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Project 1
Climate Change, Population Aging, and Health of Older Adults in LMICs
(2025-2027)
Climate change poses significant challenges to global health, particularly for vulnerable populations such as older adults in LMICs. Rising temperatures, increased frequency of extreme weather events, and environmental disruptions such as floods and droughts exacerbate health risks for older individuals, who are already more susceptible to chronic diseases, mobility limitations, and weakened immune systems (Gaugler, 2024; Tipaldo, Balk, & Hunter, 2024; Prina et al., 2024). Heat stress can lead to dehydration, heatstroke, and cardiovascular complications, while climate-induced displacement may result in overcrowded living conditions and limited access to healthcare, further endangering elderly health (Kohon et al., 2024; United States EPA).
In LMICs, the effects of climate change on older adults are compounded by weaker health infrastructure and fewer resources for climate adaptation, making older populations even more vulnerable to environmental shifts (Carr, Falchetta, & Wing, 2024; Woychik et al., 2022). In these settings, family structures and intergenerational relationships play a critical role in mitigating the impacts of climate-related challenges. Families often serve as primary caregivers and support networks, providing both emotional and physical assistance during crises (Roy & Ayalon, 2024; Dabelko-Schoeny et al., 2024). The strength of these familial bonds, however, is influenced by socioeconomic factors, family size, and generational dynamics, which can either enhance or limit older adults' resilience to climate stressors (Strough et al., 2024; Peterson et al., 2024).
These intergenerational dynamics also shape health disparities, as older adults with strong family support networks may fare better in times of climate-related crises, while those with weaker family ties may face greater isolation and health risks (Roy & Ayalon, 2024; Malecki et al., 2022). Given these factors, effective policy responses must address not only the immediate health impacts of climate change but also the structural support systems—particularly families—that are crucial in helping older adults navigate these challenges. Policy interventions should focus on strengthening health infrastructure, improving access to climate adaptation resources for elderly populations, and fostering intergenerational solidarity to build resilience against the dual threats of aging and climate change in LMICs (Tipaldo, Balk, & Hunter, 2024; Gong, Yang, & Deng, 2025; Zuelsdorff & Limaye, 2024).
References
Gaugler, J. E. (2024). Climate change and aging. The Gerontologist, 64(3), gnae006.
Wu, Y.-T., Prina, M., & Zaninotto, P. (2025). Climate change and healthy aging: What are the existing data in aging studies? Innovation in Aging, 9(4), igaf008.
Chen, S., Liu, Y., Yi, Y., Zheng, Y., Yang, J., Li, T., Chan, T.-C., Duan, R., He, S., & Guo, C. (2025). Long-term impacts of heatwaves on accelerated ageing. Nature Climate Change.
Carlson, B., Kohon, J. N., Carder, P. C., Himes, D., Toda, E., & Tanaka, K. (2024). Climate change policies and older adults: An analysis of states’ climate adaptation plans. Gerontologist, 64(3), 1–10.
Carr, D., Falchetta, G., & Wing, I. S. (2024). Population aging and heat exposure in the 21st century: Which U.S. regions are at greatest risk and why? Gerontologist, 64(3), 1–10.
Dabelko-Schoeny, H., Dabelko, G. D., Rao, S., Damico, M., Doherty, F. C., Traver, A. C., & Sheldon, M. (2024). Age-friendly and climate resilient communities: A grey green alliance. Gerontologist, 64(3), 1–6.
Kohon, J. N., Tanaka, K., Himes, D., Toda, E., Carder, P. C., & Carlson, B. (2024). Extreme heat vulnerability among older adults: A multi-level risk index for Portland, Oregon. Gerontologist, 64(3), 1–10.
Peterson, L. J., Hackett, S. E., Dobbs, D., & Haley, W. E. (2024). Dementia caregivers’ perspectives on disaster preparedness: Barriers, resources, and recommendations. Gerontologist, 64(3), 1–8.
Roy, S., & Ayalon, L. (2024). “They did not know what they were doing”: Climate change and intergenerational compassion. Gerontologist, 64(3), 1–9.
