Inequalities In Health-related Quality Of Life Research Articles

Socio-economic inequalities in health-related quality of life and the contribution of cognitive impairment in Australia: A decomposition analysis

BackgroundThe distributional effects of cognitive impairment on inequalities in health-related quality of life (HRQoL) are not well studied. This relationship has not been studied in any Australian health inequality literature. Therefore, this study aims to examine how cognitive impairment affects the distribution of HRQoL across various socio-economic classes amongst older Australians. MethodsData for this study was collected from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The final analysis consisted of 5,247 and 5,614 unique individuals from wave 2012 and wave 2016, respectively. An ordinary least squares (OLS) regression model was used to investigate the relationship between cognitive impairment and HRQoL. Additionally, the Wagstaff-Doorslaer-Watanabe standard concentration index was used to examine socioeconomic inequality in HRQoL. ResultsThe findings revealed pro-rich inequalities in HRQoL, as indicated by the concentration indices of 0.029 and 0.025 for wave 12 and wave 16, respectively. Additionally, the results showed that mild cognitive impairment accounted for 7.60% and 9.03%, respectively, of pro-rich socioeconomic inequality in HRQoL in 2012 and 2016. ConclusionPeople from lower socioeconomic status (SES) groups tend to have lower HRQoL compared to those from higher SES. This leads to a greater disparity in HRQoL based on SES. Cognitive impairment positively contributed to this inequality in HRQoL. Therefore, it is critical to incorporate cognitive impairment into the design of interventions to reduce socioeconomic inequality in HRQoL.

Sex differences in health-related quality of life and poverty risk among older people living with HIV in Spain: A cross-sectional study.

Current antiretroviral therapies have increased the life expectancy of people living with HIV (PLHIV). There is, however, limited evidence regarding the health-related quality of life (HRQoL) and living conditions of older people living with HIV (OPLHIV) in Spain. We implemented a self-administered online questionnaire to identify sex differences in HRQoL and poverty risk among Spanish OPLHIV (PLHIV ≥50 years). Participants were contacted through non-governmental organisations. We used the standardised WHOQoL-HIV BREF questionnaire and the Europe 2020 guidelines to estimate HRQoL and poverty risk respectively. The statistical analysis included multivariable generalised linear models with potential confounding variables and robust estimates. The study included 247 OPLHIV (192 men and 55 women). On the WHOQoL-HIV BREF questionnaire, men scored higher on 84% of items and in all six domains. Women had significantly lower HRQoL in five domains: physical health (β: -1.5; 95% CI: -2.5, -0.5; p: 0.002), psychological health (β: -1.0; 95% CI: -1.9, -0.1; p: 0.036), level of independence (β: -1.1; 95% CI: -1.9, -0.2; p: 0.019), environmental health (β: -1.1; 95% CI: -1.8, -0.3; p: 0.008), and spirituality/personal beliefs (β: -1.4; 95% CI: -2.5, -0.3; p: 0.012). No statistical differences were found in the domain of social relations. Poverty risk was considerable for both men (30%) and women (53%), but women were significantly more likely to experience it (OR: 2.9; 95% CI: 1.3, 6.5; p: 0.009). The aging of PLHIV is a public health concern. Our findings indicate that HRQoL and poverty risk among Spanish OPLHIV differ significantly by sex. Spain should, therefore, implement specific policies and interventions to address OPLHIV needs. The strategies must place a high priority on the reduction of sex inequalities in HRQoL and the enhancement of the structural conditions in which OPLHIV live.

Socioeconomic inequality of health-related quality of life in cancer survivors in South Korea.

We investigated the inequalities in health-related quality of life (HRQoL) among cancer survivors in Korea, focusing on income and education levels. The slope index of inequality (SII) and relative index of inequality (RII) were utilized to analyze these disparities. Data from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted between 2007 and 2021 was analyzed. The HRQoL was assessed using the EQ-5D questionnaire, which included five problem areas: mobility, self-care, usual activity, pain/discomfort, and anxiety/depression. Logistic regression was employed to calculate the odds ratios (ORs) for each education and income level, indicating the probability of reporting problems. Furthermore, the slope index of inequality (SII) and relative index of inequality (RII) were calculated to evaluate the inequalities in HRQoL. Among the 3396 cancer survivors, a considerable proportion reported pain/discomfort (29.6%) and mobility problems (21.1%). The logistic regression results demonstrated a higher likelihood of experiencing problems in all five EQ-5D items among individuals with lower income or education levels. Specifically, compared to the high-income group, the adjusted ORs for mobility problems were 2.19, 1.64, and 1.08 for the low, low-medium, and medium-high-income groups, respectively (p-value < 0.05). Notably, significant income inequalities in HRQoL problems were observed, with the greatest disparities seen in self-care and usual activity problems, as indicated by the SII and RII values. Socioeconomic disparities in HRQoL exist among cancer survivors in Korea, particularly related to income levels. Addressing the financial burdens of cancer treatment for individuals with low-income levels may help improve their HRQoL and mitigate these inequalities.

