Self-reported heat-related illness and its association with perception of health risks and adaptation behavior to heat waves in Bangladesh

Abstract

Climate change has increased the frequency and severity of heat waves, leading to a relatively high risk of heat-related illness. This study explores the heat-related illness risk in Bangladesh, focusing on the connection between perception of health risks, adaptation behaviors, and heat-related illness. Using face-to-face surveys, data were gathered from 491 participants through multi-stage sampling techniques across six areas in Dhaka in 2024. The survey examined demographic factors, heat-related illness, perception of health risk, and adaptive behaviors. Binary logistic regression examined factors associated with heat-related illness, ordinal logistic regression assessed determinants of perception of health risk, and Poisson regression identified factors associated with adaptation behaviors. A significance value of p  < 0.05 was considered for all analyses. Results showed that participants perceived heat waves as posing low (34%), moderate (24%), and high (42%) health risks, based on a 7-point Likert scale, where scores of 1–2 were classified as low risk perception, 3–5 as moderate, and 6–7 as high. Almost (99.8%) used at least one adaptation behavior. Heat-related illness was significantly higher among older adults, males, residents of the Dhaka North City Corporation, and those with lower family income. Binary logistic regression further showed that perceived high risk (AOR: 7. 77) and higher adaptation behavior (AOR: 1. 19) was associated with greater likelihood of reporting heat-related illness. This study provides novel evidence on the relationship between heat-related illness, perception of health risk, and adaptation behaviors in an urban climate-vulnerable setting in Bangladesh. These findings enhance understanding of heatwave vulnerability in this context and support the development of targeted, risk-informed public health interventions in rapidly urbanizing cities.