Health-adjusted Life Expectancy Research Articles

Living longer but in poor health: healthcare system responses to ageing populations in industrialised countries based on the Findings from the Global Burden of Disease Study 2019

ObjectivesThis study aimed to examine changes in life expectancy (LE), health-adjusted life expectancy (HALE), unhealthy years of life, and disease burden of older people in industrialised countries and associations with health systems.MethodsWe used estimates of LE and HALE, unhealthy years of life, years of life loss (YLL), years lived with disability (YLD) for individuals aged 70 years and over in 33 industrialised countries from 1990 to 2019 from the Global Burden of Disease Study 2019. A linear regression analysis was conducted to examine the association of health outcomes with the Healthcare Access and Quality (HAQ) index.ResultsLE and HALE increased with improved HAQ index from 1990 to 2019. However, the number of unhealthy years of life increased. An increased HAQ index was associated with decreases in YLL. However, changes in YLD were relatively small and were not correlated with HAQ index.ConclusionsThe healthcare system needs to more address the increased morbidity burden among older people. It should be designed to handle to healthcare needs of the ageing population.

Trends of Gaps Between Health-Adjusted Life Expectancy and Life Expectancy at the Regional Level in Korea Using a Group-Based Multi-Trajectory Modeling Approach (2008-2019).

Health-adjusted life expectancy (HALE) is an indicator of the average lifespan in good health. Through this study, we aimed to identify regional disparities in the gap between HALE and life expectancy, considering the trends that have changed over time in Korea. We employed a group-based multi-trajectory modeling approach to capture trends in the gap between HALE and life expectancy at the regional level from 2008 to 2019. HALE was calculated using incidence-based "years lived with disability." This methodology was also employed in the Korean National Burden of Disease Study. Based on five different information criteria, the most fitted number of trajectory groups was seven, with at least 11 regions in each group. Among the seven groups, one had an exceptionally large gap between HALE and life expectancy compared to that of the others. This group was assigned to 17 regions, of which six were metropolitan cities. Based on the results of this study, we identified regions in which health levels have deteriorated over time, particularly within specific areas of metropolitan cities. These findings can be used to design comprehensive policy interventions for community health promotion and urban regeneration projects in the future.

Gender-Specific Health-Adjusted Life Expectancy of Type 2 Diabetes Mellitus Among the Rural Elderly Population.

Objectives: This study aimed to estimate the life expectancy (LE) and health-adjusted life expectancy (HALE) of type 2 diabetes mellitus (T2DM) among the rural elderly population. Methods: A total of 10,318 participants aged 65 to 79 were derived from the Henan Rural Cohort. The LE and HALE were calculated via the Sullivan method and multistate life table. Results: Among 10,318 subjects, 1,325 suffered from T2DM at the baseline, and 394 participants had newly-developed T2DM. The results from the Sullivan method showed that the LE, HALE, and HALE/LE were 17.98, 16.18years, and 89.95% for men aged 65 to 69, and the corresponding estimates for women were 21.81, 18.73years, and 85.86%, respectively. The LE, HALE and HALE/LE calculated via multistate life table were 19.86, 17.53years, and 88.29% for men at aged 65, and the corresponding values for women were 25.01, 20.87years, and 83.44%, respectively. Conclusion: Rural elderly women have a longer LE and HALE of T2DM, but they have lower quality of life than men. More attention should be paid to T2DM among rural elderly people, especially in women. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Distributionally sensitive measurement and valuation of population health

We introduce a measure of population health that is sensitive to inequality in both age-specific health and lifespan and can be calculated from a health-extended period life table. By allowing for inequality aversion, the measure generalises health-adjusted life expectancy without requiring more data. A transformation of change in the (life-years) measure gives a distributionally sensitive monetary valuation of change in population health and disease burden. Application to Sub-Saharan Africa between 1990 and 2019 reveals that the change in population health is sensitive to allowing for lifespan inequality but is less sensitive to age-specific health inequality. Allowing for distributional sensitivity changes relative burdens of diseases, reduces convergence between the burdens of communicable and non-communicable diseases, and so could influence disease prioritisation. It increases the value of health improvements relative to GDP.

