Enduring impacts of El Niño on life expectancy in past and future climates

nature climate change Article https://doi.org/10.1038/s41558-025-02534-4 Enduring impacts of El Niño on life expectancy in past and future climates Received: 2 May 2025 Accepted: 1 December 2025 Published online: 9 January 2026 Check for updates Yanbin Xu 1 , Wenjun Zhu Benjamin P. Horton 3 , Dhrubajyoti Samanta 1 2 & The El Niño–Southern Oscillation (ENSO) is a major driver of global climate variability, yet its long-term effect on life expectancy remains unclear. Here we quantify how ENSO persistently impedes mortality improvement, leading to considerable life expectancy and economic losses across high-income Pacific Rim countries. We estimate life expectancy losses of 0.5 years (monetary equivalent loss of US$2.6 trillion) for the 1982–1983 El Niño and 0.4 years (US$4.7 trillion) for the 1997–1998 event. Climate projections under moderate emissions pathways suggest a cumulative decline of 2.8 years in life expectancy by 2100, amounting to US$35 trillion losses, with most of the monetary burden falling on the middle-aged population. These findings reveal that intensifying ENSO variability poses an underrecognized and enduring threat to human health and socio-economic stability, underscoring the urgent need for targeted adaptation strategies to safeguard population well-being. The El Niño–Southern Oscillation (ENSO) is Earth’s most dominant year-to-year climate variation, integrating a wide range of Earth system processes1,2. ENSO involves fluctuations between unusually warm (El Niño) and cold (La Niña) sea surface temperatures in the central and eastern Pacific Ocean1,3,4, triggering global weather extremes such as floods5–7, heat extremes8,9 and air pollution10,11. These weather extremes disrupt food security12,13 and hinder economic growth14,15. ENSO has widespread, long-term impacts through its teleconnections, influencing multiple regions globally16. Many climate models predict that rising temperatures will intensify17 and increase the frequency18 of El Niño events, leading to severe socio-economic consequences19. El Niño threatens human health, increasing mortality during event years20–22. It affects multiple health domains, including infectious and diarrhoeal diseases23–26, cardiovascular and respiratory ailments27,28 and healthcare system disruptions26,29. Vulnerable populations, such as children12,30,31 and the elderly32, face heightened risks, with El Niño events contributing to excess mortality. Emerging evidence suggests its health consequences extend beyond the event year, leading to long-term and compounding effects33,34, although this has not been quantified. Most research focuses on past ENSO-related health outcomes or conceptual climate–health linkages, without rigorously quantifying their broader demographic and economic consequences. Here we bridge this gap by systematically quantifying ENSO-induced mortality and equivalent economic losses with a panel distributed-lag regression framework. We assess ENSO’s impact on past and future mortality improvement across 10 Pacific Rim countries and regions (hereafter referred to as countries) with reliable mortality data from 1960 to 2022, calculating reductions in life expectancy and associated monetary loss. In this study, mortality improvement refers to the decline in mortality rates over time as public health improves, measured as the logarithmic year-over-year decline in age-specific mortality rates. ENSO intensity is captured using the E-index35 (Methods), whereas country-level precipitation (τP) and temperature (τT) teleconnections quantify regional climate responses and are interacted with the measure14,15 (Methods) to isolate ENSO’s influence. Focusing primarily on the five years following El Niño, we also analyse long-term impacts extending up to 20 years, including the effects of La Niña. Finally, we integrate empirical estimates with climate model projections to assess the future life expectancy losses due to ENSO Department of Banking and Finance, Nanyang Business School, Nanyang Technological University, Singapore, Singapore. 2Earth Observatory of Singapore, Nanyang Technological University, Singapore, Singapore. 3School of Energy and Environment, City University of Hong Kong, Hong Kong, China. e-mail: ; 1 Nature Climate Change | Volume 16 | February 2026 | 148–154 148 Article https://doi.org/10.1038/s41558-025-02534-4 8.0 b Mortality improvement by ENSO intensity 0 lag 5 lags Cumulative effect (p.p. per s.d.) Mortality improvement change (p.p.) a 4.0 0 −2.1 −4.0 −8.0 −1 0 1 2 3 4 E-index (s.d.) Heterogeneity by age group Age < 30 Age 30–59 Age ≥ 60 4 3 2 1 0 0 1 2 3 4 5 Year since El Niño event Fig. 1 | ENSO’s lag effect on mortality improvement. a, Mortality changes by varying ENSO intensities in the year of the event (zero lag, solid line) and the fifth year after the event (five lags, dashed line). The black lines represent the mean, whereas the shaded areas indicate the 95% CIs from bootstrap resampling (Methods). The positive shift in mortality indicates a deterioration in human mortality improvement, as more people are projected to die because of El Niño-related impacts. When ENSO intensity is zero, the mean mortality change is −2.1%, as Pacific Rim countries, on average, experienced mortality improvement over the research period. The lower histogram shows the density of the E-index in the sample. b, Cumulative effects of a 1-s.d. El Niño event over time by age group heterogeneity. Estimations begin with the year of the event (year 0) and accumulate to the fifth year after the event (year 5). The population is segmented into three age categories: < 30 years (blue), 30–59 years (orange) and ≥ 60 years (green). Dots show averages, and bars show 95% CIs. p.p., percentage points; s.d., standard deviation. intensification in a warmer climate. By leveraging climate simulations under four emissions scenarios, we analyse projected changes in ENSO and their potential impacts on life expectancy in the future (Methods). (CI: 1.3 to 4.6) after five years. This heightened vulnerability probably reflects both greater environmental exposure and lower adaptive capacity. As a support to this interpretation, our causal-chain analysis (Supplementary Table 2) shows that heat extremes, air pollution and higher health expenditures significantly mediate El Niño’s adverse effects on mortality improvement. These factors disproportionately affect younger individuals, who are more frequently engaged in outdoor labour and activities, increasing exposure to El Niño-driven stressors such as heat extremes37–39 and air pollution10,11,40. In addition, younger populations generally have fewer financial buffers and limited capacity to absorb El Niño-related increases in health expenditures, amplifying their long-term health risks. In comparison, the older population aged (60 and above) is the second most affected group (mean: 1.3 p.p., 95% CI: 0.8 to 1.8), consistent with reduc (...truncated)