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Sökning: WFRF:(Marthias Tiara) > (2021)

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1.
  • Anindya, Kanya, et al. (författare)
  • Socioeconomic inequalities in effective service coverage for reproductive, maternal, newborn, and child health: a comparative analysis of 39 low-income and middle-income countries.
  • 2021
  • Ingår i: EClinicalMedicine. - 2589-5370. ; 40
  • Tidskriftsartikel (refereegranskat)abstract
    • Reducing socioeconomic inequalities in access to good quality health care is key for countries to achieve Universal Health Coverage. This study aims to assess socioeconomic inequalities in effective coverage of reproductive, maternal, newborn and child health (RMNCH) in low- and middle-income countries (LMICs).Using the most recent national health surveys from 39 LMICs (between 2014 and 2018), we calculated coverage indicators using effective coverage care cascade that consists of service contact, crude coverage, quality-adjusted coverage, and user-adherence-adjusted coverage. We quantified wealth-related and education-related inequality using the relative index of inequality, slope index of inequality, and concentration index.The quality-adjusted coverage of RMNCH services in 39 countries was substantially lower than service contact, in particular for postnatal care (64 percentage points [pp], p-value<0·0001), family planning (48·7 pp, p<0·0001), and antenatal care (43·6 pp, p<0·0001) outcomes. Upper-middle-income countries had higher effective coverage levels compared with low- and lower-middle-income countries in family planning, antenatal care, delivery care, and postnatal care. Socioeconomic inequalities tend to be wider when using effective coverage measurement compared with crude and service contact measurements. Our findings show that upper-middle-income countries had a lower magnitude of inequality compared with low- and lower-middle-income countries.Reliance on the average contact coverage tends to underestimate the levels of socioeconomic inequalities for RMNCH service use in LMICs. Hence, the effective coverage measurement using a care cascade approach should be applied. While RMNCH coverages vary considerably across countries, equitable improvement in quality of care is particularly needed for lower-middle-income and low-income countries.None.
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2.
  • Zhao, Yang, et al. (författare)
  • Medical costs and out-of-pocket expenditures associated with multimorbidity in China: Quantile regression analysis
  • 2021
  • Ingår i: BMJ Global Health. - 2059-7908. ; 6
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective Multimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution. Methods Data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE. Results Overall, 69.5% of middle-Aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively). Conclusion Multimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.
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