Extending an inter-generational cohort to develop a multimorbidity research platform in rural and urbanising India

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In India, people that have more than one long-term health condition ("multimorbidity") are more likely to have high healthcare costs, which they usually pay out-of-pocket, and to be disabled which can affect their ability to work. As a result, multimorbidity can impact the economic well-being of people's families, potentially pushing them below the poverty line. Rural and urbanising communities are particularly vulnerable to rapid rises in multimorbidity because social changes are affecting behaviours (e.g. people are eating more processed foods) and environmental exposures (e.g. rising air pollution from traffic), while old, poverty-related health issues (e.g. malnutrition) remain common. Healthcare is also lacking in these areas, so people can struggle to manage their conditions. As a result of these factors, rising multimorbidity could inhibit future development in rural and urbanising areas. As such, it is important to understand what causes multimorbidity, so that we can develop ways to prevent it. This study will build on work done over the past 30 years in 29 villages on the outskirts of Hyderabad city, Telangana. The study team has previously collected detailed health data on families within these villages (the Andhra Pradesh Children and Parents Study) (~5% of the village population, N=6,972, aged ~22-50 in 2010-12) who were involved in a trial of nutritional supplements for pregnant women and young children in the 1980s. Our ultimate aim is to follow this cohort up over the long-term to see how conditions develop and cluster together at different life-stages, to examine what causes these clusters, and to develop ways to target these causes to prevent multimorbidity developing. We will particularly investigate how factors at early-life (e.g. malnutrition) and related to the rapidly changing environment (e.g. air pollution) are linked to multimorbidity, as their impact on multimorbidity has not been assessed. Nevertheless, we need to do considerable groundwork to be able to do this accurately. This current study will analyse previously collected data to understand which clusters of conditions and potential causes are important in the local community. We will also collect data on the presence of chronic conditions in the older sub-group of the cohort (N=~2,000, aged ~60 in 2020), who are more likely to experience multiple conditions. This will be analysed in combination with previously collected data (2010) and used to calculate how many community members we need to study to accurately quantify the impact of potential causes on the risk of multimorbidity. We will also interview people with varying severities of multimorbidity (and their family members) and conduct focus-group discussions with wider community members, to understand how multimorbidity affects people's lives and what they wish APCAPs to prioritise and research in the future. A final goal is to investigate how feasible it would be to develop a system that automatically collects data on community members' healthcare records, as this would allow us to collect data over the long-term and at low cost. We will do this by randomly selecting 200 of the surveyed cohort who have used healthcare in the past year, tracking down their records in local facilities, and comparing the diagnosis with results from our own clinical examinations. Working closely with community members and key parties (e.g. local health workers, village leaders), we will use the above findings to develop a research proposal for a multimorbidity research platform, to establish the causes of multimorbidity, assess its impact, and develop and test ways of preventing multimorbidity. We expect our findings will also be applicable to other communities experiencing similar social changes.