Structural Equation Modeling-Partial Least Square for Poverty Modeling in Papua Province

Poverty in Papua Province in 2018 has increased from the previous year. The poverty rate in Papua Province in March 2018 reached 27,74%. This study aims to analyze the factors that influence it so that it can be handled properly. The research method used in this research is Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach. The research variables used consisted of 4 latent variables (Poverty, Economy, Human Resources (HR), and Health) with 16 indicators (manifest variables). Based on the analysis that has been done, it is found that economic and health variables have a negative and significant effect on poverty with path coefficients of -0,421 and -0,270, respectively. The health variable has a positive and significant effect on HR with a path coefficient of 0,496. Meanwhile, the HR variable has a positive and significant effect on the economy with a path coefficient of 0,801. It can be concluded that there are two variables that have a significant effect on poverty in Papua Province, including the economy and health.

Gender equality and extreme poverty alleviation in sub-Saharan Africa

This article assesses the link between the four pillars of gender equality and extreme poverty in sub-Saharan Africa. Accordingly, the objective of the paper is to empirically examine whether the four pillars of gender equality, namely women’s health, women education, political participation of women and economic participation facilitate extreme poverty alleviation in sub-Saharan Africa. Data were collected from the World Bank development indicators and World Economic Forum Global Gender Gap Index for 25 sub-Saharan African countries whose data appear on both indexes for three years into the SDGs era. Th e paper applied a quantitative approach with secondary data on poverty gap index drawn from the World Economic Forum Poverty Gap Index for sub-Saharan Africa. Data for twenty-fi ve sub-Saharan African countries were analysed using the fi xed-eff ect panel data regression approach using the Hauseman model selection test. Findings from the analysis indicate that, ceteris paribus, an increase in the threegender equity variables namely economic participation of women, education of women and political participation and leadership of women in sub-Saharan Africa has a signifi cant potential to reduce extreme poverty in sub-Saharan Africa within the sample of study. Since the fi ndings of this study have shown that extreme poverty can be reduced through increased women participation in economic activity, education and leadership, the SDG of poverty alleviation can be improved in sub-Saharan Africa through better government provision of economic, educational and leadership opportunities for women such as providing women with free-interest small business start-up funds, free education for women and supporting women to ascend and survive in political and leadership positions in sub-Saharan Africa through a balanced quota for female leadership positions. Given that the women’s health variable did not prove to be signifi cant on extreme poverty, further research is recommended to separate the health variable into rural health and urban health variables in order to examine the possibility that either of the health clusters might contribute signifi cantly to reducing extreme poverty. Th is paper contributes to existing literature by providing an empirical evidence to show that gender equality in sub-Saharan Africa is a viable policy strategy for achieving the SDGs 2030 Agenda of extreme poverty eradication in sub-Saharan Africa; the paper also provides empirical model for future study.

IBN KHALDUN MODEL ON POVERTY: THE CASE OF ORGANIZATION OF ISLAMIC CONFERENCE (OIC) COUNTRIES

If we consider the state of the world economy, especially in the OIC countries, somecountries have to struggle in dealing with the problems of poverty. Hypothetically,the wealth of natural resources is potentially in the welfare of the population, but thefacts on the ground say the situation is another in which it is far from being wellbeing.This study aims to analyze poverty in OIC countries by using a developmentmodel proposed by Ibn Khaldun. The model consists of six variables: human resourcevariable (proxy HDI), the variable role of government (proxy government spendingin education and health), variable of development (proxy foreign direct investment),state assets variable (proxy for GDP/capita), justice variable (gini index proxy) andsharia variable (a proxy perception index of corruption). This study uses panel dataregression analysis with nine object OIC member countries (Indonesia, Malaysia,Egypt, Azerbaijan, Kazakhstan, Tajikistan, Kyrgyzstan, Turkey and Benin) over theyears from 2010 to 2016. The results showed that the variables of development modelIbn Khaldun significant effect on poverty in OIC countries is development variable, thevariable role of government (proxy for government spending in health sector), justicevariable, wealth nation variable and control variables (unemployment). While the roleof government variable (proxy government spending in the education sector), HRvariables and sharia variables not significant. From these studies, it can be concludedthat not all the variables of development model Ibn Khaldun significant effect onpoverty in OIC countries.