Divergences and gaps in life expectancy and health-adjusted life expectancy in Mexico: Contribution analysis of the Global Burden of Disease Study 2019

Introduction Life expectancy (LE) and Health-adjusted life expectancy (HALE) are summary indicators that reflect a population’s general life conditions and measure inequities in health outcomes. The objective of this study was to identify the differences in LE and HALE by sex, age group, and state in Mexico from 1990 to 2019. Also, to evaluate whether the changes in HALE are related to sociodemographic indicators and indicators of access to and quality of health services. Methods A secondary analysis was performed based on the Global Burden of Disease, Injuries, and Risk Factors Study (GBD). Data were obtained for LE (by sex and state) and HALE (by sex, age group, and state) for the years 1990, 2010, and 2019. The correlations between HALE with the Socio-Demographic Index (SDI) and with the Healthcare Access and Quality (HAQ) Index were estimated for 1990 and 2019 (by total population and sex). Results LE and HALE had an absolute increase of 6.7% and 6.4% from 1990 to 2019, mainly among women, although they spent more years in poor health (11.8 years) than men. The patterns of LE and HALE were heterogeneous and divergent by state. In 2019, the difference in HALE (for both sex) between the states with the highest (Hidalgo) and the lowest (Chiapas) value was 4.6 years. Conclusions Progress in LE and HALE has slowed in recent years; HALE has even had setbacks in some states. Gaps between men and women, as well as between states, are persistent. Public and population policymaking should seek to lengthen LE and focus on ensuring that such years are spent in good health and with good quality of life.

The estimated health impact of alcohol interventions in New Zealand: A modelling study.

To estimate the health impacts of key modelled alcohol interventions among Māori (indigenous peoples) and non-Māori in New Zealand (NZ). Multi-stage life-table intervention modelling study. We modelled two scenarios: (1) business-as-usual (BAU); and (2) an intervention package scenario that included a 50% alcohol tax increase, outlet density reduction from 63 to five outlets per 100 000 people, outlet hours reduction from 112 to 50 per week and a complete ban on all forms of alcohol marketing. The model's population replicates the 2018 NZ population by ethnicity (Māori/non-Māori), age and sex. Alcohol consumption was estimated using nationally representative survey data combined with sales data and corrected for tourist and unrecorded consumption. Disease incidence, prevalence and mortality were calculated using Ministry of Health data. We used dose-response relationships between alcohol and illness from the 2016 Global Burden of Disease study and calculated disability rates for each illness. Changes in consumption were based on the following effect sizes: total intervention package [-30.3%, standard deviation (SD) = 0.02); tax (-7.60%, SD = 0.01); outlet density (-8.64%, SD = 0.01); outlet hours (-9.24%, SD = 0.01); and marketing (-8.98%, SD = 0.02). We measured health gain using health-adjusted life years (HALYs) and life expectancy. Compared with the BAU scenario, the total alcohol intervention package resulted in 726 000 [95% uncertainty interval (UI) = 492 000-913 000] HALYs gained during the life-time of the modelled population. Māori experienced greater HALY gains compared with non-Māori (0.21, 95% UI = 0.14-0.26 and 0.16, 95% UI = 0.11-0.20, respectively). When modelled individually, each alcohol intervention within the intervention package produced similar health gains (~200 000 HALYs per intervention) owing to the similar effect sizes. Modelled interventions for increased alcohol tax, reduced availability of alcohol and a ban on alcohol marketing among Māori and non-Māori in New Zealand (NZ) suggest substantial population-wide health gains and reduced health inequities between Māori and non-Māori.

