scholarly journals The Effects of Smoking, Regular Drinking, and Unhealthy Weight on Healthcare Utilization in China

2020 ◽  
Author(s):  
Changle Li ◽  
Zhengzhong Mao ◽  
Caixia Yu
Keyword(s):  
Healthcare Utilization ◽  
Inpatient Care ◽  
Fixed Effects ◽  
Health Care Use ◽  
Healthy Weight ◽  
Obese People ◽  
Data Set ◽  
Former Smokers ◽  
The Government ◽  
Unhealthy Weight

Abstract Background: The preventable risk factors such as smoking, harmful drinking, and unhealthy weight have contributed to the accelerated rise in non-communicable chronic diseases that are dominant drivers of health care use and spending in China. This study aimed to ascertain the effects of smoking, regular drinking, and unhealthy weight on healthcare utilization in China. Methods: The database used in this study was obtained from the China Family Panel Studies (CFPS), and the final sample consisted of 63,260 adults in all the five waves of data collection. The fixed effects logistic regression model was used for the analysis. Results: The current study found that among Chinese adults, current and former smokers were more likely to use outpatient and inpatient care compared to those who never smoked. Former smokers increased the odds of using outpatient and inpatient care than current smokers. Moreover, compared to healthy weight people, obese people increased the likelihood of using outpatient and inpatient care, and overweight people were more likely to be hospitalized. In contrast, people who regularly drank alcohol were less likely to use outpatient and inpatient care than non-regular drinkers. Conclusion: This study ascertained the effects of smoking, regular drinking, and unhealthy weight on healthcare utilization in China using a five-waves of balanced panel data set. These results may have important implications for supporting the government to make healthcare resources allocation decisions.

scholarly journals The Effects of Smoking, Regular Drinking, and Unhealthy Weight on Healthcare Utilization in China

2020 ◽  
Author(s):  
Changle Li ◽  
Zhengzhong Mao ◽  
Caixia Yu
Keyword(s):  
Healthcare Utilization ◽  
Inpatient Care ◽  
Fixed Effects ◽  
Health Care Use ◽  
Healthy Weight ◽  
Obese People ◽  
Data Set ◽  
Former Smokers ◽  
The Government ◽  
Unhealthy Weight

Abstract Background: The preventable risk factors such as smoking, harmful drinking, and unhealthy weight have contributed to the accelerated rise in non-communicable chronic diseases that are dominant drivers of health care use and spending in China. This study aimed to ascertain the effects of smoking, regular drinking, and unhealthy weight on healthcare utilization in China. Methods: The database used in this study was obtained from the China Family Panel Studies (CFPS), and the final sample consisted of 63,260 adults in all the five waves of data collection. The fixed effects logistic regression model was used for the analysis. Results: The current study found that among Chinese adults, current and former smokers were more likely to use outpatient and inpatient care compared to those who never smoked. Former smokers increased the odds of using outpatient and inpatient care than current smokers. Moreover, compared to healthy weight people, obese people increased the likelihood of using outpatient and inpatient care, and overweight people were more likely to be hospitalized. In contrast, people who regularly drank alcohol were less likely to use outpatient and inpatient care than non-regular drinkers. Conclusion: This study ascertained the effects of smoking, regular drinking, and unhealthy weight on healthcare utilization in China using a five-waves of balanced panel data set. These results may have important implications for supporting the government to make healthcare resources allocation decisions.

scholarly journals The effects of smoking, regular drinking, and unhealthy weight on health care utilization in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Changle Li ◽  
Zhengzhong Mao ◽  
Caixia Yu
Keyword(s):  
Health Care ◽  
Health Care Utilization ◽  
Outpatient Care ◽  
Inpatient Care ◽  
Fixed Effects ◽  
Care Utilization ◽  
Healthy Weight ◽  
Obese People ◽  
Former Smokers ◽  
Unhealthy Weight

