Despite technological breakthroughs, healthcare inequality remains a pressing public health challenge across developed and developing nations. Low levels of income or education mobility can exacerbate socioeconomic disparities, leaving children from disadvantaged families with fewer opportunities to improve their social and economic prospects. Moreover,  children in families with low-income backgrounds are also more likely to experience poor health outcomes, perpetuating a cycle of disadvantage.

Huixia Wang, a visiting scholar at Shorenstein APARC, sees this phenomenon as an opportunity to better understand the dynamics of intergenerational health and how to interrupt patterns of persistent health inequalities across generations. Her research aims to identify potential interventions to improve health outcomes in developing regions.

An associate professor at Hunan University, Wang has spent the 2024 fall quarter at APARC. She recently presented her research on the intricate dynamics of intergenerational health metrics, particularly in China and Indonesia. Watch her talk, “Intergenerational Persistence of Self-Reported Health Status and Biomarkers in Indonesia,” on our YouTube channel.

Barriers to Intergenerational Health

While much has been written about the transmission of income and education across generations, “much less is known about how health is passed down between generations," Wang notes, highlighting a gap in the existing research. Emphasizing that health is a crucial factor in determining overall well-being, as it affects everything from mental health to economic productivity and social mobility, she asserts that good health is linked to better educational outcomes, higher earning potential, and improved labor market performance. Poor health, on the other hand, is associated with lower educational attainment, reduced employment prospects, and higher rates of chronic illness.

Wang’s research approach centers on recognizing the multiple challenges in implementing maternal health-oriented policies. Having identified limited access to healthcare services as a significant barrier, she considers how, in many low-income and rural areas, “access to quality healthcare is constrained by poor infrastructure, lack of transportation, and shortages of healthcare professionals, making it difficult for pregnant women to receive essential care.”

Another obstacle is the prohibitive cost of healthcare. In countries where maternal health services are not subsidized or free, the financial burden of out-of-pocket expenses for transportation, medications, and other related costs can prevent women from accessing necessary care. Furthermore, Wang shows that low levels of maternal health education can contribute to poor health-seeking behaviors. “Many women may not recognize the warning signs of complications, may not fully understand the importance of prenatal care, or may be unaware of their rights to healthcare services,” she says.

Measuring Health Outcomes Across Generations

Wang acknowledges the difficulties in studying intergenerational health mobility, as it cannot be neatly defined and measured by observable metrics such as income or education. Health is much more subjective and varies from person to person. To gauge health outcomes, researchers must therefore rely on diverse and sometimes imprecise indicators, such as the presence of chronic diseases.

Moreover, to examine intergenerational mobility, researchers need data that includes health information for both parents and children. Such datasets are not always readily available, and those that do exist often lack the necessary granularity and long-term tracking to provide meaningful insights.

To overcome these challenges, Wang draws on a variety of panel data that tracks individuals over time, as well as survey data and self-reported status. For Wang, longitudinal studies are crucial for understanding how health disparities manifest and evolve over time. 

Using data from the Indonesia Family Life Survey, she combines subjective measures like self-reported health and objective measures such as pulse, BMI, hypertension, and anemia to capture a more complete picture of health mobility. This approach expands beyond previous studies, which typically relied on fewer health indicators and focused on developed countries. Her study includes a broad range of health variables and provides a unique look at the role of gender and socioeconomic factors in shaping health outcomes across generations.

Wang uses two primary methods for measuring intergenerational health mobility: one following the Intergenerational Health Association, which regresses children's health outcomes on those of their parents, and rank-rank regressions, which examine the persistence of health outcomes by analyzing percentile ranks. These techniques, adapted from income mobility research, allow her to assess health persistence and mobility across generations.

Future Directions and Policy Impact

Wang’s time at APARC has been instrumental in shaping and refining her research. "The opportunity to engage with experts from various fields [...] opened my eyes to new ways of thinking about my research," she shared. "The collaborative environment at APARC also made me realize how much I can learn from perspectives outside my immediate area of focus.”

