Life expectancy inequalities in Wales before COVID-19: an exploration of current contributions by age and cause of death and changes between 2002 and 2018

Currie, Jonny; Boyce, Tammy; Evans, Leonard; Luker, M.; Senior, Steven L.; Hartt, Maxwell; Cottrell, Simon; Lester, Nathan; Huws, Dyfed Wyn; Humphreys, Ciarán; Little, Kirsty; Adekanmbi, Victor; Paranjothy, Shantini

doi:10.1016/j.puhe.2021.01.025

Cited by 16 publications

(14 citation statements)

References 22 publications

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“…9 A similar greater widening of life expectancy inequalities for women compared with men was shown for Wales between 2002 and 2018. 5 These findings tally with our own deprivation-stratified analyses, and also with those of Rashid et al whose analyses for England showed falls in female life expectancy in almost one-fifth (18.7%) of the country's small spatial units; the equivalent figure for men was 11.5%. 6 Of studies which examined the association between austerity measures and mortality outcomes, some did not stratify by sex, 14 15 42 while others showed broadly similar results for men and women.…”

Section: Relevance To Other Studiessupporting

confidence: 90%

“…There is clear evidence of adverse changes to mortality rates in the UK from the early 2010s onwards: a slow-down in the rate of improvement overall, alongside increasing death rates among more socioeconomically deprived populations; inequalities have widened considerably as a consequence of the latter. [1][2][3][4][5][6][7][8][9] These changes predate the COVID-19 pandemic and are important context for understanding the scale of pandemic-related inequalities. 10 11 Although a number of different contributory factors were initially proposed, a considerable body of evidence now demonstrates that UK Government's 'austerity' policies are the main cause of these pre-pandemic changes.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bearing the burden of austerity: how do changing mortality rates in the UK compare between men and women?

Walsh

Dundas

McCartney

et al. 2022

J Epidemiol Community Health

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BackgroundMortality rates across the UK stopped improving in the early 2010s, largely attributable to UK Government’s ‘austerity’ policies. Such policies are thought to disproportionately affect women in terms of greater financial impact and loss of services. The aim here was to investigate whether the mortality impact of austerity—in terms of when rates changed and the scale of excess deaths—has also been worse for women.MethodsAll-cause mortality data by sex, age, Great Britain (GB) nation and deprivation quintile were obtained from national agencies. Trends in age-standardised mortality rates were calculated, and segmented regression analyses used to identify break points between 1981 and 2019. Excess deaths were calculated for 2012–2019 based on comparison of observed deaths with numbers predicted by the linear trend for 1981–2011.ResultsChanges in trends were observed for both men and women, especially for those living in the 20% most deprived areas. In those areas, mortality increased between 2010/2012 and 2017/2019 among women but not men. Break points in trends occurred at similar time points. Approximately 335 000 more deaths occurred between 2012 and 2019 than was expected based on previous trends, with the excess greater among men.ConclusionsIt remains unclear whether there are sex differences in UK austerity-related health effects. Nonetheless, this study provides further evidence of adverse trends in the UK and the associated scale of excess deaths. There is a clear need for such policies to be reversed, and for policies to be implemented to protect the most vulnerable in society.

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Section: Relevance To Other Studiessupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bearing the burden of austerity: how do changing mortality rates in the UK compare between men and women?

Walsh

Dundas

McCartney

et al. 2022

J Epidemiol Community Health

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“…Communicable disease contributes advantageously to narrow the gender gap in mortality. In contrast, the noncommunicable disease with its the largest share of the sex difference in e 0 and G 0 contributes disadvantageously to widen the gender gap in mortality [ 73 , 92 ]. Altogether, analyses of sex differences in e 0 and G 0 confirms that the vulnerability of men in pandemic time gets amplified more in men than in women [ 10 , 15 , 93 – 96 ], attributable to the burden of COVID-19 disease, which is in addition to the higher mortality rates in men than in women in the past.…”

Section: Discussionmentioning

confidence: 99%

Impact of COVID-19 on life expectancy at birth in India: a decomposition analysis

