Local public health organisations require information about local variations in healthy life expectancy (HLE) and associated risks to inform decisions about how and where to intervene to improve HLE, a key indicator of population health. We aimed to estimate both HLE and levels of risk in small areas and quantify associations between them.
Cross-sectional population-based study.
Norfolk and Waveney Integrated Care System.
128 Middle Layer Super Output Areas and eight Lower Tier Local Authority Areas.
HLE (estimated using self-reported health status from the 2021 UK Census) in each Middle layer Super Output Area and levels of 10 risk factors (selected based on existing evidence of association with lower life expectancy or self-reported health and availability of local risk information): index of multiple deprivation; weekly net income; urban area; diet not meeting five portions of fruit and vegetables on a usual day; physical inactivity; older person living alone; falls admissions rate; alcohol mortality rate; road casualties and air pollution.
HLE in 2021 was 66.5 years for men (range 52–73) and 67.5 years for women (range 56–74). The difference between areas was 21 years for men and 18 years for women. Higher income was strongly associated with all healthy life expectancies: £100 higher weekly income was associated with 4.4 (95% confidence limits 3.5 to 5.2) and 4.6 (3.8 to 5.4) years greater HLE at birth in males and females respectively and with 1.7 (1.3 to 2.2) and 2.0 (1.5 to 2.5) greater HLE at age 65. Higher percentage of older adults living alone was associated with lower HLE at birth in males and females. Physical inactivity was associated with lower HLE at 65 in males and at birth in females.
This approach uses standard methods and publicly available data to estimate both HLE and risk exposures in small areas to find areas with low life expectancy and high risks, where local organisations may prioritise the implementation of cost-effective interventions. It could be replicated in other areas to target interventions and inequalities. More accurate data on risk exposures in small areas would allow a broader range of risk factors, including smoking, to be considered.