Spatial path models with multiple indicators and multiple causes: Mental health in US counties

Structural and social determinants of inequities in violence risk: A review of indicators

There is disproportionate risk for violence conditioned on inequities due to race, socioeconomic status, gender, and where people live. Consequently, some communities are more vulnerable to violence and its repercussions than other communities. This study aims to share indicators that might be useful for violence prevention researchers interested in measuring structural or social determinants that position communities for differential risk of experiencing violence. An existing database of indicators identified in a previous review was reassessed for measures of factors that shape community structures and conditions, which place people at risk for violence. Indicators of 86 community constructs are reported. These indicators may help to advance the field by offering innovative metrics that can be used to investigate further the structural and social determinants that serve as root causes of inequities in violence risk.

Epidemiology of coronial deaths from pesticide ingestion in Australia

Pesticides in Australia are tightly regulated but it is unknown how this may affect the distribution of misuse and self-harm across Australia, both spatially and within subgroups in the population. We performed an observational study to examine spatial differences in suicide/deliberate poisonings with pesticides in Australia. We examined Coronial inquest cases of self-harm by pesticide ingestion for the years 2001-2013 (n=209). Coronial cases were older, more likely to be male, have lower SES status and live in outer regional areas as opposed to cities when compared to the general population. Case densities (cases/100,000 population) were lower in large capital cities and higher in agricultural areas: despite this half the cases occurred in major cities.

Illuminating the lifecourse of place in the longitudinal study of neighbourhoods and health

Place and health are inextricably entwined. Whilst insights have been gained into the associations between places, such as neighbourhoods, and health, the understanding of these relationships remains only partial. One of the reasons for this relates to time and change and the inter-relationships between the dynamic nature of both neighbourhoods and health. This paper argues that the lifecourse of place can be used as a conceptual framework to understand the evolution and ongoing development of neighbourhoods, and their impact on the geographies of health, past, present and future. Moreover, this paper discusses the capacity of a longitudinal form of enquiry - latent transition analysis - that is able to operationalise conceptual models of the lifecourse of place. To date, latent transition analysis has not been applied to the study of neighbourhoods and health. Drawing on research across a range of disciplines including developmental psychology, sociology, geography and epidemiology, this paper also considers praxis-based implications and recommendations for applications of latent transition analysis that aim to advance understanding of how neighbourhoods affect health in and over time.

A Spatial Analysis of Body Mass Index and Neighborhood Factors in Community-Dwelling Older Men and Women

The spatial distribution of obesity among the older population can yield insights into the influence of contextual factors associated with this public health problem. We tested the relationship between neighborhood-level characteristics and body mass index (BMI) using global and local spatial statistics of geographic clustering, using data derived from a random-digit-dial sample of 5,319 community-dwelling adults aged 50 to 74 residing in 1,313 census tracts in New Jersey. Geographically weighted regression modeled associations between BMI clusters and neighborhood characteristics, including metrics of structure, safety, demographics, and amenities. Across the sample panel, average BMI was 28.62 kg/m(2) for women and 28.25 kg/m(2) for men. There was significant spatial clustering of obesity by census tract, varying by gender across the state. Neighborhood characteristics were more strongly related to BMI for women than men. This research illuminates the role of neighborhood contextual factors and will assist community planners, officials, and public health practitioners as they address the rise in obesity.

Realist identification of group-level latent variables for perinatal social epidemiology theory building

We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.

Socio-environmental drivers and suicide in Australia: Bayesian spatial analysis

BACKGROUND

The impact of socio-environmental factors on suicide has been examined in many studies. Few of them, however, have explored these associations from a spatial perspective, especially in assessing the association between meteorological factors and suicide. This study examined the association of meteorological and socio-demographic factors with suicide across small areas over different time periods.

METHODS

Suicide, population and socio-demographic data (e.g., population of Aboriginal and Torres Strait Islanders (ATSI), and unemployment rate (UNE) at the Local Government Area (LGA) level were obtained from the Australian Bureau of Statistics for the period of 1986 to 2005. Information on meteorological factors (rainfall, temperature and humidity) was supplied by Australian Bureau of Meteorology. A Bayesian Conditional Autoregressive (CAR) Model was applied to explore the association of socio-demographic and meteorological factors with suicide across LGAs.

