Disparities In Life Expectancy Research Articles

Trends in Prevalence, Treatment, and Control of Hypertension According to 40-Year-Old Life Expectancy at Prefectures in Japan from the National Health and Nutrition Surveys.

The prevalence of hypertension has been decreasing in Japan due to improved medical treatment and a decrease in dietary salt intake. However, disparities in the prevalence, treatment, and control of hypertension are expected to occur in different regions. This study aimed to investigate the trends in the prevalence, treatment, and control of hypertension at the prefectural level of life expectancy among Japanese population. We used data from the National Health and Nutrition Survey and analysed the individual survey information of individuals aged 40–69 years by dividing it into six terms, i.e., 1995–1997, 1999–2001, 2003–2005, 2007–2009, 2012, and 2016. Prefectures were classified into four groups according to their 40-year-old life expectancy in 2000. Outcome values were standardised to the population by 10-year age groups in 2010, and they were tested by two-way analysis of variance according to six terms and life expectancies. The prevalence of hypertension tended to decrease, especially among women, whereas the treatment and control tended to improve from the first to the sixth period in both men and women. The prevalence and treatment of hypertension in men with longer life expectancy tended to be lower than that in other groups, and there was no obvious difference in the control. In women, there were no obvious differences in the prevalence, treatment, or control. Reducing the prevalence of hypertension by improving lifestyle factors, such as high salt intake in each prefecture with a relatively short life expectancy, may be important to resolve the disparity in life expectancy among prefectures.

Bridging the Urban-Rural Divide in Chronic Disease Through Community Engagement in Health Program Delivery.

The urban-rural divide in chronic disease contributes to persistent geographic disparities in life expectancy in North Carolina. Policies and programs in resource-constrained rural areas should be designed to increase health equity and reduce this continuing divide by including greater community engagement and decision-making for meaningful, sustainable change.

Abstract 052: Social Determinants Of Health And Uncontrolled Blood Pressure In A National Cohort Of Black And White US Adults

Background: Hypertension and uncontrolled blood pressure (BP) are the largest contributors to racial disparities in life expectancy. Determining the contribution of social determinants of health (SDOH) to racial differences in uncontrolled BP could help identify ways to achieve the American Heart Association’s 2030 impact goal of equitably improving healthy life expectancy. Methods: We analyzed data from 7,497 Black and 7,306 White US adults taking antihypertensive medication from the REasons for Geographic and Racial Differences in Stroke study to determine the association between SDOH and uncontrolled BP. SDOH were defined using the Healthy People 2030 domains of education, economic stability, social context, neighborhood environment and healthcare access. Uncontrolled BP was defined as systolic BP ≥130 mm Hg or diastolic BP ≥80 mm Hg. Results: Among participants taking antihypertensive medication (mean age 66.3 years, 50.7% Black, 57.1% female), 68.0% of Black and 59.0% of White participants had uncontrolled BP. After multivariable adjustment, uncontrolled BP (prevalence ratio; 95% CI) was more common among those with less than a high school education (1.06; 1.02 – 1.09), annual household income <$20,000 (1.12; 1.06 – 1.18) and $20,000 to <$35,000 (1.09; 1.04 – 1.15) versus ≥$75,000; without health insurance (1.08; 1.03 – 1.14) and residing in a disadvantaged neighborhood (1.04; 1.01 – 1.07), a zip code with high poverty (1.03; 1.00 – 1.07) or a health professional shortage area (1.07; 1.05 – 1.10). For each SDOH, the proportion of participants with uncontrolled BP was higher among Black compared with White adults. After multivariable adjustment, having a higher number of adverse SDOH was associated with a higher prevalence of uncontrolled BP among both Black and White adults (Table). Conclusion: SDOH were associated with uncontrolled BP among both Black and White adults taking antihypertensive medication.

Why we should monitor disparities in old-age mortality with the modal age at death.

