The rally 'round the flag effect in third parties: the case of the Russian invasion of Ukraine
In: Journal of elections, public opinion and parties, S. 1-10
ISSN: 1745-7297
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In: Journal of elections, public opinion and parties, S. 1-10
ISSN: 1745-7297
BackgroundResearch suggests that preventive measures are critical to reducing the spread of coronavirus disease 2019 (COVID-19), but evidence regarding the association between trust in government and the practice of preventive measures is limited.ObjectiveTo examine whether the practice of preventive measures against COVID-19 differs by one's level of trust in government.DesignA cross-sectional analysis using the Japan COVID-19 and Society Internet Survey (JACSIS) conducted in August and September 2020.ParticipantsA nationally representative sample of Japanese individuals aged 15 through 79 years.Main measuresThe primary outcome was the composite score for COVID-19 preventive measures, defined as the percentage of preventive measures an individual reported to be practicing (out of nine measures: social distancing, wearing masks, avoiding closed spaces, avoiding crowded spaces, avoiding close contact settings, hand washing, avoiding touching one's face, respiratory hygiene, and surface disinfection). The secondary outcomes were (1) support for stay-at-home requests, (2) use of a contact-tracing app, and (3) receipt of the influenza vaccine in the previous season.Key resultsOur analysis included a total of 25,482 individuals. After adjusting for potential confounders, we found that individuals with high trust in government were likely to practice preventive measures more frequently compared to those with low trust (adjusted composite scores, 83.8% for high- vs. 79.5% for low-trust individuals; adjusted difference, +4.3 percentage points [pp]; 95% CI, +2.4 to +6.2pp; P<0.001). We also found that high trust in government was associated with higher likelihoods of support for stay-at-home requests, use of a contact-tracing app, and receipt of the influenza vaccine in the previous season.ConclusionsHigh trust in government was associated with a higher intensity of practicing COVID-19 preventive measures among Japanese individuals at the national level. Our findings may provide useful information to develop and design effective public health interventions.
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BackgroundResearch suggests that preventive measures are critical to reducing the spread of coronavirus disease 2019 (COVID-19), but evidence regarding the association between trust in government and the practice of preventive measures is limited.ObjectiveTo examine whether the practice of preventive measures against COVID-19 differs by one's level of trust in government.DesignA cross-sectional analysis using the Japan COVID-19 and Society Internet Survey (JACSIS) conducted in August and September 2020.ParticipantsA nationally representative sample of Japanese individuals aged 15 through 79 years.Main measuresThe primary outcome was the composite score for COVID-19 preventive measures, defined as the percentage of preventive measures an individual reported to be practicing (out of nine measures: social distancing, wearing masks, avoiding closed spaces, avoiding crowded spaces, avoiding close contact settings, hand washing, avoiding touching one's face, respiratory hygiene, and surface disinfection). The secondary outcomes were (1) support for stay-at-home requests, (2) use of a contact-tracing app, and (3) receipt of the influenza vaccine in the previous season.Key resultsOur analysis included a total of 25,482 individuals. After adjusting for potential confounders, we found that individuals with high trust in government were likely to practice preventive measures more frequently compared to those with low trust (adjusted composite scores, 83.8% for high- vs. 79.5% for low-trust individuals; adjusted difference, +4.3 percentage points [pp]; 95% CI, +2.4 to +6.2pp; P<0.001). We also found that high trust in government was associated with higher likelihoods of support for stay-at-home requests, use of a contact-tracing app, and receipt of the influenza vaccine in the previous season.ConclusionsHigh trust in government was associated with a higher intensity of practicing COVID-19 preventive measures among Japanese individuals at the national level. Our findings may provide useful information to develop and design effective public health interventions.
