scholarly journals Socioeconomic factors contributing to antibiotic resistance in China: a panel data analysis

2021 ◽  
Author(s):  
Xuemei Zhen ◽  
Jingchunyu Chen ◽  
Xueshan Sun ◽  
Qiang Sun ◽  
Shasha Guo ◽  
...  
Keyword(s):  
Panel Data ◽  
Socioeconomic Factors ◽  
Health Expenditure ◽  
Mainland China ◽  
Generation Cephalosporin ◽  
Gdp Per Capita ◽  
Physician Density ◽  
Hospital Bed ◽  
Per Capita ◽  
Economic Zone

Abstract Background The relationship between socioeconomic factors and ABR remains a knowledge gap in China. In this study, our aim was to examine the association between ABR proportion and socioeconomic factors across 30 provinces in mainland China. Methods We used two measures of ABR: the proportion of carbapenem-resistant Pseudomonas aeruginosa (CRPA), 3rd generation cephalosporin-resistant Klebsiella pneumoniae (3GCRKP), 3rd generation cephalosporin-resistant Escherichia coli (3GCREC), methicillin-resistant Staphylococcus aureus (MRSA); and the aggregate resistance. ABR proportion, education, gross domestic product (GDP) per capita, out-of-pocket (OOP) health expenditure, physician density, hospital bed density, access to water source, and number of public toilets per 10,000 population data during 2014 and 2018 in 30 provinces in mainland China were included. We examined the association between ABR level and potential contributing factors using panel data modelling. In addition, we explored this relationship from eastern, central, and western economic zone, respectively. Results Our results indicated that higher hospital bed density and physician density were significantly associated with lower levels of ABR. The issue of ABR was also related to socioeconomic factors such as GDP per capita, OOP health expenditure, education, which might depend on different resistant bacteria or different economic zones. GDP per capita was negatively associated with CRPA level, but positively associated with MRSA level. Higher OOP health expenditure was associated higher CRPA level. In addition, we only found that ABR prevalence was significantly negatively associated with education, and positively associated with OOP health expenditure in central economic zone, but not found in eastern and western economic zone. Conclusions Our study highlights that measures increasing hospital beds and physicians allocation to curb ABR should be implemented. Besides, intervention measures tackling the development and spread of ABR in China must better recognize and address the importance of social and economic determinants.

scholarly journals Socioeconomic Factors Contributing to Antibiotic Resistance in China: A Panel Data Analysis

Antibiotics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 994
Author(s):  
Xuemei Zhen ◽  
Jingchunyu Chen ◽  
Xueshan Sun ◽  
Qiang Sun ◽  
Shasha Guo ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Socioeconomic Factors ◽  
Health Expenditure ◽  
Mainland China ◽  
Generation Cephalosporin ◽  
Gdp Per Capita ◽  
Third Generation ◽  
Physician Density ◽  
Per Capita ◽  
Economic Zones

The relationship between socioeconomic factors and antibiotic resistance (ABR) prevalence remains a knowledge gap in China. In this study, our aim was to examine the association between ABR prevalence and socioeconomic factors across 30 provinces in mainland China. We used two measures of level of ABR: the proportion of methicillin-resistant Staphylococcus aureus (MRSA), third-generation cephalosporin-resistant Escherichia coli (3GCREC), and third-generation cephalosporin-resistant Klebsiella pneumoniae (3GCRKP), and the aggregate resistance. The data of ABR prevalence, education, gross domestic product (GDP) per capita, out-of-pocket (OOP) health expenditure, physician density, hospital bed density, and public toilet density during 2014 and 2018 in 30 provinces in mainland China were included. We examined the association between ABR prevalence and potential contributing socioeconomic factors using panel data modeling. In addition, we explored this relationship in the eastern, central, and western economic zones. Our results indicated that GDP per capita was significantly positively correlated with ABR in mainland China and the eastern economic zone; however, significantly positive associations did not exist in the central and western economic zones. Surprisingly, both higher GDP per capita and higher OOP health expenditure were associated with a higher level of MRSA, but a lower level of 3GCREC; higher physician density was associated with a lower level of MRSA, but a higher level of 3GCREC. In addition, ABR prevalence presented a decline trend during 2014 and 2018. Our study highlights that intervention measures tackling the development and spread of ABR in mainland China must better recognize and address the importance of social and economic determinants.

