Changes In Life Expectancy Research Articles

Increase in the Life Expectancy of Patients with Cancer in the United States.

Cancer is becoming more of a chronic disease due to improvements in treatment and early detection for multiple cancer sites. To gain insight on increased life expectancy due to these improvements, we quantified trends in the loss in expectation of life (LEL) due to a cancer diagnosis for six cancer sites from 1975 through 2018. We focused on patients diagnosed with female breast cancer, chronic myeloid leukemia (CML), colon and rectum cancer, diffuse large B-cell lymphoma (DLBCL), lung cancer, or melanoma between 1975 and 2018 from nine Surveillance, Epidemiology, and End Results cancer registries. Life expectancies for patients with cancer ages 50+ were modeled using flexible parametric survival models. LEL was calculated as the difference between general population life expectancy and life expectancy for patients with cancer. Over 2 million patients were diagnosed with one of the six cancers between 1975 and 2018. Large increases in life expectancy were observed between 1990 and 2010 for female breast, DLBCL, and CML. Patients with colon and rectum cancer and melanoma had more gradual improvements in life expectancy. Lung cancer LEL only began decreasing after 2005. Increases in life expectancy corresponded with decreases in LEL for patients with cancer. The reported gains in life expectancy largely correspond to progress in the screening, management, and treatment of these six cancers since 1975. LEL provides an important public health perspective on how improvements in treatment and early detection and their impacts on survival translate into changes in cancer patients' life expectancy.

Life-expectancy changes from 2019 to 22: A case study of Japan using provisional death count

Many countries struggled with suppressing the incidence of COVID-19 caused by SARS-CoV-2 Omicron variant (B.1.1.529). As the epidemic size of COVID-19 in 2022 became bigger than earlier years in Japan, the present study aimed to estimate life expectancy at birth at the end of 2022, using provisional death datasets in Aichi and Fukui prefectures. We collected monthly death count from 2019 to the end of 2022, computing the period life table. While the life expectancy at birth in Aichi, 2019 was 84.6 years, it was very slightly extended to 84.7 years in 2020 and 2021, followed by a shortening for nearly 0.4 years in 2022. In Fukui, monotonous extension pattern was seen, i.e., 85.5 years in 2019, 85.6 in 2020, followed by 85.8 and 86.2 years in 2021 and 2022, respectively. Although decades-long trend of extending life expectancy at birth was partly discontinued from 2020 due to the pandemic at the national level, we have shown that the pandemic impact was still small in Japan by the end of 2022. First Omicron wave occurred shortly after primary series vaccination, and even real time booster program was underway during that wave. Different demographic consequences between Aichi and Fukui are explained by differential epidemic sizes prior to vaccination.

Life expectancy, fertility, and retirement in an endogenous-growth model with human capital accumulation

This paper analyzes how the improvement in life expectancy affects fertility, educational investments, retirement, and economic growth based on an overlapping-generations model with human capital accumulation. We show that if the labor productivity of the old is greater (lower) than a critical value, then higher life expectancy will raise (reduce) fertility. Moreover, agents will postpone retirement as life expectancy increases if the labor productivity of the old is near the critical value. However, life expectancy changes do not affect output per capita's growth rate. A decrease in the income tax rate does not affect fertility, but causes agents to postpone retirement while simultaneously raising the growth rate of output per capita. The empirical analysis finds that life expectancy has an overall negative effect on fertility, and this negative effect diminishes as life expectancy (a proxy for labor productivity of the old) rises. Moreover, life expectancy does not significantly influence growth for countries with high life expectancy or middle or high income.