Abstract Background Preventive risk factors such as smoking, drinking, and unhealthy weight have contributed to the accelerated rise in noncommunicable chronic diseases, which are dominant drivers of health care utilization and spending in China. However, few studies have been conducted using a large longitudinal dataset to explore the impact of such preventive risk factors on health care utilization. Therefore, this study aimed to ascertain the effects of smoking, regular drinking, and unhealthy weight on health care utilization in China. Methods This research was a longitudinal study using data from five waves of the China Family Panel Studies (CFPS) conducted between 2010 and 2018, and the final sample consisted of 63,260 observations (12,652 participants) across all five waves of data collection. Health care utilization was measured from two perspectives: outpatient utilization and inpatient utilization. Smoking status was categorized as never smoker, former smoker, or current smoker. Unhealthy weight was classified based on the participants’ body mass index. A fixed effects logistic regression model was used for the analysis. Results The results of fixed effects logistic regression showed that current and former smokers were approximately 1.9 times and 2.0 times more likely to use outpatient care than those who never smoked, respectively (odds ratio (OR) = 1.88, p < 0.05; OR = 2.03, p < 0.05). Obese people were approximately 1.3 times more likely to use outpatient care than healthy weight people (OR = 1.26, p < 0.05). Moreover, the results show that compared to those who never smoked, for current and former smokers, the odds of being hospitalized increased by 42.2 and 198.2%, respectively (OR = 1.42; p < 0.1, OR = 2.98; p < 0.05). Compared to healthy weight people, overweight and obese people were also more likely to be hospitalized (OR = 1.11; p < 0.1, OR = 1.18; p < 0.1, respectively). Conclusion Among Chinese adults, current and former smokers were more likely to use outpatient and inpatient care than those who had never smoked. Moreover, compared to healthy weight people, obese people were more likely to use outpatient and inpatient care, and overweight people were more likely to use inpatient care. These results may have important implications that support the government in making health care resource allocation decisions.

scholarly journals Healthcare Utilization of Below Poverty Line Population under Government-Funded Health Protection Scheme in one sub-district in Bangladesh: A Cross-Sectional Study

2021 ◽  
Author(s):  
Md. Zahid Hasan ◽  
Mohammad Wahid Ahmed ◽  
Gazi Golam Mehdi ◽  
Jahangir AM Khan ◽  
Ziaul Islam ◽  
...  
Keyword(s):  
Healthcare Utilization ◽  
Inpatient Care ◽  
Household Survey ◽  
Poverty Line ◽  
Cross Sectional Study ◽  
Hospital Inpatient ◽  
Cross Sectional ◽  
Protection Scheme ◽  
The Government ◽  
Hospital Inpatient Care

Abstract BackgroundThe below poverty line (BPL) population in rural Bangladesh have low access to hospital inpatient-care (IPC) services. The Government of Bangladesh (GoB) launched pilot Shasthyo Suroksha Karmasuchi (SSK) at Kalihati Upazila of Tangail district in 2016 aiming to improve IPC access of the BPL population and financial protection for healthcare. The GoB funded scheme provides IPC for 78 diseases and outpatient consultation through an existing health facility. In this study, we aimed to assess the level of healthcare utilization among the scheme beneficiaries and identify the associated factors with utilization.MethodsThis was an exploratory study with a cross-sectional household survey conducted from July to September 2018 among 806 sampled households using a structured questionnaire. Data on illness and healthcare utilization was collected from the selected households for the last 90 days of the interview date. A logistic regression model was applied to determine the factors associated with healthcare utilization from SSK facility.ResultsOverall, 8% of the ill patients in the last 90 days prior to survey sought healthcare from SSK facilities (n=639; total patients who sought care), 28% from medically trained providers (MTPs), and 64% from non-MTPs. Of the 23 (3.6%) patients who sought inpatient care (IPC), less than half (10 patients) of them utilized IPC under SSK. Individuals with accident/injury, unemployed, having knowledge about SSK, non-BPL status, were more likely to utilize healthcare from SSK facility. Individuals reside more than 15 km away from facility, had 4-5 family members, and above secondary level education were less likely to utilize care from SSK facility.Conclusions It is evident that healthcare utilization of beneficiaries from the SSK scheme was very low. Effective strategies for enhancing knowledge on SSK benefits and precise BPL households targeting can be instrumental in increasing utilization of the scheme. The scheme also has a potential to bring the individuals under its coverage who utilize healthcare from other MTP and non-MTP.