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ObjectiveTo investigate the association between participation in government subsidies for domestic travel (subsidise up to 50% of all travel expenses) introduced nationally in Japan on 22 July 2020 and the incidence of symptoms indicative of COVID-19 infections.DesignCross-sectional analysis of nationally representative survey data.SettingInternet survey conducted between 25 August and 30 September 2020 in Japan. Sampling weights were used to calculate national estimates.Participants25 482 survey respondents (50.3% (12 809) women; mean (SD) age, 48.8 (17.4) years).Main outcome measuresIncidence rate of five symptoms indicative of the COVID-19 infection (high fever, sore throat, cough, headache, and smell and taste disorder) within the past month of the survey, after adjustment for characteristics of individuals and prefecture fixed effects (effectively comparing individuals living in the same prefecture).ResultsAt the time of the survey, 3289 (12.9%) participated in the subsidy programme. After adjusting for potential confounders, we found that participants in the subsidy programme exhibited higher incidence of high fever (adjusted rate, 4.7% for participants vs 3.7% for non-participants; adjusted OR (aOR) 1.83; 95% CI 1.34 to 2.48; p<0.001), sore throat (19.8% vs 11.3%; aOR 2.09; 95% CI 1.37 to 3.19; p=0.002), cough (19.0% vs 11.3%; aOR 1.96; 95% CI 1.26 to 3.01; p=0.008), headache (29.2% vs 25.5%; aOR 1.24; 95% CI 1.08 to 1.44; p=0.006) and smell and taste disorder (2.6% vs 1.8%; aOR 1.98; 95% CI 1.15 to 3.40; p=0.01) compared with non-participants. These findings remained qualitatively unaffected by additional adjustment for the use of 17 preventative measures (eg, social distancing, wearing masks and handwashing) and fear against the COVID-19 infection.ConclusionsThe participation of the government subsidy programme for domestic travel was associated with a higher probability of exhibiting symptoms indicative of the COVID-19 infection.
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OBJECTIVES: The unprecedented coronavirus disease 2019 (COVID‐19) pandemic and the corresponding government state of emergency have dramatically changed our workstyle, particularly through implementing teleworking and social distancing. We investigated the degree to which people's work performance is affected and the association between sedentary behavior under the state of emergency and worsened work performance during the COVID‐19 pandemic, as previous studies have suggested that sedentary behavior decreases work performance. METHODS: We used data from the Japan "COVID‐19 and Society" Internet Survey (JACSIS) study, a cross‐sectional, web‐based, self‐reported questionnaire survey. The main outcome was change in work performance after the COVID‐19 pandemic compared with that before the pandemic. We analyzed the association between the change in work performance and sitting duration under the state of emergency, adjusted for work‐related stress, participants' demographics, socio‐economic status, health‐related characteristics, and personality. RESULTS: The change of work environment from the pandemic decreased work performance in 15% of workers, which was 3.6 times greater than the number of workers reporting increased performance in 14 648 workers (6134 women and 8514 men). Although telework both improved and worsened performance (odds ratio [OR], 95% confidence interval [CI] = 2.0, 1.6‐2.5 and 1.7, 1.5‐1.9, respectively), sitting for long periods after the state of emergency was significantly associated only with worsened performance (OR, 95% CI = 1.8, 1.5‐2.2) in a dose–response manner. CONCLUSION: Sitting duration is likely a risk barometer of worsened work performance under uncertain working situations, such as the COVID‐19 pandemic.
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IMPORTANCE: As countermeasures against the economic downturn caused by the coronavirus 2019 (COVID-19) pandemic, many countries have introduced or considering financial incentives for people to engage in economic activities such as travel and use restaurants. Japan has implemented a large-scale, nationwide government-funded program that subsidizes up to 50% of all travel expenses since July 2020 with the aim of reviving the travel industry. However, it remains unknown as to how such provision of government subsidies for travel impacted the COVID-19 pandemic. OBJECTIVE: To investigate the association between participation in government subsidies for domestic travel in Japan and the incidence of COVID-19 infections. DESIGN, SETTING, AND PARTICIPANTS: Using the data from a large internet survey conducted between August 25 and September 30, 2020, in Japan, we examined whether individuals who used subsidies experienced a higher likelihood of symptoms indicative of the COVID-19 infection. EXPOSURE: Participation in the government subsidy program for domestic travel. MAIN OUTCOMES AND MEASURES: Five symptoms indicative of the COVID-19 infection (high fever, throat pain, cough, headache, and smell and taste disorder) within the past one month of the survey. RESULTS: Of the 25,482 respondents (50.3% [12,809] women; mean [SD] age, 48.4 [17.4] years), 3,289 (12.9%) participated in the subsidy program at the time of survey. After adjusting for potential confounders, we found that the participants of the subsidy program exhibited higher incidence of high fever (adjusted rate, 4.8% for participants vs. 3.7% for non-participants; adjusted odds ratio [aOR], 1.90; 95%CI, 1.40-2.56; p<0.001), throat pain (20.0% vs. 11.3%; aOR, 2.13; 95%CI, 1.39-3.26; p=0.002), cough (19.2% vs. 11.2%; aOR 1.97; 95%CI, 1.28-3.03; p=0.004), headache (29.4% vs. 25.5%; aOR, 1.26; 95%CI, 1.09-1.46; p=0.005), and smell and taste disorder (2.6% vs. 1.7%; aOR 2.01; 95%CI; 1.16-3.49; p=0.01) compared with the non-participants. CONCLUSION AND RELEVANCE: ...