Investigating mortality trends in Italy during the COVID-19 pandemic: life expectancy changes within provinces and vaccination campaign impact up to December 2022

ObjectivesWe used publicly available population data from 1 January 2019 up to 31 December 2022, to investigate mortality trends in Italy during the COVID-19 pandemic, evaluating changes in life expectancy (LE) at birth within provinces and the impact of COVID-19 vaccinations. Study designAggregate data analysis. MethodsAnnual period life tables were used to estimate sex-specific LEs within provinces from 2019 to 2022. We used Arriaga decomposition to analyze the contribution of age groups (<60 years and ≥60 years) to annual LE changes. We implemented a Quasi-Poisson regression model to estimate the number of averted deaths by the achieved COVID-19 vaccination rates from January 2021 up to December 2022, simulating a counterfactual scenario where vaccine doses were not administered. ResultsThe results revealed geographical heterogeneity in annual LE changes across Italian provinces during the pandemic. By the end of 2022, LE was below the prepandemic levels in 88% of provinces for females and in 76% for males. In addition, we estimated that the achieved vaccination rates averted 460,831 deaths (95% confidence interval: 250,976–707,920), corresponding to a 25% reduction in expected all-cause mortality. ConclusionsOverall, the study highlighted the significant role of COVID-19 vaccinations in averting a considerable number of deaths and improving LE. However, by the end of 2022, LE had not fully recovered to prepandemic levels in many provinces. This could be attributed to concurrent factors, including enduring COVID-19 pandemic effects, intense summer heat waves and early onset of seasonal flu. Further research and continuous monitoring are essential to fully comprehend long-term mortality trends and optimize public health strategies.

Online Health Communities’ Portrayal of Obesity on Social Media Platforms in South Africa

The rapidly increasing prevalence of obesity in South Africa, intertwined with extensive changes in diet, life expectancy, and nutritional status has led to a complex framing of obesity on social media. This has prompted the prioritization of media-based social and behavior change communication interventions leveraging social media for obesity prevention. This study was conducted to understand how obesity is constructed and represented on social media in South Africa. A media review of Facebook and Twitter platforms in South Africa was conducted over a six-month period using Meltwater software for data collection. The search yielded 13 500 posts and tweets. Data were cleaned and coded in Microsoft Excel. Content and framing analysis were performed to add insight into the nature of obesity discourse on social media. Portrayals of obesity on social media were dominated by stigmatizing imagery blaming individuals for unhealthy lifestyles, poor diets, and lack of physical activity. Future media-based social and behavior change communication interventions for obesity prevention can leverage social media to reach the broader public and insights into media portrayals of obesity have the potential to influence the shape and development of these behavioral interventions.

Why is care use declining? Changes in residential long-term care between 1999 and 2018 in Finland

Abstract Background Residential long-term care (LTC) coverage has declined in many countries over the past decade. However, it is unclear to what extent the decline is attributable to a smaller proportion of older people entering or shorter time spent in LTC, and if the change has been similar across sociodemographic groups. This study analysed changes in life expectancy in LTC at age 65, the proportion ever entering, and years spent in LTC among those who entered, and quantified the contributions of changing rates of admission, mortality and exit to the change in life expectancy in LTC. Methods We analysed linked population register data that covered all Finnish residents aged 65+ between 1999 and 2018 (n = 2,016,987) on dates of entries to and exits from LTC, dates of death, and sociodemographic characteristics. We estimated transition rates between home, LTC and death, and calculated multistate life tables by sex, marital status and education across four periods 1999-2003, 2004-2008, 2009-2013 and 2014-2018. Results Life expectancy in LTC increased from 0.75 to 0.89 years among men and from 1.61 to 1.83 years among women between 1999-2003 and 2003-2008. The increase was mainly attributable to declining rates of exit from LTC, and thereby longer time spent in LTC for those who entered. Life expectancy in LTC started declining in 2009-2013 and reached 0.80 years among men and 1.51 years among women in 2014-2018. The decline mainly related to an increasing death rate in LTC. In all periods, declining mortality in the community contributed to an increase in life expectancy in LTC, but this was offset by steady declines in admission rates. Life expectancy in LTC changed similarly across marital status and education groups. Conclusions Recent declines in LTC use - driven by lower rates of entry and higher mortality in LTC when entered - imply that across sociodemographic strata it is has become more difficult to find LTC placement and older people enter LTC in ever worse health. Key messages • Overall LTC use increased in early 2000s despite declining admission rates. The increase was mainly due to declining exit rate from LTC indicating longer time spent in LTC for those who entered. • The recent shortening of life expectancy in LTC derives from entering LTC at a later stage and closer to death, indicating greater level of disability and worse health at the time of entry.

