Headlines
- Male life expectancy at birth is 77.3 years and female life expectancy at birth is 81.4 years (2018-20). Generally, the long-term small year-on-year increases in life expectancy stopped around 2012-14 and have stayed fairly constant since. However, the inclusion of 2020 COVID-19 mortality data in the latest calculations has led to decreases in life expectancy for both males and females in Wakefield District, compared to 2017-19, as it has nationally.
- There are marked inequalities in life expectancy for those living in the most deprived neighbourhoods compared to those living in the least deprived neighbourhoods. For males the gap is 9.2 years and for females the gap is 8.2 years.
- At ward level, the highest life expectancy is in Stanley and Outwood East ward (87.8 years for females; 82.3 years for males), and lowest in Wakefield East ward (77.5 years for females; 71.9 years for males).
The Challenges
Male life expectancy at birth is 77.3 years and female life expectancy at birth is 81.4 years (2018-20). Generally, the long-term year-on-year small increases in life expectancy stopped around 2012-14 in Wakefield District and have stayed fairly constant since. The inclusion of 2020 COVID-19 mortality data in the latest calculations has led to decreases in life expectancy for both males and females in Wakefield District, compared to 2017-19, as it has nationally.
Life expectancy at age 65 years is a further 20.1 years for females and a further 17.6 years for males.
Healthy life expectancy statistics combine life expectancy measurements with survey data, and are an estimate of lifetime spent in “very good” or “good” health, based on how individuals perceive their general health. Females in Wakefield District can expect to live 56.7 years in good health, and males can expect to live 58.0 years in good health. Both these healthy life expectancies end well before state pension age. Healthy life expectancy for females declined markedly in 2015-17 (down to 56.6 years, from 60.3 years in 2014-16) and has tended to stay around this lower level since then.
The Office for Health Improvement and Disparities (OHID) fingertips system holds data and analysis for a number of different life expectancy indicators. The dashboard below provides a summary of these. It highlights the recent trend over time (where it can be calculated) and gives an indication of how the Wakefield District life expectancies compare against those for England as a whole. Clicking on an indicator name will open up the relevant page on the OHID profiles website, where more details and analysis are available.
The Inequality
Higher levels of deprivation can lead to lower life expectancy in both males and females, the effect can be estimate by using the slope index of inequality (SII). SII is a measure of the social gradient in life expectancy, i.e. how much life expectancy varies with deprivation. This represents the range in years of life expectancy across the social gradient from most to least deprived, based on a statistical analysis of the relationship between life expectancy and deprivation across all deprivation deciles. This means in Wakefield District life expectancy for those in the most deprived deprivation decile is 9.6 years less for males and 8.4 years less for females than those in the least deprived decile [2].
These inequalities are seen across various geography types. The dashboard below allows you to select by geography types, gender and years to see the differences.
References
- Office for National Statistics, accessed 16/11/2022, National life tables – life expectancy in the UK: 2018 to 2020, https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/bulletins/nationallifetablesunitedkingdom/2018to2020
- Public Health England, Public Health Outcomes Framework – Overarching Indicators, Technical User Guide, May 2014, revised February 2021, accessed 16/11/2022, https://fingertips.phe.org.uk/documents/PHOF_Overarching_user_guide_Feb_2021_FINAL.pdf
Resources
- OHID Segment Tool
- This tool provides information on the causes of death and age groups that are driving inequalities in life expectancy at local area level. Targeting the causes of death which contribute most to the life expectancy gap should have the biggest impact on reducing inequalities.