我国居民与收入相关的健康不平等实证研究

本文利用中国健康与营养调查（CHNS）2006年的调查数据，从定量的角度对我国居民与收入相关的健康不平等进行了分析。本文利用有序Probit模型获得了自评健康数据背后的实际健康得分，在此基础上计算健康集中指数衡量我国居民与收入相关的健康不平等程度。结果表明，我国居民的健康不平等问题较为严重，健康不平等问题在城乡之间和不同经济发展水平地区之间存在着较大的差别。     

与收入相关的健康不平等及其分解

目的:测量与收入相关的自评健康不平等程度,并分析各因素的贡献。方法:利用家庭健康询问调查数据,采用集中指数法测量居民基于收入的自评健康不平等程度及各因素对自评健康不平等的贡献。结果:不同收入人群的自评健康有差异,集中指数为0.034,仍存在亲富人的健康不平等;各因素对自评健康不平等的贡献中,收入贡献率为46.30%,地区为22.00%,性别-年龄为13.80%,城乡类型为10.10%,文化程度为7.20%。结论:收入和地区因素对自评健康不平等贡献较大;改善收入分配、缩小地区间发展差距、加快城乡一体化建设、推进教育公平等有利于降低健康不平等。     

经济状况相关的老年人健康不平等演变研究——基于CHARLS的实证研究

目的了解我国经济状况相关的老年人健康不平等及其来源和变化。方法利用"中国健康与养老追踪调查"(CHARLS)2008年和2012年的面板数据,采用集中指数及Oaxaca分解法分析居民健康状况与水平公平目标的差距和不平等产生的因素及其演变。结果 2008年和2012年健康自评得分的集中指数分别为0.085和0.049,存在亲富人的健康不平等现象,高收入人群的健康自评得分更高。健康不平等主要来源为收入、职业、受教育程度和生活行为习惯等。收入因素对不平等的变化起到主要作用,占83.05%,并且主要是由于收入对健康自评得分的弹性变化引起的。结论应该以全面深化改革为契机,通过降低居民的收入差距,全面提高社会保障水平来降低收入不平等对老年人健康的不利影响。     

我国农村居民不同社会经济地位群体之间的健康差距

目的：考察我国农村居民不同社会经济地位群体之间的健康差距。资料与方法：主要依据全国31个省份2003—2006年农村固定观察点数据,计算不同社会经济地位群体的组间健康集中指数。结果：在我国农村居民中,社会经济地位较好的人群在健康方面享有优势;不同收入组间的健康不平等程度大于不同教育程度组间的健康不平等程度;收入较低和受教育程度较高的人群更容易患上慢性病。讨论：自评健康与收入的相关性要强于其与教育的相关性;受教育程度高的人群更容易患上慢性病,其原因可能与缺乏身体锻炼有关。结论：在我国农村居民中,不同社会经济地位群体间确实存在系统性的健康差异,但这种差异小于个体间的健康差异。     

我国农村居民健康及健康不平等的变化分析

通过CHNS数据考察1997～2006年期间健康及健康不平等的变化。研究发现:农村居民的健康水平下降,患病严重程度增加,感染性疾病与慢性疾病的双重存在;健康不平等总体上呈现扩大趋势,高收入群体比低收入群体享有更高的平均健康水平,但健康不平等的程度并不是很严重。     

收入相关健康不平等实证研究

本文应用自报健康资料测算了上海市4区（县）的健康集中指数，考察收入相关健康不平等。研究不仅从实证角度阐述了收入相关健康不平等的测算方法，而且研究结果表明在样本地区存在收入相关健康不平等，并提示改善低收入人群的经济状况特别是收入状况对改善健康的重要性。     

我国流动人口的健康不平等测量及其分解

目的:了解我国流动人口的健康不平等状况及其影响因素,为促进流动人口健康公平提供参考。方法:利用大样本调查数据,采用SPSS 21.0进行回归分析,测算健康集中指数并对其分解。结果:流动人口存在亲富人的健康不平等,但是程度小于农村人口和所在城市户籍人口,收入是影响健康不平等的最主要因素。结论:人口流动有利于促进城乡居民健康平等,促进流动人口的健康平等需要重点关注低收入、女性、年龄较大、教育程度较高和已婚等人群。     