Yadav

2021

BMC Public Health

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Background Quantifying excess deaths and their impact on life expectancy at birth (e0) provide a more comprehensive understanding of the burden of coronavirus disease of 2019 (COVID-19) on mortality. The study aims to comprehend the repercussions of the burden of COVID-19 disease on the life expectancy at birth and inequality in age at death in India. Methods The mortality schedule of COVID-19 disease in the pandemic year 2020 was considered one of the causes of death in the category of other infectious diseases in addition to other 21 causes of death in the non-pandemic year 2019 in the Global Burden of Disease (GBD) data. The measures e0 and Gini coefficient at age zero (G0) and then sex differences in e0 and G0 over time were analysed by assessing the age-specific contributions based on the application of decomposition analyses in the entire period of 2010–2020. Results The e0 for men and women decline from 69.5 and 72.0 years in 2019 to 67.5 and 69.8 years, respectively, in 2020. The e0 shows a drop of approximately 2.0 years in 2020 when compared to 2019. The sex differences in e0 and G0 are negatively skewed towards men. The trends in e0 and G0 value reveal that its value in 2020 is comparable to that in the early 2010s. The age group of 35–79 years showed a remarkable negative contribution to Δe0 and ΔG0. By causes of death, the COVID-19 disease has contributed − 1.5 and − 9.5%, respectively, whereas cardiovascular diseases contributed the largest value of was 44.6 and 45.9%, respectively, to sex differences in e0 and G0 in 2020. The outcomes reveal a significant impact of excess deaths caused by the COVID-19 disease on mortality patterns. Conclusions The COVID-19 pandemic has negative repercussions on e0 and G0 in the pandemic year 2020. It has severely affected the distribution of age at death in India, resulting in widening the sex differences in e0 and G0. The COVID-19 disease demonstrates its potential to cancel the gains of six to eight years in e0 and five years in G0 and has slowed the mortality transition in India.

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“…Although considerable research has been published on the evolution of inequalities in alcohol-related harm, particularly mortality, the evolution of inequality in drinking behaviors has been less frequently reported. In general, previous findings suggest that in recent years, the relative SEP inequality in alcohol-related mortality (favoring higher SEPs) has increased [ 37 , 38 , 39 , 40 , 41 ], although not in all countries [ 42 ]. Therefore, results in the same direction could be expected with regard to SEP inequalities in the highest-risk drinking behavior, i.e., HAD or HED prevalence.…”

Section: Introductionmentioning

confidence: 99%

Educational Gradients in Drinking Amount and Heavy Episodic Drinking among Working-Age Men and Women in Spain

Donat

Barrio

Guerras

et al. 2022

IJERPH

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Alcohol-related harm decreases as socioeconomic position increases, although sometimes the opposite happens with alcohol intake. The objective was to know the educational gradient in monthly measures of drinking amount and heavy episodic drinking (HED) among people aged 25–64 years in Spain from 1997–2017. Such gradient was characterized with the relative percent change (PC) in drinking measures per year of education from generalized linear regression models after adjusting for age, year, region, marital status and immigration status. Among men, the PCs were significantly positive (p < 0.05) for prevalence of <21 g alcohol/day (2.9%) and 1–3 HED days (1.4%), and they were negative for prevalences of 21–40 g/day (−1.1%), >40 g/day (−6.0%) and ≥4 HED days (−3.2%), while among women they ranged from 3.6% to 5.7%. The gradient in prevalences of >40 g/day (men) and >20 g/day (women) was greatly attenuated after additionally adjusting for HED, while that of ≥4 HED days was only slightly attenuated after additionally adjusting for drinking amount. Among women, the gradients, especially in HED measures, seem steeper in 2009–2017 than in 1997–2007. Educational inequality remained after additional adjustment for income and occupation, although it decreased among women. These results can guide preventive interventions and help explain socioeconomic inequalities in alcohol-related harm.

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Life expectancy inequalities in Wales before COVID-19: an exploration of current contributions by age and cause of death and changes between 2002 and 2018

Cited by 16 publications

References 22 publications

Bearing the burden of austerity: how do changing mortality rates in the UK compare between men and women?

Bearing the burden of austerity: how do changing mortality rates in the UK compare between men and women?

Impact of COVID-19 on life expectancy at birth in India: a decomposition analysis

Educational Gradients in Drinking Amount and Heavy Episodic Drinking among Working-Age Men and Women in Spain

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