Econometric models derived from meta-analysis to estimate VSL and VOLY associated to air pollution at a global level: preliminary results

Abstract Epidemiological research has shown a strong correlation between air pollution and risk of premature death. Among the damage costs of air pollution, premature mortality is by far the largest contributor, hence accounting for the number of deaths linked to poor air quality has become a key environmental indicator. Monetizing reductions in risks of death through cost-benefit analyses can be useful to create efficient public policies aiming at improving air quality. The benefits of prevented mortalities can be expressed in terms of a Value of a Statistical Life (VSL), an economic parameter representing individuals’ willingness to exchange wealth for mortality risk reduction. In addition, the monetary Value Of a Life Year (VOLY) is also an important parameter to be measured, as it considers the change in life expectancy associated with air pollution. However, determining reliable estimates of VSL and VOLY can be challenging, as the methods employed in different studies can vary widely between, and even within, countries. Furthermore, most countries have insufficient and unreliable VSL and VOLY estimates. Lack of country-specific data and common methodology makes it difficult to assess climate policy at a global scale. To address this gap, a meta-analysis of existing literature is conducted to develop econometric models for estimating VSL and VOLY on a global level. The comprehensive search of articles and databases revisits established quantification methodologies for air pollution related mortality, which results in an extensive database of empirical data on VSL and VOLY estimates. Based on this new and updated database, transfer functions of VSL and VOLY are estimated for specific pollutants and different countries, according to each country's distinctive characteristics.

Effects of the COVID-19 pandemic on life expectancy at birth at the global, regional, and national levels: A joinpoint time-series analysis.

Current estimates indicate that coronavirus disease 2019 (COVID-19) caused 14.9 million excess deaths in 2020 and 2021. Thus, estimating the change in life expectancy at birth due to the COVID-19 pandemic could aid in understanding its impact and implementing public health initiatives. We collected data on the life expectancy at birth of the combined population between 1990 and 2021 at the global, regional, and national levels from the 2022 Revision of World Population Prospects. In this time series study, we estimated the trend segments, the change of trend years (joinpoints), the annual percentage change (APC) in life expectancy at birth within each trend segment, and the average APC (AAPC) in life expectancy at birth during the full study period using joinpoint regression analysis. The global life expectancy at birth decreased from 72.8 years in 2019 to 71.0 years in 2021, with an annual decrease of 1.2% (95% confidence interval (CI) = 1.0, 1.5) during the 2019-2021 period, despite an overall increasing trend during the entire period from 1990 to 2021 (AAPC = 0.3%; 95% CI = 0.3, 0.4). We observed a significantly increasing trend in life expectancy at birth in all regions and nearly 87.7% (207/236) of the world's countries and areas during the entire period (1990-2021). All continental regions except Africa and Oceania experienced a significant decreasing trend in life expectancy at birth in 2019-2021, with an APC of -1.2% (95% CI = -1.5, -0.9) for Asia, -2.1% (95% CI = -2.7, -1.6) for Latin America and the Caribbean, -1.1% (95% CI = -1.6, -0.6) for Northern America, and -1.4% (95% CI = -1.9, -0.9) for Europe. Among all countries and areas, 107 countries and areas (45.3%) experienced a significant decreasing trend in life expectancy at birth in the most recent time segment, with 77 countries and areas (32.6%) experiencing a significant decreasing trend during the 2019-2021 period. The world experienced a significant decreasing trend in life expectancy at birth in 2019-2021, with a decrease of 1.8 years; all continental regions except Africa and Oceania and 77 countries and areas experienced a significant decreasing trend in life expectancy at birth. These decreasing trends at global, regional, and national levels during the 2019-2021 period reflected the COVID-19 pandemic's direct and indirect adverse effects on life expectancy at birth.