The socioeconomic distribution of life expectancy and healthy life expectancy in Chile

BackgroundLife expectancy (LE) has usually been used as a metric to monitor population health. In the last few years, metrics such as Quality-Adjusted-Life-Expectancy (QALE) and Health-Adjusted-Life- Expectancy (HALE) have gained popularity in health research, given their capacity to capture health related quality of life, providing a more comprehensive approach to the health concept. We aimed to estimate the distribution of the LE, QALEs and HALEs across Socioeconomic Status in the Chilean population.MethodsBased on life tables constructed using Chiang II´s method, we estimated the LE of the population in Chile by age strata. Probabilities of dying were estimated from mortality data obtained from national registries. Then, life tables were stratified into five socioeconomic quintiles, based on age-adjusted years of education (pre-school, early years to year 1, primary level, secondary level, technical or university). Quality weights (utilities) were estimated for age strata and SES, using the National Health Survey (ENS 2017). Utilities were calculated using the EQ-5D data of the ENS 2017 and the validated value set for Chile. We applied Sullivan´s method to adjust years lived and convert them into QALEs and HALEs.ResultsLE at birth for Chile was estimated in 80.4 years, which is consistent with demographic national data. QALE and HALE at birth were 69.8 and 62.4 respectively. Men are expected to live 6.1% less than women. However, this trend is reversed when looking at QALEs and HALEs, indicating the concentration of higher morbidity in women compared to men. The distribution of all these metrics across SES showed a clear gradient in favour of a better-off population-based on education quintiles. The absolute and relative gaps between the lowest and highest quintile were 15.24 years and 1.21 for LE; 18.57 HALYs and 1.38 for HALEs; and 21.92 QALYs and 1.41 for QALEs. More pronounced gradients and higher gaps were observed at younger age intervals.ConclusionThe distribution of LE, QALE and HALEs in Chile shows a clear gradient favouring better-off populations that decreases over people´s lives. Differences in LE favouring women contrast with differences in HALEs and QALEs which favour men, suggesting the need of implementing gender-focused policies to address the case-mix complexity. The magnitude of inequalities is greater than in other high-income countries and can be explained by structural social inequalities and inequalities in access to healthcare.

Estimation of the population, death, and quality of life in Shaanxi Province, western China: a cross-sectional study.

Measuring the health of the population is of great significance to the development of a region. We aimed to estimate the population, probability of death, and quality of life in western China. We calculated the age-specific mortality rate and prevalence rate of diseases and injuries using the Full Population Database and the Home Page of Inpatient Medical Record. We used multiple interpolation methods to insert missing information from the death data and the model of Kannisto to adjust the mortality rate for elderly individuals. The age-specific prevalence rate of diseases and injuries was adjusted according to the standard ratio of age and methods of equal proportional allocation. Life expectancy was calculated by a life table, and the quality of life was estimated using the Sullivan method. The total population continued to increase in 2015 to 2019 in the Shaanxi Province, China. The mortality rate of children under five has improved, and the mortality rate of people over 65 is decreasing year by year. Life expectancy increased from 74.66 years in 2015 to 77.19 years in 2019. Even with the total risk of disease and injury, the health-adjusted life expectancy increased by 1.90 years within 5 years, and the number of unhealthy years significantly improved. Health-adjusted life expectancy increased by 1.75 years when only considered the ten major disease systems (tumors; endocrinology, nutrition and metabolism; mental and behavioral disorders; nervous system; sensory diseases; circulatory system; respiratory system; digestive system; genitourinary system; musculoskeletal system and connective tissue), and the number of unhealthy years increased slightly. In the past five years, Shaanxi Province has made progress in improving life expectancy and controlling the development of chronic diseases. It is necessary to take specific preventive measures and improve the quality of basic public health services.

Distributional impact of infectious disease interventions in the Ethiopian Essential Health Service Package: a modelling study

ObjectivesReducing inequalities in health and financial risk are key goals on the path toward universal health coverage, particularly in low-income and middle-income countries. The design of the health benefit package...

The Trend of Healthcare Needs among Elders and Its Association with Healthcare Access and Quality in Low-Income Countries: An Exploration of the Global Burden of Disease Study 2019.

To investigate the trend of healthcare needs among elders in low-income countries (LICs) and how changes in healthcare access and quality (HAQ) have correlated with these changes from 1990 to 2019, this study used estimates from the global burden of disease (GBD) 2019 study, including prevalence, years of life lost (YLLs), years lived with disability (YLDs), life expectancy (LE), health-adjusted life expectancy (HALE) and the HAQ index for years 1990 and 2019. We found increases in numbers of YLLs, YLDs, and prevalent cases due to NCDs, and the rate of increase was higher for all indicators of non-communicable diseases (NCDs) when compared with communicable, maternal, neonatal and nutritional diseases among elders. We also observed increases in LE and HALE among all countries. However, this was also challenged by increases in unhealthy life years (ULYs) and their constant percentage of LE. The HAQ index of LICs was also found to be low, although it had increased during the period. A reduction in the burden of acute diseases explains the increase in LE, but increases in ULYs and the NCD burden were also observed. LICs need to improve their HAQ to counter the growing threat of longer but less healthy lives.