scholarly journals Interpretation of China’s 2017 health expenditure: a latent profile analysis of panel data

BMJ Open ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. e035512
Author(s):  
Shuang Zang ◽  
Meizhen Zhao ◽  
Jing OuYang ◽  
Xin Wang
Keyword(s):  
Panel Data ◽  
Health Expenditure ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Mainland China ◽  
Health Financing ◽  
Socioeconomic Indicators ◽  
Macroeconomic Factors ◽  
Per Capita ◽  
Latent Profile

ObjectiveTo explore the latent structure of health financing and the institutional distribution of health expenditure (focused on hospital expenditure) in provinces, autonomous regions and municipalities of mainland China, and to examine how these profiles may be related to their externalising and internalising characteristics.Study designThe study used panel data harvested from the China National Health Accounts Report 2018.MethodsMainland China’s provincial data on health expenditure in 2017 was studied. A latent profile analysis was conducted to identify health financing and hospital health expenditure profiles in China. Additionally, rank-sum tests were used to understand the difference of socioeconomic indicators between subgroups.ResultsA best-fitting three-profile solution for per capita health financing was identified, with government health expenditure (χ2=10.137, p=0.006) and social health expenditure (χ2=6.899, p=0.032) varying significantly by profiles. Health expenditure in hospitals was subject to a two-profile solution with health expenditure flow to urban hospitals, county hospitals and community health service centres having significant differences between the two profiles (p<0.001).ConclusionsPer capita health financing and health expenditure spent in hospitals have discrepant socioeconomic characteristics in different profiles, which may be attributed to macroeconomic factors and government policies. The study provided new and explicit ideas for health financing and health policy regulation in China.

scholarly journals Socioeconomic Determinants of Infant Mortality Rate in Asean: A Panel Data Analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Vita Kartika Sari ◽  
Dwi Prasetyani
Keyword(s):  
Health Status ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Strong Influence ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Per Capita

The infant mortality rate indicates the health status of a country. Previous studies have proven that socioeconomic factors have a significant influence on infant mortality rates in both developed and developing countries. Further studies on infant mortality rates are useful for public service strategic policy in the health sector. The main purpose of this study was to analyze the socioeconomic factors influencing infant mortality rates in ASEAN based on panel data estimates for 2000-2017. The dependent variable for this study was infant mortality rate, while the independent variables were health expenditure, female labor force, maternal fertility rate, and GDP per capita. The authors concluded that the main cause of infant mortality in ASEAN is care during delivery. Other influencing factors include family health status, maternal education level, and socio-economic inequality. This study found that the size of the female workforce has a strong influence on increasing the infant mortality rate in ASEAN. The fertility rate also had a strong influence on increasing infant mortality rate in ASEAN, while GDP per capita had a negative influence on infant mortality rate.  Health expenditure is proven to have no effect on the increase of infant mortality rates in ASEAN.

scholarly journals Commentary: on the effects of health expenditure on infant mortality in sub-Saharan Africa: evidence from panel data analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mwoya Byaro
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Random Effects ◽  
Health Expenditure ◽  
Panel Data Analysis ◽  
Health Expenditures ◽  
Sub Saharan Africa ◽  
Gdp Per Capita ◽  
Per Capita ◽  
Sub Saharan