Decomposing income-related inequality in health-related quality of life in mainland China: a national cross-sectional study

IntroductionHealth equity is an important indicator measuring social development and solidarity. However, there is a paucity in nationwide studies into the inequity in health-related quality of life (HRQoL) in mainland...

Decomposition of Quality-Adjusted Life Expectancy Inequalities by Mortality and Health-Related Quality of Life Dimensions.

Quality-adjusted life expectancy (QALE) combines mortality risk and multidimensional health-related quality of life (HRQoL) information to measure healthy life expectancy in terms of quality-adjusted life years (QALYs). This paper estimates the relative importance of individual quality of life dimensions in explaining inequalities in QALE. We combined EQ-5D-5L data from the Health Survey for England for 2017 and 2018 (N = 14,412) with full population mortality data from the Office for National Statistics to calculate QALE by age, sex and deprivation quintile. The effect of HRQoL dimensions on the socioeconomic gradient in QALE was decomposed using an iterative imputation approach, in which inequalities associated with socioeconomic status in each domain were removed by imputing the response distribution of the richest quintile for all participants. Sampling uncertainty in the HRQoL data was evaluated using bootstrapping. People in the least deprived fifth of neighbourhoods in England can expect to live 7.0 years longer and experience 11.1 more QALYs than those in the most deprived fifth. Inequalities in HRQoL accounted for 28.0% and 45.7% of QALE inequalities for males and females, respectively. Pain/discomfort, anxiety/depression and mobility were the most influential HRQoL domains. Our results identify the extent of inequalities associated with socioeconomic status in lifetime health and the relative importance of inequalities by mortality and HRQoL. The contributions of the individual dimensions of HRQoL towards lifetime inequalities vary substantially by sex. Our findings can help to identify the types of interventions most likely to alleviate health inequalities, which may be different for males and females.

Health-related quality of life by household income in Chile: a concentration index decomposition analysis

BackgroundHealth inequities have a profound impact on all dimensions of people’s lives, with invariably worse results among the most disadvantaged, transforming them into a more fragile and vulnerable population. These unfair inequalities also affect dimensions focused on subjectivity, such as health-related quality of life (HRQoL), which has been positioned, in recent decades, as an important outcome in health decision-making. The main objective of this study is to estimate socioeconomic inequality in HRQoL of Chilean by household income. MethodsSecondary analysis of the National Health Survey (ENS 2016–2017, Chile). This survey includes a nationally representative, stratified, and multistage household sample of people aged 15 and above. Socioeconomic inequality in HRQoL (EQ5D) is estimated by the concentration index (CI) ranked by household income. Decomposition analysis is conducted to examine potential explanatory sociodemographic factors. ResultsThe CI for household income inequality in HRQoL was -0.063. The lower the household income, the worse the HRQoL reported by in Chile. The decomposition analysis revealed that socioeconomic position contributes 75,7% to inequality in the quality of life, followed by educational level (21.8%), female gender (17.3%), and type of Health Insurance (15%), age (-19.7%) and residence (-10.8%). Less than 1% corresponds to the unexplained residual component.ConclusionsOur findings suggest the existence of a disproportionate concentration of worse HRQoL in the most disadvantaged socioeconomic groups in Chile. This inequality is largely, yet not completely, associated with household income. Other significant factors associated with this inequality are education, gender, and healthcare insurance. These results suggest the need of strengthening efforts to reducing socioeconomic gaps in health outcomes in Chile, as a means to achieve social justice and equity in health and healthcare.