Socioeconomic Determinants of Life Expectancy: Southeastern European Countries

This paper analyses the socioeconomic determinants of life expectancy in Southeastern Europe countries highlighting the most important factors that can affect life expectancy in this part of Europe. 
 Two Panel Data Regression with fixed–effects model was applied for 20 years from 2000 to 2019. Eight socioeconomic and environmental explanatory variables were used to verify their influence on life expectancy.
 The analysis highlights the important influence of factors such as urbanization; GDP per capita; fertility rate; education; marital status; CO2 emission and the non-significant influence of other factors, such as health expenditure or health care out-of-pocket healthcare expenditure. This study points out that healthcare spending (public and/or household out-of-pocket spending) is not a significant factor in improving life expectancy in SEE countries. Results illustrate that GDP per capita; urbanization, CO2 emissions, and fertility rate are the most influential and significant explanatory factors. A surprising result concerns marital status, which in this study affects life expectancy inversely in one of the panel regressions.
 Life expectancy is a very important and expressive outcome indicator for public health. Each country is committed to spending public money to improve people's quality of life, which translates into a longer life (Life expectancy), or even better, a longer and healthier life (Health Adjusted Life Expectancy). The results of this study, considering the demographic development of the SEE countries (low fertility rate and aged people), show that policymakers need to consider public healthcare organization and reassess the effectiveness of public health expenditure. On the other hand, the balanced urbanization process with a clean ecosystem (less CO2 emissions) conducts a better life quality (consequently an improved life expectancy).
 Keywords: Panel data analysis; Life Expectancy; Public Health; SEE Countries
 Jel Classification: C33; H51; I15

Potential Gains in Health-Adjusted Life Expectancy by Reducing Burden of Noncommunicable Diseases in 188 Countries: A Population-Based Study

ObjectivesThis article quantifies the potential gains in health-adjusted life expectancy for people aged 30 to 70 years (HALE[30-70]) by examining the reductions in disability in addition to premature mortality from noncommunicable diseases (NCDs). MethodsWe extracted data from the Global Burden of Disease Study 2019 for 4 major NCDs (cancers, cardiovascular diseases, chronic respiratory diseases, and diabetes mellitus) in 188 countries from 2010 to 2019. Estimates of the potential gains in HALE[30-70] were based on a counterfactual analysis involving 3 alternative future scenarios: (1) achieve Sustainable Development Goals target 3.4 but do not make any progress on disability reduction, (2) achieve Sustainable Development Goals target 3.4 and eliminate NCD-related disability, and (3) eliminate all NCD-related mortality and disability. ResultsIn all scenarios, the high-income group has the greatest potential gains in HALE[30-70], above the global average. For all specific causes, potential gains in HALE[30-70] decrease as income levels fall. Across these 3 scenarios, the potential gains in HALE[30-70] globally of reducing premature mortality for 4 major NCDs are 3.13 years, 4.53 years, and 7.32 years, respectively. In scenario A, all income groups have the greatest potential gains in HALE[30-70] from diabetes and chronic respiratory diseases. In scenarios B and C, the high-income group has the greatest potential gains in HALE[30-70] from cancer intervention, and the other income groups have the greatest potential gains in HALE[30-70] from cardiovascular diseases intervention. ConclusionReducing premature death and disability from 4 major NCDs at once and attaching equal importance to each lead to a sizable improvement in HALE[30-70].

Health-adjusted life expectancy according to lifestyle classified by the Yonsei Lifestyle Profile-BREF.