Indicators based a fixed “old” age threshold have been widely used for assessing socioeconomic disparities in mortality at older ages. Interpretation of long-term trends and determinants of these indicators is challenging because mortality above a fixed age that in the past would have reflected old age deaths is today mixing premature and old-age mortality. We propose the modal (i.e., most frequent) age at death, M, an indicator increasingly recognized in aging research, but which has been infrequently used for monitoring mortality disparities at older ages. We use mortality and population exposure data by occupational class over the 1971-2017 period from Finnish register data. The modal age and life expectancy indicators are estimated from mortality rates smoothed with penalized B-splines. Over the 1971-2017 period, occupational class disparities in life expectancy at 65 and 75 widened while disparities in M remained relatively stable. The proportion of the group surviving to the modal age was constant across time and occupational class. In contrast, the proportion surviving to age 65 and 75 has roughly doubled since 1971 and showed strong occupational class differences. Increasing socioeconomic disparities in mortality based on fixed old age thresholds may be a feature of changing selection dynamics in a context of overall declining mortality. Unlike life expectancy at a selected fixed old age, M compares individuals with similar survival chances over time and across occupational classes. This property makes trends and differentials in M easier to interpret in countries where old-age survival has improved significantly.

Characteristics of Indigenous and Non-Indigenous Australians Requiring Urgent Percutaneous Coronary Intervention at a Regional Hospital

In Australia, ischaemic heart disease accounts for a significant portion of disparity in life expectancy between the Indigenous and non-Indigenous population. We aimed to assess differences in patient characteristics between Indigenous and non-Indigenous Australians undergoing urgent percutaneous coronary intervention (PCI) in a regional hospital setting.

Role of Disease-Specific Incidence and Survival in Disparities in Life Expectancy in the United States

There are persisting geographic and racial disparities in life expectancy (LE) across the United States (US). We used 5% Medicare Claims data (2000-2017) to investigate how disease incidence and survival contribute to such disparities. Disease-specific hazard ratios (HRs) were calculated for Medicare beneficiaries living in the US states with the lowest LE (the states with the highest LE were used as a reference group), in gender- and race-/ethnicity-specific populations. Analysis of incidence showed that the greatest contribution to between-the-state disparities in LE was due to higher incidence (HRs≥1.30) of atherosclerosis, heart failure, influenza/pneumonia, Alzheimer’s disease, and lung cancer among older adults living in the states with the lowest LE. The list of diseases that contributed most to LE through the differences in their survival substantially differed from the above listed diseases: namely, diabetes, chronic ischemic heart disease, and cerebrovascular disease had HRs≥1.28 for their respective survival rates, with the highest HRs for lung cancer (HR=1.37, in females) and prostate cancer (HR=1.30). Respective race-/ethnicity-specific patterns of incidence and survival HRs were investigated and diseases contributed most to racial disparities in LE were identified. Study showed that when planning the strategies targeting between-the-state differences in LE in the US, it is important to address both 1) primary and secondary prevention for diseases demonstrating substantial differences in contributions of incidence, and 2) treatment choice, adherence to treatment, and comorbidities for diseases contributing to LE disparities predominantly through the differences in survival. Such strategies can be disease-, race-/ethnicity-, and geographic area-specific.

Disparities in Disease-Specific Remaining Life Expectancy Among Medicare Beneficiaries in the United States

Racial and geographic disparities in life expectancy (LE) in the US are a persistent problem. We used 5% Medicare Claims for 2000-2017 to investigate the patterns of remaining LE (RLE) in the U.S. with the highest and the lowest LE. RLEs in race-/ethnicity specific populations aged 65+ were calculated in patients with specific diseases and in the total population using the area under the Kaplan-Meier estimator. The Cox model was used to investigate the effect of state-specific residence on total LE and RLE. Between-the-states differences in RLE were most pronounced for cerebrovascular disease, atherosclerotic heart disease, breast and prostate cancer. RLE was the lowest for lung cancer and sepsis, followed by Alzheimer’s disease, dementia, pneumonia, and heart failure. RLE for myocardial infarction and cerebrovascular disease decreased over time, while for renal failure, diabetes, atherosclerotic heart disease, and cancers of breast and prostate RLE increased.

