STUDY DESIGN: This is a cross-sectional study.
METHODS: In total, 774 households from four states in Malaysia completed face-to-face interviews. A validated structured questionnaire was used, which was composed of a combination of open-ended questions, bidding games and contingent valuation methods regarding the participants' willingness to pay.
RESULTS: The study found that the majority of households supported the establishment of the National Health Financing Scheme, and half proposed that a government body should manage the scheme. Most (87.5%) of the households were willing to contribute 0.5-1% of their salaries to the scheme through monthly deductions. Over three-quarters (76.6%) were willing to contribute to a higher level scheme (1-2%) to gain access to both public and private healthcare basic services. Willingness to pay for the National Health Financing Scheme was significantly higher among younger persons, females, those located in rural areas, those with a higher income and those with an illness.
CONCLUSION: There is a high level of acceptance for the National Health Financing Scheme in the Malaysian community, and they are willing to pay for a scheme organised by a government body. However, acceptance and willingness to pay are strongly linked to household socio-economic status. Policymakers should initiate plans to establish the National Health Financing Scheme to provide the necessary financing for a sustainable health system.
METHODS: Data from 12,330 participants of the International SCI Community Survey (InSCI) performed in 22 countries were used. We regressed social relationships (belongingness, relationship satisfaction, social interactions) on individual SES (education, income, employment, financial hardship, subjective status) and countries' SED (Human Development Index) using multi-level models (main effects). To test potential moderation of the SED, interaction terms between individual SES and countries' SED were entered into multi-level models.
RESULTS: Paid work, absence of financial hardship and higher subjective status were related to higher belongingness (OR, 95% CI: 1.50, 1.34-1.67; 1.76, 1.53-2.03; 1.16, 1.12-1.19, respectively), higher relationship satisfaction (OR, 95% CI: 1.28, 1.15-1.42; 1.97, 1.72-2.27; 1.20, 1.17-1.24, respectively) and fewer problems with social interactions (Coeff, 95% CI: 0.96, 0.82-1.10; 1.93, 1.74-2.12; 0.26, 0.22-0.29, respectively), whereas associations with education and income were less consistent. Main effects for countries' SED showed that persons from lower SED countries reported somewhat higher relationship satisfaction (OR, 95% CI: 0.97, 0.94-0.99) and less problems with social interactions (Coeff, 95% CI: -0.04, -0.09- -0.003). Results from moderation analysis revealed that having paid work was more important for relationships in lower SED countries, while education and subjective status were more important for relationships in higher SED countries (interaction terms p<0.05).
CONCLUSION: Social relationships in persons with spinal cord injury are patterned according to individual SES and the countries' SED and larger socioeconomic structures partly moderate associations between individual SES and social relationships.
METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family.
FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries.
INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
METHODS: Medline and Embase were searched for articles reporting outcomes of ACS patients stratified by SES using a multidimensional index, comprising at least 2 of the following components: Income, Education and Employment. A comparative meta-analysis was conducted using random-effects models to estimate the risk ratio of all-cause mortality in low SES vs high SES populations, stratified according to geographical region, study year, follow-up duration and SES index.
RESULTS: A total of 29 studies comprising of 301,340 individuals were included, of whom 43.7% were classified as low SES. While patients of both SES groups had similar cardiovascular risk profiles, ACS patients of low SES had significantly higher risk of all-cause mortality (adjusted HR:1.19, 95%CI: 1.10-1.1.29, p
Methods: This study used five series of National Health and Morbidity Survey data from 1986 to 2015. Healthcare utilisation for inpatient, outpatient and dental care were analysed. SES was grouped based on household expenditure variables accounting for total number of adults and children in the household using consumption per adult equivalents approach. The determination of healthcare utilisation across the SES segments was measured using concentration index.
Results: The overall distribution of inpatient utilisation tended towards the pro-poor, although only data from 1996 (P-value = 0.017) and 2006 (P-value = 0.021) were statistically significant (P < 0.05). Out-patient care showed changing trends from initially being pro-rich in 1986 (P < 0.05), then gradually switching to pro-poor in 2015 (P < 0.05). Dental care utilisation was significantly pro-rich throughout the survey period (P < 0.05). Public providers mostly showed significantly pro-poor trends for both in- and out-patient care (P < 0.05). Private providers, meanwhile, constantly showed a significantly pro-rich (P < 0.05) trend of utilisation.
Conclusion: Total health utilisation was close to being equal across SES throughout the years. However, this overall effect exhibited inequities as the effect of pro-rich utilisation in the private sector negated the pro-poor utilisation in the public sector. Strategies to improve equity should be consistent by increasing accessibility to the private sectors, which has been primarily dominated by the richest population.