Dataset Information

Trends in Life Expectancy and Its Association with Economic Factors in the Belt and Road Countries-Evidence from 2000?2014.

ABSTRACT: In 2013, China launched the Belt and Road (B&R) Initiative in an effort to promote trade and economic collaboration. This study examined the change in life expectancy (LE) among countries along B&R and studied the impact of economic development on LE. Data from 65 B&R countries from 2000 to 2014 were compiled and analyzed. Trend of LE was examined by sex and country. Linear quantile mixed model was used to study the associations between LE and economic factors. In 2014, the average LE in all B&R countries was 69.7 years for men and 73.7 years for women. Across countries in 2014, LE for men ranged from 58.6 years in Afghanistan to 80.2 years in Israel. LE for women ranged from 61.3 years in Afghanistan to 85.9 in Singapore. GDP per capita was positively associated with longevity across B&R countries. The unemployment rate was positively associated with LE only for countries in the top LE quantiles. GDP growth rate and Inflation were negatively associated with LE for the countries in the bottom LE quantiles for men, not for women. LE increased substantially among B&R countries during 2000?2014. The influence of macroeconomic factors on LE was related to the distribution of LE.

SUBMITTER: Bai R

PROVIDER: S-EPMC6313698 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Publications

Trends in Life Expectancy and Its Association with Economic Factors in the Belt and Road Countries-Evidence from 2000⁻2014.

Bai Ruhai R Wei Junxiang J An Ruopeng R Li Yan Y Collett Laura L Dang Shaonong S Dong Wanyue W Wang Duolao D Fang Zeping Z Zhao Yaling Y Wang Youfa Y

International journal of environmental research and public health 20181217 12

In 2013, China launched the Belt and Road (B&R) Initiative in an effort to promote trade and economic collaboration. This study examined the change in life expectancy (LE) among countries along B&R and studied the impact of economic development on LE. Data from 65 B&R countries from 2000 to 2014 were compiled and analyzed. Trend of LE was examined by sex and country. Linear quantile mixed model was used to study the associations between LE and economic factors. In 2014, the average L ...[more]

PMID: 30562984

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Project description:Economic vulnerability is an important indicator to measure regional coordination, health and stability. Despite the importance of vulnerabilities, this is the first study that presents 26 indicators selected from the dimensions of the domestic economic system, external economic system and financial system in the Belt and Road Initiative (BRI) countries. A quantitative analysis is conducted to analyze the characteristics of spatial heterogeneity of vulnerability of the economic subsystems and the comprehensive economic system of the BRI countries and the main influencing factors of the comprehensive economic system vulnerability (CESV) are identified based on obstacle degree model. The results show that the CESV of the East Asia, South Asia and ASEAN countries are lower than that of the Middle Eastern Europe, Central Asia and West Asia countries. The CESV of the BRI countries are generally in the middle level and the average vulnerability index of highly vulnerable countries is twice as much as that of lowly vulnerable countries. In addition, in terms of the vulnerability of the three subsystems, the spatial distribution of vulnerability of the domestic economic system (DESV) and financial system (FSV) is basically consistent with the spatial distribution pattern of CESV, both of which are low in East Asia and South Asia and high in West Asia and Central Asia. While, the vulnerability of external economic system (EESV) shows a different spatial pattern, with vulnerability of West Asia, Central Asia and ASEAN higher than that of East Asia and South Asia. The main obstacle factors influencing the CESV of BRI countries include GDP growth rate, saving ratio, ratio of bank capital to assets, service industry level, industrialization level and loan rate. Therefore, the key way to maintain the stability and mitigate the vulnerability of the economic system of BRI countries is to focus on the macroeconomic development and operation, stimulate the economy and market vitality, promote the development of industries, especially the service and secondary industries, and optimize the economic structure, banking system and financial system.

Project description:ImportanceExamining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policy makers, clinicians, and researchers seeking to reduce disparities and increase longevity.ObjectiveTo estimate annual life tables by county from 1980 to 2014; describe trends in geographic inequalities in life expectancy and age-specific risk of death; and assess the proportion of variation in life expectancy explained by variation in socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.Design, setting, and participantsAnnual county-level life tables were constructed using small area estimation methods from deidentified death records from the National Center for Health Statistics (NCHS), and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. Measures of geographic inequality in life expectancy and age-specific mortality risk were calculated. Principal component analysis and ordinary least squares regression were used to examine the county-level association between life expectancy and socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.ExposuresCounty of residence.Main outcomes and measuresLife expectancy at birth and age-specific mortality risk.ResultsCounties were combined as needed to create stable units of analysis over the period 1980 to 2014, reducing the number of areas analyzed from 3142 to 3110. In 2014, life expectancy at birth for both sexes combined was 79.1 (95% uncertainty interval [UI], 79.0-79.1) years overall, but differed by 20.1 (95% UI, 19.1-21.3) years between the counties with the lowest and highest life expectancy. Absolute geographic inequality in life expectancy increased between 1980 and 2014. Over the same period, absolute geographic inequality in the risk of death decreased among children and adolescents, but increased among older adults. Socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors explained 60%, 74%, and 27% of county-level variation in life expectancy, respectively. Combined, these factors explained 74% of this variation. Most of the association between socioeconomic and race/ethnicity factors and life expectancy was mediated through behavioral and metabolic risk factors.Conclusions and relevanceGeographic disparities in life expectancy among US counties are large and increasing. Much of the variation in life expectancy among counties can be explained by a combination of socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors. Policy action targeting socioeconomic factors and behavioral and metabolic risk factors may help reverse the trend of increasing disparities in life expectancy in the United States.

Project description:BackgroundReducing child mortality was one of the Millennium Development Goals. In the current Sustainable Development Goals era, achieving equity is prioritized as a major aim.ObjectiveThis study aims to provide a comprehensive and updated picture of inequalities in child health intervention coverage and child health outcomes by wealth status, as well as their trends between 2000 and 2014.MethodsUsing data from Demographic Health Surveys and Multiple Indicator Cluster Surveys, we adopted three measures of inequality, including one absolute inequality indicator and two relative inequality indicators, to estimate the level and trends of inequalities in three child health outcome variables and 17 intervention coverages in 88 developing countries.ResultsWhile improvements in child health outcomes and coverage of interventions have been observed between 2000 and 2014, large inequalities remain. There was a high level of variation between countries' progress toward reducing child health inequalities, with some countries significantly improving, some deteriorating, and some remaining statistically unchanged. Among child health interventions, the least equitable one was access to improved sanitation (The absolute difference in coverages between the richest quintile and the poorest quintile reached 49.5% [42.7, 56.2]), followed by access to improved water (34.1% [29.5, 38.6]), and skilled birth attendant (SBA) (34.1% [28.8, 39.4]). The most equitable intervention coverage was insecticide-treated bed net for children (1.0% [-3.9, 5.9]), followed by oral rehydration therapy for diarrhea ((8.0% [5.2, 10.8]), and vitamin A supplement (8.4% [5.1, 11.7]). These findings were robust to various inequality measurements.ConclusionsAlthough child health outcomes and coverage of interventions have improved largely over the study period for almost all wealth quintiles, insufficient progress was made in reducing child health inequalities between the poorest and richest wealth quintiles. Future efforts should focus on reaching the poorest children by increasing investments toward expanding the coverage of interventions in resource-limited settings.

Dataset Information

Trends in Life Expectancy and Its Association with Economic Factors in the Belt and Road Countries-Evidence from 2000?2014.

Publications

Trends in Life Expectancy and Its Association with Economic Factors in the Belt and Road Countries-Evidence from 2000⁻2014.

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