0～3岁儿童照顾模式与健康不平等关系

目的了解0～3岁儿童照顾模式与健康不平等的关系,为促进儿童健康发展提供参考依据。方法收集中国家庭追踪调查(CFPS)2018年全国数据,从中抽取1 837名0～3岁儿童,采用集中指数与分解的方法测量儿童健康不平等状况及相关贡献因素,重点分析照顾模式对儿童健康不平等的贡献。结果全国0～3岁儿童健康不平等指数为0.039,表明我国存在与社会经济地位相关的儿童健康不平等,来自高收入家庭的儿童普遍健康状况更好。儿童健康集中指数分解结果显示,隔代抚养与混合抚养对0～3岁儿童健康不平等的贡献率分别为4.99%和8.04%,一定程度造成了不平等。儿童的家庭规模(53.98%)、年均家庭收入(38.81%)和父亲的健康状况(23.63%)是对儿童健康不平等贡献最大的3个要素。医疗保险和母乳喂养时长对儿童健康不平等的贡献率分别为–6.36%和–7.56%,有助于缩小儿童健康不平等。结论儿童照顾模式及相关家庭因素均对0～3岁儿童的健康有重要影响,并会造成儿童健康的不平等,应注意规避相关危险因素。     

农村地区经济状况相关的健康不平等演变研究——基于济南市的实证研究

目的了解农村地区居民经济状况相关的健康不平等及其来源和变化。方法采用济南市三县、区2009年和2012年的面板数据,利用集中指数及Oaxaca分解法分析居民健康状况与水平公平目标的差距和不平等产生的因素及其演变。结果2009年和2012年居民不良健康得分的集中指数分别为-0.017和-0.022;收入对不平等的贡献率分别为21.88%和63.98%,60岁以上年龄组、受教育程度、职业以及自来水供应的贡献率也较大;在健康不平等的变动中收入对健康不平等增大的贡献最大,为225.97%,主要归因于弹性变化;受教育程度和职业对健康不平等扩大的贡献为负,主要归因于集中指数的变化。结论济南市三县、区存在健康不平等现象,健康水平较差人群较多的集中在低收入人群中,并且在2009年至2012年期间是扩大的。建议增加收入分配的公平性,关注老年人口的保障水平,提高低收入者受教育、就业机会,改善公共服务的提供和社会福利水平,扩大医疗保险覆盖面和保障水平。     

宁夏海原县农村老年人健康公平性及其分解分析

目的评价海原县农村老年人自评健康公平性,并分析各影响因素的贡献。方法利用家庭健康询问调查数据,采用集中指数及其分解法分析老年人自评健康公平性及各因素的贡献率。结果不同收入组老年人自评健康存在差异(P<0.01),基线和随访调查的集中指数分别为-0.0280和-0.0118,均存在亲富人的健康不平等。各因素对健康不平等的贡献中,基线调查,收入的贡献率为81.58%,就医距离≤1公里为24.45%,文盲为11.10%;随访调查,收入的贡献率为69.97%,就医距离1~2公里为69.03%,文盲为47.96%。结论新农合方案的调整使得健康不公平性有所改善但依然存在,收入对自评健康不平等的贡献仍最大,就医距离和文化水平的贡献有所突出。     

Income inequality,area-level poverty,perceived aversion to inequality,and self-rated health in Japan

In this study we conduct a multilevel analysis to investigate the association between regional income inequality and self-rated health in Japan, based on two nationwide surveys. We confirm that there is a significant association between area-level income inequality and individual-level health assessment. We also find that health assessment tends to be more sensitive to income inequality among lower income individuals, and to degree of area-level poverty, than income inequality for the society as a whole. In addition, we examine how individuals are averse to inequality, based on the observed association between inequality and self-rated health.     

