Dataset Information

Income-related inequality in distribution of health human resource among districts of Pakistan.

ABSTRACT:

Background

Solving inequality of health human resource (HHR) is one of the motives of Pakistan health policies, however, there is still exists a massive quantity of HHR inequality in almost every district of Pakistan. The main goal of this research is to scrutinize the disparity in allocation of human health resources among 114 regions of Pakistan from the year 2012 to 2016 and to expose the foundations and aspects of HHR inequality.

Methods

The data regarding this research has been obtained from Pakistan Statistical Bureau from the year 2012 to 2016. The statistics had also been collected from United Nation Development Program (UNDP) Pakistan 2017, Pakistan economic surveys, Ministry of finance Islamabad, Pakistan, Pakistan Social and Living standards Measurement (PSLM) Surveys from 2012 to 2016. The information incorporates district wise; the number of specialists and medical caretakers those are doctors and nurses, number of hospitals, number of beds, number of dispensaries, number of beds in dispensaries, urbanization, total estimated GNI per capita, infant mortality rate, geographical area, and population size. The concentration index is used to compute the extent of disparity in allocation of human health resources and decomposition analysis is also carried out to enumerate the contribution of each variable towards total inequality. Furthermore, the horizontal concentration was used to measure the participation of the need variable.

Results

7. The consequent Concentration Indexes (CI) of the doctors and nurses for the year 2016 are 0.60 (95% CI= 0.42, 0.78) and 0.67 (95% CI= 0.42, 0.92) respectively. Decomposition of the concentration indexes exposed that the monetary status accounts are the leading percentage contributor in doctors disparity (77.5, 44.9, 30.6, -?11.6% and 13%) and population size (-?20.7,-10.5%, 4.6, 49.8, 19.7%). Furthermore, the monetary status formulates the superior contribution HHR disparity from nurses inequality (104.5, 75.1, 59.2, -?54.3%, -?40.1%), and population size (-?53.7, -?53.6%, -?36.3, 83.8, 65.3%). Moreover, after the identification of the need variable the Horizontal Concentration Index (HCI) values of doctors from the year 2012 to 2016 are 0.62, 0.64, 0.63, 0.62 and 0.61 and HCI of the nurses are 0.69, 0.70, 0.69, 0.68 and 0.67.

Conclusion

The pro-rich disparity in allocation of HHR has been scrutinized from the year 2012 to 2016 among 114 districts of Pakistan. The hard concern of HHR disparity should be concentrated by the complete procedures from a multidisciplinary approach.

SUBMITTER: Nawaz R

PROVIDER: S-EPMC7885567 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Income-related inequality in distribution of health human resource among districts of Pakistan.

Nawaz Rashed R Zhou Zhongliang Z Khalid Neelum N Cao Dan D Liu Guanping G Ren Yangling Y Zhao Dantong D Zhao Yaxin Y Chen Yaru Y

BMC health services research 20210215 1

<h4>Background</h4>Solving inequality of health human resource (HHR) is one of the motives of Pakistan health policies, however, there is still exists a massive quantity of HHR inequality in almost every district of Pakistan. The main goal of this research is to scrutinize the disparity in allocation of human health resources among 114 regions of Pakistan from the year 2012 to 2016 and to expose the foundations and aspects of HHR inequality.<h4>Methods</h4>The data regarding this research has be ...[more]

PMID: 33588831

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Project description:ObjectiveHealth equality has drawn much public attention in both developed and developing countries. China, the largest developing country, has implemented a new round of health system reform to improve health equality since 2009. This study aims to examine the magnitude and sources of income-related health inequality in western rural regions of China.MethodsData were obtained from the Survey of Rural Economic and Social Development in Western China conducted in 2014, in which 14,555 individuals from 5,299 households in 12 provinces were included. Health outcome variables of interest were self-rated health status, prevalence of chronic disease and four-week illness. Concentration index was calculated to assess magnitude of income-related health inequality, and nonlinear decomposition analysis was performed to identify the sources of health inequality.ResultsThe Concentration indexes for poor self-rated health status, prevalence of chronic disease and four-week illness were -0.0898 (P<0.001),-0.0860 (P<0.001) and -0.1284 (P<0.001), respectively. Income and education were two main sources of health inequality, accounting for about 25-50% and 15% contribution to the inequality. Ethnicity made <10% contribution to income-related health inequality, and enrollment in New Rural Cooperative Medical Scheme contributed to <1%.ConclusionThis study found slight income-related health inequality among rural residents in western China, implying that although China has made substantial progress in economic development and poverty alleviation, health inequality in western rural region should still be concerned by the government. To achieve health equality further, the Chinese government should not only strengthen its reimbursement mechanism of the current health insurance scheme to improve affordability of primary healthcare for residents in western rural regions, but also implement health poverty alleviation policies targeting socioeconomically vulnerable population and ethnic minorities in future.

Project description:BACKGROUND:Several studies have confirmed the existence of a significant positive relationship between income and health. Conventional regression techniques such as Ordinary Least Squares only help identify the effect of the covariates on the mean of the health variable. In this way, important information of the income-health relationship could be overlooked. As an alternative, we apply and compare unconventional regression techniques. METHODS:We adopt a distributional approach because we want to allow the effect of income on health to vary according to people's health status. We start by analysing the income-health relationship using a distributional regression model that falls into the GAMLSS (Generalized Additive Models for Location, Scale and Shape) framework. We assume a gamma distribution to model the health variable and specify the parameters of this distribution as linear functions of a set of explanatory variables. For comparison, we also adopt a quantile regression analysis. Based on predicted health quantiles, we use both a parametric and a non-parametric approach to estimate the lower tail of the health distribution. RESULTS:Our data come from Wave 13 of the Household, Income and Labour Dynamics in Australia (HILDA) survey, collected in 2013-2014. According to GAMLSS, we find that the risk of ending up in poor, fair or average health is lower for those who have relatively high incomes ($80,000) than for those who have relatively low incomes ($20,000), for both smokers and non-smokers. In relative terms, the risk-lowering effect of income appears to be the largest for those who are in poor health, again for both smokers and non-smokers. The results obtained on the basis of quantile regression are to a large extent comparable to those obtained by means of GAMLSS regression. CONCLUSIONS:Both distributional regression techniques point in the direction of a non-uniform effect of income on health, and are therefore promising complements to conventional regression techniques as far as the analysis of the income-health relationship is concerned.

Dataset Information

Income-related inequality in distribution of health human resource among districts of Pakistan.

Background

Methods

Results

Conclusion

Publications

Income-related inequality in distribution of health human resource among districts of Pakistan.

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