Socio-economic inequalities in life expectancy of older adults with and without multimorbidity: a record linkage study of 1.1 million people in England.
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ABSTRACT:
SUBMITTER: Chan MS
PROVIDER: S-EPMC6693817 | biostudies-literature | 2019 Aug
REPOSITORIES: biostudies-literature
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Project description:BackgroundLife expectancy in Australia is amongst the highest globally, but national estimates mask within-country inequalities. To monitor socioeconomic inequalities in health, many high-income countries routinely report life expectancy by education level. However in Australia, education-related gaps in life expectancy are not routinely reported because, until recently, the data required to produce these estimates have not been available. Using newly linked, whole-of-population data, we estimated education-related inequalities in adult life expectancy in Australia.MethodsUsing data from 2016 Australian Census linked to 2016-17 Death Registrations, we estimated age-sex-education-specific mortality rates and used standard life table methodology to calculate life expectancy. For men and women separately, we estimated absolute (in years) and relative (ratios) differences in life expectancy at ages 25, 45, 65 and 85 years according to education level (measured in five categories, from university qualification [highest] to no formal qualifications [lowest]).ResultsData came from 14,565,910 Australian residents aged 25 years and older. At each age, those with lower levels of education had lower life expectancies. For men, the gap (highest vs. lowest level of education) was 9.1 (95 %CI: 8.8, 9.4) years at age 25, 7.3 (7.1, 7.5) years at age 45, 4.9 (4.7, 5.1) years at age 65 and 1.9 (1.8, 2.1) years at age 85. For women, the gap was 5.5 (5.1, 5.9) years at age 25, 4.7 (4.4, 5.0) years at age 45, 3.3 (3.1, 3.5) years at 65 and 1.6 (1.4, 1.8) years at age 85. Relative differences (comparing highest education level with each of the other levels) were larger for men than women and increased with age, but overall, revealed a 10-25 % reduction in life expectancy for those with the lowest compared to the highest education level.ConclusionsEducation-related inequalities in life expectancy from age 25 years in Australia are substantial, particularly for men. Those with the lowest education level have a life expectancy equivalent to the national average 15-20 years ago. These vast gaps indicate large potential for further gains in life expectancy at the national level and continuing opportunities to improve health equity.
| S-EPMC8330008 | biostudies-literature
Project description:Background and aimsWhen measuring inequalities in health, public health and addiction research has tended to focus on differences in average life-span between socio-economic groups. This does not account for the extent to which age of death varies between individuals within socio-economic groups or whether this variation differs between groups. This study assesses (1) socio-economic inequalities in both average life-span and variation in age at death, (2) the extent to which these inequalities can be attributed to alcohol-specific causes (i.e. those attributable only to alcohol) and (3) how this contribution has changed over time.DesignCause-deleted life table analysis of national mortality records.SettingEngland and Wales, 2001-16.CasesAll-cause and alcohol-specific deaths for all adults aged 18+, stratified by sex, age and quintiles of the index of multiple deprivation (IMD).MeasurementsLife expectancy at age 18 yearss and standard deviation in age at death within IMD quintiles and the contribution of alcohol to overall differences in both measures between the highest and lowest IMD quintiles by comparing observed and cause-deleted inequality 'gaps'.FindingsIn 2016, alcohol-specific causes reduced life expectancy for men and women by 0.26 and 0.14 years, respectively, and increased the standard deviation in age at death. These causes also increased the inequality gap in life expectancy by 0.33 years for men and 0.17 years for women, and variation in age at death by 0.14 years and 0.13 years, respectively. For both measures, the contribution of alcohol to mortality inequalities rose after 2001 and subsequently fell back. For women, alcohol accounted for 3.6% of inequality in age at death and 6.0% of life-span uncertainty, suggesting that using only the former may underestimate alcohol-induced inequalities. There was no comparable difference for men.ConclusionsDeaths from alcohol-specific causes increase inequalities in both life expectancy and variation in age of death between socio-economic groups. Using both measures can provide a fuller picture of overall inequalities in health.