Strough, J. N., Parker, A. M., Ayer, L., Parks, V., & Finucane, M. L. (2024). Aging and emotional well-being after disasters: Vulnerability and resilience. Gerontologist, 64(3), 1–11.
Zuelsdorff, M., & Limaye, V. S. (2024). A framework for assessing the effects of climate change on dementia risk and burden. Gerontologist, 64(3), 1–7.
United States Environmental Protection Agency: Climate Change and the Health of Older Adults
Malecki, K. M. C., Andersen, J. K., Geller, A. M., et al. (2022). Integrating environment and aging research: Opportunities for synergy and acceleration. Frontiers in Aging Neuroscience, 14, 824921.
Prina, M., Khan, N., Akhter Khan, S., et al. (2024). Climate change and healthy ageing: An assessment of the impact of climate hazards on older people. Journal of Global Health, 14, 04101.
Tipaldo, J. F., Balk, D., & Hunter, L. M. (2024). A framework for ageing and health vulnerabilities in a changing climate. Nature Climate Change, 14(11), 1125–1135.
Woychik, R. P., Bianchi, D. W., Gibbons, G. H., et al. (2022). The NIH Climate Change and Health Initiative and Strategic Framework: Addressing the threat of climate change to health. The Lancet, 400(10366), 1831–1833.
Zuelsdorff, M., & Limaye, V. S. (2024). A framework for assessing the effects of climate change on dementia risk and burden. In J. E. Gaugler (Ed.), The Gerontologist, 64(3), gnad082.
Kim, J. S., & Kim, S. K. (2024). Ageing population and green space dynamics for climate change adaptation in Southeast Asia. Nature Climate Change, 14(5), 490–495.
Gong, F.-Y., Yang, Z., & Deng, S. (2025). Fine-scale assessment of diurnal heat health risk based on satellite and street view images. Cities, 162, 105963.
Resource
The virtual Center for Aging, Climate, and Health aims to facilitate research and foster collaborations among a wide-range of researchers working at the nexus of aging, health and climate change through targeted interdisciplinary training, information sharing, and investments in research support. Through these objectives, CACHE improves understanding of the public health consequences of environmental conditions and change of the 21st century.
For decades, Cornell University gerontologists and geriatricians have conducted are search program on the question: How can we best protect and improve the quality of life of the most vulnerable older persons? The Cornell Initiative for Research on Climate and Aging (CIRCA) builds upon this long standing collaboration to address one of the most daunting and understudied challenges to the health and wellbeing of older persons: climate change. Recognizing that older people are the most at-risk population for many of the effects of climate change, CIRCA’s work focuses on the intersection of the climate crisis and the rapidly growing aging population through a comprehensive approach that includes biological, psychological, and social factors. CIRCA's focus moves beyond the issue of vulnerability to examine how older people can become active agents in climate change prevention and resilience. By leveraging interdisciplinary research, fostering collaborations, and translating findings into practical interventions, CIRCA is dedicated to protecting and enhancing the well-being of older adults in the face of climate-related challenges. CIRCA unites researchers, policy makers, and practitioners to create a resilient future for aging populations.
Project 2
Early-Life Conditions and Health Disparities of Older Adults in LMICs
(2025-2027)
Early-life conditions play a critical role in shaping the health trajectories of individuals as they age, particularly in LMICs, where access to healthcare and socioeconomic resources is often limited. Adverse childhood conditions—such as malnutrition, exposure to infectious diseases, and lack of access to education—have been shown to contribute to long-term health disparities, including chronic diseases, disabilities, and mental health challenges in older adulthood. These disparities are compounded by the socio-economic and healthcare environments prevalent in many LMICs, where public health systems may be under-resourced and unable to meet the complex needs of aging populations.
Family structures and intergenerational relationships also significantly influence the health and well-being of older adults in LMICs. In many contexts, the family remains the primary source of care and support for elderly individuals, with varying levels of economic, emotional, and caregiving support depending on family size, wealth, and generational dynamics. The support—or lack thereof—that older adults receive from younger generations can impact their access to healthcare, mental health outcomes, and overall life satisfaction. Additionally, intergenerational reciprocity, both in terms of financial assistance and caregiving, can mitigate the adverse effects of early-life disadvantages, while also contributing to health disparities if such support is insufficient or uneven.
