Time-varying residential neighborhood effects on cardio-metabolic health

Cardio-metabolic (CM) diseases are one of the leading causes of premature death worldwide and a major contributor to health disparities (Diez Roux et al., 2016). CM diseases have various intertwined proximal causes such as physical inactivity, unhealthy diet, obesity, hypertension, type 2 diabetes, dyslipidemia and the metabolic syndrome. More distal (environmental) causes remain poorly understood at the population level and are barely tackled by public health interventions. Research on CM health has two major shortcomings that are addressed in this proposal: i) incomplete understanding of the complex mechanisms explaining how neighborhood environmental exposure contributes to CM health; ii) causal inference limitations due to insufficient longitudinal evidence. Epidemiology has traditionally focused on the individual risk factors of CM health (i.e. behavioral, biological and genetic), rather than environmental ones (Diez Roux et al., 2016). However, the dramatic increase in CM diseases over recent decades is more likely to be related to changes in the socio-economic environment in which behavioral patterns occur, and in the physical environment?amenities, urban form, transport infrastructure?than to biological or genetic changes (Leal and Chaix, 2011). These changes have resulted in the hegemonic development of motorized transportation, increased fast-food consumption, more sedentary occupations and growing sedentary leisure (TV viewing, video games, etc.), which, together, constitute a breeding ground for CM-related disorders (Leal and Chaix, 2011). More-recent evidences about CM health variability at the neighborhood level have increased interest in how social and environmental factors contribute to shape CM risks. The meso-level of neighborhoods is most suited for studying the links between environments and CM health disparities. Three major reasons support this approach (Diez Roux et al., 2016): i) the neighborhood provides a concrete opportunity to observe the dynamic processes linking social and environmental factors to CM health ii) socio-economic disparities and residential segregation crystallize at the neighborhood scale, thus revealing health inequalities iii) disparities between neighborhoods are notably the result of policies and public (in)action, which can be addressed by tailored and geographically-driven interventions Causal inference regarding neighborhood effects on CM health is constrained by the scarce investigation of time-varying social and environmental factors on the development of CM diseases. Most neighborhood and health studies suffer directly from design limitations ascribable to cross-sectional studies (Daniel et al., 2008). The dynamic processes between cumulative place-based exposure and CM health over time can only be established through a longitudinal approach, which to date remains very underused and mostly oriented towards obesity-related outcomes (Chandrabose et al., 2019). In this context, one of the most significant opportunity for reducing CM diseases and further social disparities in health lies in identifying the causal pathways linking neighborhood characteristics to CM health.