This study aimed to investigate health-adjusted life expectancy (HALE) by demographic characteristics (sex, educational achievement, and residential area) according to the lifestyle classifications of the Yonsei Lifestyle Profile-BREF (YLP-BREF). This study included 569 participants aged 55 years or older living in Korea. The YLP-BREF domains were physical activity, activity participation, and nutrition. Females had a longer HALE (mean±standard deviation, 8.90±5.06 years) in the physical activity domain, while males had a longer HALE in the nutrition domain (9.44±5.91 years). People living in rural areas had longer HALE in physical activity (12.02±5.60 years), activity participation (8.58±4.21 years), and nutrition (11.33±6.43 years). There were no significant differences according to sex or residential area. High school graduates showed the longest HALE (physical activity: 10.38± 6.89; activity participation: 7.64±4.29; nutrition: 9.59±6.40 years). There was a significant difference in educational achievement. As people age, the demand for a healthy lifestyle increases. This study attempted to calculate HALE by demographic characteristics according to lifestyle. The results of this study will help inform future research directions for providing a healthy lifestyle.

The gaps in health-adjusted life Expectancy (HALE) by income and region in Korea

Abstract This study aims to calculate the health-adjusted life expectancy (HALE) by using years lived with disability (YLD) from the national claims data, as well as to identify the differences and inequalities in sex, income level and region. The study was carried out on total population receiving national health insurance and medical benefits. We calculated incidence-based YLD for 260 disease groups, and used it as the number of healthy years lost to calculate HALE. We adopted the insurance premium to calculate the income as a proxy indicator. For the region classification, we chose 250 Korean municipal-level administrative districts. The primary outcome was HALE in the Korean population. The second outcome was the HALE’s gap in terms of sex, income, and region. Our results revealed that HALE increased from 2008 (68.89 years) to 2019 (70.58 years). HALE in males increased faster than that in females. HALE was higher in higher income levels. In 2019, the gap in HALE between Q1 and Q2, the lower income group, was about 5.70 years. The gap in females by income level was smaller than that in males. Moreover, the gap in HALE by region was found to increase. Results suggest that there is an inequality in YLD in terms of income level in Korea. Therefore, we need intensive management for the low-income group to increase HALE at the national level. Key messages • Males’ health level may be more sensitive to the socioeconomic level than females’ health level. • In the 5th National Health Plan (HP2030), it was decided to set a target value for the overall goals based on this result.

The asymmetric effects of fossil fuel dependency on the carbon intensity of well-being: A U.S. state-level analysis, 1999–2017

The resource dependency literature argues that intensifying processes of dependency can lead to poorer socioecological outcomes, but the effects of reducing dependency remain untested. Some scholars argue that it improves socioecological conditions, while other strands of research suggest that it causes economic hardship, as evidenced by the deaths of despair crisis. Here, I examine the asymmetric effects of fossil fuel dependency (measured as the energy production-consumption ratio, the share of exports from the mining sector, and the share of GDP from the mining sector) on the carbon intensity of well-being (CIWB) at the U.S. state-level. I do so by estimating dynamic asymmetric models with fixed effects estimation. I find that increases in all three measures are associated with increases in the CIWB. Decreases in the energy production-consumption ratio and the share of exports from the mining sector do not affect the CIWB, while a decrease in the share of GDP from the mining sector produces a proportional reduction in the CIWB relative to an increase. The estimated net effect of all three variables suggests that an increase in fossil fuel dependency increases the CIWB, while a decrease has no effect. When the CIWB is disaggregated, I find that changes in the energy production-consumption ratio are driving changes in emissions and that changes in the share of GDP from the mining sector are responsible for changes in health-adjusted life expectancy. Given that the net effect of a decrease in fossil fuel dependency is not statistically significant, I conclude by arguing that a planned, managed transition away from fossil fuel extraction is critical to ensuring simultaneous improvements in human and environmental well-being.