Income-related health inequality in Canada

This study uses data from the 1994 National Population Health Survey and applies the methods developed by Wagstaff and van Doorslaer (1994, measuring inequalities in health in the presence of multiple-category morbidity indicators. Health Economics 3, 281-291) to measure the degree of income-related inequality in self-reported health in Canada by means of concentration indices. It finds that significant inequalities in self-reported ill-health exist and favour the higher income groups--the higher the level of income, the better the level of self-assessed health. The analysis also indicates that lower income individuals are somewhat more likely to report their self-assessed health as poor or less-than-good than higher income groups, at the same level of a more 'objective' health indictor such as the McMaster Health Utility Index. The degree of inequality in 'subjective' health is slightly higher than in 'objective' health, but not significantly different. The degree of inequality in self-assessed health in Canada was found to be significantly higher than that reported by van Doorslaer et al. (1997, income related inequalities in health: some international comparisons, Journal of Health Economics 16, 93-112) for seven European countries, but not significantly different from the health inequality measured for the UK or the US. It also appears as if Canada's health inequality is higher than what would be expected on the basis of its income inequality.     

不同收入人群的卫生公平性研究：来自陕西眉县的证据

文章利用陕西省眉县家庭健康调查数据,采用收入五分组、Gini系数等方法,对我国卫生保健筹资和利用的不平等程度进行了实证分析。结果发现人群之间的贫富差距较大;基本实现了医疗保险的全覆盖,但是低收入人群自己支付了更多的医疗费;较低收入组的需要比较高收入组更高,而最低收入组有着更高的需要,但是很多收入较低的人即使在健康状况很差的情况下,也无法得到所需要的医疗卫生服务,住院利用的公平性亟待改善,低收入人群的福利受到了特别的损害。如何解决低收入人群的基本医疗保障问题,是目前在新型医疗保障体系建立过程中需要深入研究的一个突出问题。最后指出了研究的局限性,并对未来的研究方向和策略提出了建议。     

Income inequality and mental health--empirical evidence from Australia

The causal association between absolute income and health is well-established; however, the relationship between income inequality and health is not. The conclusions from the received studies vary across the region or country studied and/or the methodology employed. Using the Household, Income and Labour Dynamics in Australia panel survey, this paper investigates the relationship between mental health and inequality in Australia. A variety of income inequality indices are calculated to test both the income inequality and relative deprivation hypotheses. We find that mental health is only adversely affected by the presence of relative deprivation to a very small degree. In addition, we do not find support for the income inequality hypothesis. Importantly, our results are robust to a number of sensitivity analyses.     

Growing old before growing rich: inequality in health service utilization among the mid-aged and elderly in Gansu and Zhejiang Provinces, China

ABSTRACT: BACKGROUND: China's recent growth in income has been unequally distributed, resulting in an unusually rapid retreat from relative income equality, which has impacted negatively on health services access. There exists a significant gap between health care utilization in rural and urban areas and inequality in health care access due to differences in socioeconomic status is increasing. We investigate inequality in service utilization among the mid-aged and elderly, with a special attention of health insurance. METHODS: This paper measures the income-related inequality and horizontal inequity in inpatient and outpatient health care utilization among the mid-aged and elderly in two provinces of China. The data for this study come from the pilot survey of the China Health and Retirement Longitudinal Study in Gansu and Zhejiang. Concentration Index (CI) and its decomposition approach were deployed to reflect inequality degree and explore the source of these inequalities. RESULTS: There is a pro-rich inequality in the probability of receiving health service utilization in Gansu (CI outpatient = 0.067; CI inpatient = 0.011) and outpatient for Zhejiang (CI = 0.016), but a pro-poor inequality in inpatient utilization in Zhejiang (CI = -0.090). All the Horizontal Inequity Indices (HI) are positive. Income was the dominant factor in health care utilization for out-patient in Gansu (40.3 percent) and Zhejiang (55.5 percent). The non-need factors' contribution to inequity in Gansu and Zhejiang outpatient care had the same pattern across the two provinces, with the factors evenly split between pro-rich and pro-poor biases. The insurance schemes were strongly pro-rich, except New Cooperative Medical Scheme (NCMS) in Zhejiang. CONCLUSIONS: For the middle-aged and elderly, there is a strong pro-rich inequality of health care utilization in both provinces. Income was the most important factor in outpatient care in both provinces, but access to inpatient care was driven by a mix of income, need and non-need factors that significantly differed across and within the two provinces. These differences were the result of different levels of health care provision, different out-of-pocket expenses for health care and different access to and coverage of health insurance for rural and urban families. To address health care utilization inequality, China will need to reduce the unequal distribution of income and expand the coverage of its health insurance schemes.     