Wang credits Stanford’s vibrant academic environment, with its rich array of seminars and talks, to broadening her understanding of Southeast Asian health systems, a subject she was less familiar with. She expressed gratitude to APARC faculty for their “invaluable guidance for both my research and my life at Stanford.” In particular,  APARC’s Asia Health Policy Program Director Karen Eggleston “dedicated a significant amount of time to advising my work, introducing me to key researchers in my field, and sharing the valuable resources that I might benefit from on campus,” Wang said.

Looking ahead, she is excited to continue exploring the role of health in intergenerational mobility, particularly in the Southeast Asian context, and plans to expand her research into the health effects of pollution, an area she has already begun to investigate. Wang also hopes to contribute to policymaking that addresses health inequality. By providing a deeper understanding of how health disparities are perpetuated across generations, she aims to inform policies that could improve health outcomes and reduce inequality in developing countries.

Wang’s research on intergenerational health mobility offers a fresh and much-needed perspective on the crucial yet understudied role of health in social mobility. She hopes her research helps policymakers and scholars address health inequalities that perpetuate socioeconomic disadvantage across generations.

Rapid advancements in digital health — spanning technologies like telemedicine, personalized digital nudges, and large language models — present new possibilities for addressing persistent problems in healthcare access, cost, and quality. Yet there is an urgent need for effective strategies to ensure digital health innovations improve healthcare delivery and health outcomes benefiting underserved populations especially in low- and middle-income countries (LMICs).

A new viewpoint paper published in the Journal of Medical Internet Research presents an analytic framework for evaluating the foundations of digital health innovations. Focusing on the digital health landscape in LMICs in South and Southeast Asia, the paper’s co-authors provide actionable recommendations for tailoring and implementing digital health solutions across diverse global health settings.

The co-authors include Siyan Yi, an associate professor at the National University of Singapore’s School of Public Health and a former postdoctoral fellow with the Asia Health Policy Program (AHPP) at Shorenstein APARC; Stanford health economist Karen Eggleston, the director of AHPP; Kochukoshy Cheruvettolil, former senior strategy officer with the Bill & Melinda Gates Foundation’s Digital Health and Artificial Intelligence division; Kiran Gopal Vaska of the National Health Authority, Ministry of Health and Family Welfare in New Delhi, India; and several collaborators from Stanford’s School of Medicine, among others.

Citing the advantages of a “human-in-the-loop” approach to Artificial intelligence (AI) — a collaborative approach that integrates human input and expertise into the lifecycle of machine learning and AI systems — the co-authors emphasize the potential benefits of a “researcher-in-the-loop” approach to digital health innovations in LMICs. Their collaboration for this paper was conceived during a panel discussion on digital health innovation featuring Cheruvettolil, Vaska, and Yi. Hosted by AHPP in October 2023, this event was part of APARC’s Autumn 2023 seminar series, Exploring APEC’s Role in Facilitating Regional Cooperation.

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Building Social Value in Digital Health Adoption

While the promise of digital health is universal, its implementation must address local needs and be tailored to promote adoption, recognizing that underserved populations lack adequate infrastructure and equitable access to healthcare services and digital innovations. Yet it is crucial to balance the social benefits of digital health innovations with the social costs of adoption. It is also imperative to gather evidence and insights on successes and failures when adopting such innovations in diverse local contexts.

To address these needs, the paper's coauthors advocate for a dual approach that combines a top-down, evidence-based strategy focused on designing and scaling national digital health infrastructures with the bottom-up creation of a vibrant ecosystem of local experiments generating shared experience.

“This two-pronged approach of top-down design and bottom-up experimentation, enabled through careful evaluation of effectiveness and impact, allows economies with different starting conditions to seize opportunities to ‘leapfrog’ towards more robust, resilient health systems fitting their contexts rather than imitate the development path of any given current high-income country or region,” the coauthors argue.