From convergence to divergence: Lifespan variation in US states, 1959–2017

BackgroundLarge disparities in life expectancy exist across US states and the gaps have been widening in recent decades. Less is known about the lifespan variability – a measure that can provide important insights into mortality inequalities both between and within states. MethodUsing yearly lifetables from the United States Mortality Database, we explore geographic and temporal patterns in lifespan variation (unconditional and conditional on survival to age 10, 35 and 65) across US states between 1959 and 2017. We also examine the contribution of state differences in life expectancy to overall lifespan variation using standard decomposition techniques. ResultsDespite overall convergence in lifespan variation across states over the last six decades, in more recent years there has been notable divergence. Gender-specific analyses show that lifespan variation was generally greater among males than among females; but this pattern reverses for mortality past age 65. Much of the state disparities in lifespan variation, unconditional and conditional on survival to age 10 and 35, were due to mortality differences under the age 65. Decomposition analysis shows that while within-state variability remains the primary driver of overall lifespan variation, the contribution of cross-state differences in life expectancy is growing. ConclusionsVariation in longevity is greater within US States than between them, yet cross-states disparities in mortality are increasing. This likely reflects the long-term consequences of rising social, economic, and political stratification for health inequalities both within and across states.

Inequality in Life Expectancy-Acceleration due to COVID-19

The study of inequality in life expectancy by socio-economic groups has been receiving more and more attention with the rise in inequality. The present study investigates the prevailing situation in Bangladesh by using the age-specific mortality data available from various sources like the Sample Vital Registration System(SVRS) of the BBS and the Bangladesh Maternal Mortality Survey. The BBS, however, has been presenting a life table by sex, and there is a disparity in life expectancy in favour of females presently by three years. Rural life expectancy was lower in Bangladesh from 1981-to 2014, after which it exhibited that the difference in rural and urban life expectancy is being narrowed down. In India, the life expectancy at birth is slightly more than one year higher in urban areas than in rural areas. Life expectancy at birth was computed for seven regions (administrative divisions) using the age-specific mortality rates given in SVRS reports. For the year 2016, the highest value of life expectancy at birth (73.9 years) was found for the Rajshahi division, followed by Khulna division(73.5 years), Rangpur(73.0 years), Barisal(72.8 years), Sylhet(72.6 years) and the lowest for Chattogram division(72.1 years). We also compared the life expectancy and Household average income of the administrative divisions as obtained in the HIES 2016. No systematic relationship between household income and life expectancy was observed. Analysing the mortality of BMMCHS between 2010 and 2016, the life expectancy increased with the increase in wealth quintile for both males and females. The difference in life expectancy between the richest and poorest quintile of the male was 3.37 years, and for females, it was 1.34 years. But the much higher difference in life expectancy at birth between the richest and poorest quintile has been observed in other countries like India, the United Kingdom, the United States and Norway.

Social Determinants of Health and Health Inequality in South Korea

Purpose: Recognizing the social factors behind population health and health equity, the present study examines the role of locality in regional health and assesses the its contribution to local health inequality at municipality level in South Korea. Research design, data, and methodology: The present study investigates the association between a vector of municipal socioeconomic characteristics and population health, taking into account possible unobservable geographical fixed effects at metropolitan/province level, and quantifies the contribution of sources of inter-municipality health inequality by decomposing the disparity in life expectancy across municipalities. For empirical analysis, it draws upon life expectancy data at municipal level in South Korea estimated by The Korean Society for Equity in Health in 2018 and data obtained from various souces such as National Health Insurance Service (NHIS), Annual Local Tax Statistical Report of Ministry of the Interior and Safety (MOIS), National Election Commission (NEC) and Korea Statistical Information Service (KOSIS). Results: This study provides the empirical evidence to the importance of social determinants on local population health and health inequality within and between municipalities. Taking life expectancy as a proxy of municipal population health, we finds the different role of social determinants on local health and health inequality between the highest and the lowest income group within a municipality. While some variables (eg. income inequality among municipal population), for instance, are associated with both life expectancy and its gap, many of other factors such as municipal income level and the degree of financial self-reliance are not prone to life expectancy but the disparity of life expectancy in the context of population health. Implications: The study highlights three findings; (1) level of local autonomy contributed in reducing life expectancy gap across municipality; (2) Geography is closely associated with health inequality across municipalities. Approximately 40 % of inequality stem from non-residence in Seoul metropolitan area; (3) Given the universal population coverage of the national health insurance service, a positive association between the local health related resources and health disparity among municipal population might imply a discrepancy in the level of treatment of diseases. This may result from different household financial capacity and an unequal access to private health insurance.

