Individual level risk factors associated with episodes of heat as recorded within primary care records: a time-stratified case-cross over study

Abstract

Abstract Background A key recommended action outlined in Heat-Health Action Plans is to identify individuals at risk and deploy targeted interventions, however this is not routinely undertaken. A major contributing factor is a lack of understanding of individual-level risk factors to support an evidence-based approach to targeted prevention. Aim To use electronic health data to identify individual level characteristics associated with increased risk of mortality during heatwaves in England. Methods A time-stratified case-crossover analysis was undertaken of individual-level clinical and socio-environmental (SE) risk factors. Conditional logistic regression was used to characterise associations between temperature and the risk of death on hot days, with analysis stratified by potential risk modifying factors. Results Heat mortality risk was modified by a large range of chronic conditions, with cardio-respiratory, mental health and cognitive function conditions, diabetes and Parkinson’s, all increasing risk. Prescribed medications also increased odds of death during heatwaves. Heat mortality risk was modified by a range of SE determinants of health investigated, with ORs increasing with age; OR differences by sex, ethnicity and living arrangement; an increasing trend in ORs by alcohol intake and body mass index, excluding the obese-3 group. Results suggest the least deprived have the lowest OR and the most deprived have the highest. Conclusions This study has important implications for patient medication management during heat events, incorporating heat-risk considerations into other health policies. The results also provide important evidence on the role of disadvantage in driving the inequitable distribution of climate impacts, and the need for better socio-economic data sets linked to health records. The findings highlight the importance of incorporating an assessment of individual SE circumstances when prioritising patients at highest risk during heat events.