Evidence map›Paper›PMID 38909195›Full record

ArticleBMC public health2024

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

San Qian Chen, Yu Cao, Jing Jie Ma, Xing Chao Zhang, Song Bo Hu

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

San Qian ChenSchool of Public Health, Jiangxi Medical College, Nanchang University, Donghu Campus, Nanchang, Jiangxi Province, 330006, PR China.ORCID 0000-0002-1577-619X
Yu CaoSchool of Public Health, Jiangxi Medical College, Nanchang University, Donghu Campus, Nanchang, Jiangxi Province, 330006, PR China.ORCID 0009-0004-5799-4568
Jing Jie MaSchool of Public Health, Jiangxi Medical College, Nanchang University, Donghu Campus, Nanchang, Jiangxi Province, 330006, PR China.ORCID 0009-0003-7177-2534
Xing Chao ZhangSchool of Public Health, Jiangxi Medical College, Nanchang University, Donghu Campus, Nanchang, Jiangxi Province, 330006, PR China.ORCID 0009-0004-6857-7831
Song Bo HuSchool of Public Health, Jiangxi Medical College, Nanchang University, Donghu Campus, Nanchang, Jiangxi Province, 330006, PR China. husbo0910@ncu.edu.cn.ORCID 0000-0002-2132-6988

Funding

National Natural Science Foundation of China 81960618Natural Science Foundation of Jiangxi Province 20224BAB206094Science and Technology Plan Project of Jiangxi Province Health Commission 202211345
6 · The paper itself

Abstract

backgroundHALE 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.

methodsFirst, 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).

resultsA 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%).

conclusionWe 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.

Indexed as

Life ExpectancyAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChinaDisability-Adjusted Life YearsFemaleHumansInfantInfant, NewbornMaleMiddle AgedModels, StatisticalChinaHealth-adjusted life expectancyPractical modelUncertainty intervalsYears lived with disability rate

Identifiers

PMID38909195
PMCPMC11193283

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