Differences In Life Expectancy Research Articles

Robust correlation estimation and UMAP assisted topological analysis of omics data for disease subtyping

Deciphering information hidden in the gene expression assays for identifying disease subtypes has significant importance in precision medicine. However, computational limitations thwart this process due to the intricacy of the biological networks and the curse of dimensionality of gene expression data. Therefore, clustering in such scenarios often becomes the first choice of exploratory data analysis to identify natural structures and intrinsic patterns in the data. However, sparse and high dimensional nature of omics data prevents conventional clustering algorithms to discover subtypes that are clinically relevant and statistically significant. Hence, non-linear dimensionality reduction techniques coupled with clustering in such scenarios often becomes imperative to improve the clustering results. In this study, we present a robust pipeline to discover disease subtypes with clinical relevance. Specifically, we focus on discovering patient sub-groups that have a residual life patterns remarkably different from other sub-groups. This is significant because by refining prognosis, subtyping can reduce uncertainty in approximating patients expected outcome. The methodology present is based on robust correlation estimation, UMAP– a non-linear dimensionality reduction method and mapper– a tool from topology. Notably, we suggest a method for improving the robustness of the correlation matrix of gene expression data for improving the clustering results. The performance of the model is evaluated by applying to five cancer datasets obtained through TCGA and comparisons are performed with some state of the art methods of NEMO, RSC-OTRI and SNF with regard to log−rank test and Restricted Life Expectancy Difference. For example in GBM dataset, the minimum separation for any two discovered subtypes is 221 days which is significantly higher than the other methodologies. We also compared the results without using the robust correlation based estimate and observed that robust correlation improves separability between survival curves significantly. From the results we infer that our methodology performs better compared to other methodologies with regard to separating survival curves of patient sub-groups despite using single omics profiles of patients compared to multiple omics profiles of SNF and NEMO. Pathway over-representation analysis is performed on the final clustering results to investigate the biological underpinnings characterizing each subtype.

Changes in mortality during the Covid-19 pandemic in Moldova

The study aims to highlight changes in mortality during the Covid-19 pandemic in Moldova. Two sources of data were used: the National Bureau of Statistics database for overall mortality and mortality by major and specific causes of death and the Ministry of Health for Covid-19 deaths. The primary analysis methods applied in the research were direct mortality standardization and the decomposition of the difference in life expectancy. The results show that the Covid-19 pandemic caused a substantial increase in the number of deaths, which lead to a significant decrease in life expectancy in both sexes. The results emphasize an increase in mortality due to diseases of the cardiovascular system and diseases of the respiratory system. The more detailed analysis of the major causes of death increased during the pandemic period showed an increase in mortality due to coronary atherosclerosis and acute pneumonia, contrary to the trends existing in the pre-pandemic period. It is important to note that mortality due to Covid-19 was higher than major leading causes of death before the pandemic period. The decomposition of changes in life expectancy between the years 2021 and 2019 by age shows quite similar age profiles between sexes, indicating the pandemic's direct and indirect impact on the dynamic of mortality. The effect of the Covid-19 pandemic on mortality, but also on the health of the population, is much more complex, requiring further research to identify prompt and effective responses.

Association of the risk factor UNC13A with survival and upper motor neuron involvement in amyotrophic lateral sclerosis.