Key Social Determinants to Narrow the Gap between Health-adjusted Life Expectancy and Life Expectancy in Megacities

ObjectiveImprovement in the quality of life is reflected in the narrowing of the gap between health-adjusted life expectancy (HALE) and life expectancy (LE). The effect of megacity expansion on narrowing the gap is rarely reported. This study aimed to disclose this potential relationship. MethodsAnnual life tables were constructed from identified death records and population counts from multiple administrative sources in Guangzhou, China, from 2010 to 2020. Joinpoint regression was used to evaluate the temporal trend. Generalized principal component analysis and multilevel models were applied to examine the county-level association between the gap and social determinants. ResultsAlthough LE and HALE in megacities are increasing steadily, their gap is widening. Socio-economic and health services are guaranteed to narrow this gap. Increasing personal wealth, a growing number of newborns and healthy immigrants, high urbanization, and healthy aging have helped in narrowing this gap. ConclusionIn megacities, parallel LE and HALE growth should be highly considered to narrow their gap. Multiple social determinants need to be integrated as a whole to formulate public health plans.

Economic evaluation of postdischarge malaria chemoprevention in preschool children treated for severe anaemia in Malawi, Kenya, and Uganda: A cost-effectiveness analysis.

SummaryBackgroundChildren hospitalised with severe anaemia in malaria-endemic areas are at a high risk of dying or being readmitted within six months of discharge. A trial in Kenya and Uganda showed that three months of postdischarge malaria chemoprevention (PDMC) with monthly dihydroartemisinin-piperaquine (DP) substantially reduced this risk. The World Health Organization recently included PDMC in its malaria chemoprevention guidelines. We conducted a cost-effectiveness analysis of community-based PDMC delivery (supplying all three PDMC-DP courses to caregivers at discharge to administer at home), facility-based PDMC delivery (monthly dispensing of PDMC-DP at the hospital), and the standard of care (no PDMC).MethodsWe combined data from two recently completed trials; one placebo-controlled trial in Kenya and Uganda collecting efficacy data (May 6, 2016 until November 15, 2018; n=1049), and one delivery mechanism trial from Malawi collecting adherence data (March 24, 2016 until October 3, 2018; n=375). Cost data were collected alongside both trials. Three Markov decision models, one each for Malawi, Kenya, and Uganda, were used to compute incremental cost-effectiveness ratios expressed as costs per quality-adjusted life-year (QALY) gained. Deterministic and probabilistic sensitivity analyses were performed to account for uncertainty.FindingsBoth PDMC strategies were cost-saving in each country, meaning less costly and more effective in increasing health-adjusted life expectancy than the standard of care. The estimated incremental cost savings for community-based PDMC compared to the standard of care were US$ 22·10 (Malawi), 38·52 (Kenya), and 26·23 (Uganda) per child treated. The incremental effectiveness gain using either PDMC strategy varied between 0·3 and 0·4 QALYs. Community-based PDMC was less costly and more effective than facility-based PDMC. These results remained robust in sensitivity analyses.InterpretationPDMC under implementation conditions is cost-saving. Caregivers receiving PDMC at discharge is a cost-effective delivery strategy for implementation in malaria-endemic southeastern African settings.FundingResearch Council of Norway.

Multidimensional evaluation of healthy life expectancy indicators based on mental health among the rural older population: A large-scale cross-sectional study

BackgroundThis study aimed to estimate healthy life expectancy (HLE) regarding anxiety, depression and their comorbidity among rural older adults. MethodsA total of 12,851 subjects (5790 men and 7061 women) enrolled from the Henan Rural Cohort Study were used to evaluate healthy status expectancy (HSE), and 10,096 (4475 men and 5621 women) of them were used to estimate health-adjusted life expectancy (HALE). The life expectancy was calculated using period life table, and HSE and HALE indicators were calculated via the Sullivan method. ResultsFor participants aged 60, the depression-free life expectancy (DFLE), anxiety-free life expectancy (AFLE), and depression- and anxiety-free life expectancy (DAFLE) were 23.0993, 23.3314, and 22.7206 years, respectively. The quality-adjusted life expectancy (QALE) of those with neither anxiety nor depression, with anxiety, with depression, and with comorbidity was 22.0727, 20.8751, 18.1484, and 17.0823 years, respectively. The ratio of DFLE (AFLE) to LE increased with age among both genders, while the DAFLE/LE showed a decreasing trend. Regardless of HSE or HALE indicators, women tended to have higher HLE, while HLE/LE was lower than men. Furthermore, all HLE indicators associated with anxiety were the largest in both genders compared to indicators regarding depression. LimitationsThe HLE may be overestimated ignoring institutional population in the study. ConclusionAnxiety and depression played essential roles in the quality of life among rural older adults, especially depression. Comorbidity would intensify the adverse effect in rural areas, especially for older men. More attention should be paid to the psychological problems among rural older population.