This intersection of early-life conditions, family dynamics, and aging presents critical implications for policy and intervention strategies to reduce health disparities in older populations. Effective policies must address the root causes of early-life disadvantages, while also considering how family-based interventions can support the health of aging adults. Approaches that promote better access to healthcare, enhance social protection systems, and strengthen intergenerational solidarity are essential for improving health outcomes and reducing inequalities in aging populations in LMICs.
References
Wanka, A., Freutel-Funke, T., Andresen, S., & Oswald, F. (Eds.). (2024). Linking Ages: A Dialogue between Childhood and Ageing Research. Routledge.
Project 3
Aging and Digital (In)Equality in LMICs
(2025-2028)
The Institute for Advanced Study (IAS) School of Social Science's 2025–26 theme on Digital (In)Equality provides a timely and crucial lens to examine the intersection of digital inequality and equality, particularly in the context of an aging global population. Digital technologies are increasingly shaping how societies respond to the challenges and opportunities posed by population aging, especially in areas such as healthcare, economic security, social participation, and intergenerational relationships (Gallistl et al., 2024). However, the digital divide—both within and across nations—continues to exacerbate inequalities among older adults, particularly in LMICs. Older adults face unique barriers to digital inclusion, including limited digital literacy, inadequate access to technology, and algorithmic biases that fail to consider their specific needs (Chu et al., 2022; Guo, 2025). These challenges are compounded by broader structural inequalities related to income, education, gender, and geographic location (Poli et al., 2023).
At the same time, digital technologies hold significant potential to enhance the lives of older adults, offering tools for improved healthcare delivery, expanded social networks, and opportunities for lifelong learning and civic engagement (Felber et al., 2024). This paradox—where digital technologies both constrain and enable equity—aligns closely with the theme’s exploration of the co-constitution of digital inequality and equality (Gallistl et al., 2024).
This research operates at the nexus of demographic trends and digital transformations. The global aging population presents unprecedented challenges and opportunities for societies. By 2050, nearly 2.1 billion people—22% of the global population—will be aged 60 or older, with the majority residing in LMICs. This demographic shift necessitates innovative approaches to addressing age-related inequalities, particularly as digital technologies become integral to public and private life. In this context, the research will explore how digital technologies can serve as both a tool for equity and a source of exclusion in aging societies (Chu et al., 2022; Gallistl et al., 2024). It will investigate how digital inclusion strategies, such as digital literacy programs and equitable technology design, can empower older adults while addressing structural inequities (Poli et al., 2023; MDPQ). Moreover, it will critically assess the potential risks of over-reliance on digital solutions, including the reinforcement of existing inequalities and the erosion of privacy and autonomy (Felber et al., 2024; Guo, 2025).
Key Questions
This research seeks to address several critical questions at the intersection of digital inequality and population aging:
Forms of Digital Inequality: How do digital inequalities manifest uniquely among older adults in diverse social, cultural, and economic contexts?
Algorithmic Bias: In what ways do algorithms in healthcare, employment, and social services disadvantage aging populations, and how can these biases be mitigated?
Digital Rights and Participation: How do digital technologies expand or limit older adults’ access to rights claims, civic participation, and advocacy?
Inequality in LMICs: How can digital interventions in LMICs address disparities in access to healthcare, education, and social support for aging populations?
Equality-Enhancing Technologies: Can emerging digital tools, such as artificial intelligence and social media platforms, be leveraged to reduce social isolation, improve health outcomes, and amplify the political voice of older adults?
References
Chu, C. H., Nyrup, R., Leslie, K., Shi, J., Bianchi, A., Lyn, A., McNicholl, M., Khan, S., Rahimi, S., & Grenier, A. (2022). Digital ageism: Challenges and opportunities in artificial intelligence for older adults. The Gerontologist, 62(7), 947–955.
Poli, A., Kelfve, S., Berg, K., & Motel-Klingebiel, A. (2023). Old-age diversity is underrepresented in digital health research: findings from the evaluation of a mobile phone system for post-operative progress monitoring in Sweden. Ageing and Society, 43(10), 2264–2286.