The UNC13A gene is an established susceptibility locus for amyotrophic lateral sclerosis (ALS) and a determinant of shorter survival after disease onset, with up to 33.0 months difference in life expectancy for carriers of the rs12608932 risk genotype. However, its overall effect on other clinical features and ALS phenotypic variability is controversial. Genotype data of the UNC13A rs12608932 SNP (A-major allele; C-minor allele) was obtained from a cohort of 972 ALS patients. Demographic and clinical variables were collected, including cognitive and behavioral profiles, evaluated through the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) - Italian version and the Frontal Behavioral Inventory (FBI); upper and lower motor neuron involvement, assessed by the Penn Upper Motor Neuron Score (PUMNS) and the Lower Motor Neuron Score (LMNS)/Medical Research Council (MRC) scores, respectively; the ALS Functional Rating Scale Revised (ALSFRS-R) score at evaluation and progression rate; age and site of onset; survival. The comparison between the three rs12608932 genotypes (AA, AC, and CC) was performed using the additive, dominant, and recessive genetic models. The rs12608932 minor allele frequency was 0.31 in our ALS cohort, in comparison to 0.33-0.41 reported in other Caucasian ALS populations. Carriers of at least one minor C allele (AC + CC genotypes) had a shorter median survival than patients with the wild-type AA genotype (-11.7 months, p = 0.013), even after adjusting for age and site of onset, C9orf72 mutational status and gender. Patients harboring at least one major A allele (AA + AC genotypes) and particularly those with the wild-type AA genotype showed a significantly higher PUMNS compared to CC carriers (p = 0.015 and padj = 0.037, respectively), thus indicating a more severe upper motor neuron involvement. Our analysis did not detect significant associations with all the other clinical parameters considered. Overall, our findings confirm the role of UNC13A as a determinant of survival in ALS patients and show the association of this locus also with upper motor neuron involvement.

Losses of Life Expectancy and Productivity Associated with COVID-19 Pandemic in Canada: Policy Implication for Future Communicable Disease Control.

This research examines whether the Coronavirus disease 2019 (COVID-19) did harm to the population's health through comparing the changes in the life expectancy of Canadians with those of Australians over the period from March 2019 to February 2021 by using a difference-in-differences (DID) estimation method. We found that the pandemic did cause differences in life expectancies between Canada and Australia, probably because of different initial control policies for COVID-19. This study uses the indicator of disability-adjusted life years (DALYs) to measure the societal health burden, which was corroborated by estimating temporal productivity loss (TPL) and permanent productivity loss (PPL) based on the human capital approach (HCA) using data from Health Canada. The societal health burden in Canada amounted to 6.493 DALYs per 1000 male persons and 5.316 DALYs per 1000 female persons. The economy's permanent productivity loss was around USD 5.3 billion, while the temporary productivity loss was around USD 3 billion from February 2020 to April 2022. The sum of the above two losses amounted to 0.477% of the GDP in 2019. Swift and decisive decisions at the very early stage of a pandemic can nip contagions in the bud before numbers get out of hand and would be less damaging to people's health and the economy, as seen in Australia, in contrast to what happened in Canada. We thus recommend that such policies plus telecommunication systems in healthcare services be implemented early on to cope with the future outbreak of any emerging infectious diseases such as COVID-19.

