Dataset Information

Socio-economic inequalities in cancer survival: how do they translate into Number of Life-Years Lost?

ABSTRACT:

Background

We aimed to investigate the impact of socio-economic inequalities in cancer survival in England on the Number of Life-Years Lost (NLYL) due to cancer.

Methods

We analysed 1.2 million patients diagnosed with one of the 23 most common cancers (92.3% of all incident cancers in England) between 2010 and 2014. Socio-economic deprivation of patients was based on the income domain of the English Index of Deprivation. We estimated the NLYL due to cancer within 3 years since diagnosis for each cancer and stratified by sex, age and deprivation, using a non-parametric approach. The relative survival framework enables us to disentangle death from cancer and death from other causes without the information on the cause of death.

Results

The largest socio-economic inequalities were seen mostly in adults <45 years with poor-prognosis cancers. In this age group, the most deprived patients with lung, pancreatic and oesophageal cancer lost up to 6 additional months within 3 years since diagnosis than the least deprived. For most moderate/good prognosis cancers, the socio-economic inequalities widened with age.

Conclusions

More deprived patients and particularly the young with more lethal cancers, lose systematically more life-years than the less deprived. To reduce these inequalities, cancer policies should systematically encompass the inequities component.

SUBMITTER: Exarchakou A

PROVIDER: S-EPMC9090931 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Socio-economic inequalities in cancer survival: how do they translate into Number of Life-Years Lost?

Exarchakou Aimilia A Kipourou Dimitra-Kleio DK Belot Aurélien A Rachet Bernard B

British journal of cancer 20220211 10

<h4>Background</h4>We aimed to investigate the impact of socio-economic inequalities in cancer survival in England on the Number of Life-Years Lost (NLYL) due to cancer.<h4>Methods</h4>We analysed 1.2 million patients diagnosed with one of the 23 most common cancers (92.3% of all incident cancers in England) between 2010 and 2014. Socio-economic deprivation of patients was based on the income domain of the English Index of Deprivation. We estimated the NLYL due to cancer within 3 years since dia ...[more]

PMID: 35149855

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Project description:Background Hypertension (HTN) is a leading cause of mortality and morbidity in developing countries. For India, the hidden burden of undiagnosed hypertension is a major concern. This study aims to assess and explain socio-economic inequalities among self-reported and undiagnosed hypertensives in India. Methods The study utilized data from the Longitudinal Aging Study in India (LASI), a nationally-representative survey of more than 72,000 older adults. The study used funnel plots, multivariable logistic regression, concentration indices, and decomposition analysis to explain the socio-economic gap in the prevalence of self-reported and undiagnosed hypertension between the richest and the poorest groups. Results The prevalence of self-reported and undiagnosed hypertension was 27.4 and 17.8% respectively. Monthly per capita consumption expenditure (MPCE) quintile was positively associated with self-reported hypertension but negatively associated with undiagnosed hypertension. The concentration index for self-reported hypertension was 0.133 (p < 0.001), whereas it was − 0.047 (p < 0.001) for undiagnosed hypertension. Over 50% of the inequalities in self-reported hypertension were explained by the differences in the distribution of the characteristics whereas inequalities remained unexplained for undiagnosed hypertension. Obesity and diabetes were key contributors to pro-rich inequality. Conclusions Results imply that self-reported measures underestimate the true prevalence of hypertension and disproportionately affect the poorer MPCE groups. The prevalence of self-reported HTN was higher in the richest group, whereas socio-economic inequality in undiagnosed hypertension was significantly concentrated in the poorest group. As majority of the inequalities remain unexplained in case of undiagnosed hypertension, broader health systems issues including barriers to access to health care may be contributing to inequalities. Supplementary Information The online version contains supplementary material available at 10.1186/s12939-023-01833-6.

Dataset Information

Socio-economic inequalities in cancer survival: how do they translate into Number of Life-Years Lost?

Background

Methods

Results

Conclusions

Publications

Socio-economic inequalities in cancer survival: how do they translate into Number of Life-Years Lost?

Similar Datasets

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