Pengaruh Kondisi Kesehatan Lingkungan Terhadap Kepuasan dan Jumlah Kunjungan Pasien di Puskesmas Kota Pekanbaru

Given the importance of environmental health at puskesmas in the environmental health care system to create a healthy environment that can provide protection for patients and puskesmas. This study aims to analyze the partial and simultaneous influence between the buildings outside, building in the building, sanitation facilities and hygiene management on environmental health condition, analyze the effect of Puskesmas environment condition to the satisfaction and number of patient visit at Pekanbaru Health Center. This study used survey methods conducted at all public health centers in Pekanbaru City from April to August 2017. The sample size was 20 Puskesmas and 400 patients visited the Puskesmas. The tools and materials used in this research are observation instruments and use checklists and questionnaire interview instruments (questionnaires). The partial simultaneous effect of outbuildings, in-building buildings, sanitation facilities and hygiene management on the health condition of the puskesmas was used multiple regression tests, with the result of correlation of the condition of outsides to 0.321 outbuildings, buildings in 0.834, sanitation facilities 0.876 and cleanliness management 0.640. The direction of positive relationships shows the greater the assessment of the four variables will increasingly make the score of environmental health assessments getting bigger as well. Influence of health condition of environment of puskesmas toward patient satisfaction using multiple linear regression test and the result is 0,669. This shows a strong influence between environment health variable of puskesmas and satisfaction of respondent who come to visit puskesmas. R Square 0,448 or coefficient of determination mean 44,8% satisfaction of respondent can be explained by environment health variable of puskesmas. The influence of health condition of puskesmas on the number of patient visit using simple linear regression test and the result is 0,628. This shows a strong correlation between environment health variables of puskesmas with respondent visit coming to visit puskesmas. R Square 0,394 or coefficient of determination mean 39,4% of respondent visit can be explained by environment health variable of puskesmas while the rest is explained by other cause. It is necessary to increase health promotion and education about the importance of environmental health of puskesmas for the community about the health condition of the environment that fulfill the health requirement and increasing the role of Dinas Kesehatan in supervision of health of puskesmas environment to be better and become the reference of accreditation of puskesmas according to standard from the Ministry of Health RI.

The Measurement of Health Inequalities: Does status matter?

The measurement of health inequalities usually involves either estimating the concentration of health outcomes using an income-based measure of status or applying conventional inequality-measurement tools to a health variable that is non-continuous or, in many cases, categorical. However, these approaches are problematic as they ignore less restrictive approaches to status. The approach in this paper is based on measuring inequality conditional on an individual's position in the distribution of health outcomes: this enables us to deal consistently with categorical data. We examine several status concepts to examine self-assessed health inequality using the sample of world countries contained in the World Health Survey. We also perform correlation and regression analysis on the determinants of inequality estimates assuming an arbitrary cardinalisation. Our findings indicate major heterogeneity in health inequality estimates depending on the status approach, distributional-sensitivity parameter and measure adopted. We find evidence that pure health inequalities vary with median health status alongside measures of government quality.

Estimates of the Relative Risk of Mortality Based on the Ontario Longitudinal Study of Aging

ABSTRACTData from the Ontario Longitudinal Study of Aging were analyzed to examine the associations of the independent variables income, income change, education, smoking and perceived health with the dependent variable mortality during a ten year follow-up beginning in 1969. The analyses investigate the associations of the independent variables with deaths, with other causes of attrition and with all causes of attrition. The results indicate that smoking is the strongest predictor of mortality, and income is the strongest socioeconomic predictor. The analyses also show that perceived health measured prior to the mortality follow-up masks the association between the independent variables and mortality. Since the exclusion of the perceived health variable did not appreciably reduce the fit of the models, it was omitted from further analyses. The distributions of mortality for the various independent variables differed appreciably between models using deaths and all causes, but the bivariate and multivariate associations between variables were relatively unaffected by the alternative methods of operationalizing the dependent variable.