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In: Journal of biosocial science: JBS, Band 55, Heft 5, S. 908-920
ISSN: 1469-7599
AbstractJapan has faced a decline in fertility since the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to investigate the rate of pregnancy postponement and its contributing factors, with a particular focus on economic- and COVID-19 infection-related indicators. This study used data from 768 observations of married women aged 18 to 50 years with pregnancy intentions. The data were obtained from two rounds of a large web-based survey conducted by the Japan COVID-19 and Society Internet Survey (JACSIS) in 2020 and 2021. A generalised estimating equation (GEE) model was employed, as well as Poisson regression models for sub-sample analysis divided by year to estimate the year differential magnitude of the contributing factors' impacts. Approximately 20% of married women with childbearing intentions postponed their childbearing. The analyses revealed that declining income and anxiety about future household finances were significantly related to delayed childbearing, while fear of COVID-19 and infection rate were not. Additionally, the adverse effects of unfavourable economic conditions were stronger in 2021. Notably, age did not influence the decision of pregnancy postponement. Older women postponed pregnancy just as much as younger women. In conclusion, this study confirmed that the COVID-19 pandemic, particularly its related adverse economic conditions, contributed to Japan's current baby bust. Considering that advanced maternal age is already common in Japan, this decreased fertility may result in the long-term negative consequence of further population decline.
During crisis, trust has been found to have a buffering effect in the prevention of the deterioration of mental well-being, as trust is considered to reflect the individual's capability to gain social resources including both formal and informal support. Additionally, during the COVID-19 pandemic, political trust has been found to reduce anxiety. Taking these findings into account, this study explores the association of generalised and political trust with mental well-being on current postpartum women who were particularly at risk due to a decline in social support leaving them an increased burden of caring newborns during the pandemic. We conducted a crosssectional survey in October 2020 in Japan (n=558). Depressive symptoms (above the cutoff of the Edinburgh Postnatal Depression Scale (EPDS)) and Fear of Coronavirus-19 Scale (FCV–19S) scores were used as mental well-being indicators. Generalised and political trust were captured by binary variables. Results of regression analyses, in which covariates were fully adjusted, showed that higher generalised trust had a statistically significant association with lower possibility of depressive symptoms and a lower FCV-19S score, while political trust was not significantly associated with either indicator. For further understanding, we divided respondents into two groups; women living in cities where higher COVID-19 cases were reported and women living in areas with lower COVID-19 cases, to test whether the role of trust differs depending on the infection spread status. It was found that a higher generalised trust was significantly associated with a lower probability of having depressive symptoms in the areas with lower COVID-19 cases. However, statistical significance was not observed in the areas with high COVID-19 cases. This highlighted that even postpartum women who were normally capable of receiving formal and informal social support need to be taken care of in the current situation.
