Background: Few controlled studies have examined social class as a risk factor for suicide in Korea.Aim: The objective of the present study was to investigate the effects of social class on suicide risk in Korea.Methods: A case-control design was constructed from cause-of-death statistics for the period 1999 to 2001, in Korea, as published by the Korean National Statistical Office. The cases were defined as people aged between 20 and 64 who died by suicide, while the controls were defined as those who died of natural causes in the same age groups.Results and conclusions: The proportions and odds ratios for suicide were higher in young people than in elderly people, and higher for divorced subjects than for cohabitants. They were also higher for residents of rural areas, as opposed to residents of Seoul and other metropolitan areas, and for people in social classes III and IV, than they were for those in social class I. To control the variables that influence risk of suicide, such as age, marital status and area of residence, we used multiple logistic regression. Compared with class I, risk of suicide was higher in social classes III and IV, in both sexes. The principal conclusion of this study is that, regardless of sex, lower social class constitutes a high risk for suicide in Korea, even after controlling for variables such as age, marital status and area of residence. We conclude that a well-controlled and balanced social welfare system could reduce suicide risk, especially among people in lower social class.
BACKGROUND: The Korean Health Insurance Review and Assessment Service (HIRA) has launched the Chronic Obstructive Pulmonary Disease (COPD) Quality Assessment Program (CQAP) since 2014. We aimed to reveal the influence of this national program on clinical outcomes and the burden of COPD in Korea. METHODS: The CQAP is conducted annually. We used healthcare claims data linked with the results of the program provided by HIRA between May 2014 and April 2017. Patients were considered to have COPD if they visited a hospital for COPD management during the assessment term. Those who visited a medical institution for COPD and were prescribed COPD medications at least twice were assessed by the CQAP (assessed subjects, AS; not-assessed subjects, NAS). CQAP evaluated the pulmonary function test conduction rate, regular visitation rate, and prescription rates of COPD medications. RESULTS: Among the 560,000 patients with COPD, about 140,000 were assessed by the CQAP annually. In both groups, the pulmonary function test conduction rate and inhaled bronchodilator prescription rate improved since 2014. Compared to the NAS group, the risk of admission and all-cause mortality rate in the AS group were significantly reduced by 21.2% and 40.7%, respectively. In patients who were assessed for 3 consecutive years, all of the above variables were high at baseline and were not improved much from implementation of CQAP. In matching analysis, we observed this improvement to be limited in the COPD quality assessment year. CONCLUSIONS: The CQAP by the health insurance bureau has improved the management protocol and prognosis of COPD.
Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Funding Bill & Melinda Gates Foundation.