What do climate impacts, health, and migration reveal about vulnerability and adaptation in the Marshall Islands?

The study examines how climate impacts, health, and migration interact to shape vulnerability and adaptation in the Republic of the Marshall Islands (RMI). Climate change is altering migration patterns globally and in the Pacific, while health risks related to climate stressors (e.g., extreme events, droughts, flooding) can both drive and result from migration. These interactions are complex and heterogeneous, making generalizable frameworks difficult. The RMI—a highly climate-vulnerable nation of low-lying atolls—faces multiple public health challenges, including inadequate water and sanitation infrastructure, limited healthcare access, and exposure to climate hazards. The research asks: (1) To what extent are climate stressors and health impacts related to migration outcomes in the RMI? (2) Are there differential climate vulnerabilities, health impacts, and migration outcomes across respondents? The purpose is to generate nuanced, policy-relevant insights to address inequities and support adaptive capacity in the face of climate change.

Prior Pacific research on climate-related migration has addressed displacement, risk and vulnerability, agency in decision-making, and policy/adaptation mechanisms. However, few studies explicitly integrate climate stressors, health impacts, and migration together. Health impacts of climate stressors in Pacific Island communities are direct (injury, loss), indirect (infectious disease outbreaks post-flood/drought; disrupted food and water security), and diffuse (heat-related morbidity, reduced physical activity, metabolic impacts), with important mental health dimensions (stress, trauma, solastalgia). In the RMI, long-standing constraints on arable land, freshwater, and infrastructure, compounded by sea-level rise and extreme events, contribute to health risks and motivate internal and international migration. Under the Compact of Free Association, many Marshallese migrate to the USA for education, employment, and especially healthcare. Empirical evidence is needed to untangle how climate stressors relate to health and migration within broader social and economic contexts, acknowledging heterogeneous experiences and agency.

Design: Secondary analysis of a 2017 household survey conducted in the RMI (van der Geest et al. 2019b,c,2020). The instrument was developed by University of Hawai'i and Marshall Islands Conservation Society, translated into Marshallese, and administered by a locally led team. Sample and sites: 199 households across three islands: Majuro (urban; n=99), Maloelap (rural atoll; n=50), and Mejit (rural raised coral island; n=50). On Majuro, a random sample of 100 households from a geocoded list of 2,398 eligible households on the eastern atoll side (with replacement for unavailable/abandoned). On Mejit, all available households; on Maloelap, all available households on two of five inhabited islands. One incomplete response was removed; response rate >90%. Survey content: Questions covered household-ranked problems (e.g., healthcare access, job opportunities, education, food/water insecurity, climate threats); experience of climate stressors (drought, heatwaves, storm surge, typhoons, king tides); direct and indirect health impacts (food, water, land, crops, housing, safety, disease, injury); perceived trends in severity; and migration history and expectations with reasons (financial, health, education, employment, climate). Outcomes and variables: - Primary outcome: Expectation to migrate within 10 years (binary), coded 1 for Yes/Maybe and 0 for No. - Predictors: Climate stressors experienced and perceived severity/trends; climate-related health impacts and proximate determinants of health (food, water, land, crops, housing, safety); and demographics (including proxies for wealth/education where available). Analytic approach: 1) Logistic regression assessed associations between climate stressors and health impacts (independent variables) and expectation to migrate (dependent variable). Additional models evaluated associations among climate stressors, health impacts, and demographic variables. 2) Hierarchical clustering grouped respondents based on variables capturing experiences of climate stressors, perceptions of natural resource/ecosystem service state/trends, and problem rankings related to climate stressors. Clustering sought to minimize within-cluster variance and maximize between-cluster variance to reveal heterogeneous vulnerability profiles.

- Climate stressors were widely experienced across the sample (n=199), yet, across the full population, no significant correlations emerged between climate stressors, climate-related health impacts, and expectation to migrate within 10 years. - Hierarchical clustering identified distinct groups based on climate stressor exposure and related characteristics: • Cluster A: Low climate stressors, higher wealth, low expectation to migrate. In this group, climate-related health impacts were significantly associated with migration expectations. • Cluster B: Very high climate stressors, lower wealth, high expectation to migrate. In this group, climate stressors were significantly associated with proximate determinants of health (e.g., food, water, housing, safety), but showed no association with migration expectations. - These patterns indicate heterogeneous vulnerability and agency: migration decisions are not uniformly driven by climate stressors or health impacts across the population. - Policy implication: To promote equitable adaptation, interventions should expand economic and educational opportunities and reduce vulnerability to both direct and indirect health impacts of climate change.

The findings address the research questions by demonstrating that the relationships among climate stressors, health impacts, and migration in the RMI are heterogeneous. While all households reported climate stressors, these did not uniformly predict migration expectations at the population level. Instead, subgroup analysis via clustering revealed distinct vulnerability profiles. In relatively wealthier, lower-stressor households, climate-related health impacts aligned with higher migration expectations, suggesting greater agency to move in response to health concerns. Conversely, in lower-wealth, high-stressor households, climate stressors were linked to deteriorating proximate determinants of health, yet migration expectations did not correlate, consistent with constrained agency or barriers to mobility. These insights underscore that climate acts as a “cause of causes” by shaping health and livelihood determinants, but migration responses depend on socioeconomic context and access to resources. The relevance to the field lies in integrating health into climate–migration analyses and highlighting the need for equity-focused adaptation and mobility policies.

This study integrates climate stressors, health impacts, and migration outcomes using regression and clustering of household survey data from the RMI. It shows that while climate stressors are pervasive, their influence on migration expectations varies across socioeconomically distinct groups. One segment exhibits a linkage between health impacts and migration, whereas another experiences worsening determinants of health without a corresponding migration association, indicating constrained adaptation options. The work contributes evidence for tailoring policies to expand education, healthcare access, and livelihood opportunities, thereby reducing health-related vulnerability and supporting equitable adaptation pathways. Future work could deepen analysis with longitudinal data, richer health and socioeconomic measures, and evaluation of policy interventions as the climate changes and migration regimes evolve.