Socioeconomic inequalities in HRQoL in England: an age-sex stratified analysis

BackgroundSocioeconomic status is a key predictor of lifetime health: poorer people can expect to live shorter lives with lower average health-related quality-of-life (HRQoL) than richer people. In this study, we aimed to improve understanding of the socioeconomic gradient in HRQoL by exploring how inequalities in different dimensions of HRQoL differ by age.MethodsData were derived from the Health Survey for England for 2017 and 2018 (14,412 participants). HRQoL was measured using the EQ-5D-5L instrument. We estimated mean EQ-5D utility scores and reported problems on five HRQoL dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) for ages 16 to 90+ and stratified by neighbourhood deprivation quintiles. Relative and absolute measures of inequality were assessed.ResultsMean EQ-5D utility scores declined with age and followed a socioeconomic gradient, with the lowest scores in the most deprived areas. Gaps between the most and least deprived quintiles emerged around the age of 35, reached their greatest extent at age 60 to 64 (relative HRQoL of most deprived compared to least deprived quintile: females = 0.77 (95% CI: 0.68–0.85); males = 0.78 (95% CI: 0.69–0.87)) before closing again in older age groups. Gaps were apparent for all five EQ-5D dimensions but were greatest for mobility and self-care.ConclusionThere are stark socioeconomic inequalities in all dimensions of HRQoL in England. These inequalities start to develop from early adulthood and increase with age but reduce again around retirement age.

Combining education and income into a socioeconomic position score for use in studies of health inequalities

BackgroundIn studies of social inequalities in health, there is no consensus on the best measure of socioeconomic position (SEP). Moreover, subjective indicators are increasingly used to measure SEP. The aim of this paper was to develop a composite score for SEP based on weighted combinations of education and income in estimating subjective SEP, and examine how this score performs in predicting inequalities in health-related quality of life (HRQoL).MethodsWe used data from a comprehensive health survey from Northern Norway, conducted in 2015/16 (N = 21,083). A composite SEP score was developed using adjacent-category logistic regression of subjective SEP as a function of four education and four household income levels. Weights were derived based on these indicators’ coefficients in explaining variations in respondents’ subjective SEP. The composite SEP score was further applied to predict inequalities in HRQoL, measured by the EQ-5D and a visual analogue scale.ResultsEducation seemed to influence SEP the most, while income added weight primarily for the highest income category. The weights demonstrated clear non-linearities, with large jumps from the middle to the higher SEP score levels. Analyses of the composite SEP score indicated a clear social gradient in both HRQoL measures.ConclusionsWe provide new insights into the relative contribution of education and income as sources of SEP, both separately and in combination. Combining education and income into a composite SEP score produces more comprehensive estimates of the social gradient in health. A similar approach can be applied in any cohort study that includes education and income data.

Inequality and heterogeneity in health-related quality of life: findings based on a large sample of cross-sectional EQ-5D-5L data from the Swedish general population

PurposeThis study aimed to investigate inequality and heterogeneity in health-related quality of life (HRQoL) and to provide EQ-5D-5L population reference data for Sweden.MethodsBased on a large Swedish population-based survey, 25,867 respondents aged 30‒104 years, HRQoL is described by sex, age, education, income, economic activity, health-related behaviours, self-reported diseases and conditions. Results are presented by EQ-5D-5L dimensions, respondents rating of their overall health on the EQ visual analogue scale (EQ VAS), VAS index value and TTO (time trade-off) index value allowing for calculation of quality-adjusted life years (QALYs). Ordinary Least Squares and multivariable logistic regression analyses were used to study inequalities in observed EQ VAS score between socioeconomic groups and the likelihood to report problems on the dimensions, respectively, adjusted for confounders.ResultsIn total, 896 different health states were reported; 24.1% did not report any problems. Most problems were reported with pain/discomfort. Women reported worse HRQoL than men, and health deteriorated with age. The strongest association between diseases and conditions and EQ VAS score was seen for depression and mental health problems. There was a socioeconomic gradient in HRQoL; adjusting for health-related behaviours, diseases and conditions slightly reduced the differences between educational groups and income groups, but socioeconomic inequalities largely remained.ConclusionEQ-5D-5L population reference (norms) data are now available for Sweden, including socioeconomic differentials. Results may be used for comparisons with disease-specific populations and in health economic evaluations. The observed socioeconomic inequality in HRQoL should be of great importance for policy makers concerned with equity aspects.

