Ambient temperature and the variability between neighbouring days impacts in-patient hospitalizations in the United Kingdom

Journal article

Abstract Background Acute health effects of temperature extremes and variability in temperate zones has been rarely quantified. We examine the associations of ambient temperature and temperature change between neighbouring days with all-cause and cause-specific hospitalizations. Methods Daily hospital admission data were identified through hospital record linkage with UK Biobank, a cohort of half-a-million participants during 2006-2022. Temperature exposure was measured at 1×1 Km 2 spatial resolution based on participants’ residential addresses. We used a time-stratified case-crossover design to examine short-term associations of ambient temperature and change in temperature between neighbouring days with all-cause and cause-specific hospitalizations. Results We identify 709,052 warm-season hospitalizations and 676,686 cold-season hospitalizations. During warm season, high temperature cumulated over lag 0-3 days is associated with 9% [odds ratio (OR) = 1.09, 95% confidence interval (CI) = 1.02, 1.16] and 18% (OR = 1.18, 95% CI = 1.05, 1.34) higher odds of hospitalizations for renal disease and heat-related illness, respectively. During cold season, high temperature is associated with 4% (OR = 1.04, 95% CI = 1.01, 1.06) higher odds of overall hospitalizations from any cause, and also for cardiovascular disease (OR = 1.06, 95% CI = 1.02, 1.09), respiratory disease (OR = 1.05, 95% CI = 1.00, 1.11), mental disorders (OR = 1.08, 95% CI = 1.00, 1.16) and heat-related illness (OR = 1.25, 95% CI = 1.05, 1.48). We observe more pronounced associations between ambient temperature and overall hospitalization among subgroups residing in the most deprived neighbourhoods and with the least greenspace coverage during both warm and cold seasons. Conclusions Our findings suggest the need for multilevel mitigation and adaptation strategies for strengthening individual and urban resilience to minimize adverse health effects attributable to temperature extremes.

Authors: Lai, KY; Webster, C; Gallacher, J; Sarkar, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: communications medicine
• Publication date: 2026-01-26
• Acceptance date: 2025-12-22
• DOI: 10.1038/s43856-025-01355-y
• EISSN: 2730-664X
• ISSN: 2730-664X
• Language: English
• Keywords: Confidence interval; Odds ratio; Temperate climate; Cohort study; Record linkage; Disease; Odds; Cohort; Apparent temperature