Neighborhood deprivation and epigenetic aging

BACKGROUND AND AIM: Recent research suggests widening socioeconomic disparities in life expectancy in the United States. Both individual-level and small-area socioeconomic status factors, such as living in a socioeconomically disadvantaged neighborhood, are independently associated with early onset of age-related disease, reduced life expectancy and all-cause mortality. Neighborhood deprivation may increase the risk of early onset of age-related disease, reduced life expectancy, and all-cause mortality. Mechanisms linking neighborhood deprivation and age-related disease are multifactorial and complex. Residence in a deprived neighborhood can lead to poor health behaviors, increased toxicant exposures, lack of access to health services, and low social cohesion. Living in a deprived neighborhood can also lead to chronic stress and induce biological weathering on endocrine and inflammatory systems. METHODS: Emerging evidence suggests epigenetics may be implicated in biological mechanisms underpinning this relationship. DNA methylation is the most well-understood epigenetic factor and involves the addition of a methyl group to DNA, typically at the 5-carbon of cytosine at cytosine-guanine (CpG) dinucleotides. Recently developed ‘epigenetic clocks’ are a class of biological age predictors that use DNA methylation at predetermined CpG sites to measure biological variation among those with the same chronologic age. These clocks are better at predicting chronologic age than other markers including telomere length and may be a more sensitive measure of biologic aging. RESULTS:This presentation will focus on recent findings of the association between neighborhood deprivation and epigenetic measures of age acceleration from the Sister Study, a prospective breast cancer cohort study. CONCLUSIONS:Findings from this study suggest that residing in a neighborhood with higher deprivation is associated with methylation-based markers of aging. African American/Black women in the U.S. may be more likely to live in disadvantaged neighborhoods. Planned research focused on methylation patterns in African American/Black individuals will allow researchers to evaluate how neighborhood disadvantage and methylation changes contribute to health disparities. KEYWORDS: ‘Advancing racial health equity through studies of the environment and epigenetic aging’, neighborhood environment, epigenetics, aging

Borders, Immigrants, And Health.

There are roughly 45million immigrants living in the United States. People from Mexico account for 25% of all US immigrants, although the demography of the immigrant population continues to change. Migration patterns along the US southern border are especially dynamic. Immigration and other policies affect the health of people on both sides of the US-Mexico border. Many factors, including citizenship status, geographic location, and language, influence immigrant health and contribute to disparities in life expectancy, health care access, and participation in safety-net programs.

Life Expectancy At The US-Mexico Border: Evidence Of Disparities By Place, Race, And Ethnicity.

The mortality experience for the cluster of US counties in the US-Mexico border region has not been well described. We calculated 2016-18 life expectancy for the border region (counties within 100 kilometers of the border), making key comparisons to the US overall and to nonborder counties in border states. Life expectancy from birth for the border region was 81.1 years, which was greater than for the US and for the nonborder counties of border states. However, the disparity in life expectancy between racial/ethnic subgroups in the border region was also greater, within a range of more than thirteen years. Although White, Black, and Asian residents of the border region could expect to live significantly longer than residents of the US and nonborder counties of border states, Hispanic and American Indian residents could not. Understanding the mortality experience via life expectancy can help public health professionals and leaders prioritize efforts to ensure that all border residents have an equal opportunity to live a long, healthy life.