HEALTH-RELATED QUALITY OF LIFE OF HEALTH PROFESSIONALS IN A TERTIARY HEALTH INSTITUTION OF SOUTHWESTERN NIGERIA: A CROSS-SECTIONAL SURVEY

Introduction: Health professionals (HP) are frequently exposed to a high number of hazards at the workplace. Consequently, low ratings for their well-being and satisfaction with health care may adversely affect the quality of health services they provide. This study aimed to assess health-related quality of life (HRQOL) and determine the effects of socio-demographic variables on HRQOL across HP in a tertiary health institution in Nigeria, a low-middle-income economy. Method: This was a cross-sectional survey of 385 HP purposively recruited from different units of Obafemi Awolowo University Teaching Hospital (OAUTH), Ile-Ife, Nigeria. All respondents completed the Medical Outcomes Study short-form (SF-36) questionnaire. Also, the socio-demographic information on the respondents was obtained. Descriptive statistics of mean, standard deviation, frequency and percentages; and inferential statistics of independent t-test and one way ANOVA was used to analyze data. Alpha level was set at p&lt;0.05. Results: Respondents comprised 273 males and 112 females. They scored well above the cut-off point of 50 in most subscales with higher physical (80.95±12.03) than mental (67.58±7.88) component score on SF-36. There were significant differences between gender in favour of male respondents with the highest mean score across each of the age groups, educational and professional qualifications (p&lt;0.01) on most subscales. Conclusion: There are considerable inequalities in HRQOL among HP in this study. These inequalities are gender-biased and favour professionals with post-graduate degree. Findings from this study are comparable to other climes and advocate support for female HP, those on low cadre and higher degree training.

Ethnic inequalities in health-related quality of life among older adults in England: secondary analysis of a national cross-sectional survey

The population of older adults (ie, those aged ≥55 years) in England is becoming increasingly ethnically diverse. Previous reports indicate that ethnic inequalities in health exist among older adults, but information is limited by the paucity of data from small minority ethnic groups. This study aimed to analyse inequalities in health-related quality of life (HRQoL) and five determinants of health in older adults across all ethnic groups in England. In this cross-sectional study, we analysed data from five waves (July 1, 2014, to April 7, 2017) of the nationally representative English General Practice Patient Survey (GPPS). Study participants were adults aged 55 years or older who were registered with general practices in England. We used regression models (age-adjusted and stratified by gender) to estimate the association between ethnicity and HRQoL, measured by use of the EQ-5D-5L index and its domains (mobility, self-care, usual activities, pain or discomfort, and anxiety or depression). We also estimated associations between ethnicity and five determinants of health (presence of long-term conditions or multimorbidity, experience of primary care, degree of support from local services, patient self-confidence in managing own health, and degree of area-level social deprivation). We examined robustness to differential handling of missing data, alternative EQ-5D-5L value sets, and differences in area-level social deprivation. There were 1 416 793 GPPS respondents aged 55 years and older. 1 394 361 (98·4%) respondents had complete data on ethnicity and gender and were included in our analysis. Of these, 152 710 (11·0%) self-identified as belonging to minority ethnic groups. HRQoL was worse for men or women, or both, in 15 (88·2%) of 17 minority ethnic groups than the White British ethnic group. In both men and women, inequalities were widest for Gypsy or Irish Traveller (linear regression coefficient -0·192 [95% CI -0·318 to -0·066] in men; -0·264 [-0·354 to -0·173] in women), Bangladeshi (-0·111 [-0·136 to -0·087] in men; -0·209 [-0·235 to -0·184] in women), Pakistani (-0·084 [-0·096 to -0·073] in men; -0·206 [-0·219 to -0·193] in women), and Arab (-0·061 [-0·086 to -0·035] in men; -0·145 [-0·180 to -0·110] in women) ethnic groups, with magnitudes generally greater for women than men. Differentials tended to be widest for the self-care EQ-5D-5L domain. Ethnic inequalities in HRQoL were accompanied by increased prevalence of long-term conditions or multimorbidity, poor experiences of primary care, insufficient support from local services, low patient self-confidence in managing their own health, and high area-level social deprivation, compared with the White British group. We found evidence of wide ethnic inequalities in HRQoL and five determinants of health for older adults in England. Outcomes varied between minority ethnic groups, highlighting heterogeneity in the direction and magnitude of associations. We recommend further research to understand the drivers of inequalities, together with policy changes to improve equity of socioeconomic opportunity and access to services for older adults from minority ethnic groups. University of Manchester and National Institute for Health Research.