The state of health in Pakistan and its provinces and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Understanding health trends and estimating the burden of disease at the national and subnational levels helps policy makers track progress and identify disparities in overall health performance. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides comprehensive estimates for Pakistan. Comparison of health indicators since 1990 provides valuable insights about Pakistan's ability to strengthen its health-care system, reduce inequalities, improve female and child health outcomes, achieve universal health coverage, and meet the UN Sustainable Development Goals. We present estimates of the burden of disease, injuries, and risk factors for Pakistan provinces and territories from 1990 to 2019 based on GBD 2019 to improve health and health outcomes in the country. We used methods and data inputs from GBD 2019 to estimate socio-demographic index, total fertility rate, cause-specific deaths, years of life lost, years lived with disability, disability-adjusted life-years, healthy life expectancy, and risk factors for 286 causes of death and 369 causes of non-fatal health loss in Pakistan and its four provinces and three territories from 1990 to 2019. To generate estimates for Pakistan at the national and subnational levels, we used 68 location-years of data to estimate Pakistan-specific demographic indicators, 316 location-years of data for Pakistan-specific causes of death, 579 location-years of data for Pakistan-specific non-fatal outcomes, 296 location-years of data for Pakistan-specific risk factors, and 3089 location-years of data for Pakistan-specific covariates. Life expectancy for both sexes in Pakistan increased nationally from 61·1 (95% uncertainty interval [UI] 60·0-62·1) years in 1990 to 65·9 (63·8-67·8) years in 2019; however, these gains were not uniform across the provinces and federal territories. Pakistan saw a narrowing of the difference in healthy life expectancy between the sexes from 1990 to 2019, as health gains for women occurred at faster rates than for men. For women, life expectancy increased by 8·2% (95% UI 6·3-13·8) between 1990 and 2019, whereas the male life expectancy increased by 7·6% (3·5-11·8). Neonatal disorders, followed by ischaemic heart disease, stroke, diarrhoeal diseases, and lower respiratory infections were the leading causes of all-age premature mortality in 2019. Child and maternal malnutrition, air pollution, high systolic blood pressure, dietary risks, and tobacco consumption were the leading all-age risk factors for death and disability-adjusted life-years at the national level in 2019. Five non-communicable diseases-ischaemic heart disease, stroke, congenital defects, cirrhosis, and chronic kidney disease-were among the ten leading causes of years of life lost in Pakistan. Burden varied by socio-demographic index. Notably, Balochistan and Khyber Pakhtunkhwa had the lowest observed gains in life expectancy. Dietary iron deficiency was the leading cause of years lived with disability for both men and women in 1990 and 2019. Low birthweight and short gestation and particulate matter pollution were the leading contributors to overall disease burden in both 1990 and 2019 despite moderate improvements, with a 23·5% (95% UI 3·8-39·2) and 27·6% (14·3-38·6) reduction in age-standardised attributable DALY rates during the study period. Our study shows that progress has been made on reducing Pakistan's disease burden since 1990, but geographical, age, and sex disparities persist. Equitable investment in the health system, as well as the prioritisation of high-impact policy interventions and programmes, are needed to save lives and improve health outcomes. Pakistan is facing several domestic and foreign challenges-the Taliban's return to power in Afghanistan, political turmoil, catastrophic flooding, the COVID-19 pandemic-that will shape the trajectory of the country's health and development. Pakistan must address the burden of infectious disease and curb rising rates of non-communicable diseases. Prioritising these three areas will enhance Pakistan's ability to achieve universal health coverage, meet its Sustainable Development Goals, and improve the overall health outcomes. Bill & Melinda Gates Foundation. For the Urdu translation of the abstract see Supplementary Materials section.

The effect of the COVID-19 pandemic on life expectancy in the USA: An application of hybrid life expectancy.

Pandemics are, by definition, temporary intervals of substantially increased mortality rates experienced across a wide geographic area. One way of assessing the magnitude of the COVID-19 pandemic in the USA has been to compute the differences in life expectancy at birth during a pandemic year and the year before the pandemic. Such comparisons are misleading because they do not account for the duration of the pandemic. The computation of life expectancy in 2019 assumes that people spend their entire lives experiencing prepandemic mortality rates. The computation of life expectancy in 2021 assumes that people live their entire lives in a permanent pandemic. However, people do not live their entire lives experiencing the elevated mortality rates of 2021. This article introduces a method for calculating life expectancy that reflects the experience of people enduring pandemic-level mortality rates for fixed durations. We call the new quantity hybrid life expectancy because it integrates both pandemic and prepandemic mortality rates. The difference in life expectancy at birth in the USA in 2019 with and without a 3-year-long pandemic is 0.01 years. This is because mortality rates at ages 0, 1, and 2 in the pandemic were essentially unchanged from their prepandemic levels. Life expectancy at age 65 incorporating a 3-year pandemic is 0.18 years lower than life expectancy would have been without it. Reductions in life expectancy due to the COVID-19 pandemic using hybrid life expectancy are dramatically lower than differences in life expectancy that do not take the duration of the pandemic into account.

Interpreting changes in life expectancy during temporary mortality shocks.

Life expectancy is a pure measure of the mortality conditions faced by a population, unaffected by that population's age structure. The numerical value of life expectancy also has an intuitive interpretation, conditional on some assumptions, as the expected age at death of an average newborn. This intuitive interpretation gives life expectancy a broad appeal. Changes in life expectancy are also routinely used to assess mortality trends. Interpreting these changes is not straightforward as the assumptions underpinning the intuitive interpretation of life expectancy are no longer valid. This is particularly problematic during mortality 'shocks,' such as during wars or pandemics, when mortality changes may be sudden, temporary, and contrary to secular trends. This study aims to provide an alternative perspective on what changes in life expectancy measure that remains applicable during mortality shocks. Returning to two different models that the period life table may represent, I show that a difference in life expectancy is typically interpreted from the synthetic cohort model as the difference in mean longevity between different birth cohorts. However, it can also be interpreted from the stationary population model as a measure of premature mortality in a death cohort. The latter, less common interpretation makes more sense for temporary declines in life expectancy induced by mortality shocks. The absolute change in life expectancy is then an age-standardized value of the average lifespan reduction for people dying during the mortality shock. To clarify what a decline in life expectancy measures during mortality shocks is important, especially as demographers often assess the mortality impact of those shocks using this metric, which gets widely reported beyond demographers' inner circle.