Rural-urban differences in stroke risk

Rural-urban health disparities in life expectancy are large and increasing, with the rural-urban disparity stroke mortality serving as a potential contributor. Data from Vital Statistics shows an unexplained temporal pattern in the rural-urban disparity in stroke-specific mortality, with the magnitude of the disparity increasing from 15% to 25% between 1999 and 2010, but subsequently decreasing to 8% by 2019. This recent decrease in the magnitude of the rural-urban disparity in stroke mortality appears to be driven by a previously unreported plateauing of stroke mortality in urban areas and a continued decline of stroke mortality in rural areas. There is a need to better understand the contributors to these temporal changes; however, a general lack of temporal data on potential contributors prevents this investigation. However considering contributors to the rural-urban differences pooled across time, an overall a higher stroke incidence in rural areas appears to be a contributor to the higher rural stroke mortality, with this higher incidence potentially associated with a higher prevalence of stroke risk factors in rural areas. Conversely, studies assessing rural-urban disparities in stroke case fatality show smaller and inconsistent associations. To the extent that disparities in case fatality do exist, there are many studies showing rural-urban disparities in stroke care could be contributing. While these data offer insights to the overall rural-urban disparities in stroke mortality, additional data are needed to help understand temporal changes in the magnitude of the rural-urban stroke mortality disparity.

Physical health monitoring of patients prescribed depot antipsychotic medication in north west Edinburgh community mental health team

AimsTo monitor the quality of physical health monitoring of patients prescribed depot antipsychotic medication in the North West Edinburgh Community Mental Health Team (CMHT). We also evaluated the completeness of prescriptions and Mental Health Act (Scotland) (Act) 2003 paperwork where relevant.BackgroundAntipsychotic medications are medicines for treating conditions such as Schizophrenia, but some may be associated with an increased risk of Metabolic Syndrome. Moreover, evidence indicates that patients with major mental disorder have a reduced life expectancy in comparison to those without such diagnoses. These two factors illustrate the importance of the physical health of this patient cohort being monitored on a regular basis. This project will evaluate how a local CMHT is performing, with the possibility of enacting service improvements if required.MethodThe records of the 60 patients prescribed depot antipsychotic medication administered by this CMHT were reviewed. A check-list was created consisting of 14 categories analysing the quality of physical health monitoring, as well as compliance with prescription standards and, where relevant, Mental Health Act (Scotland) (Act) 2003 paperwork. We compared patient records against our checklist for the calendar year of 2019. The Scottish Intercollegiate Guidelines Network (SIGN) 131 (Management of Schizophrenia) section 5.2 was used as the gold standard for physical health monitoring against which the data we collected was compared.ResultWe identified a wide range of flaws with the current system and implementation of monitoring, and difficulty in locating the required information. There was no consistent monitoring of physical observations on electronic record, nor an accepted alternative way in which this was documented. Furthermore, blood tests were not consistently obtained either by the service or GP practices in a reproducible manner. This led to discussions within the CMHT regarding creation of a new pathway for the monitoring of this patient cohort using a Quality Improvement model, with the ultimate goal to establish a regular physical health clinic.ConclusionThere is significant evidence that patients with major mental disorder do not access healthcare as consistently as those without, leading to a disparity in life expectancy. In light of the fact that antipsychotic medications can be associated with Metabolic Syndrome, we have an even greater responsibility to tackle this marked health inequality by appropriately monitoring our patients. This was not done well in this particular CMHT, but this project will lead to improvements in the service and ultimately patient care.