Effect of the COVID-19 pandemic on life expectancy in Australia, 2020-22.

Australia provides a valuable international case study of life expectancy during the pandemic. In contrast to many other countries, it experienced relatively stringent restrictions and low COVID-19 mortality during 2020-21, followed by relaxation of these restrictions when high vaccination rates were achieved. This study measures Australia's life expectancy trends and the contributions of age group and causes of death, during the pandemic. Trends in life expectancy at birth in Australia and its states and territories were measured from 2020 to 2022. The contributions of age group and cause of death to these trends were measured using decomposition methods. Life expectancy was compared with other high-income countries. Australia's life expectancy fell by more than half a year in 2022, following a sharp increase in 2020 and moderate decline in 2021. For the 3 years 2020 to 2022, life expectancy was 0.13 years (95% confidence interval 0.07-0.19) higher for males and 0.09 years (0.03-0.14) higher for females versus 2017-19. Australia's life expectancy increase in 2020 was larger than that in the vast majority of other high-income countries, but its decline in 2022 was greater than in other countries whose life expectancy rose in the first year of the pandemic. The small negative contribution of COVID-19 deaths to life expectancy in Australia was more than offset by lower non-communicable disease mortality. There were only small differences in life expectancy change between the states with the most stringent restrictions (Victoria and New South Wales) and the rest of Australia. Australia's life expectancy trends during 2020-22 were relatively favourable compared with other high-income countries, with the exception of its sharp decline in 2022 once restrictions were loosened.

Life Expectancy Changes During the COVID-19 Pandemic, 2019-2021: Highly Racialized Deaths in Young and Middle Adulthood in the United States as Compared With Other High-Income Countries.

We estimated changes in life expectancy between 2019 and 2021 in the United States (in the total population and separately for 5 racial/ethnic groups) and 20 high-income peer countries. For each country's total population, we decomposed the 2019-2020 and 2020-2021 changes in life expectancy by age. For US populations, we also decomposed the life expectancy changes by age and number of coronavirus disease 2019 (COVID-19) deaths. Decreases in US life expectancy in 2020 (1.86 years) and 2021 (0.55 years) exceeded mean changes in peer countries (a 0.39-year decrease and a 0.23-year increase, respectively) and disproportionately involved COVID-19 deaths in midlife. In 2020, Native American, Hispanic, Black, and Asian-American populations experienced larger decreases in life expectancy and greater losses in midlife than did the White population. In 2021, the White population experienced the largest decrease in US life expectancy, although life expectancy in the Native American and Black populations remained much lower. US losses during the pandemic were more severe than in peer countries and disproportionately involved young and middle-aged adults, especially adults of this age in racialized populations. The mortality consequences of the COVID-19 pandemic deepened a US disadvantage in longevity that has been growing for decades and exacerbated long-standing racial inequities in US mortality.

Life-expectancy changes during the COVID-19 pandemic from 2019-2021: estimates from Japan, a country with low pandemic impact.

The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020-2021 into age-specific and cause of death-specific contributions. We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019-21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. From 2019-2020, Japan's national level life expectancy across the entire population was extended by 0.24 years. From 2020-2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020-2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020-2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life expectancy, whereas respiratory diseases did not. The decades-long increasing trend in life expectancy was suspended by the COVID-19 pandemic. However, life expectancy changes from 2019-2020 and 2020-2021 were small in Japan. This may be attributable to the small epidemiological impact of COVID-19 during this time period, but nonetheless, the negative impact of COVID-19 on life expectancy was indicated in the present study. The chance of death accelerated in older people in 2021, but a smaller number of deaths than usual among infants and working age adults contributed to extended life expectancy, and the change in the cause of death structure under the COVID-19 pandemic also significantly contributed to shortening life expectancy.

