early consolidation of health behaviors implies that interventions should begin prior to sixth grade, before behavioral patterns are resistant to change. The smoking results suggest that students are experiencing difficulty quitting smoking; thus, youth smoking cessation interventions are warranted.

Objectives. We assessed the association between minority stress, mental health, and potential ameliorating factors in a large, community-based, geographically diverse sample of the US transgender population.

Methods. In 2003, we recruited through the Internet a sample of 1093 male-to-female and female-to-male transgender persons, stratified by gender. Participants completed an online survey that included standardized measures of mental health. Guided by the minority stress model, we evaluated associations between stigma and mental health and tested whether indicators of resilience (family support, peer support, identity pride) moderated these associations.

Results. Respondents had a high prevalence of clinical depression (44.1%), anxiety (33.2%), and somatization (27.5%). Social stigma was positively associated with psychological distress. Peer support (from other transgender people) moderated this relationship. We found few differences by gender identity.

Conclusions. Our findings support the minority stress model. Prevention needs to confront social structures, norms, and attitudes that produce minority stress for gender-variant people; enhance peer support; and improve access to mental health and social services that affirm transgender identity and promote resilience.