Estimated life expectancy gains with antiretroviral therapy among adults with HIV in Latin America and the Caribbean: a multisite retrospective cohort study

There are few data on life expectancy gains among people living with HIV in low-income and middle-income settings where antiretroviral therapy (ART) is increasingly available. We aimed to analyse life expectancy trends from 2003 to 2017 among people with HIV beginning treatment with ART within the Caribbean, central America, and South America. We did a multisite retrospective cohort study and included people with HIV who had started treatment with ART and were aged 16 years or older between Jan 1, 2003, and Dec 31, 2017, from Caribbean, Central and South America network for HIV epidemiology (CCASAnet) sites in Argentina, Brazil, Chile, Haiti, Honduras, Mexico, and Peru, who contributed person-time data from the age of 20 years until date of death, last contact, database closure, or Dec 31, 2017. We used the Chiang method of abridged life tables to estimate life expectancy at age 20 years for three eras (2003-08, 2009-12, and 2013-17) overall and by demographic and clinical characteristics at ART initiation. We used Poisson regression models to weight mortality rates to account for informative censoring. 30 688 people with HIV were included in the study; 17 491 (57·0%) were from the Haiti site and 13 197 (43·0%) were from all other sites. There were 2637 deaths during the study period: 1470 in Haiti and 1167 in other sites. Crude and weighted mortality rates decreased among all age groups over calendar eras. From 2003-08 to 2013-17, overall life expectancy for people with HIV at age 20 years increased from 13·9 years (95% CI 12·5-15·2) to 61·2 years (59·0-63·4) in Haiti and from 31·0 years (29·3-32·8) to 69·5 years (67·2-71·8) in other sites. Life expectancies at the end of the study period were within 10 years of those of the general population (69·9 years in Haiti and 78·0 years in all other sites in 2018). Disparities in life expectancy among people with HIV by sex or HIV transmission risk factor, CD4 cell count, level of education, and history of tuberculosis at or before ART initiation persisted across calendar eras. Life expectancy among people with HIV receiving ART has significantly improved in Latin America and the Caribbean. Persistent disparities in life expectancy among people with HIV by demographic and clinical factors at ART initiation highlight vulnerable populations in the region. National Institutes of Health. For the Spanish translation of the abstract see Supplementary Materials section.

Greenness and education inequalities in life expectancy in Latin American cities: an ecological study

BackgroundGreenness has been found to be associated with reduced mortality and morbidity and improved wellbeing, with recent evidence further linking it to narrower health inequalities. However, results come mostly from high-income countries and thus might not be generalisable to other settings. In this preliminary analysis, we address this gap by examining whether education inequalities in life expectancy in Latin American cities vary by area-level greenness. MethodsWe used data from the Salud Urbana en America Latina (SALURBAL) study. The analysis sample included 28 large cities in nine Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico, Panama, and El Salvador), comprising 671 sub-city units (>10 per city), for the period 2012–16. We used sub-city data on life expectancy, education (percentage of residents with high school or university education, as an indicator for socioeconomic status), and greenness (as calculated by the satellite image-derived normalised difference vegetation index). We used multilevel linear models of sub-cities nested within cities, with country fixed effects to predict life expectancy by education, greenness, and their interaction, while accounting for covariates at the city and sub-city levels. FindingsHigher education was associated with higher life expectancy in both sexes (men: standardised regression coefficient b=0·51 [95% CI 0·36–0·65]; women: 0·34 [0·23–0·45]), whereas increased area-level greenness was associated with higher life expectancy among men (0·39 [0·03–0·75]). The educational gradient in life expectancy was steeper in greener areas for both sexes (men: b for interaction=0·20 [0·08–0·32]; women: 0·15 [0·05–0·24]). InterpretationContrary to evidence from high-income countries, our initial results from Latin America suggest education disparities in life expectancy might increase with greater levels of green space. Given the already wide intra-urban inequalities in Latin American cities, and the sparse and unequal distribution of urban green spaces, greening policies need to make a concerted effort to ensure that unequal access to green spaces does not exacerbate existing health inequalities. FundingWellcome Trust (205177/Z/16/Z).

Assessing mortality inequality in the U.S.: What can be said about the future?