Open Economy Neoclassical Growth Models and the Role of Life Expectancy

AbstractThis paper applies the Ramsey–Cass–Koopmans (RCK) growth model to an open economy so that, when calibrated with standard parameter values that are commonly used in the small open economy macroeconomic literature, the time paths of the model variables and the speeds of convergence implied by the model conform with empirical evidence. Open-economy versions of the RCK growth model lead to several counterfactual conclusions including: infinite speeds of convergence for physical capital and output; and unbalanced consumption and asset growth. We avoid these undesired results by extending the baseline model with human capital, international credit constraints, and finite horizons. Given its finite-horizons feature, our model allows us to study the growth implications of changes in life expectancy from the perspective of an open economy, as most of the existing theoretical-quantitative literature that focus on the relationship assumes a closed economy. The model predicts that increased life expectancy has positive but diminishing marginal effect on long-run output per capita. We find that, between 1960 and 2018, improvements in average life expectancy at birth raised long-run output per capita in sub-Saharan Africa, the OECD region, and Canada by an estimated 57.49 %, 14.94 %, and 11.58 %, respectively. In addition, if average life expectancy at birth in sub-Saharan African countries converges from its current level to the level in their OECD counterparts, the region’s long-run output per capita will increase by an estimated 22.89 %.

PROGRAM PENINGKATAN TOLERANSI SOSIAL KEMANUSIAAN UMAT BERAGAMA DALAM KOMUNIKASI VERBAL DI DUSUN LENDANG GUAR TIMUR, LOMBOK BARAT

The residents of Lendang Guar hamlet are residents who are very difficult to access from the West Lombok Regency Highway to get to other places, this position is very difficult to reach by local transportation so social understanding is very closed. This is necessary sharpening insights regarding Hinduism actually needs to be recalled so that there are no deviations from the teachings of Hinduism. Going down directly to the hamlet is carried out continuously to produce what is expected by all levels of society to maintain inter- and inter-religious harmony. The results that are felt and obtained by the community with this community service program are changes in life expectancy or life status that are confined to the surrounding area, now an understanding of inter- and inter-religious tolerance has been gained. What is even more special is the belief that the sons and daughters of the regions have the opportunity to pursue education up to tertiary institutions to graduate postgraduate. The implementation of community service has been carried out and received a welcome and understanding of the essence of the teachings of Hinduism with direct verbal communication.

Analysis of dynamic restricted mean survival time based on pseudo-observations.

In clinical follow-up studies with a time-to-event end point, the difference in the restricted mean survival time (RMST) is a suitable substitute for the hazard ratio (HR). However, the RMST only measures the survival of patients over a period of time from the baseline and cannot reflect changes in life expectancy over time. Based on the RMST, we study the conditional restricted mean survival time (cRMST) by estimating life expectancy in the future according to the time that patients have survived, reflecting the dynamic survival status of patients during follow-up. In this paper, we introduce the estimation method of cRMST based on pseudo-observations, the statistical inference concerning the difference between two cRMSTs (cRMSTd), and the establishment of the robust dynamic prediction model using the landmark method. Simulation studies are conducted to evaluate the statistical properties of these methods. The results indicate that the estimation of the cRMST is accurate, and the dynamic RMST model has high accuracy in coefficient estimation and good predictive performance. In addition, an example of patients with chronic kidney disease who received renal transplantations is employed to illustrate that the dynamic RMST model can predict patients' expected survival times from any prediction time, considering the time-dependent covariates and time-varying effects of covariates.

Scaling-up Evidence-based Interventions for Communities of Color With Marked Health Disparities: Lessons Learned From COVID-19 Can Be Applied to Reduce Morbidity and Mortality and Achieve Health Equity.

Scaling-up Evidence-based Interventions for Communities of Color With Marked Health Disparities: Lessons Learned From COVID-19 Can Be Applied to Reduce Morbidity and Mortality and Achieve Health Equity.

