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      Trends and projections of universal health coverage indicators in China, 1993–2030: An analysis of data from four nationwide household surveys

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          Summary

          Background

          Universal health coverage (UHC) is a core element of Sustainable Development Goals and has become a global healthcare priority. China has been committing to provide all citizens with affordable and equitable basic healthcare over past decades. However, progress towards UHC in China has not been comprehensively assessed. This study aims to comprehensively evaluate the progress towards UHC in China by examining trends in service coverage and financial protection from 1993 to 2018, and estimating the probability of achieving UHC targets by 2030.

          Methods

          Following the framework proposed by World Health Organization and World Bank, we selected 12 prevention service indicators, 12 treatment service indicators, and two financial protection indicators to evaluate China's progress towards UHC. We used data from four nationally representative household surveys to assess the trends in service coverage and financial protection between 1993 and 2018, as well as their inequalities across subgroups. Meta-analysis was used to construct the composite prevention and treatment indices. The regression-based relative index of inequality was used to measure the income-related inequality of UHC indicators. Bayesian linear regression was conducted to predict progress towards UHC by 2030, and the probability of achieving UHC targets.

          Findings

          Of the 24 service coverage indicators used in this study, most of them experienced improvements between 1993 and 2018. The composite prevention index increased from 65.6% (95% CI: 52.1%–77.9%) to 87.7% (95% CI: 81.8%–92.6%) and the composite treatment index increased from 57.1% (95% CI: 43.5%–70.1%) to 75.5% (95% CI: 66.6%–83.5%). The inequalities of service coverage experienced significant declines during this period. Based on our projections, most indicators except ones in the area of non-communicable diseases (NCD) will achieve the 80% coverage target by 2030, and the prevention and treatment indices will increase to 92.7% (95% CrI: 90.3%–94.7%) and 83.2% (95% CrI: 75.1%–88.8%) by then. However, we observed limited reductions in the incidences of catastrophic health expenditure and medical impoverishment. Inequalities in financial protection remained large in 2018.

          Interpretation

          China had made significant progress in improving healthcare service coverage and reducing inequalities between 1993 and 2018. However, China faces great challenges in improving financial protection and controlling NCD on its path towards UHC. Establishment of a primary-healthcare-based integrated delivery system and provision of better financial protection for vulnerable population should be prioritized.

          Funding

          None.

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          Most cited references36

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          Status of Hypertension in China

          Although the prevalence of hypertension (HTN) continues to increase in developing countries, including China, recent data are lacking. A nationwide survey was conducted from October 2012 to December 2015 to assess the prevalence of HTN in China.
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            Metaprop: a Stata command to perform meta-analysis of binomial data

            Background Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. Methods Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. Results The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). Conclusion By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.
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              Prevalence, awareness, treatment, and control of hypertension in China: data from 1·7 million adults in a population-based screening study (China PEACE Million Persons Project)

              Hypertension is common in China and its prevalence is rising, yet it remains inadequately controlled. Few studies have the capacity to characterise the epidemiology and management of hypertension across many heterogeneous subgroups. We did a study of the prevalence, awareness, treatment, and control of hypertension in China and assessed their variations across many subpopulations.
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                Author and article information

                Contributors
                Journal
                Lancet Reg Health West Pac
                Lancet Reg Health West Pac
                The Lancet Regional Health: Western Pacific
                Elsevier
                2666-6065
                17 November 2022
                February 2023
                17 November 2022
                : 31
                : 100646
                Affiliations
                [a ]School of Public Health, Peking University Health Science Center, Beijing, China
                [b ]National School of Development, Peking University, Beijing, China
                [c ]School of Public Affairs, Zhejiang University, Hangzhou, Zhejiang, China
                [d ]Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
                Author notes
                []Corresponding author. School of Public Health, Peking University Health Science Center, Room 233, Nursing Building, Beijing, 100191, China. hofu90@ 123456bjmu.edu.cn
                [e]

                These authors contributed equally to this work.

                Article
                S2666-6065(22)00261-9 100646
                10.1016/j.lanwpc.2022.100646
                9676220
                36419465
                2e41b374-0c27-423d-afa9-76c374304fdf
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 August 2022
                : 20 October 2022
                : 1 November 2022
                Categories
                Articles

                universal health coverage,healthcare service coverage,financial protection,bayesian analysis,inequality,china

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