Global burden and inequality of maternal and neonatal disorders: based on data from the 2019 Global Burden of Disease study

Abstract

Summary Background Maternal and neonatal disorders account for substantial health loss across the lifespan from early childhood. These problems may be related to health inequality. Aim To provide evidence for improvement in health policies regarding maternal and neonatal disorder inequity. Design This was a population-based cross-sectional study based on 2019 Global Burden of Disease data. Methods Annual cases and age-standardized rates (ASRs) of incidence, prevalence, death, and disability-adjusted life-years (DALYs) in maternal and neonatal disorders between 1990 and 2019 were collected from the 2019 Global Burden of Disease study. Concentration curves and concentration indices were used to summarize the degree of socioeconomic-related inequality. Results For maternal disorders, the global ASRs of incidence, prevalence, death, and DALYs were 2889.4 (95% uncertainty interval (UI), 2562.9-3251.9), 502.9 (95% UI 418.7-598.0), 5.0 (95% UI 4.4-5.8) and 324.9 (95% UI 284.0-369.1) per 100,000 women in 2019, respectively. The ASRs of maternal disorders were all obviously reduced and remained pro-poor from 1990 to 2019. In neonatal disorders, the global ASRs of incidence, prevalence, death, and DALYs of neonatal disorders was 363.3 (95% UI 334.6-396.8), 1239.8 (95% UI 1142.1-1356.7), 29.1 (95% UI 24.8-34.5) and 2828.3 (95% UI 2441.6-3329.6) per 100,000 people in 2019, respectively. The global ASRs of incidence, death, and DALYs in neonatal disorders has remained pro-poor. However, the socioeconomic-related fairness in the ASR of neonatal disorder prevalence is being levelled. Conclusions The global burden of maternal and neonatal disorders has remained high, and socioeconomic-related inequality (pro-poor) tended not to change between 1990 and 2019.

Global burden and inequality of autism spectrum disorders: Based on data from the 2019 Global Burden of Disease study

“…The covariance method was used to calculate the concentration index ( Peng et al, 2023 ). In the above calculation formula, C represents the concentration index, cov means the covariance, r indicates the ranking of region i in the socio-economic distribution (from poorest to wealthiest), and h represents the health outcomes, μ considered as an average health outcome ( Peng et al, 2023 ).…”