Changes in contributions of age- and cause-specific mortality to the widening life expectancy gap between North and South Korea, 1990–2019: An analysis of the Global Burden of Disease Study 2019

BackgroundLife expectancy gaps between North and South Korea have increased but contributions to these gaps remain poorly understood. Using data from the Global Burden of Disease Study (GBD) 2019, we examined how much death from specific diseases contributed to these gaps in different age groups over three decades. MethodsData for death numbers and population by sex and 5-year age groups in both North and South Korea from 1990 to 2019 were extracted from the GBD 2019 to calculate life expectancy. Joinpoint regression analysis was conducted to investigate changes in life expectancy in North and South Korea. We used decomposition analysis to partition differences in life expectancy within and between the two Koreas into changes in age- and cause-specific death contributions. ResultsLife expectancy increased in two Koreas from 1990 to 2019, but North Korea experienced a marked decline in life expectancy during the mid-1990s. The life expectancy gaps between the two Koreas were greatest in 1999, with a difference of 13.3 years for males and 14.9 years for females. The main contributors to these gaps were higher under-5 mortality from nutritional deficiencies for males (4.62 years) and females (4.57 years) in North Korea, accounting for about 30% of the total gap in life expectancy. After 1999, the life expectancy gaps reduced but persisted with differences of about ten years by 2019. Notably, chronic diseases contributed to about 8 out of 10 years of life expectancy gap between the two Koreas in 2019. Differential cardiovascular disease mortality in the older groups was the main contributor to the life expectancy gap. ConclusionsThe contributors to this gap have shifted from nutritional deficiencies in children younger than five years to cardiovascular disease among elderly people. Efforts for strengthening social and healthcare systems are needed to curb this large gap.

The effect of the COVID-19 pandemic on life expectancy in 27 countries

The expected year-on-year intrinsic mortality variations/changes are largely overlooked in the existing research when estimating the effect of the COVID-19 pandemic on mortality patterns. To fill this gap, this study provides a new assessment of the loss of life expectancy caused by COVID-19 in 27 countries considering both the actual and the expected changes in life expectancy between 2019 and 2020. Life expectancy in 2020 and the expected life expectancy in the absence of COVID-19 are estimated using the Lee-Carter model and data primarily from the Human Mortality Database. The results show that life expectancy in 21 of the 27 countries was expected to increase in 2020 had COVID-19 not occurred. By considering the expected mortality changes between 2019 and 2020, the study shows that, on average, the loss of life expectancy among the 27 countries in 2020 amounted to 1.33 year (95% CI 1.29–1.37) at age 15 and 0.91 years (95% CI 0.88–0.94) at age 65. Our results suggest that if the year-on-year intrinsic variations/changes in mortality were considered, the effects of COVID-19 on mortality are more profound than previously understood. This is particularly prominent for countries experiencing greater life expectancy increase in recent years.

Declining life expectancy in the Great Lakes region: contributors to Black and white longevity change across educational attainment

BackgroundThe East North Central Census division (aka the Great Lakes region) experienced a decrease in life expectancy of 0.3 years from 2014 to 2016 – one of the largest declines across the nine Census divisions. Disadvantaged groups that typically have below-average life expectancy, including Black individuals and those without a college education, may have been disproportionately affected by this longevity shift. This investigation examines life expectancy changes among different sex, race, and education groups in the Great Lakes region, and how specific causes of death contributed to within-group longevity changes over time and across age.MethodsWe used 2008 to 2017 death counts from the National Center for Health Statistics and American Community Survey population estimates to measure within-group change in life expectancy at age 25 among non-Hispanic Black and white males and females by educational attainment. We decomposed life expectancy change over time for each subgroup by 24 causes of death and measured their contribution to longevity change across 13 age groups.ResultsAmong persons with ≤ 12 years of education, white males and females experienced 1.3- and 1.7-year longevity declines respectively, compared to a 0.6-year decline among Black males and a 0.3-year decline among Black females. Life expectancy declined among all groups with 13–15 years of education, but especially Black females, who experienced a 2.2-year loss. With the exception of Black males, all groups with 16 + years of education experienced longevity gains. Homicide contributed 0.34 years to longevity decline among Black males with ≤ 12 years of education. Drug poisoning made large contributions to longevity losses among Black females with ≤ 12 years of education (0.31 years), white males and females with 13–15 years of education (0.35 and 0.21 years, respectively), and white males and females with ≤ 12 years of education (0.92 and 0.65 years, respectively).ConclusionsPublic health efforts to reduce the risks of homicide among Black males without a college education and drug poisoning among all groups could improve life expectancy and reduce racial and educational longevity disparities in the Great Lakes region.