This theoretical framework recognizes that the social net benefit of digital innovations is heavily influenced by the initial conditions and the intended outcomes shaped by the local context. For example, in LMICs, persistent disparities in digital access and digital literacy determine the unfolding of the introduction, adoption, and integration of digital health interventions into the broader health system and compound existing inequities in access to healthcare.

Still, the co-authors emphasize that digital technologies can potentially deliver significant, even transformative benefits in LMICs that surpass the impacts seen in high-income health systems — provided that robust oversight and stewardship uphold the “First, do no harm” principle.

Integrated Digital Health Solutions

One of the coauthors’ key recommendations is to create a robust digital health infrastructure with adaptable data architectures, interoperability, and stringent privacy standards. They underscore the necessity of creating an integrated data ecosystem, as exemplified by India's Ayushman Bharat Digital Mission (ABDM), which facilitates personalized healthcare and evidence-based policymaking through effective data management.

Yet varying data standards across countries can pose challenges to comparability and effectiveness, in addition to ethical and legal dilemmas around sensitive health data. Singapore's Personal Data Protection Act and India's Digital Personal Data Protection Act are examples of regulatory frameworks protecting sensitive health information. These regulations are crucial for building trust among patients and healthcare providers — an essential prerequisite for successfully adopting digital health solutions.

The paper also highlights the potential of mobile health (mHealth) interventions and AI applications in revolutionizing healthcare delivery by bridging geographical barriers, expanding access to underserved populations, and shifting care from hospitals to communities. For instance, mHealth initiatives in India and Cambodia leveraging the widespread adoption of low-cost smartphones have shown promise in improving maternal and child health outcomes in low-income settings. Social media platforms further amplify the reach of public health campaigns and community-based interventions by utilizing trusted local voices.

AI is a new transformative force in digital health, enabling advancements in precision health, from diagnosing complex conditions to supporting clinical decisions. For example, in Thailand, a deep learning algorithm integrated into the national diabetic retinopathy screening program provides real-time, specialist-level diagnostics in community settings. AI solutions like this hold particular promise for addressing the challenges of low-resource health systems, including shortages of trained staff and limited equipment.

On the other hand, the coauthors caution against the risks associated with digital health technologies, including misinformation and ethical concerns. Clear data collection, storage, and sharing guidelines are critical, along with measures to safeguard sensitive health information.

Social Legitimacy and Local Partnerships

The paper emphasizes a call to action for researchers, policymakers, healthcare professionals, and civic organizations to invest in digital health infrastructure and foster interdisciplinary, local partnerships to promote need-driven, culturally sensitive, and equitable interventions. By prioritizing community engagement, the co-authors argue, digital health innovations can bridge geographical gaps, enhance healthcare accessibility, and ultimately improve health outcomes for underserved populations.

For example, the NGO Noora Health has successfully leveraged digital health across India, Bangladesh, and Indonesia to improve access to caregiver training. Successful features of their programs include mobile chat services and digital curricula integrated into comprehensive care delivery models that utilize local healthcare systems through partnerships with local governments, policymakers, and community health workers.

Ultimately, the co-authors note that the key to success lies in effectively stewarding health sectors to address priority population health needs and improve equity. “Policies should support the generation of evidence assessing digital health applications so that patients, providers, and policymakers can ask and answer the right questions in a suitable timeframe to enable a virtuous cycle of learning and improvement.” In resource-constrained LMICs, it is also essential to consider the financing levers in the public and private sectors to understand the feasibility of adopting and scaling up. In these contexts, private philanthropy can secure resources, mitigate risks, and generate evidence about best practices and scalability.

In a landscape where technology and healthcare intersect, the path forward must include prioritization of local contexts, engaging communities, and building a robust digital health infrastructure that serves the needs of all. The future of healthcare may depend on it.