Comparison of inequity in health-related quality of life among unemployed and employed individuals in China

BackgroundIn China, achieving health equity has been regarded as a key issue for health reform and development in the current context. It is well known that unemployment has a negative effect on health. However, few studies have addressed the association between unemployment and inequity in health-related quality of life (HRQOL). This study aims to compare the inequality and inequity in HRQOL between the unemployed and employed in China.MethodsThe material regarding this study was derived from the Chinese National Health Services Survey of Shaanxi Province for 2013. We controlled for confounding factors by utilizing the coarsened exact matching method. Finally, 7524 employed individuals and 283 unemployed individuals who were 15 to 64 years old in urban areas were included in this study. We used HRQOL as the outcome variable, which was evaluated by using the Chinese version of EQ-5D-3L. The health concentration index, decomposition analysis based on the Tobit model, and the horizontal inequity index were employed to compute the socioeconomic-related equity between the unemployed and employed and the contribution of various factors.ResultsAfter matching, unemployed people tended to have poorer EQ-5D utility scores than employed people. There were statistically pro-rich inequalities in HRQOL among both employed and unemployed people, and the pro-rich health inequity of unemployed people was substantially higher than that of employed people. Economic status, age, education, smoking and health insurance were the factors influencing inequality in HRQOL between employed and unemployed individuals. Education status and basic health insurance have reduced the pro-rich inequity in HRQOL for unemployed people.ConclusionIt is suggested that unemployment intensifies inequality and inequity in HRQOL. According to policymakers, basic health insurance is still a critical health policy for improving health equity for the unemployed. Intervention initiatives aiming to tackle long-term unemployment through active labour market programmes, narrow economic gaps, improve educational equity and promote the health status of the unemployed should be considered by the government to achieve health equity.

The effects of family physician-contracted service on health-related quality of life and equity in health in China

BackgroundFamily physician-contracted service (FPCs) has been recently implemented in Chinese primary care settings. This study was aimed at measuring the effects of FPCs on residents’ health-related quality of life (HRQoL) and equity in health among the Chinese population.MethodsThe study data was drawn from the 2018 household health survey (Shaanxi Province, China) using multistage, stratified cluster random sampling. We measured HRQoL using EQ-5D-3L based on the Chinese-specific time trade-off values set. Coarsened exact matching (CEM) technique was used to control for confounding factors between residents with and without a contracted family physician. The concentration index (C) was calculated to measure equity in health.ResultsIndividuals with a contracted family physician had significantly higher HRQoL than those without, after data matching (0.9355 vs. 0.8995; P < 0.001). Additionally, the inequity in HRQoL among respondents with a contracted family physician was significantly lower than those without a contracted family physician (Cs of EQ-5D utility score: 0.0084 vs. 0.0263; p < 0.001).ConclusionsThis study highlights the positive effects of FPCs on HRQoL and socioeconomic-related equity in HRQoL. Future efforts should prioritize the economically and educationally disadvantaged groups, the expansion of service coverage, and the competency of family physician teams to further enhance health outcome and equity in health.

Inequalities in health-related quality of life: repeated cross-sectional study of trends in general practice survey data.

After decades of steady progress, life expectancy at birth has stalled in England. Inequalities are also rising, and life expectancy has fallen for females living in the most deprived areas. However, less attention has been given to trends in other measures of population health, particularly health-related quality of life (HRQoL). To examine trends and inequalities in HRQoL in England between 2012 and 2017. The authors used nationally representative survey data on 3.9 million adults to examine HRQoL (measured by EQ-5D-5L overall score, plus each of the five health domains - mobility, selfcare, usual activity, pain/discomfort, and anxiety/depression). The study explored trends across time, and inequalities by sex, age, and deprivation. Although HRQoL seemed steady overall between 2012 and 2017, there is evidence of increasing inequality across population subgroups. There was a rise in sex disparity over time, the female-male gap in EQ-5D-5L increased from -0.009 in 2012 to -0.016 in 2017. Trends for the youngest females and those living in the most deprived areas were of the greatest concern. Females in the most deprived regions suffered a 1.3% decrease in HRQoL between 2012 and 2017, compared with a 0.5% decrease for males. The key contribution to the decline in HRQoL, particularly in females, was a 1.5% increase in reported levels of anxiety/depression between 2012 and 2017. Developing interventions to address these worrying trends should be a policy priority. A particular focus should be on mental health in younger populations, especially for females and in deprived areas.