Abstract Background This commentary assesses critically the published article in the Health Economics Review. 2020; 10 (1), 1–9. It explains the effects of health expenditure on infant mortality in sub-Saharan Africa using a panel data analysis (i.e. random effects) over the year 2000–2015 extracted from the World Bank Development Indicators. The paper is well written and deserve careful attention. Main text The main reasons for inaccurate estimates observed in this paper are due to endogeneity issue with random effects panel estimators. It occurs when two or more variables simultaneously affect/cause each other. In this paper, the presence of endogeneity bias (i.e. education, health, health care expenditures and real GDP per capita variables) and its omitted variable bias leads to inaccurate estimates and conclusion. Random effects model require strict exogeneity of regressors. Moreover, frequentist/classic estimation (i.e. random effects) relies on sampling size and likelihood of the data in a specified model without considering other kinds of uncertainty. Conclusion This comment argues future studies on health expenditures versus health outcomes (i.e. infant, under-five and neonates mortality) to use either dynamic panel (i.e. system Generalized Method of Moments, GMM) to control endogeneity issues among health (infant or neonates mortality), GDP per capita, education and health expenditures variables or adopting Bayesian framework to adjust uncertainty (i.e. confounding, measurement errors and endogeneity of variables) within a range of probability distribution.

The monetary value of disability-adjusted-life-years lost in Kenya in 2017.pdf

2019 ◽  
Author(s):  
Joses Kirigia ◽  
Rose Nabi Deborah Karimi Muthuri
Keyword(s):  
New York ◽  
International Monetary Fund ◽  
Health Expenditure ◽  
Analytical Framework ◽  
World Health ◽  
Gdp Per Capita ◽  
Current Health ◽  
Monetary Value ◽  
Life Years ◽  
Per Capita

<div>A variant of human capital (or net output) analytical framework was applied to monetarily value DALYs lost from 166 diseases and injuries. The monetary value of each of the 166 diseases (or injuries) was obtained through multiplication of the net 2019 GDP per capita for Kenya by the number of DALYs lost from each specific cause. Where net GDP per capita was calculated by subtracting current health expenditure from the GDP per capita. </div><div> </div><p>The DALYs data for the 166 causes were from IHME (Global Burden of Disease Collaborative Network, 2018), GDP per capita data from the International Monetary Fund world economic outlook database (International Monetary Fund, 2019), and the current health expenditure per person data from the WHO Global Health Expenditure Database (World Health Organization, 2019b). A model consisting of fourteen equations was calculated with Excel Software developed by Microsoft (New York).</p><p> </p>

Golf, supply and demand

2016 ◽  
Vol 23 (6) ◽  
pp. 1220-1234 ◽  
Author(s):  
E Bárcena-Martín ◽  
M Rodríguez-Fernández ◽  
S Borrego-Domínguez
Keyword(s):  
Panel Data ◽  
Financial Crisis ◽  
Stock Market ◽  
Supply And Demand ◽  
Dynamic Panel Data ◽  
Economic Situation ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
Stock Market Index ◽  
Per Capita

Macroeconomic conditions can have a substantial effect on the economic circumstances of individuals and therefore on the golf demand in a country. Using panel data on golf demand (number of golf players) and supply (number of courses), and indicators of the economic situation for 15 European countries, encompassing years 2000 through 2014, we estimate a dynamic panel data model in order to evaluate the influence of the economic conditions and golf supply on the number of registered golfers. Economic situation is assessed through two variables: the gross domestic product (GDP) and the main stock market index of each country. We also test the hypothesis of uneven effects of the GDP before and after the beginning of the economic recession. The most crucial finding is that from the start of the financial crisis, the level of GDP imposes statistically significant effect on golf demand, making those countries with higher GDP per capita the ones whose golf demand is harmed the least by the financial crisis. The number of golf players responds to the state of the economy after the start of the economic downturns, while the high persistence of the golf demand makes it rather difficult to find significant differences in the changes in GDP before the recession. We also find that the number of golf courses is not seen to bear a close relationship with the number of players unless we control for economic factors and business cycle. Within the economic factors, the level of development of a country, as measured by GDP per capita, outweighs stock market role in determining the demand for golf.

scholarly journals Evaluating the EKC Hypothesis for the BCIM-EC Member Countries under the Belt and Road Initiative

2020 ◽  
Vol 12 (4) ◽  
pp. 1478 ◽  
Author(s):  
Arifur Rahman ◽  
S. M. Woahid Murad ◽  
Fayyaz Ahmad ◽  
Xiaowen Wang
Keyword(s):  
Panel Data ◽  
Carbon Emission ◽  
Structural Breaks ◽  
Energy Use ◽  
Trade Openness ◽  
Gdp Per Capita ◽  
Ekc Hypothesis ◽  
Long Run ◽  
Short Run ◽  
Per Capita