scholarly journals Human Capital Formation and Economic Growth in Emerging Asia: Empirical Evidence Using Panel Data

2020 ◽  
Vol 3 (2) ◽  
pp. 205-212
Author(s):  
Muhammad Atiq-ur- Rehman ◽  
Suleman Ghaffar ◽  
Kanwal Shahzadi ◽  
Rabail Ghazanfar
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Panel Data ◽  
Fixed Effects ◽  
Random Effect ◽  
Capital Formation ◽  
Human Capital Formation ◽  
Data Set ◽  
The Government ◽  
The Impact

After the emergence of endogenous growth theory, the role of human capital along with physical capital is considered to be imperative in promoting economic growth. The government social sector spending, mainly on education and health, contributes in forming human capital and promotes economic growth. This study examines the impact of health and education provisions on economic growth of emerging Asian economies, including Bangladesh, China, India, Indonesia, Malaysia, Pakistan, Philippine, and Thailand. Using the data set for 1995-2018, the fixed effects (FE) and the random effect (RE) methods of panel data estimation are employed. Both methods reveal that the health and education support the human capital formation and stimulate economic growth.

scholarly journals Healthcare Utilization of Below Poverty Line Population under Government-Funded Health Protection Scheme in One Sub-district in Bangladesh: A Cross-Sectional Study

2021 ◽  
Author(s):  
Md. Zahid Hasan ◽  
Mohammed Wahid Ahmed ◽  
Gazi Golam Mehdi ◽  
Jahangir A. M. Khan ◽  
Ziaul Islam ◽  
...  
Keyword(s):  
Healthcare Utilization ◽  
Inpatient Care ◽  
Household Survey ◽  
Poverty Line ◽  
Cross Sectional Study ◽  
Hospital Inpatient ◽  
Cross Sectional ◽  
Protection Scheme ◽  
The Government ◽  
Hospital Inpatient Care

Abstract Background The below poverty line (BPL) population in rural Bangladesh have low access to hospital inpatient-care (IPC) services. The Government of Bangladesh (GoB) launched pilot Shasthyo Suroksha Karmasuchi (SSK) at Kalihati Upazila of Tangail district in 2016 aiming to improve IPC access of the BPL population and financial protection for healthcare. The GoB funded scheme provides IPC for 78 diseases and outpatient consultation through an existing health facility. In this study, we aimed to assess the level of healthcare utilization among the scheme beneficiaries and identify the associated factors with utilization. MethodsThis was an exploratory study with a cross-sectional household survey conducted from July to September 2018 among 806 sampled households using a structured questionnaire. Data on illness and healthcare utilization was collected from the selected households for the last 90 days of the interview date. A logistic regression model was applied to determine the factors associated with healthcare utilization from SSK facility. ResultsOverall, 8% of the ill patients in the last 90 days prior to survey sought healthcare from SSK facilities (n=639; total patients who sought care), 28% from medically trained providers (MTPs), and 64% from non-MTPs. Of the 23 (3.6%) patients who sought inpatient care (IPC), less than half (10 patients) of them utilized IPC under SSK. Individuals with accident/injury, unemployed, having knowledge about SSK, non-BPL status, were more likely to utilize healthcare from SSK facility. Individuals reside more than 15 km away from facility, had 4-5 family members, and above secondary level education were less likely to utilize care from SSK facility. Conclusions It is evident that healthcare utilization of beneficiaries from the SSK scheme was very low. Effective strategies for enhancing knowledge on SSK benefits and precise BPL households targeting can be instrumental in increasing utilization of the scheme. The scheme also has a potential to bring the individuals under its coverage who utilize healthcare from other MTP and non-MTP.