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The Japanese national and prefectural governments have accredited high‐capacity, high‐experience cancer care hospitals as "designated cancer care hospitals" to standardize cancer care, centralize patients, and improve clinical outcomes, but the performance of these designated hospitals has not been evaluated. We retrospectively compared 3‐year patient survival in national, prefectural, and nondesignated cancer care hospitals in 2010‐2012 in Osaka using registry‐based data of 86 456 surgically treated cancer patients aged 15 years or older. Hazard ratios and 3‐year survival probabilities were compared among national, prefectural, and nondesignated hospitals using a Cox proportional hazard regression model. Subgroup analyses for six cancers (stomach, colorectum, lung, breast, uterus, and prostate) and other cancers were carried out. In 2010‐2012, 36 634 (42.4%), 38 048 (44.0%), and 11 774 (13.6%) patients were treated at national, prefectural, and nondesignated hospitals, respectively. The mortality hazard for all‐site cancer was significantly lower in national and prefectural designated hospitals (adjusted hazard ratio 0.60 [95% confidence interval, 0.53‐0.68] and 0.72 [0.66‐0.80], respectively) than in nondesignated hospitals. The adjusted 3‐year survival probabilities for all‐site cancer were 86.6%, 84.2%, and 78.8% in national, prefectural, and nondesignated hospitals, respectively. Site‐specific subgroup analyses revealed significantly lower hazard ratios in national and prefectural hospitals than in nondesignated hospitals for stomach, colorectal, lung, breast, and other cancers. To conclude, the majority of cancer patients underwent surgeries at designated hospitals and had higher 3‐year survival probabilities than those treated at nondesignated hospitals. Further centralization of patients from nondesignated to designated hospitals could improve population‐level survival.
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In: JVAC-D-22-00361
SSRN
Tobacco smoking is the number one preventable cause of disease and death in China as it is globally. Indeed, the toll of smoking in China is much greater than its status as the world's most populous country. There is a persistent and continuing need for China to implement the measures specified in the global tobacco control treaty, the World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC), which China ratified in 2005. The theme for the 2021 WHO World No Tobacco Day focuses on the need to support smoking cessation. This article presents findings from the International Tobacco Control (ITC) Policy Evaluation Project cohort surveys in China, in comparison to ITC cohort surveys in two neighboring countries: Japan and the Republic of Korea. These findings demonstrate that smokers in China very much want to quit, but these intentions are not being translated into quit attempts, relative to smokers in Japan and the Republic of Korea. Additionally, about 80% of Chinese smokers want the Chinese government to do more to control smoking. These findings reaffirm the need for China to implement strong, evidence-based measures to reduce smoking. The objective of Healthy China 2030 to reduce deaths from non-communicable diseases by 30% can be achieved by reducing smoking prevalence from its current 26.6% to 20%, and this reduction can be achieved through strong implementation of FCTC measures.
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Importance Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). Conclusions and Relevance The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer
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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.
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Publisher's version (útgefin grein) ; 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. ; Lucas Guimaraes Abreu acknowledges support from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior -Brasil (Capes) -Finance Code 001, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) and Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG). Olatunji O Adetokunboh acknowledges South African Department of Science & Innovation, and National Research Foundation. Anurag Agrawal acknowledges support from the Wellcome Trust DBT India Alliance Senior Fellowship IA/CPHS/14/1/501489. Rufus Olusola Akinyemi acknowledges Grant U01HG010273 from the National Institutes of Health (NIH) as part of the H3Africa Consortium. Rufus Olusola Akinyemi is further supported by the FLAIR fellowship funded by the UK Royal Society and the African Academy of Sciences. Syed Mohamed Aljunid acknowledges the Department of Health Policy and Management, Faculty of Public Health, Kuwait University and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia for the approval and support to participate in this research project. Marcel Ausloos, Claudiu Herteliu, and Adrian Pana acknowledge partial support by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDSUEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Till Winfried Barnighausen acknowledges support from the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. Juan J Carrero was supported by the Swedish Research