Sociodemographic variations in health-related quality of life (HRQOL) among elderly individuals in an urban locality in India.

Background:Elderly population is growing rapidly in India. To direct public health actions to improve quality of life among elderly, it is important to understand the sociodemographic factors associated with quality of life. The aim of study was to assess health-related quality of life (HRQOL) among urban elderly in a setting of Assam, India, and to examine how HRQOL varied across different sociodemographic groups among the elderly populations.Materials and Methods:A cross-sectional study was carried among elderly aged ≥60 involving 300 participants. Eight domains of HRQOL of participants were measured using RAND SF-36. Analysis of variance test was used to examine sociodemographic differences in HRQOL.Results:The BP domain had highest (71.78 ± 22.25) and GH had lowest mean HRQOL score (48 ± 16.93). Males had significantly higher HRQOL score than females only in BP domain. Age gradients were observed with respect to HRQOl scores in five domains, with youngest age group having the best and oldest age group having the poorest HRQOL. Financially dependent subjects had lower HRQOL in five domains than those who were financially independent. Significant associations between education and HRQOL were found only in physical components of HRQOL, with lowest educated group being the most disadvantaged in terms of HRQOL. Marital status was found to be significantly associated with lower HRQOL scores.Conclusion:The study highlights sociodemographic inequalities in HRQOL among urban elderly in an Indian setting. The results may help reducing sociodemographic health inequalities among elderly in this region initiating public health actions paying more attention toward more vulnerable sections of populations.

Differences in health-related quality of life between HIV-positive and HIV-negative people in Zambia and South Africa: a cross-sectional baseline survey of the HPTN 071 (PopART) trial.

SummaryBackgroundThe life expectancy of HIV-positive individuals receiving antiretroviral therapy (ART) is approaching that of HIV-negative people. However, little is known about how these populations compare in terms of health-related quality of life (HRQoL). We aimed to compare HRQoL between HIV-positive and HIV-negative people in Zambia and South Africa.MethodsAs part of the HPTN 071 (PopART) study, data from adults aged 18–44 years were gathered between Nov 28, 2013, and March 31, 2015, in large cross-sectional surveys of random samples of the general population in 21 communities in Zambia and South Africa. HRQoL data were collected with a standardised generic measure of health across five domains. We used β-distributed multivariable models to analyse differences in HRQoL scores between HIV-negative and HIV-positive individuals who were unaware of their status; aware, but not in HIV care; in HIV care, but who had not initiated ART; on ART for less than 5 years; and on ART for 5 years or more. We included controls for sociodemographic variables, herpes simplex virus type-2 status, and recreational drug use.FindingsWe obtained data for 19 750 respondents in Zambia and 18 941 respondents in South Africa. Laboratory-confirmed HIV status was available for 19 330 respondents in Zambia and 18 004 respondents in South Africa; 4128 (21%) of these 19 330 respondents in Zambia and 4012 (22%) of 18 004 respondents in South Africa had laboratory-confirmed HIV. We obtained complete HRQoL information for 19 637 respondents in Zambia and 18 429 respondents in South Africa. HRQoL scores did not differ significantly between individuals who had initiated ART more than 5 years previously and HIV-negative individuals, neither in Zambia (change in mean score −0·002, 95% CI −0·01 to 0·001; p=0·219) nor in South Africa (0·000, −0·002 to 0·003; p=0·939). However, scores did differ between HIV-positive individuals who had initiated ART less than 5 years previously and HIV-negative individuals in Zambia (−0·006, 95% CI −0·008 to −0·003; p<0·0001). A large proportion of people with clinically confirmed HIV were unaware of being HIV-positive (1768 [43%] of 4128 people in Zambia and 2026 [50%] of 4012 people in South Africa) and reported good HRQoL, with no significant differences from that of HIV-negative people (change in mean HRQoL score −0·001, 95% CI −0·003 to 0·001, p=0·216; and 0·001, −0·001 to 0·001, p=0·997, respectively). In South Africa, HRQoL scores were lower in HIV-positive individuals who were aware of their status but not enrolled in HIV care (change in mean HRQoL −0·004, 95% CI −0·01 to −0·001; p=0·010) and those in HIV care but not on ART (−0·008, −0·01 to −0·004; p=0·001) than in HIV-negative people, but the magnitudes of difference were small.InterpretationART is successful in helping to reduce inequalities in HRQoL between HIV-positive and HIV-negative individuals in this general population sample. These findings highlight the importance of improving awareness of HIV status and expanding ART to prevent losses in HRQoL that occur with untreated HIV progression. The gains in HRQoL after individuals initiate ART could be substantial when scaled up to the population level.FundingNational Institute of Allergy and Infectious Diseases, National Institute on Drug Abuse, National Institute of Mental Health, President's Emergency Plan for AIDS Relief, International Initiative for Impact Evaluation, the Bill & Melinda Gates Foundation.