Dispositional and situational attributions for why the rich live longer than the poor

AbstractDespite considerable focus on predictors of attitudes towards economic inequality, there is less psychological research into attitudes towards other unequal outcomes between the rich and poor, including differences in health and life expectancy. Two studies examine whether causal attributions for these socioeconomic health inequalities predict attitudes towards them. A cross‐sectional study of 332 UK and US respondents showed that most respondents indicate a preference for some degree of income inequality but no life expectancy inequality between the richest and poorest in society. These preferences for equal life expectancy for the rich and poor were significantly less likely for respondents who viewed health inequalities to be caused by dispositional factors (e.g., self‐control, ability or effort). In a second pre‐registered cross‐sectional study (n = 602), dispositional attributions negatively predicted self‐reported concern about health inequality, whilst endorsing situational attributions (e.g., discrimination and prejudice, wages) was positively associated with concerns on this issue. Moreover, situational attributions positively predicted support for six policy proposals for reducing health inequality, while dispositional attributions were associated with increased support for some of these interventions and decreased support for others. Despite very distinct distribution preferences for income and life expectancy outcomes, causal attributions continue to predict attitudes towards health inequality and associated policy interventions.

National and education-specific trends in life and health expectancies in Denmark 2004-2015.

Several studies have revealed widening of inequalities in life expectancy, but little is known about the recent changes in health expectancy nationally and between socioeconomic groups. This study examines dynamics of national and education-specific life expectancy and health expectancies at age 50 years in Denmark from 2004/2007 to 2015. Nationwide register data on education and mortality were linked and combined with Danish health data from the Survey of Health, Ageing and Retirement in Europe and changes in life expectancy and three health expectancy indicators were estimated by Sullivan's method. From 2004 to 2015, national life expectancy at age 50 years increased by 2.4 years for men and 2.1 years for women. Simultaneously, after an initial rapid improvement from 2004 to 2007, the pace of progress in health expectancy decreased. From 2007 to 2015, the difference in life expectancy at age 50 years between men with long and short education increased from 4.3 to 5.0 years. For women, the corresponding increase in the life expectancy gap was less pronounced from 3.5 to 3.8 years. The educational gap in lifetime without long-term illness decreased from 4.6 years to 3.1 years for men and from 6.1 years to 4.6 years for women. On the contrary, the educational gap increased for lifetime without activity limitations and in self-rated good health. Previously observed improvements in health expectancy in Denmark slowed down despite continuing progress in life expectancy. This worrying change coincides with persistent educational inequalities in life expectancy and health expectancy and is a challenge to a sustainable social and health development in the future.

Mortality risk and years of life lost for people with reduced renal function detected from regular health checkup: A matched cohort study

With the increasing threat of metabolic syndromes, a focus on maintaining kidney health from early- to mid-adulthood is necessary. This study elucidates mortality risk and years of life lost (YLLs) due to abnormal renal function. This was a retrospective, matched cohort study from health checkup data from 2000 to 2015. We identified 12,774 participants with abnormal renal function (eGFR < 60 mL/min/1.73 m2) and used propensity score matching to identify 25,548 participants with normal renal function (eGFR ≥ 60). YLLs were estimated using the life expectancy differences between the abnormal and matched normal cohorts. Cox models were used to estimate the adjusted mortality risk. The estimated life expectancy of participants with proteinuria and eGFR < 60 was 26.24 years, with a 95 % confidence interval of (23.96, 29.36), 17.62 (16.37, 18.78), and 11.70 (11.02, 12.46) for age groups of 30 – 54, 55 – 64, and 65 – 79 years, respectively. The estimated YLLs of participants with proteinuria and eGFR < 60, as compared with the matched normal cohort, were 17.86 (13.41, 20.36), 12.55 (11.41, 13.78), and 8.31 (7.47, 9.13) years for the three age groups, respectively. The Cox model estimates of mortality hazard ratios of participants having proteinuria and eGFR < 60 against matched referents were 5.29 (3.97, 7.05), 3.99 (3.34, 4.75), and 3.05 (2.62, 3.55) for the three age groups, respectively. Abnormal renal function shortens life expectancy, particularly in patients with proteinuria and in younger adults. Active health management of renal function can reduce the disease burden.

