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Exposure to natural disasters has been linked to a range of adverse outcomes, including mental health problems (e.g., posttraumatic stress symptoms [PTSS], depression), declines in role functioning (e.g., occupational difficulties), and physical health problems (e.g., somatic complaints). However, prior research and theory suggest that the modal postdisaster response in each of these domains is resilience, defined as low levels of symptoms or problems in a given outcome over time, with minimal elevations that are limited to the time period during the disaster and its immediate aftermath. However, the extent to which disaster survivors exhibit mental health wellness (resilience across multiple mental health conditions) or general wellness (resilience across mental health, physical health, and role functioning domains) remains unexplored. The purpose of this study was to quantify mental health and general wellness, and to examine predictors of each form of wellness, in a three-wave population-based study of Hurricane Ike survivors (N = 658). Latent class growth analysis was used to determine the frequency of resilience on four outcomes (PTSS: 74.9%; depression: 57.9%; functional impairment: 45.1%; days of poor health: 52.6%), and cross-tabulations were used to determine the frequency of mental health wellness (51.2%) and general wellness (26.1%). Significant predictors of both mental health and general wellness included lower perievent emotional reactions and higher community-level collective efficacy; loss of sentimental possessions or pets and disaster-related financial loss were negative predictors of mental health wellness, and loss of personal property was a negative predictor of general wellness. The results suggest that studies focusing on a single postdisaster outcome may have overestimated the prevalence of mental health and general wellness, and that peri-event responses, personal property loss and collective efficacy have a cross-cutting influence across multiple domains of postdisaster functioning.

respondents who practised the highest levels of physical activity and who performed athletic activities were at lower risk for depression. Interventions aimed at promoting athletic physical activity among older adults may generate benefits for mental health.

The pathways through which neighborhood poverty can affect resident depression are still unknown. We investigated mechanisms through which neighborhood poverty may influence depression among older adults. Participants were drawn from the New York City Neighborhood and Mental Health in the Elderly Study II, a 3-wave study of adults aged 65–75 (n=3,497) at baseline. Neighborhood poverty and homicide were associated with depressive symptoms at follow-up waves (RR:1.20, 95%CI: 1.05, 1.36; RR: 1.09, 95%CI: 1.02, 1.17, respectively). Homicide accounted for 30% of the effect of neighborhood poverty on depressive symptoms. Neighborhood exposure to violence may be a key mechanism through which neighborhood poverty influences depression among older adults.

Background Few older adults achieve recommended physical activity levels. We conducted a ‘Neighborhood Environment-Wide Association Study (NE-WAS)’ of neighborhood influences on physical activity among older adults, analogous, in a genetic context, to a Genome Wide Association Study (GWAS). Methods Physical Activity Scale for the Elderly (PASE) and socio-demographic data were collected via telephone survey of 3,497 residents of New York City aged 65–75. Using Geographic Information Systems, we created 337 variables describing each participant’s residential neighborhood’s built, social, and economic context. We used survey-weighted regression models adjusting for individual-level covariates to test for associations between each neighborhood variable and 1) total PASE score, 2) gardening activity, 3) walking, and 4) housework (as a negative control). We also applied two ‘Big Data’ analytic techniques, LASSO regression and Random Forests, to algorithmically select neighborhood variables predictive of these four physical activity measures. Results Of all 337 measures, proportion of residents living in extreme poverty was most strongly associated with total physical activity (−0.85 (95% CI: −1.14, −0.56) PASE units per 1% increase in proportion of residents living with household incomes less than half the federal poverty line). Only neighborhood socioeconomic status and disorder measures were associated with total activity and gardening, whereas a broader range of measures was associated with walking. As expected, no neighborhood measures were associated with housework after accounting for multiple comparisons. Conclusions This systematic approach revealed patterns in the domains of neighborhood measures associated with physical activity. Impact The NE-WAS approach appears to be a promising exploratory technique.

Introduction Little research to date has explored typologies of physical activity among older adults. An understanding of physical activity patterns may help to both determine the health benefits of different types of activity and target interventions to increase activity levels in older adults. This analysis, conducted in 2014, used a latent class analysis approach to characterize patterns of physical activity in a cohort of older adults. Methods A total of 3,497 men and women aged 65–75 years living in New York City completed the Physical Activity Scale for the Elderly (PASE) in 2011. PASE scale items were used to classify subjects into latent classes. Multinomial regression was then used to relate individual and neighborhood characteristics to class membership. Results Five latent classes were identified: “least active,” “walkers,” “domestic/gardening,” “athletic,” and “domestic/gardening athletic.” Individual-level predictors, including more education, higher income, and better self-reported health, were associated with membership in the more-active classes, particularly the athletic classes. Residential characteristics, including living in single-family housing and living in the lower-density boroughs of New York City, were predictive of membership in one of the domestic/gardening classes. Class membership was associated with BMI even after controlling for total PASE score. Conclusions This study suggests that individual and neighborhood characteristics are associated with distinct physical activity patterns in a group of older urban adults. These patterns are associated with body habitus independent of overall activity.

We investigated geographic concentration in elevated risk for a range of postdisaster trajectories of chronic posttraumatic stress symptom (PTSS) and depression symptoms in a longitudinal study (N = 561) of a Hurricane Ike affected population in Galveston and Chambers counties, TX. Using an unadjusted spatial scan statistic, we detected clusters of elevated risk of PTSS trajectories, but not depression trajectories, on Galveston Island. We then tested for predictors of membership in each trajectory of PTSS and depression (e.g., demographic variables, trauma exposure, social support), not taking the geographic nature of the data into account. After adjusting for significant predictors in the spatial scan statistic, we noted that spatial clusters of PTSS persisted and additional clusters of depression trajectories emerged. This is the first study to show that longitudinal trajectories of postdisaster mental health problems may vary depending on the geographic location and the individual- and community-level factors present at these locations. Such knowledge is crucial to identifying vulnerable regions and populations within them, to provide guidance for early responders, and to mitigate mental health consequences through early detection of mental health needs in the population. As human-made disasters increase, our approach may be useful also in other regions in comparable settings worldwide.

Neighborhood physical disorder-the visual indications of neighborhood deterioration-may inhibit outdoor physical activity, particularly among older adults. However, few previous studies of the association between neighborhood disorder and physical activity have focused on this sensitive population group, and most have been cross-sectional. We examined the relationship between neighborhood physical disorder and physical activity, measured using the Physical Activity Scale for the Elderly (PASE), in a three-wave longitudinal study of 3497 New York City residents aged 65-75 at baseline weighted to be representative of the older adult population of New York City. We used longitudinal mixed linear regression controlling for a number of individual and neighborhood factors to estimate the association of disorder with PASE score at baseline and change in PASE score over 2 years. There were too few subjects to assess the effect of changes in disorder on activity levels. In multivariable mixed regression models accounting for individual and neighborhood factors; for missing data and for loss to followup, each standard deviation increase in neighborhood disorder was associated with an estimated 2.0 units (95% CI 0.3, 3.6) lower PASE score at baseline, or the equivalent of about 6 min of walking per day. However, physical disorder was not related to changes in PASE score over 2 years of follow-up. In this ethnically and socioeconomically diverse population of urban older adults, residents of more disordered neighborhoods were on average less active at baseline. Physical disorder was not associated with changes in overall physical activity over time.