Health-adjusted life expectancy in residents in Guangzhou, 2010-2019

Objective: To analyze the spatiotemporal distribution of life expectancy (LE) and health-adjusted life expectancy (HALE) in Guangzhou from 2010 to 2019, and quantize the comprehensive impact of different causes and sequelae on health. Methods: The LE, HALE, and cause-excluded health adjusted life expectancy (CEHALE) were estimated using cause-of-death surveillance datasets from Guangzhou Municipal Center for Disease Control and Prevention from 2010 to 2019 and open data from the Global Burden of Disease Study. Joinpoint log-linear regression model was used to analyze the temporal trend and described spatial distribution. Results: In 2019, the LE in residents in Guangzhou was 82.9 years (80.1 years in men and 85.9 years in women), and the HALE was 75.6 years (74.0 years in men and 77.3 years in women). Compared with the urban fringe, the central urban area had higher LE and HALE, and the differences between LE and HALE were small. The LE and HALE in Guangzhou showed an increasing trend from 2010 to 2019. The LE increased by 2.8 years (AAPC=0.4, 95%CI: 0.3-0.4), with the increase of 2.8 years in men and 2.9 years in women. The HALE increased by 2.4 years (AAPC=0.3, 95%CI: 0.3-0.4), with the increase of 2.5 years in men and 2.2 years in women. The median healthy life lost due to communicable, maternal, neonatal, and nutritional diseases was 6.2 years (AAPC=-4.2, 95%CI: -5.3--3.1), while the median healthy life lost due to non-communicable diseases was 14.7 years (AAPC=1.6, 95%CI: 0.9-2.3), the median healthy life expectancy reduced by injury was 6.3 years (AAPC=-3.5, 95%CI: -4.5--2.6). Musculoskeletal disorders, skin and subcutaneous diseases, cardiovascular diseases, nutritional deficiencies, diabetes and kidney diseases were the top five diseases causing healthy life expectancy loss. Conclusion: The LE and HALE in residents in Guangzhou increased steadily from 2010 to 2019, but the quality of life in the urban fringe was lower than that of the central urban area. Non-communicable diseases were the leading causes of healthy life expectancy loss. Health policies and prevention measures should be developed according to area specific characteristics, and social medical resources should be rationally allocated to key diseases to reduce their disease burden.

Well-Being Adjusted Health Expectancy: A New Summary Measure of Population Health

We propose a new summary measure of population health (SMPH), the well-being-adjusted health expectancy (WAHE). WAHE belongs to a subgroup of health-adjusted life expectancy indicators and gives the number of life years equivalent to full health. WAHE combines health and mortality information into a single indicator with weights that quantify the reduction in well-being associated with decreased health. WAHE's advantage over other SMPHs lies in its ability to differentiate between the consequences of health limitations at various levels of severity and its transparent, simple valuation function. Following the guidelines of a Committee on Summary Measures of Population Health, we discuss WAHE's validity, universality, feasibility sensitivity and ensure its reproducibility. We evaluate WAHE's performance compared to life expectancy, the most commonly used indicators of health expectancy (HE) and disability-adjusted life expectancy (DALE) in an empirical application for 29 European countries. Data on health and well-being are taken from the 2018 EU-SILC, and the life tables are from Eurostat. DALE is taken from the database of the Global Burden of Disease Programme. WAHE's sensitivity to univariate and multivariate state specifications is studied using the three Minimum European Health Module health dimensions: chronic morbidity, limitations in activities of daily living, and self-rated health. The empirical tests of the indicators’ correspondence reveal that WAHE has the strongest correlation with the other SMPHs. Moreover, WAHE estimates are in agreement with all other SMPHs. Additionally, WAHE and all other SMPHs form a group of reliable indicators for studying population health in European countries. Finally, WAHE estimates are robust, regardless of whether health is defined across one or multiple simultaneous dimensions of health. We conclude that WAHE is a useful and reliable indicator of population health and performs at least as well as other commonly used SMPHs.