Socioeconomic inequalities in health-related quality of life between men and women, 5years after a coronary angiography.

BackgroundThe aim of this study is to measure gender differences in health-related quality of life (HRQOL) among men and women patients with cardiovascular diseases (CVD), and to assess the impact of socioeconomic factors on HRQOL between men and women, 5 years after a coronary angiography.MethodsThe study included 1,289 out of 4,391 patients who had undergone an angiography in the National Institute for Cardiac Surgery and Interventional Cardiology, Luxembourg in 2008/2009. Four indicators of the WHOQOL-BREF questionnaire (Self-rated health, Quality of life, Physical health, and Psychological health) were used in this study as interest variables. To assess the socioeconomic inequalities in HRQOL between men and women, general linear models were constructed for every indicator, with educational level and living conditions as predictors, and demographic variables, cardiovascular risk factors, and cardiovascular events as covariates.ResultsWomen were older than men (71.5 versus 68.1, p <0.0001) and less likely to be married. HRQOL was significantly different between men and women despite the fact they had the same socioeconomic status. The average score for overall health was 3.7/5 for men versus 3.5/5 for women; similarly, the life quality score was 3.8/5 for men versus 3.6/5 for women. Education level and living conditions were associated with lower HRQOL scores in men and women.ConclusionThe findings showed that women have lower HRQOL than men regarding self-rated health, quality of life, and the WHOQOL-BREF physical and psychological domains 5 years after a coronary angiography. Socioeconomic inequalities affect HRQOL, and their influence was similar in both men and women. Socioeconomic inequalities in HRQOL in women and men with CVD are strong 5 years after a coronary angiography. Taking into account differences in gender and socioeconomic status in intervention strategies to substantially reduce the differences observed between women and men could help improve the effectiveness of secondary prevention.

Socioeconomic status and health-related quality of life among patients with prostate cancer 6 months after radical prostatectomy: a longitudinal analysis

ObjectivesTo identify the associations between socioeconomic status (SES) and health-related quality of life (HRQOL) and the explanatory contribution of disease, patient and healthcare factors among patients with prostate cancer.DesignProspective cohort...

Health inequalities in the Netherlands: trends in quality-adjusted life expectancy (QALE) by educational level.

Quality-adjusted life expectancy (QALE) has been proposed as a summary measure of population health because it encompasses multiple health domains as well as length of life. However, trends in QALE by education or other socio-economic measure have not yet been reported. This study investigates changes in QALE stratified by educational level for the Dutch population in the period 2001-2011. Using data from multiple sources, we estimated mortality rates and health-related quality of life (HRQoL) as functions of age, gender, calendar year and educational level. Subsequently, predictions from these regressions were combined for calculating QALE at ages 25 and 65. QALE changes were decomposed into effects of mortality and HRQoL. In 2001-2011, QALE increased for men and women at all educational levels, the largest increases being for highly educated resulting in a widening gap by education. In 2001, at age 25, the absolute QALE difference between the low and the highly educated was 7.4 healthy years (36.7 vs. 44.1) for men and 6.3 healthy years (39.5 vs. 45.8) for women. By 2011, the QALE difference increased to 8.1 healthy years (38.8 vs. 46.9) for men and to 7.1 healthy years (41.3 vs. 48.4) for women. Similar results were observed at age 65. Although the gap was largely attributable to widening inequalities in mortality, widening inequalities in HRQoL were also substantial. In the Netherlands, population health as measured by QALE has improved, but QALE inequalities have widened more than inequalities in life expectancy alone.

Impact of the economic crisis on children's health in Catalonia: a before–after approach

ObjectivesTo analyse changes in the family living conditions of children in Catalonia between 2006 and the 2010–2012 period, and to study associations between these changes and health outcomes.DesignA before–after analysis...