Abstract Low-income and middle-income countries (LMICs) share a higher burden of cardiovascular diseases (CVD). Rapid transitions in the built environment impacts life course trajectories of physical activity, diet, and body composition. Life course epidemiology is a valid approach to unravel CVD aetiology. Effective use of life course approaches requires the adoption of conceptual models, overcoming data availability gaps in resource-poor settings, and using appropriate statistical methods. We provide a template for using life course epidemiology in LMICs to highlight the knowledge and resource gaps. For illustration we use a case study to assess multi-level determinants of the South Asian thin-fat phenotype in the Andhra Pradesh Children and Parents Study (APCAPS, 1994-2023) based in rural India. A socio-ecological causal model of CVD risk specific to South Asians was adopted and setting-specific indicators identified. Life course data acquisition challenges and solutions used were described. The complex nature of multi-level determinants and appropriate statistical approaches were discussed using Directed Acyclic Graphs (DAGs). An increasing number of birth cohort studies in LMICs are at different stages of maturity and are spread across settings that have an untapped potential to contribute towards contextualization of life course epidemiology in these settings. The proposed template in this paper serves as a guide towards the same.
Sharma et al. (Mon,) studied this question.