Sex-differences in life expectancy at birth: A descriptive analysis of the contributions of age and causes of death to the gap in Norway, 1881–2011

Official mortality statistics provide ample evidence that women live longer than men. In many European countries, the sex difference in life expectancy began to increase near the end of the nineteenth century, peaking between the 1960s and the 1980s, before declining again. In Norway, there was another earlier peak before the sex gap started to converge to that in other European countries.This study investigated changes in sex differences in life expectancy at birth in Norway from 1881 to 2011 as well as the contribution of broad age groups and causes of death to those differences. The total sex gap was broken down by age and cause using decomposition methods. Available mortality statistics were used for every tenth year between 1881 and 2011, excluding the war year of 1941. We regrouped the causes of death into 14 categories to reduce comparability problems across different classification systems.At the end of the 19th century, the gap in life expectancy at birth was largely due to the excessive mortality in males aged 15–29, particularly external causes of death, and in infant mortality in boys (under 1 year) due to perinatal and congenital causes. Since the 1970s, excess mortality in males aged 60 years and over has explained more than half of the sex gap, and the most relevant contributors have been circulatory diseases, neoplasms, and external causes. The recent narrowing of this gap has been related to the increase in pathologies affecting women in old age, such as senility and dementia. Differences in smoking behavior have likely played a role as well: women started smoking a few decades later than men, and they also reduced their smoking later.

Racial and Ethnic Differences in Sleep Duration Life Expectancies among Men and Women in Mid-to-Late Life.

This analysis documents U.S. racial/ethnic and gender differences in life expectancies with different self-reported sleep durations among adults aged 50 and older. We used self-reported sleep duration and linked mortality information from the 2004-2015 National Health Interview Survey (n = 145,015) to calculate Sullivan Method Lifetables for life expectancies with different self-reported sleep duration states: short (≤6hours), optimal (seven to 8hours), and long (≥9hours) sleep duration per-day by race/ethnicity and gender. Non-Hispanic Black men (35.8%, 95% CI: 34.8%-36.8%) and women (36.5%, 95% CI: 35.7%-37.1%) exhibited the highest proportion of years lived with short sleep duration followed by Hispanic men (31.1%, 95% CI: 29.9%-32.3%) and women (34.1%, 95% CI: 33.1%-35.1%) and Non-Hispanic White men (25.8%, 95% CI: 25.4%-26.2%) and women (27.4%, 95% CI: 27.0%-27.7%). These results highlight how race/ethnic inequality in sleep duration and life expectancy are intertwined among older adults in the U.S.

Associations between multimorbidity patterns of 4 chronic diseases and physical activity with all-cause mortality