Gallistl, V., Banday, M. U. L., Berridge, C., Grigorovich, A., Jarke, J., Mannheim, I., Marshall, B., Martin, W., Moreira, T., Van Leersum, C. M., & Peine, A. (2024). Addressing the black box of AI—A model and research agenda on the co-constitution of aging and artificial intelligence. The Gerontologist, 64(6), gnae039.
Felber, N. A., Alavi, H., Mugellini, E. & Wangmo, T. (2024). The smart home, a true home? How new technologies disrupt the experience of home for older persons. Universal Access in the Information Society, 1–14.
Guo, C. (2025). Digital Media and the Daily Lives of China's Senior Citizens. Routledge.
Asian Development Bank. (2025). Digitalization for Improving Elder Care (Bangladesh,China, People’s Republic of,Hong Kong, China,India,Singapore,Sri Lanka). Asian Development Bank.
Resources
Artificial Intelligence and Technology Collaboratories for Aging Research: Empowering innovation in AI/tech and aging
Project 4
Intergenerational Reciprocity, Old-age Poverty Risks, and Subjective Well-being from the Perspective of Family Structure: Findings from Three Longitudinal Cohort Studies in Middle-Income Countries (MICs)
（2022-2025）
Publications
Cai, Q. (2025). Intergenerational Reciprocity and Economic Well-being of Older Adults From the Perspective of Family Structure Heterogeneity: Preliminary Findings From India. Population Association of America 2025 Annual Meeting. Washington DC, USA.
Cai, Q. (2024). Intergenerational reciprocity and well-being of older adults from the perspective of family structure heterogeneity: Findings from India. Manuscript for Journal of Happiness Studies.
Cai, Q. (2024, November). Intergenerational reciprocity and well-being of older adults from the perspective of family structure heterogeneity: Preliminary findings from India. Institute of Advanced Studies in Humanities and Social Sciences (IAS) 4th Annual Conference, University of Macau, Macao SAR, China.
Cai, Q. (2024, September). Intergenerational reciprocity and economic well-being of older adults from the perspective of family structure heterogeneity: Preliminary findings from India. 3rd Collaborative for Innovation in Data & Measurement in Aging (CIDMA) Institute, The University of Chicago, Chicago, IL, USA.
Cai, Q. (2024, May). Does family structure matter? Intergenerational reciprocity, old-age poverty risks, and their implications for subjective well-being: Evidence from an Indian national representative survey. Annual SIGMA Research Symposium 2024 & 20th International Conference on Pensions, Insurance and Savings, Renmin University of China, Beijing, China.
Cai, Q., & Zanwar, P. P. (2024, April). Intergenerational reciprocity and old-age poverty risks—from the perspective of intergenerational family solidarity: Evidence from three middle-income countries (Poster presentation). Population Association of America (PAA) 2024 Annual Meeting, Columbus, Ohio, USA.
Cai, Q. (2023, September).Intergenerational Reciprocity, Old-age Poverty Risks, and Subjective Well-being from the Perspective of Intergenerational Family Solidarity: Evidence from three middle-income countries (MICs). 2nd Collaborative for Innovation in Data & Measurement in Aging (CIDMA) Institute, The University of Chicago, Chicago, IL, USA.
Project 5
The Impact of Parental Migration on the Health of School-Aged Left-Behind Children in China
（2022-2024）
Publications
Cai, Q., & Zhu, X., Chan, K. S., Jiang, W. L., Leou, C.*, Chao, W. (2024). Parental migration and health outcomes of Chinese school-aged left-behind children: Perspective from family structure heterogeneity (under review).
Cai, Q. (2025). Temporal windows matters? Examining the long-term mental health impact of childhood father absence experience. Manuscript for Journal of Affective Disorders.
Cai, Q. (2022, November). Parental migration and health outcomes of school-aged left-behind children: Evidence from China. Annual Conference of Association for Public Policy Analysis and Management (APPAM) 2022 Fall Research Conference, Washington DC, USA.
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