Harnessing Longitudinal Health Data for Aging Populations

Importance: Longitudinal data are crucial for understanding rapid population aging in East and Southeast Asia, yet challenges in establishing and managing infrastructures remain undocumented. Objective: To investigate challenges and adaptations across longitudinal aging datasets in East and Southeast Asia and synthesize stakeholder-informed processes and recommendations to guide future study design, implementation, sustainability, and data sharing. Design, Setting, and Participants: This qualitative study used semistructured interviews conducted online and in-person from September 2024 to June 2025. Data were analyzed using a combined inductive, deductive, and abductive approach to identify themes related to the life cycle of longitudinal aging studies. Stakeholders were engaged across 13 East and Southeast Asia countries and regions (China, Japan, South Korea, and countries in the Association of Southeast Asian Nations), and experts from India, the United Kingdom, and the US. Participants were a purposive and snowball sample of 33 stakeholders involved in aging research data collection and management, including principal investigators, coordinators, and data platform leaders, and other key personnel with experience establishing or managing aging-related health datasets. Main Outcomes and Measures: Themes on challenges and strategies in the establishment, implementation, maintenance, and sharing of longitudinal aging data were identified through thematic analysis. An iterative thematic analysis to identify recurring patterns was conducted from January to June 2025. Results: Of 33 participants, 23 (72.7%) were principal investigators or co-principal investigators. Four themes emerged: (1) structural and contextual barriers, including funding instability, collaboration silos, and personnel shortages; (2) adapting research design and logistics to local contexts, addressing cultural differences, data accuracy, and biospecimen handling; (3) retaining funding and staff to ensure sustainability amid external disruptions; and (4) constraints related to data governance, privacy regulations, and limited comparability. Conclusions and Relevance: In this qualitative study of stakeholders involved in longitudinal aging research data systems, participants described structural and contextual barriers, reported adaptations to local research logistics and design, highlighted sustainability threats related to funding and retention, and identified persistent constraints in data governance and cross-study comparability. These findings suggest that building longitudinal aging data ecosystems in East and Southeast Asia requires context-specific strategies aligned with policies, strengthened multidisciplinary collaboration, improved data harmonization, and intentional inclusion of vulnerable populations to inform healthy aging policy, while yielding stakeholder-informed processes and recommendations to support future cohort development and sustainability.