Construction and evaluation of a practical model for measuring health-adjusted life expectancy (HALE) in China

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Abstract

Background

HALE is now a regular strategic planning indicator for all levels of the Chinese government. However, HALE measurements necessitate comprehensive data collection and intricate technology. Therefore, effectively converting numerous diseases into the years lived with disability (YLD) rate is a significant challenge for HALE measurements. Our study aimed to construct a simple YLD rate measurement model with high applicability based on the current situation of actual data resources within China to address challenges in measuring HALE target values during planning.

Methods

First, based on the Chinese YLD rate in the Global Burden of Disease (GBD) 2019, Pearson correlation analysis, the global optimum method, etc., was utilized to screen the best predictor variables from the current Chinese data resources. Missing data for predictor variables were filled in via spline interpolation. Then, multiple linear regression models were fitted to construct the YLD rate measurement model. The Sullivan method was used to measure HALE. The Monte Carlo method was employed to generate 95% uncertainty intervals. Finally, model performances were assessed using the mean absolute error (MAE) and mean absolute percentage error (MAPE).

Results

A three-input-parameter model was constructed to measure the age-specific YLD rates by sex in China, directly using the incidence of infectious diseases, the incidence of chronic diseases among persons aged 15 and older, and the addition of an under-five mortality rate covariate. The total MAE and MAPE for the combined YLD rate were 0.0007 and 0.5949%, respectively. The MAE and MAPE of the combined HALE in the 0-year-old group were 0.0341 and 0.0526%, respectively. There were slightly fewer males (0.0197, 0.0311%) than females (0.0501, 0.0755%).

Conclusion

We constructed a high-accuracy model to measure the YLD rate in China by using three monitoring indicators from the Chinese national routine as predictor variables. The model provides a realistic and feasible solution for measuring HALE at the national and especially regional levels, considering limited data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-024-19112-6.

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Most cited references 28

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Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study

Christopher Murray, Alan Lopez (1997)

The Lancet, 349(9064), 1498-1504

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Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

Theo Vos, Abraham D. Flaxman, Mohsen Naghavi … (2013)

Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350,000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient -0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Rates of YLDs per 100,000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.

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Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Maheswar Satpathy, Mathilde Touvier, Shafiu Mohammed … (2019)

Summary Background How long one lives, how many years of life are spent in good and poor health, and how the population’s state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1–7·8), from 65·6 years (65·3–65·8) in 1990 to 73·0 years (72·7–73·3) in 2017. The increase in years of life varied from 5·1 years (5·0–5·3) in high SDI countries to 12·0 years (11·3–12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1–33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8–15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9–6·7), from 57·0 years (54·6–59·1) in 1990 to 63·3 years (60·5–65·7) in 2017. The increase varied from 3·8 years (3·4–4·1) in high SDI countries to 10·5 years (9·8–11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4–1·7) in Saint Vincent and the Grenadines (62·4 years [59·9–64·7] in 1990 to 63·5 years [60·9–65·8] in 2017) to 23·7 years (21·9–25·6) in Eritrea (30·7 years [28·9–32·2] in 1990 to 54·4 years [51·5–57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6–2·3) in Algeria to 11·9 years (10·9–12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4–78·7]) and males (72·6 years [69·8–75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7–50·2] for females and 42·8 years [40·1–45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8–43·5) for communicable diseases and by 49·8% (47·9–51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8–43·0), although age-standardised DALY rates decreased by 18·1% (16·0–20·2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health. Funding Bill & Melinda Gates Foundation.

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Author and article information

Contributors

Song Bo Hu:

ORCID: https://orcid.org/0000-0002-2132-6988

husbo0910@ncu.edu.cn

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 22 June 2024

Publication date PMC-release: 22 June 2024

Publication date Collection: 2024

Volume: 24

Electronic Location Identifier: 1667

Affiliations

[1 ]School of Public Health, Jiangxi Medical College, Nanchang University, ( https://ror.org/042v6xz23) Donghu Campus, Nanchang, Jiangxi Province 330006 PR China

[2 ]Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, ( https://ror.org/042v6xz23) Nanchang, 330006 PR China

Author information

San Qian Chen https://orcid.org/0000-0002-1577-619X

Yu Cao https://orcid.org/0009-0004-5799-4568

Jing Jie Ma https://orcid.org/0009-0003-7177-2534

Xing Chao Zhang https://orcid.org/0009-0004-6857-7831

Song Bo Hu https://orcid.org/0000-0002-2132-6988

Article

Publisher ID: 19112

DOI: 10.1186/s12889-024-19112-6

PMC ID: 11193283

PubMed ID: 38909195

SO-VID: a529e2e9-6d0f-4660-b1c1-63a671d34930

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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 12 December 2023

Date accepted : 12 June 2024

Funding

Funded by: Natural Science Foundation of Jiangxi Province

Award ID: 20224BAB206094

Funded by: National Natural Science Foundation of China

Award ID: 81960618

Funded by: Science and Technology Plan Project of Jiangxi Province Health Commission

Award ID: 202211345

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ScienceOpen disciplines: Public health

Keywords: china,years lived with disability rate,health-adjusted life expectancy,practical model,uncertainty intervals

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ScienceOpen disciplines: Public health

Keywords: china, years lived with disability rate, health-adjusted life expectancy, practical model, uncertainty intervals

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Construction and evaluation of a practical model for measuring health-adjusted life expectancy (HALE) in China

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Abstract

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Supplementary Information

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Chinese Journal of School Health

Most cited references 28

Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

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