Associations between residential daytime indoor temperature and self-reported sleep disturbances in UK adults: A cross-sectional study.

BACKGROUND

In the past few decades, research on the association between indoor temperature and sleep has primarily used laboratory rather than field data collected in epidemiological cohorts.

METHODS

Secondary data on 2493 individuals aged 43 years was obtained from the National Survey of Health and Development (NSHD). Logistic regression models were used to investigate the associations between temperatures (indoor at home, spot measurement when the nurses visited during the day; and outdoor, monthly average) and self-reported sleep disturbances, adjusting for socio-demographics, health variables, housing variables, and temperature-related variables.

RESULTS

Associations were found between daytime indoor temperature with difficulty initiating (OR: 0.95, 95%CI: 0.91-0.98) and maintaining sleep (OR: 0.96, 95%CI: 0.93-0.99). Compared with neutral indoor temperatures (17-28 °C), low indoor temperature (≤17 °C) was associated with difficulty initiating sleep (OR: 1.79, 95%CI: 1.21-2.65). Stratified analysis results across tertiles showed that associations with difficulty initiating (OR: 0.87, 95%CI: 0.77-0.99) and maintaining sleep (OR: 0.88, 95%CI: 0.79-0.98) were observed respectively in the lowest (≤20 °C) and highest tertile (≥23 °C) of indoor temperature. There was no association between outdoor temperature and self-reported sleep disturbances in this study.

CONCLUSION

In this first UK-based epidemiology study investigating temperature and sleep, self-reported sleep disturbances were associated with residential daytime indoor temperatures. Low indoor temperature had significantly higher odds ratio for difficulty initiating sleep compared with the neutral indoor temperature. A warmer indoor environment might be more suitable for sleep maintenance than sleep initiation. Indoor temperature in this study was a superior indicator of sleep disturbances than outdoor temperature. Although these findings are based on a UK sample, they may be relevant to other high-income settings with similar housing stock and climatic conditions.