This paper investigates mortality inequality across U.S. states by modeling and forecasting mortality rates via a forecast reconciliation approach. Understanding the heterogeneity in state-level mortality experience is of fundamental importance, as it can assist decision making for policymakers, health authorities, as well as local communities who are seeking to reduce inequalities and disparities in life expectancy. A key challenge of multi-population mortality modeling is high dimensionality, and the resulting complex dependence structures across sub-populations. Moreover, when projecting future mortality rates, it is important to ensure that the state-level forecasts are coherent with the national-level forecasts. We address these issues by first obtaining independent state-level forecasts based on classical stochastic mortality models, and then incorporating the dependence structure in the forecast reconciliation process. Both traditional bottom-up reconciliation and the cutting-edge trace minimization reconciliation methods are considered. Based on the U.S. total mortality data for the period 1969–2017, we project the 10-year-ahead mortality rates at both national-level and state-level up to 2027. We find that the geographical inequality in the longevity levels is likely to continue in the future, and the mortality improvement rates will tend to slow down in the coming decades.

Linking Data on Constituent Health with Elected Officials' Opinions: Associations Between Urban Health Disparities and Mayoral Officials' Beliefs About Health Disparities in Their Cities.

A substantive body of research has explored what factors influence elected officials' opinions about health issues. However, no studies have assessed the potential influence of the health of an elected official's constituents. We assessed whether the magnitude of income-based life expectancy disparity within a city was associated with the opinions of that city's mayoral official (i.e., mayor or deputy mayor) about health disparities in their city. The independent variable was the magnitude of income-based life expectancy disparity in US cities. The magnitude was determined by linking 2010-2015 estimates of life expectancy and median household income for 8,434 census tracts in 224 cities. The dependent variables were mayoral officials' opinions from a 2016 survey about the existence and fairness of health disparities in their city (n = 224, response rate 30.3%). Multivariable logistic regression was used to adjust for characteristics of mayoral officials (e.g., ideology) and city characteristics. In cities in the highest income-based life expectancy disparity quartile, 50.0% of mayoral officials "strongly agreed" that health disparities existed and 52.7% believed health disparities were "very unfair." In comparison, among mayoral officials in cities in the lowest disparity quartile 33.9% "strongly agreed" that health disparities existed and 22.2% believed the disparities were "very unfair." A 1-year-larger income-based life expectancy disparity in a city was associated with 25% higher odds that the city's mayoral official would "strongly agree" that health disparities existed (odds ratio [OR] = 1.25; P = .04) and twice the odds that the city's mayoral official would believe that such disparities were "very unfair" (OR = 2.24; P <.001). Mayoral officials' opinions about health disparities in their jurisdictions are generally aligned with, and potentially influenced by, information about the magnitude of income-based life expectancy disparities among their constituents.

The changing trend of life expectancy for the Chinese elderly and its rural–urban disparity

Using data from Population Censuses, 1% National Population Sample Surveys of China and the Human Mortality Database, this article adopts robust percentile-based methods to analyze the changing trend of life expectancy of the Chinese elderly especially the young–old and rural–urban disparity from 1989 to 2015, and attempt to explain the disadvantage of old-age mortality improvement in China compared to developed countries. We find that life expectancy at age 65 in China has increased continuously in recent decades, but at a lower speed than in developed countries, leading to a widening gap between China and developed countries, and the increase in e65 has not shown a clear catch-up trend that has been observed in the life expectancy at birth. Similar patterns are found when we explore the rural–urban disparity of China. Based on the age-at-death distribution, we find that the old-age deaths in rural areas are more concentrated at relatively younger ages compared to urban areas due to the higher death risks and slower improvement in mortality of the young–old in rural China. Our findings describe the age-patterns underlying the rural–urban disparity in life expectancy of the elderly within China, and also the main reason for the slower improvement of life expectancy among the Chinese elderly compared with those in developed countries. Survival improvement of the young–old and equalization of available health services are key to reducing the rural–urban bias and achieving accelerated increase in life expectancy among the elderly in China.