Objective: To identify the prevalence of multimorbidity among a Chinese population, analyze the risk of all-cause mortality with different multimorbidity patterns, and the impact of exercise on the risk of multimorbidity-related mortality and life lost. Methods: The study was based on 437 408 MJ Health Management Center participants. The classification decision tree was used to explore multimorbidity patterns composed of hypertension, diabetes, chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD). The Cox proportional hazards model was used to calculate the all-cause mortality hazard ratio (HR) for different multimorbidity patterns. Using Chiang's life table method, years of life lost were the difference in life expectancy for those with and without multimorbidity. Results: The prevalence rate of multimorbidity was 8.7%. Among multivariate patterns, the most common ones were "hypertension+CKD" (3.6%), "hypertension + diabetes + CKD" (1.1%) and "hypertension+diabetes+CKD+COPD" (0.1%). Compared with a healthy population, patterns with the highest mortality risk were "diabetes+CKD" (HR=3.80, 95%CI: 3.45-4.18), "diabetes+CKD+COPD" (HR=4.34, 95%CI: 3.43-5.49) and "hypertension+ diabetes+CKD+COPD" (HR=4.75,95%CI:4.15-5.43). Through low-intensity and moderate to high-intensity exercise, the increased HRs were attenuatedcompared with the inactive population. People with single disease and multimorbidity shortened life by 4.6 and 13.4 years, while exercise attenuated 2.3 and 4.6 years of life lost, of which low-intensity and moderate to high-intensity exercise saved 1.5 and 3.7 years of life lost due to chronic diseases. Conclusions: Multimorbidity patterns based on "diabetes + CKD" cause the highest mortality risk, and physical activity in reducing mortality was significant for either with or without multimorbidity. Higher exercise intensity leads to a greater relative reduction of mortality risk.

Current Trends and Approaches to the Search for Genetic Determinants of Aging and Longevity.

The online version contains supplementary material available at 10.1134/S1022795422120067.

Sex-Biased Differences in Infant Mortality and Life Expectancy at Síi Túupentak , an Ancestral Ohlone Village in Central California (ca. 540–145 cal. BP)

ABSTRACT: Síi Túupentak (CA-SCA-565/H) is a late precontact ancestral Ohlone village and cemetery site in Central California (ca. 540–145 cal. BP). Integration of proteomic, genomic, and osteological analyses provided highly confident biological sex estimates for remains of most individuals at this site (65 of 76), spanning all age groups, from perinatal infants to aged adults. Based on these relatively comprehensive data, it was possible to generate sex-specific Kaplan-Meier survival curves for this burial population of sedentary hunter-gatherers. As was common among societies predating modern Western medicine and antibiotics, infant mortality was high for both males and females. However, male infants (from birth to 5 years of age) appear to have died at nearly twice the rate of female infants (10 of 33 males vs. 5 of 32 females) and had a mean age of survival at birth of only 19 years, compared to 30 years for females. The difference in male and female survival was statistically significant by log-rank test ( p = 0.005). Compared to survival curves for other societies predating modern Western medicine and antibiotics, including American-era historical deaths recorded for a cemetery in San Francisco, this bias is larger than might be expected. We suspect the pattern of sex-biased infant mortality at Síi Túupentak could relate to an intrinsic survival advantage for female infants, combined with extrinsic factors such as environmental pathogens, nutritional stress, and gendered differences in weaning patterns detected through stable isotope analyses. Using isotopic data on weaning ages and ethnographic accounts of gendered foraging activities, we focus on the potential role of sex-biased differences in weaning patterns and highlight potential demographic and social implications. Broader application of proteomic and genomic sex estimation would allow sex-biased differences in nutrition and health, as well as social and cultural aspects of male and female life histories, to be compared across a wide range of archaeologically known hunter-gatherer societies.

Income differences in partial life expectancy between ages 35 and 64 from 1988 to 2017: the contribution of living arrangements.

Socioeconomic differences in mortality among the working-age population have increased in several high-income countries. The aim of this study was to assess whether changes in the living arrangement composition of income groups have contributed to changing income differences in life expectancy during the past 30 years. We used Finnish register data covering the total population to calculate partial life expectancies between ages 35 and 64 by income quartile in 1988-2017. The contribution of living arrangements to these differences was assessed by direct standardization. Decomposition methods were used to determine the extent of life expectancy differences due to external (accidental, violent and alcohol-related) causes of death. The life expectancy gap between the highest and lowest income quartile increased until 2003-07, but decreased thereafter. The contribution of living arrangements to these differences remained mostly stable: 36-39% among men and 15-23% among women. Those living without children consistently showed the greatest life expectancy differences by income. External causes of death significantly contributed to income differences in life expectancy. The living arrangement composition of income groups explained part of the differences in life expectancy, but not their changes. Our results on the contribution of external causes of death imply that both the persistent income gradient in mortality as well as the mortality disparities by living arrangements are at least partially related to similar selection or causal mechanisms.