RESULTS

In Model I (socio-demographic factors), proportion of ATSI and UNE were positively associated with suicide from 1996 to 2000 (Relative Risk (RR)ATSI = 1.0107, 95% Credible Interval (CI): 1.0062-1.0151; RRUNE = 1.0187, 95% CI: 1.0060-1.0315), and from 2001 to 2005 (RRATSI = 1.0126, 95% CI: 1.0076-1.0176; RRUNE = 1.0198, 95% CI: 1.0041-1.0354). Socio-Economic Index for Area (SEIFA) and IND, however, had negative associations with suicide between 1986 and 1990 (RRSEIFA = 0.9983, 95% CI: 0.9971-0.9995; RRATSI = 0.9914, 95% CI: 0.9848-0.9980). Model II (meteorological factors): a 1°C higher yearly mean temperature across LGAs increased the suicide rate by an average by 2.27% (95% CI: 0.73%, 3.82%) in 1996-2000, and 3.24% (95% CI: 1.26%, 5.21%) in 2001-2005. The associations between socio-demographic factors and suicide in Model III (socio-demographic and meteorological factors) were similar to those in Model I; but, there is no substantive association between climate and suicide in Model III.

CONCLUSIONS

Proportion of Aboriginal and Torres Strait Islanders, unemployment and temperature appeared to be statistically associated with of suicide incidence across LGAs among all selected variables, especially in recent years. The results indicated that socio-demographic factors played more important roles than meteorological factors in the spatial pattern of suicide incidence.

The relationship between social fragmentation and sleep among adolescents living in Boston, Massachusetts

BACKGROUND

Sufficient sleep is needed for the healthy development of youth. However, only a small minority of adolescents obtain adequate amounts of sleep. Although individual-level correlates of sleep have been identified, studies investigating the influence of the environment on sleep are warranted.

METHODS

By using cross-sectional data collected from 1878 urban adolescents living in 38 neighborhoods participating in the 2008 Boston Youth Survey (BYS), we determined the association between neighborhood social fragmentation and sleep. Social fragmentation of each participant's residential neighborhood was composed using 2010 US Census data. Multilevel regression models were used to determine the association between social fragmentation and meeting the recommended hours of sleep (>8.5 h) and sleep duration while controlling for individual-level sex, race, age and nativity.

RESULTS

Moderate (OR = 0.51, 95% CI = 0.27, 0.97) and high (OR = 0.33, 95% CI = 0.18, 0.61) social fragmentation within the residential neighborhood was associated with a decreased likelihood of obtaining adequate sleep. Those in moderate (β = -23.9, 95% CI = -43.1, -4.8) and high (β = -22.1, 95% CI = -43.3, -0.9) socially fragmented neighborhoods obtained fewer minutes of sleep per night.

CONCLUSIONS

Social fragmentation may be an important determinant of sleep among youth living in urban settings.

Displacement, county social cohesion, and depression after a large-scale traumatic event

BACKGROUND

Depression is a common and potentially debilitating consequence of traumatic events. Mass traumatic events cause wide-ranging disruptions to community characteristics, influencing the population risk of depression. In the aftermath of such events, population displacement is common. Stressors associated with displacement may increase risk of depression directly. Indirectly, persons who are displaced may experience erosion in social cohesion, further exacerbating their risk for depression.

METHODS

Using data from a population-based cross-sectional survey of adults living in the 23 southernmost counties of Mississippi (N = 708), we modeled the independent and joint relations of displacement and county-level social cohesion with depression 18-24 months after Hurricane Katrina.

RESULTS

After adjustment for individual- and county-level socio-demographic characteristics and county-level hurricane exposure, joint exposure to both displacement and low social cohesion was associated with substantially higher log-odds of depression (b = 1.34 [0.86-1.83]). Associations were much weaker for exposure only to low social cohesion (b = 0.28 [-0.35-0.90]) or only to displacement (b = 0.04 [-0.80-0.88]). The associations were robust to additional adjustment for individually perceived social cohesion and social support.

CONCLUSION

Addressing the multiple, simultaneous disruptions that are a hallmark of mass traumatic events is important to identify vulnerable populations and understand the psychological ramifications of these events.

Neighborhood characteristics and depressive symptoms of older people: local spatial analyses

Depressive symptoms in community-dwelling older people significantly increase the risk of developing clinically diagnosable depressive disorders. Knowledge of the spatial distribution of depressive symptoms in the older population can add important information to studies of neighborhood contextual factors and mental health outcomes, but analysis of spatial patterns is rarely undertaken. This study uses spatial statistics to explore patterns of clustering in depressive symptoms using data from a statewide survey of community-dwelling older people in New Jersey from 2006 to 2008. A significant overall pattern of clustering in depressive symptoms was observed at the state level. In a subsequent local clustering analysis, places with high levels of depressive symptoms near to other places with high levels of depressive symptoms were identified. The relationships between the level of depressive symptoms in a place and poverty, residential stability and crime were analyzed using geographically weighted regression. Significant local parameter estimates for the three independent variables were observed. Local parameters for the poverty variable were positive and significant almost everywhere in the state. The significant local parameters for residential stability and crime varied in their association with depressive symptoms in different regions of the state. This study is among the first to examine spatial patterns in depressive symptoms among community-dwelling older people, and it demonstrates the importance of exploring spatial variations in the relationships between neighborhood contextual factors and health outcomes.