Changes in life expectancy and house prices in London from 2002 to 2019: hyper-resolution spatiotemporal analysis of death registration and real estate data.

London has outperformed smaller towns and rural areas in terms of life expectancy increase. Our aim was to investigate life expectancy change at very-small-area level, and its relationship with house prices and their change. We performed a hyper-resolution spatiotemporal analysis from 2002 to 2019 for 4835 London Lower-layer Super Output Areas (LSOAs). We used population and death counts in a Bayesian hierarchical model to estimate age- and sex-specific death rates for each LSOA, converted to life expectancy at birth using life table methods. We used data from the Land Registry via the real estate website Rightmove (www.rightmove.co.uk), with information on property size, type and land tenure in a hierarchical model to estimate house prices at LSOA level. We used linear regressions to summarise how much life expectancy changed in relation to the combination of house prices in 2002 and their change from 2002 to 2019. We calculated the correlation between change in price and change in sociodemographic characteristics of the resident population of LSOAs and population turnover. In 134 (2.8%) of London's LSOAs for women and 32 (0.7%) for men, life expectancy may have declined from 2002 to 2019, with a posterior probability of a decline >80% in 41 (0.8%, women) and 14 (0.3%, men) LSOAs. The life expectancy increase in other LSOAs ranged from <2 years in 537 (11.1%) LSOAs for women and 214 (4.4%) for men to >10 years in 220 (4.6%) for women and 211 (4.4%) for men. The 2.5th-97.5th-percentile life expectancy difference across LSOAs increased from 11.1 (10.7-11.5) years in 2002 to 19.1 (18.4-19.7) years for women in 2019, and from 11.6 (11.3-12.0) years to 17.2 (16.7-17.8) years for men. In the 20% (men) and 30% (women) of LSOAs where house prices had been lowest in 2002, mainly in east and outer west London, life expectancy increased only in proportion to the rise in house prices. In contrast, in the 30% (men) and 60% (women) most expensive LSOAs in 2002, life expectancy increased solely independently of price change. Except for the 20% of LSOAs that had been most expensive in 2002, LSOAs with larger house price increases experienced larger growth in their population, especially among people of working ages (30-69 years), had a larger share of households who had not lived there in 2002, and improved their rankings in education, poverty and employment. Large gains in area life expectancy in London occurred either where house prices were already high, or in areas where house prices grew the most. In the latter group, the increases in life expectancy may be driven, in part, by changing population demographics. Wellcome Trust; UKRI (MRC); Imperial College London; National Institutes of Health Research.

Decrease in Mexico's life expectancy due to multiple homicides: the murder of women adjacent to the homicide of one or more men

The objective is to analyze the effect of multiple homicides on male and female life expectancy and to provide empirical evidence of the temporal and spatial associations between male and female homicide rates by age group during the period 2002-2020. Using data from the National Institute of Statistics and Geography (INEGI) and population projections from the National Population Council (CONAPO), mortality rates due to homicide from 2002-2020 were estimated for both men and women, and the adjacency of homicides of men and women was analyzed, along with the spatial proximity between multiple homicides of men and women, along with changes in life expectancy due to homicide. Individual homicides have caused the greatest decrease in life expectancy for both men and women. The negative impact of multiple homicides on both female and male life expectancy began to draw attention in 2008. By analyzing the murders of women adjacent to the homicides of one or more men questions are raised about whether these crimes are primarily the result of criminal violence, and to a lesser extent the role of gender.