Squeezing Blood From a Stone: How Income Inequality Affects the Health of the American Workforce

Income inequality is very topical—in both political and economic circles—but although income and socioeconomic status are known determinants of health status, income inequality has garnered scant attention with respect to the health of US workers. By several measures, income inequality in the United States has risen since 1960. In addition to pressures from an increasingly competitive labor market, with cash wages losing out to benefits, workers face pressures from changes in work organization.We explored these factors and the mounting evidence of income inequality as a contributing factor to poorer health for the workforce.Although political differences may divide the policy approaches undertaken, addressing income inequality is likely to improve the overall social and health conditions for those affected.Income inequality in the United States is now a common theme in national policy debates, and both major parties are seemingly embracing the need to address it, although their messaging and the degree of importance they assign to the issue vary significantly.1,2 Although income itself and the broader construct of socioeconomic status are known key determinants of health status, income inequality has garnered scant attention with respect to health in general and with respect to the health of US workers specifically.Because income inequality is inexorably linked to employment, a more complete picture of the effects of inequality on health emerges when analyzed through the lens of the working population. Moreover, differences in income are associated with differences in occupations and work environments, potentially exacerbating the overall effect of income inequality on workers’ health.We considered trends in US workforce composition, income inequality, and work organization; how income inequality alone and together with income status affects health; and exemplary issues facing the large and growing health care workforce.     

Health inequalities in rural China: evidence from HeBei Province

The purpose of this study was to examine the degree to which commonly used social class indicators-education, income, and occupation-are associated with health in the context of rural China. Data were collected from 10,226 individuals of working age (16-60) living in HeBei Province, the PRC. The association between education and income observed resembles the patterns documented in industrial societies, but the health status of farmers is quite similar to that of white collar employees. Persons in other than mainstream occupations report the poorest health status. Social selection and the costs of relative deprivation appear to be useful to the understanding of health inequality in rural China, though in a manner shaped by the particular social context.     

An exploratory multilevel analysis of income,income inequality and self-rated health of the elderly in China

In the last three decades, China has experienced rapid economic development and growing economic inequality, such that economic disparities between rural and urban areas, as well as coastal and interior areas have deepened. Since the late 1990s China has also experienced an ageing population which has attracted attention to the wellbeing of the rapidly growing number of elderly. This research aims to characterise province differences in health and to explore the effects of individual income and economic disparity in the form of income inequality on health outcomes of the elderly. The study is based on the Chinese Longitudinal Healthy Longevity Survey data collected in 2008 for 23 provinces. Multilevel logistic models are employed to investigate the relationship between income, income inequality and self-rated health for the elderly using both individual and province-level variables. Results are presented as relative odds ratios, and for province differentials as Median Odds Ratios. The analysis is deliberately exploratory so as to find evidence of income effects if they exist and particular attention is placed on how province-level inequality (contemporaneous and lagged) may moderate individual relationships. The results show that the health of the elderly is not only affected by individual income (the odds of poor health are 3 times greater for the elderly with the lowest income compared to those at the upper quartile) but also by a small main effect for province-level income inequality (odds ratio of 1.019). There are significant cross-level interactions such that where inequality is high there are greater differences between those with and without formal education, and between men and women with the latter experiencing poorer health.     

Explaining the differences in income-related health inequalities across European countries

This paper provides new evidence on the sources of differences in the degree of income-related inequalities in self-assessed health in 13 European Union member states. It goes beyond earlier work by measuring health using an interval regression approach to compute concentration indices and by decomposing inequality into its determining factors. New and more comparable data were used, taken from the 1996 wave of the European Community Household Panel. Significant inequalities in health (utility) favouring the higher income groups emerge in all countries, but are particularly high in Portugal and - to a lesser extent - in the UK and in Denmark. By contrast, relatively low health inequality is observed in the Netherlands and Germany, and also in Italy, Belgium, Spain Austria and Ireland. There is a positive correlation with income inequality per se but the relationship is weaker than in previous research. Health inequality is not merely a reflection of income inequality. A decomposition analysis shows that the (partial) income elasticities of the explanatory variables are generally more important than their unequal distribution by income in explaining the cross-country differences in income-related health inequality. Especially the relative health and income position of non-working Europeans like the retired and disabled explains a great deal of 'excess inequality'. We also find a substantial contribution of regional health disparities to socio-economic inequalities, primarily in the Southern European countries.