| S-EPMC7687183 | biostudies-literature
Project description:BackgroundTo plan for pensions and health and social services, future mortality and life expectancy need to be forecast. Consistent forecasts for all subnational units within a country are very rare. Our aim was to forecast mortality and life expectancy for England and Wales' districts.MethodsWe developed Bayesian spatiotemporal models for forecasting of age-specific mortality and life expectancy at a local, small-area level. The models included components that accounted for mortality in relation to age, birth cohort, time, and space. We used geocoded mortality and population data between 1981 and 2012 from the Office for National Statistics together with the model with the smallest error to forecast age-specific death rates and life expectancy to 2030 for 375 of England and Wales' 376 districts. We measured model performance by withholding recent data and comparing forecasts with this withheld data.FindingsLife expectancy at birth in England and Wales was 79·5 years (95% credible interval 79·5-79·6) for men and 83·3 years (83·3-83·4) for women in 2012. District life expectancies ranged between 75·2 years (74·9-75·6) and 83·4 years (82·1-84·8) for men and between 80·2 years (79·8-80·5) and 87·3 years (86·0-88·8) for women. Between 1981 and 2012, life expectancy increased by 8·2 years for men and 6·0 years for women, closing the female-male gap from 6·0 to 3·8 years. National life expectancy in 2030 is expected to reach 85·7 (84·2-87·4) years for men and 87·6 (86·7-88·9) years for women, further reducing the female advantage to 1·9 years. Life expectancy will reach or surpass 81·4 years for men and reach or surpass 84·5 years for women in every district by 2030. Longevity inequality across districts, measured as the difference between the 1st and 99th percentiles of district life expectancies, has risen since 1981, and is forecast to rise steadily to 8·3 years (6·8-9·7) for men and 8·3 years (7·1-9·4) for women by 2030.InterpretationPresent forecasts underestimate the expected rise in life expectancy, especially for men, and hence the need to provide improved health and social services and pensions for elderly people in England and Wales. Health and social policies are needed to curb widening life expectancy inequalities, help deprived districts catch up in longevity gains, and avoid a so-called grand divergence in health and longevity.FundingUK Medical Research Council and Public Health England.
| S-EPMC4502253 | biostudies-literature
Project description:BackgroundDifferences in cancer survival exist across socio-economic groups for many cancer types. Standard metrics fail to show the overall impact for patients and the population.MethodsThe available data consist of a population of ∼2.5 million patients and include all patients recorded as being diagnosed with melanoma, prostate, bladder, breast, colon, rectum, lung, ovarian and stomach cancers in England between 1998 and 2013. We estimated the average loss in expectation of life per patient in years and the proportion of life lost for a range of cancer types, separately by deprivation group. In addition, estimates for the total number of years lost due to each cancer were also obtained.ResultsLung and stomach cancers result in the highest overall loss for males and females in all deprivation groups in terms of both absolute life years lost and loss as a proportion of expected life remaining. Female lung cancer patients in the least- and most-deprived group lose 14.4 and 13.8 years on average, respectively, that is translated as 86.1% and 87.3% of their average expected life years remaining. Melanoma, prostate and breast cancers have the lowest overall loss. On the basis of the number of patients diagnosed in 2013, lung cancer results in the most life years lost in total followed by breast cancer. Melanoma and bladder cancer account for the lowest total life years lost.ConclusionsThere are wide differences in the impact of cancer on life expectancy across deprivation groups, and for most cancers the most affluent lose less years.
| S-EPMC5672926 | biostudies-literature
Project description:Comparison of whole blood DNA methylation in 45 year-old humans with low and high childhood and adulthood socio-economic position Background: Disadvantaged socio-economic position (SEP) in childhood is associated with increased adult mortality and morbidity. We aimed to establish whether childhood SEP was associated with differential methylation of adult DNA. Methods: Forty adult males from the 1958 British Birth Cohort Study were selected from SEP extremes in both early childhood and mid-adulthood. We performed genome-wide methylation analysis on blood DNA taken at 45y using MeDIP (methylated DNA immunoprecipitation). We mapped in triplicate the methylation state of promoters of ~20,000 genes and 400 microRNAs. Probe methylation scores were averaged across triplicates and differential methylation between groups of individuals was determined. Differentially methylated promoter sites of selected genes were validated using pyrosequencing of bisulfite-converted DNA. Results: 9,112 variably methylated probes (from N=223,359 on the microarray) corresponded to 6,176 gene promoters with at least one variable probe. Unsupervised hierarchical clustering of probes obtained from the 500 most variable promoters revealed a cluster enriched with high SEP individuals confirming that SEP differences contribute to overall epigenetic variation. Methylation levels for 1252 gene promoters were associated with childhood SEP vs 545 promoters for adulthood SEP. Functionally, associations with childhood SEP appear in promoters of genes enriched in key cell signalling pathways. The differentially methylated promoters associated with SEP cluster in megabase-sized regions of the genome. Conclusions: Adult blood DNA methylation profiles show more associations with childhood SEP than adult SEP. Organization of these associations across the genome suggests a well-defined epigenetic pattern linked to early socio-economic environment.