This paper attempts to examine the environmental Kuznets curve (EKC) hypothesis for the BCIM-EC (Bangladesh–China–India–Myanmar economic corridor) member countries under the Belt and Road Initiative (BRI) of China. Both time series and panel data are covered, with respect to carbon dioxide (CO2) emissions, GDP per capita, energy use, and trade openness. For panel data analysis, GDP per capita and energy consumption have positive effects on CO2, while the effect of the quadratic term of GDP per capita is negative in the short-run. However, the short-run effects do not remain valid in the long-run, except for energy use. Therefore, the EKC hypothesis is only a short-run phenomenon in the case of the panel data framework. However, based on the Autoregressive Distributed Lag (ARDL) approach with and without structural breaks, the EKC hypothesis exists in India and China, while the EKC hypothesis holds in Bangladesh and Myanmar with regard to disregarding breaks within the short-run. The long-run estimates support the EKC hypothesis of considering and disregarding structural breaks for Bangladesh, China, and India. The findings of the Dumitrescu and Hurlin panel noncausality tests show that there is a unidirectional causality that runs from GDP per capita to carbon emission, squared GDP to carbon emission, and carbon emission to trade openness. Therefore, the BCIM-EC under the BRI should not only focus on connectivity and massive infrastructural development for securing consecutive economic growth among themselves, but also undertake a long-range policy to cope with environmental degradation and to ensure sustainable green infrastructure.

scholarly journals Title of Manuscript: Health System Performance Towards Universal Health Coverage in Iran: A Comparative Panel Data Analysis

2020 ◽  
Author(s):  
Haniye Sadat Sajadi ◽  
Zahra Goudarzi ◽  
Amirhossein Takian ◽  
Efat Mohamadi ◽  
Alireza Olyaeemanesh ◽  
...  
Keyword(s):  
Panel Data ◽  
Health System ◽  
Universal Health Coverage ◽  
Health Expenditure ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Health Coverage ◽  
System Efficiency ◽  
Per Capita ◽  
Universal Health

Abstract Background Building upon decades of continuous reforms, since 2014 under the banner of health transformation plan (HTP), Iran has been implementing various initiatives to strengthen its health system. Improving efficiency of the health system is fundamental to achieve better performance and reach universal health coverage (UHC). This article aimed to measure the efficiency and productivity changes in the Iranian health system during 2010-2015 in comparison with 36 selected other upper-middle income countries. Methods We used panel data to measure the variations in technical efficiency (TE) and total factor productivity (TFP) through an extended data envelopment analysis (EDEA) and Malmquist productivity index, respectively. General Government Health Expenditure (GGHE) per capita (International dollar) was selected as input variable. Service coverage of diphtheria, tetanus and pertussis; family planning; antiretroviral therapy; skilled attendants at birth; Tuberculosis treatment success rate; and GGHE as % of Total Health Expenditure (THE) were considered as output variables. The data for each indicator were taken from Global Health Observatory data repository and World Development Indicator database, for a period of six years (2010-2015). Results The TE scores of Iran’s health system were 0.75, 0.77, 0.74, 0.74, 0.97 and 0.84 in the period 2010-2015, respectively. TFP improved in 2011 (1.02), 2013 (1.01), and 2014 (1.30, generally). The overall efficiency and TFP increased in 2014. Changes made in CCHE per capita and GGHE/THE attributed to the increase of efficiency. ConclusionThere is a growing demand for efficiency improvements in the health systems to achieve UHC. While there are no defined set of indicators or precise methods to measure heath system efficiency, EDEA helped us to draw the picture of health system efficiency in Iran. Our findings also highlighted the essential need for targeted and sustained interventions, i.e. allocation of enough proportion of public funds to the health sector, to improve universal financial coverage against health costs aiming to enhance the future performance of Iran’s health system, ultimately. Such tailored interventions may be also useful for settings with similar context to speed up their movement towards improving efficiency, which in turn might lead to more resources to reach UHC.

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