Council (2019-01059). Felix Carvalho acknowledges UID/MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/MCTES through national funds. Vera Marisa Costa acknowledges support from grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundacao para a Ciencia e a Tecnologia (FCT), IP, under the Norma TransitA3ria DL57/2016/CP1334/CT0006. Jan-Walter De Neve acknowledges support from the Alexander von Humboldt Foundation. Kebede Deribe acknowledges support by Wellcome Trust grant number 201900/Z/16/Z as part of his International Intermediate Fellowship. Claudiu Herteliu acknowledges partial support by a grant co-funded by European Fund for Regional Development through Operational Program for Competitiveness, Project ID P_40_382. Praveen Hoogar acknowledges the Centre for Bio Cultural Studies (CBiCS), Manipal Academy of Higher Education(MAHE), Manipal and Centre for Holistic Development and Research (CHDR), Kalghatgi. Bing-Fang Hwang acknowledges support from China Medical University (CMU108-MF-95), Taichung, Taiwan. Mihajlo Jakovljevic acknowledges the Serbian part of this GBD contribution was co-funded through the Grant OI175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Aruna M Kamath acknowledges funding from the National Institutes of Health T32 grant (T32GM086270). Srinivasa Vittal Katikireddi acknowledges funding from the Medical Research Council (MC_UU_12017/13 & MC_UU_12017/15), Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15) and an NRS Senior Clinical Fellowship (SCAF/15/02). Yun Jin Kim acknowledges support from the Research Management Centre, Xiamen University Malaysia (XMUMRF/2018-C2/ITCM/0001). Kewal Krishan acknowledges support from the DST PURSE grant and UGC Center of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. Manasi Kumar acknowledges support from K43 TW010716 Fogarty International Center/NIMH. Ben Lacey acknowledges support from the NIHR Oxford Biomedical Research Centre and the BHF Centre of Research Excellence, Oxford. Ivan Landires is a member of the Sistema Nacional de InvestigaciA3n (SNI), which is supported by the Secretaria Nacional de Ciencia Tecnologia e Innovacion (SENACYT), Panama. Jeffrey V Lazarus acknowledges support by a Spanish Ministry of Science, Innovation and Universities Miguel Servet grant (Instituto de Salud Carlos III/ESF, European Union [CP18/00074]). Peter T N Memiah acknowledges CODESRIA; HISTP. Subas Neupane acknowledges partial support from the Competitive State Research Financing of the Expert Responsibility area of Tampere University Hospital. Shuhei Nomura acknowledges support from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (18K10082). Alberto Ortiz acknowledges support by ISCIII PI19/00815, DTS18/00032, ISCIII-RETIC REDinREN RD016/0009 Fondos FEDER, FRIAT, Comunidad de Madrid B2017/BMD-3686 CIFRA2-CM. These funding sources had no role in the writing of the manuscript or the decision to submit it for publication. George C Patton acknowledges support from a National Health & Medical Research Council Fellowship. Marina Pinheiro acknowledges support from FCT for funding through program DL 57/2016 -Norma transitA3ria. Alberto Raggi, David Sattin, and Silvia Schiavolin acknowledge support by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C Besta, Linea 4 -Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). Daniel Cury Ribeiro acknowledges support from the Sir Charles Hercus Health Research Fellowship -Health Research Council of New Zealand (18/111). Perminder S Sachdev acknowledges funding from the NHMRC Australia. Abdallah M Samy acknowledges support from a fellowship from the Egyptian Fulbright Mission Program. Milena M Santric-Milicevic acknowledges support from the Ministry of Education, Science and Technological Development of the Republic of Serbia (Contract No. 175087). Rodrigo Sarmiento-Suarez acknowledges institutional support from University of Applied and Environmental Sciences in Bogota, Colombia, and Carlos III Institute of Health in Madrid, Spain. Maria Ines Schmidt acknowledges grants from the Foundation for the Support of Research of the State of Rio Grande do Sul (IATS and PrInt) and the Brazilian Ministry of Health. Sheikh Mohammed Shariful Islam acknowledges a fellowship from the National Heart Foundation of Australia and Deakin University. Aziz Sheikh acknowledges support from Health Data Research UK. Kenji Shibuya acknowledges Japan Ministry of Education, Culture, Sports, Science and Technology. Joan B Soriano acknowledges support by Centro de Investigacion en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. Rafael Tabares-Seisdedos acknowledges partial support from grant PI17/00719 from ISCIII-FEDER. Santosh Kumar Tadakamadla acknowledges support from the National Health and Medical Research Council Early Career Fellowship, Australia. Marcello Tonelli acknowledges the David Freeze Chair in Health Services Research at the University of Calgary, AB, Canada. ; "Peer Reviewed"
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The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. ; Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing. ; Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163). ; Peer reviewed
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