Research on racial residential segregation and health typically uses multilevel, population-based, slice-in-time data. Although research using this approach, including that by Kershaw et al. (Am J Epidemiol. 2013;177(4):299-309), has been valuable, I argue that to advance our understanding of how residential segregation influences health and health disparities, it is critical to incorporate a life-course perspective and integrate social theory. Applying a life-course perspective would entail modeling transitions, cumulative risk, and developmental and dynamic processes and mechanisms, as well as recognizing the contingency of contextual effects on different social groups. I discuss the need for analytic methods appropriate for modeling health effects of distal causes experienced across the life course, such as segregation, that operate through multiple levels and sequences of mediators, potentially across decades. Sociological theories of neighborhood attainment (e.g., segmented assimilation, ethnic resurgence, and place stratification theories) can guide effect-modification tests to help illuminate health effects resulting from intersections of residential processes, race/ethnicity, immigration, and other social determinants of health. For example, nativity and immigration history may crucially shape residential processes and exposures, but these have received limited attention in prior segregation-health literature.

Retaining severely impaired individuals poses a major challenge in longitudinal studies of determinants of dementia or memory decline. In the Health and Retirement Study (HRS), participants complete direct memory assessments biennially until they are too impaired to complete the interview. Thereafter, proxy informants, typically spouses, assess the subject's memory and cognitive function using standardized instruments. Because there is no common scale for direct memory assessments and proxy assessments, proxy reports are often excluded from longitudinal analyses. The Aging, Demographics, and Memory Study (ADAMS) implemented full neuropsychological examinations on a subsample (n=856) of HRS participants, including respondents with direct or proxy cognitive assessments in the prior HRS core interview. Using data from the ADAMS, we developed an approach to estimating a dementia probability and a composite memory score on the basis of either proxy or direct assessments in HRS core interviews. The prediction model achieved a c-statistic of 94.3% for DSM diagnosed dementia in the ADAMS sample. We applied these scoring rules to HRS core sample respondents born 1923 or earlier (n=5483) for biennial assessments from 1995 to 2008. Compared with estimates excluding proxy respondents in the full cohort, incorporating information from proxy respondents increased estimated prevalence of dementia by 12 percentage points in 2008 (average age=89) and suggested accelerated rates of memory decline over time.

Population health improvements are the most relevant yardstick against which to evaluate the success of social epidemiology. In coming years, social epidemiology must increasingly emphasize research that facilitates translation into health improvements, with continued focus on macro-level social determinants of health. Given the evidence that the effects of social interventions often differ across population subgroups, systematic and transparent exploration of the heterogeneity of health determinants across populations will help inform effective interventions. This research should consider both biological and social risk factors and effect modifiers. We also recommend that social epidemiologists take advantage of recent revolutionary improvements in data availability and computing power to examine new hypotheses and expand our repertoire of study designs. Better data and computing power should facilitate underused analytic approaches, such as instrumental variables, simulation studies and models of complex systems, and sensitivity analyses of model biases. Many data-driven machine-learning approaches are also now computationally feasible and likely to improve both prediction models and causal inference in social epidemiology. Finally, we emphasize the importance of specifying exposures corresponding with realistic interventions and policy options. Effect estimates for directly modifiable, clearly defined health determinants are most relevant for building translational social epidemiology to reduce disparities and improve population health.

Research evidence indicates that 2 forms of racial discrimination - perceived interpersonal discrimination and racial/ethnic residential segregation (a form of institutional discrimination) - may influence children's health and disparities. Although research on these 2 forms of discrimination and health has primarily focused on adults, smaller bodies of work have documented that perceived interpersonal discrimination and segregation have a negative effect on infants' health, and that perceived interpersonal discrimination may negatively affect children's mental health. Three directions for research are (1) incorporating a life-course perspective into studies of discrimination and children's health, (2) linking residential segregation with geographyof- opportunity conceptual frameworks and measures, and (3) considering residential segregation along with segregation in other contexts that influence children's health (e.g., schools).

OBJECTIVE: Leverage an experimental study to determine whether gender or recent crime victimization modify the mental health effects of moving to low-poverty neighborhoods. METHODS: The Moving to Opportunity (MTO) study randomized low-income families in public housing to an intervention arm receiving vouchers to subsidize rental housing in lower-poverty neighborhoods or to controls receiving no voucher. We examined 3 outcomes 4 to 7 years after randomization, among youth aged 5 to 16 years at baseline (n = 2829): lifetime major depressive disorder (MDD), psychological distress (K6), and Behavior Problems Index (BPI). Treatment effect modification by gender and family's baseline report of recent violent crime victimization was tested via interactions in covariate-adjusted intent-to-treat and instrumental variable adherence-adjusted regression models. RESULTS: Gender and crime victimization significantly modified treatment effects on distress and BPI (P < .10). Female adolescents in families without crime victimization benefited from MTO treatment, for all outcomes (Distress B = -0.19, P = .008; BPI B = -0.13, P = .06; MDD B = -0.036, P = .03). Male adolescents in intervention families experiencing crime victimization had worse distress (B = 0.24, P = .004), more behavior problems (B = 0.30, P < .001), and nonsignificantly higher MDD (B = 0.022, P = .16) versus controls. Other subgroups experienced no effect of MTO treatment. Instrumental variable estimates were similar but larger. CONCLUSIONS: Girls from families experiencing recent violent crime victimization were significantly less likely to achieve mental health benefits, and boys were harmed, by MTO, suggesting need for cross-sectoral program supports to offset multiple stressors.

In 1 previous study, it was shown that neighborhood socioeconomic disadvantage is associated with cognitive decline among Latinos. No studies have explored whether and to what extent individual-level socioeconomic factors account for the relation between neighborhood disadvantage and cognitive decline. The purpose of the present study was to assess the influence of neighborhood socioeconomic position (SEP) on cognitive decline and examine how individual-level SEP factors (educational level, annual income, and occupation) influenced neighborhood associations over the course of 10 years. Participants (n = 1,789) were community-dwelling older Mexican Americans from the Sacramento Area Latino Study on Aging. Neighborhood SEP was derived by linking the participant's individual data to the 2000 decennial census. The authors assessed cognitive function with the Modified Mini-Mental State Examination. Analyses used 3-level hierarchical linear mixed models of time within individuals within neighborhoods. After adjustment for individual-level sociodemographic characteristics, higher neighborhood SEP was significantly associated with cognitive function (beta = -0.033; P < 0.05) and rates of decline (beta = -0.0009; P < 0.10). After adjustment for individual educational level, neighborhood SEP remained associated with baseline cognition but not with rates of decline. Differences in individual educational levels explained most of the intra- and interneighborhood variance. These results suggest that the effect of neighborhood SEP on cognitive decline among Latinos is primarily accounted for by education.