Exploring the Spatial Association between Social Deprivation and Cardiovascular Disease Mortality at the Neighborhood Level

Abstract

Cardiovascular disease (CVD), the leading cause of death in the United States, is impacted by neighborhood-level factors including social deprivation. To measure the association between social deprivation and CVD mortality in Harris County, Texas, global (Ordinary Least Squares (OLS) and local (Geographically Weighted Regression (GWR)) models were built. The models explored the spatial variation in the relationship at a census-tract level while controlling for age, income by race, and education. A significant and spatially varying association (p < .01) was found between social deprivation and CVD mortality, when controlling for all other factors in the model. The GWR model provided a better model fit over the analogous OLS model (R2 = .65 vs. .57), reinforcing the importance of geography and neighborhood of residence in the relationship between social deprivation and CVD mortality. Findings from the GWR model can be used to identify neighborhoods at greatest risk for poor health outcomes and to inform the placement of community-based interventions.

Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany

“…Former studies applying GWR on hypertension also found that the association between socio-economic status and hypertension depends largely on the place of residence [ 65 ]. Similar findings were reported for the association between cardiovascular disease and area deprivation [ 60 ]. Our results correspond well to these findings, showing that area deprivation is a significant predictor only in a part of the study area.…”

“…Although the proportion of insurants aged 65 and older was significant in almost the entire study area, the strongest associations could also be observed in more deprived areas. The finding that demographic variables display a stronger association to chronic diseases in areas with higher deprivation is supported by previous findings for cardiovascular disease mortality [ 60 ] and highlights the use of GWR to analyze location-specific correlations between chronic conditions, demographic variables and area deprivation.…”

“…Local clustering was especially observed in rural areas surrounding Berlin and in parts of Mecklenburg-West Pomerania. Strong regional variations in prevalence estimates for chronic diseases are typical, not only for hypertension [ 3 , 55 , 56 ] but also for a wide range of other diseases such as Diabetes Mellitus [ 26 , 57 , 58 ] or cardiovascular diseases [ 59 , 60 ]. It is important to note that the spatial distribution of hypertension in northeastern Germany is partially similar to the spatial distribution of type 2 diabetes mellitus [ 26 ], which has also been observed in the United States [ 61 ] and Germany [ 3 ].…”

Neighborhood Environmental Health and Premature Death From Cardiovascular Disease

“…Additionally, living in a healthy place can affect different subpopulations in different ways (26). For example, modification of CVD risk factors may have less effect among those with diagnosed or advanced CVD when compared with those who are yet undiagnosed and have modifiable risk factors, such as obesity or inactivity (27). The different relationship between neighborhood-level food access and premature CVD mortality in the 2 series of models presented here supports the importance of examining how the characteristics of a place might have different effects on the health of the population living there.…”

Small-area variation of cardiovascular diseases and select risk factors and their association to household and area poverty in South Africa: Capturing emerging trends in South Africa to better target local level interventions

“…A systematic review of the socio-demographic patterns of hypertension prevalence in low-and-middle-income countries (LMIC) found that the prevalence of hypertension was associated with and varied by socio-demographic region [7]. Elsewhere, Ford and Highveld [8] have shown that geographic disparities in the distribution of certain cardiovascular morbidity have been observed and linked to socioeconomic deprivation; however, little is known about the geographic overlaps in these conditions. The overlapping epidemiology of the conditions may be better understood by pooling data across the conditions in a unified way [9].…”