Latent Trajectory Modeling of Spatiotemporal Relationships Between Land Cover and Land Use, Socioeconomics, and Obesity in Ghana
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Obesity is a growing public health concern in both developed and developing countries, creating acute challenges in places with scant resources. In Ghana, obesity rates have risen substantially in recent decades, a trend particularly noted in urban areas. However, high levels of migration and urbanization indicate a situation that is more complex than a simple urban/rural distinction may be able to explain. Latent trajectory modeling (LTM) with eigenvector spatial filtering offers a methodology to explore the spatial and temporal patterns of body mass index (BMI) change by going beyond the urban/rural distinction and examining how different environmental, social, and demographic variables contribute to BMI changes over time. Using data from a regional LULC study and the Ghana Demographic Health Survey (1993, 1998, 2003, 2008), the relationship between BMI and the amounts of urban, agricultural, and natural land covers, household size, % of houses with electricity, % houses with flush toilets, and % of houses with no toilets for 845 survey clusters is explored. Our findings suggest higher BMIs in the most urban areas, yet larger BMI increases in peri-urban areas (and lower BMI changes in slums and increasingly rural areas). The LTM modeling indicates a trajectory of BMI growth in the study region, yet one that is slowing over time. Earlier, indicators of higher socioeconomic status and larger households are associated with high BMIs, but these indicators are not associated with rising BMI over the entire study period. Areas with increases in urban land cover show consistent, significant relationships with BMI growth.
KeywordsObesity Spatial modeling Eigenvector spatial filtering Latent trajectory model Ghana The urban transition
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