Quantum Healthy Longevity for healthy people, planet, and growth

Quantum Healthy Longevity for healthy people, planet, and growth

The state of health in Indonesia's provinces, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

SummaryBackgroundAnalysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030.MethodsWe analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations.FindingsLife expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3–63·7) to 69·4 years (67·2–71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5–66·8) to 73·5 years (71·6–75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90–77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7–81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9–68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7–67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019.InterpretationOur findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country.FundingThe Bill & Melinda Gates Foundation and the Government of Indonesia.TranslationFor the Bahasa Indonesia translation of the abstract see Supplementary Materials section.

Examining the association between health status and subjective life expectancy among older Indian adults based on the mindsponge approach

Gender and socioeconomic differences in subjective life expectancy (SLE) are an unexplored arena in the geriatric literature concerning low-resource settings. Information on several health outcomes that might influence the SLE could guide targeted interventions, particularly in countries with rapidly ageing populations like India. This study aimed to explore SLE and the associations of SLE with the objective and subjective health status of older Indian adults, based on the mindsponge mechanism that links the contextual factors with individuals' evaluation of health. Data from the Longitudinal Ageing Study in India were used and the final sample included 5969 older adults aged 60 years and above. Independent t-tests were used to assess the gender difference in SLE according to various health-related factors. Additionally, we used generalized linear regression models (GLMs) with a logit link and a binomial family to fulfil the study objectives. The proportion of older adults who reported a 100% probability of survival for a 1-year period was nearly 38%, compared with 12% and 6% of the respondents who reported the same for 5 and 10 years survival periods, respectively. Older men reported a greater average probability of own survival than older women for all the time periods. Older men who reported poor self-rated health had a significantly lower SLE for a 1-year period (β = −0.232, SD = 0.107) and a 5-year period (β = −0.226, SD = 0.077) than those who reported good self-rated health. On the other hand, older women with poor self-rated health had a significantly lower SLE for a 10 years time horizon than women with good self-rated health. Underweight men had significantly lower SLE for a 1-year period than men with normal BMI (β = −0.213, SD = 0.097). Further, cognitively impaired women reported significantly lower SLE for a 1-year period (β = −0.399, SD = 0.108) and 5 years period (β = −0.160, SD = 0.077). Depressed older men reported significantly lower SLE for 1-year period (β = −0.309, SD = 0.101), 5-year period (β = −0.194, SD = 0.084), and 10-year period (β = −0.129, SD = 0.071). The current findings, supporting the mindsponge mechanism, indicate that older adults base their estimation of longevity on health factors that they are aware of or not. This finding has significant implications for health professionals and public policy in planning targeted interventions that can benefit at-risk population cohorts.

Two Wives and Ten Husbands: A Comparative Reading of The Wife of Bath’s Prologue and The Wife of Willesden’s Prologue

This paper juxtaposes two literary works, Geoffrey Chaucer’s The Wife of Bath’s Prologue in The Canterbury Tales (1386-1400) and Zadie Smith’s The Wife of Willesden’s Prologue in The Wife of Willesden (2021). Both women, one in the fourteenth century (Alisoun) and one in the twenty-first century (Alvita), say what they feel and follow any path that they choose. They hardly mind what others say about them. They decide their own mind and their own perspectives. They hold five husbands seamlessly: in the space of 40 years in the case of Alisoun, and over 50 years in the case of Alvita, adjusted to fit the modern difference in life expectancy. In presenting these two literary pieces, this paper examines the relish of reading about the assertive ladies of both worlds, who claim their lives to be theirs more than anyone else’s. What is conspicuous in this comparative reading is that Smith’s pastiche of Chaucer’s The Wife of Bath’s Prologue in the theatrical form brings to life the five voiceless husbands of Alisoun, whose distantly muted voices the audience and the reader are allowed to hear reverberating in Kiln Theatre in their aural imagination. Thus, this comparative reading brings out the voices of Alvita’s five husbands and their views of their shared wife. Moreover, the paper examines how Alisoun’s husbands see Alisoun, and imagines how Alisoun would have been looked at when the reader of The Canterbury Tales was left with only Alisoun’s view of herself.