scholarly journals Association between participation in the government subsidy programme for domestic travel and symptoms indicative of COVID-19 infection in Japan: cross-sectional study

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e049069
Author(s):  
Atsushi Miyawaki ◽  
Takahiro Tabuchi ◽  
Yasutake Tomata ◽  
Yusuke Tsugawa
Keyword(s):  
Sore Throat ◽  
Fixed Effects ◽  
Cross Sectional Study ◽  
High Fever ◽  
Internet Survey ◽  
Government Subsidy ◽  
Sampling Weights ◽  
Cross Sectional ◽  
Taste Disorder ◽  
The Government

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.

scholarly journals Mediating distributive politics: political alignment and electoral business cycle effects on municipality financing in Greece

2021 ◽  
Author(s):  
Anastasios Kitsos ◽  
Antonios Proestakis
Keyword(s):  
Business Cycle ◽  
Fixed Effects ◽  
Central Government ◽  
Intergovernmental Transfers ◽  
Negative Effects ◽  
National Elections ◽  
Data Set ◽  
Resource Misallocation ◽  
Run Up ◽  
Political Alignment

AbstractWe examine the role of political alignment and the electoral business cycle on municipality revenues in Greece for the period 2003–2010. The misallocation of resources for political gain represents a waste of resources with significant negative effects on local growth and effective decentralization. The focus of our analysis is municipality mayors since they mediate the relationship between central government and voters and hence can influence the effectiveness of any potential pork-barrelling activity. A novel panel data set combining the results of two local and three national elections with annual municipality budgets is used to run a fixed-effects econometric model. This allows us to identify whether the political alignment between mayors and central government affects municipality financing. We examine this at different stages of local and national electoral cycles, investigating both direct intergovernmental transfers (grants) and the remaining sources of local revenues (own revenues, loans). We find that total revenues are significantly higher for aligned municipalities in the run-up to elections due to higher intergovernmental transfers. We also find evidence that the 2008 crisis has reduced such pork-barrelling activity. This significant resource misallocation increases vertical networking dependency and calls for policy changes promoting greater decentralization and encouraging innovation in local revenue raising.

Twitter users exhibited coping behaviours during the COVID-19 lockdown: an analysis of tweets using mixed methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mittal ◽  
Wasim Ahmed ◽  
Amit Mittal ◽  
Ishan Aggarwal
Keyword(s):  
Data Analysis ◽  
The Body ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Long Run ◽  
The World ◽  
Twitter Users ◽  
The Government ◽  
Using Data

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.

An Experimental Study of Spammer Detection on Chinese Microblogs

2020 ◽  
Vol 30 (11n12) ◽  
pp. 1759-1777
Author(s):  
Jialing Liang ◽  
Peiquan Jin ◽  
Lin Mu ◽  
Jie Zhao
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
User Behavior ◽  
Real Data ◽  
User Profile ◽  
Data Set ◽  
Sina Weibo ◽  
Factors Affecting ◽  
The Government ◽  
Hot Event

With the development of Web 2.0, social media such as Twitter and Sina Weibo have become an essential platform for disseminating hot events. Simultaneously, due to the free policy of microblogging services, users can post user-generated content freely on microblogging platforms. Accordingly, more and more hot events on microblogging platforms have been labeled as spammers. Spammers will not only hurt the healthy development of social media but also introduce many economic and social problems. Therefore, the government and enterprises must distinguish whether a hot event on microblogging platforms is a spammer or is a naturally-developing event. In this paper, we focus on the hot event list on Sina Weibo and collect the relevant microblogs of each hot event to study the detecting methods of spammers. Notably, we develop an integral feature set consisting of user profile, user behavior, and user relationships to reflect various factors affecting the detection of spammers. Then, we employ typical machine learning methods to conduct extensive experiments on detecting spammers. We use a real data set crawled from the most prominent Chinese microblogging platform, Sina Weibo, and evaluate the performance of 10 machine learning models with five sampling methods. The results in terms of various metrics show that the Random Forest model and the over-sampling method achieve the best accuracy in detecting spammers and non-spammers.

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