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

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.

Despite rapid urbanisation, 65% of India's population resides in rural areas. Socioeconomic development is changing these communities, affecting behaviours (e.g. poor diet) and environmental exposures (e.g. air pollution) alongside prevailing poverty-related risks (e.g. undernutrition), which is predicted to lead to a significant rise in multimorbidity. Local healthcare services, which are largely private, are ill-equipped to manage multimorbidity, leaving rural and peri-urban populations highly vulnerable to catastrophic health expenditures and loss of productivity, potentially inhibiting future development. Our ultimate goal is to establish a multimorbidity research platform for examining the lifecourse and environmental determinants of multimorbidity in rural and urbanising India, and for developing interventions for multimorbidity prevention and management. We propose to do this by extending the Andhra Pradesh Children and Parents Study cohort (N=6,972) and thus capitalising on 30 years of investment from participants, investigators and funders. The current proposal will lay the foundations for the future research platform by: using existing APCAPs data to identify key lifecourse and environmental risk-factors and common clusters of multimorbidity, estimating incident multimorbidity to inform on the required sample size, qualitatively assessing multimorbidity burden and community wishes for future research, and evaluating the feasibility of developing a healthcare surveillance system for future low-cost data collection. Findings from this research will have applications for multimorbidity prevention and management in rural and urbanising India and other populations at similar stages of socioeconomic development.

We expect our study to generate the following impact:
1) Economic productivity and reduced inequalities
Lost productivity (of both the individual and their caregiver) and high healthcare costs associated with multimorbidity can lead to declines in household income and consumption, pushing low-income households into poverty and extending the economic burden onto younger generations. Caregiving can lead to women leaving their jobs and curtailing their careers, which inhibits the already low proportion of women in the workforce and thus India's continued socioeconomic development. By developing interventions to prevent multimorbidity and its burden, our research will help stop the intergenerational cycle of poverty that results from lost economic productivity and catastrophic health expenditure, and which exacerbates social and gender inequalities.
2) Improve policy making across various domains, for instance rural development, taxation
Local and national decision-makers will be provided with a policy-brief outlining our findings, for instance clear evidence on the impact of environmental change (for instance rapid and unplanned urbanisation) and lack of change (for instance lack of primary care services) on the multimorbidity burden in rural and urbanising India. Our findings on the healthcare system in rural and urbanising India will be particularly useful for the local government at this time, as they are in the midst of implementing healthcare reform ("Modicare") which aims to reduce the urban/rural divide in service availability. The highly detailed nature of APCAPs data means it can also be used to inform on policies outside of health. For example, assessment of the effects of different types and sources (e.g. workplace, construction) of ambient pollution on chronic health could guide on policies related to workers' rights or urban planning, while detailed evidence on the influence of diet could be used for related polices, for instance a sugar tax.
3) Industry
We will assess the feasibility of different tech-based healthcare surveillance models (for example a patient-led mHealth application). A low-cost surveillance system would be very attractive to policy makers, for instance the Indian Council of Medical Research previously agreed to fund the establishment of a surveillance system in the APCAPs villages. In the future, we will develop the tech-based system with input from state-level policy makers and utilise the potential and infrastructure available in the Indian science and technology industry. We predict that government interest in the system will be very attractive to the industry, and may thus spark interest in the development of similar applications which could be used nationwide or further. We shall particularly aim to use the emerging talent in the Indian tech industry, for instance through approaching start-up hubs (e.g. T-Hub based in Hyderabad, or the Indian Institute of Madras Incubation Cell).
4) Improved public health interventions
Our research will identify key risk factors that influence the emergence and onset of multimorbidity across the lifecourse in populations (such as rural and urbanising India) experiencing the convergence of traditional "rural" and novel "urban" risks. The lifecourse approach is crucial for the development of well-timed, high-impact, and contextually relevant prevention and health promotion efforts. Our findings will guide the development and testing of interventions to prevent and treat multimorbidity, and reduce its individual and household-level burden.
5) Improved capacity in-country: Through rigorous and structured capacity building activities we will enhance research competencies of emerging- and mid- career researchers in India. This will allow the creation of a cohort of young researchers with competencies to conceptualise, plan, and deploy high quality epidemiological research studies necessary to answer crucial public health questions in low-resource settings