2016-05-25 | GSE31713 | GEO
Project description:Stunting in children less than five years of age is widespread in Sub-Saharan Africa. We aimed to: (i) evaluate how the prevalence of stunting has changed by socio-economic status and rural/urban residence, and (ii) assess inequalities in children's diet quality and access to maternal and child health care. We used data from nationally representative demographic and health- and multiple indicator cluster-surveys (DHS and MICS) to disaggregate the stunting prevalence by wealth quintile and rural/urban residence. The composite coverage index (CCI) reflecting weighed coverage of eight preventive and curative Reproductive, Maternal, Neonatal, and Child Health (RMNCH) interventions was used as a proxy for access to health care, and Minimum Dietary Diversity Score (MDDS) was used as a proxy for child diet quality. Stunting significantly decreased over the past decade, and reductions were faster for the most disadvantaged groups (rural and poorest wealth quintile), but in only 50% of the countries studied. Progress in reducing stunting has not been accompanied by improved equity as inequalities in MDDS (p < 0.01) and CCI (p < 0.001) persist by wealth quintile and rural-urban residence. Aligning food- and health-systems' interventions is needed to accelerate stunting reduction more equitably.
| S-EPMC7019538 | biostudies-literature
Project description:ObjectiveUnderstanding the socio-economic inequalities in dietary intake is crucial when addressing the socio-economic gradient in obesity rates and non-communicable diseases. We aimed to systematically assess the association between socio-economic position (SEP) and dietary intake in Chile.DesignWe searched for peer-reviewed and grey literature from inception until 31 December 2019 in PubMed, Scopus, PsycINFO, Web of Sciences and LILACS databases. Observational studies published in English and Spanish, reporting the comparison of at least one dietary factor between at least two groups of different SEP in the general Chilean population, were selected. Two researchers independently conducted data searches, screening and extraction and assessed study quality using an adaptation of the Newcastle Ottawa Quality Assessment Scale.ResultsTwenty-one articles (from eighteen studies) were included. Study quality was considered low, medium and high for 24, 52 and 24 % of articles, respectively. Moderate-to-large associations indicated lower intake of fruit and vegetables, dairy products and fish/seafood and higher pulses consumption among adults of lower SEP. Variable evidence of association was found for energy intake and macronutrients, in both children and adults.ConclusionsOur findings highlight some socio-economic inequalities in diets in Chile, evidencing an overall less healthy food consumption among the lower SEP groups. New policies to reduce these inequalities should tackle the unequal distribution of factors affecting healthy eating among the lower SEP groups. These findings also provide important insights for developing strategies to reduce dietary inequalities in Chile and other countries that have undergone similar nutritional transitions.
| S-EPMC9991770 | biostudies-literature
Project description:BackgroundThere is strong and well-documented evidence that socio-economic inequality in cancer survival exists within and between countries, but the underlying causes of these differences are not well understood.MethodsWe systematically searched the Ovid Medline, EMBASE, and CINAHL databases up to 31 May 2020. Observational studies exploring pathways by which socio-economic position (SEP) might causally influence cancer survival were included.ResultsWe found 74 eligible articles published between 2005 and 2020. Cancer stage, other tumor characteristics, health-related lifestyle behaviors, co-morbidities and treatment were reported as key contributing factors, although the potential mediating effect of these factors varied across cancer sites. For common cancers such as breast and prostate cancer, stage of disease was generally cited as the primary explanatory factor, while co-morbid conditions and treatment were also reported to contribute to lower survival for more disadvantaged cases. In contrast, for colorectal cancer, most studies found that stage did not explain the observed differences in survival by SEP. For lung cancer, inequalities in survival appear to be partly explained by receipt of treatment and co-morbidities.ConclusionsMost studies compared regression models with and without adjusting for potential mediators; this method has several limitations in the presence of multiple mediators that could result in biased estimates of mediating effects and invalid conclusions. It is therefore essential that future studies apply modern methods of causal mediation analysis to accurately estimate the contribution of potential explanatory factors for these inequalities, which may translate into effective interventions to improve survival for disadvantaged cancer patients.
| S-EPMC8204531 | biostudies-literature
Project description:BackgroundMultimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB.MethodsThis is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR).ResultsThirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82).ConclusionsMultimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.
| S-EPMC10496247 | biostudies-literature
Project description:BackgroundSocio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors.MethodsData were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education.ResultsLower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest.ConclusionsThese observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities.
| S-EPMC7266549 | biostudies-literature