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Socioeconomic inequalities in health in the context of multimorbidity: A Korean panel study.

ABSTRACT: Socioeconomic inequalities in health are commonly known to decrease at late age. Yet, it remains unclear whether socioeconomic inequalities in health at late age appear in relation to multimorbidity, particularly in Korea where social support remains unsatisfactory for older people. Using three waves of Korea Health Panel, data of 19,942 observations with repeated measure were constructed to ensure a temporal sequence between three socioeconomic measures (i.e., poverty, employment status, and education) and multimorbidity with a t to t+1 year transition. A multilevel multinomial model was applied to quantify the socioeconomic impact across different age, diseases and disease groups, both separately and in combination. There were associations between socioeconomic position (SEP) and multimorbidity, and increasing trends of socioeconomic inequalities not only with greater number of morbidity but also with age. The latter result was only observed with employment status through mid-to-early old age; i.e., between the 40s (odds ratio (OR) = 2.45, 95% confidence interval (CI):1.08-5.57) and 70s (OR = 3.48, 95%CI: 1.24-9.74). The patterns of socioeconomic inequalities in multimorbidity varied for particular pairs of diseases and were stronger in the disease pairs co-occurring with mental and cardiovascular diseases but weaker in the disease pairs co-occurring with cancer. Accumulation of adversity tended to intensify with increase in number of diseases and older age, though this finding was not consistently supported. The labour market should be encouraged to actively participate in actions to promote healthy aging needs to be complemented by the provision of more generous and universal income support to the elderly in Korea.

SUBMITTER: Ki M

PROVIDER: S-EPMC5351993 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Existing studies in Tanzania, based mostly on rural samples, have primarily focused on individual behaviors responsible for the lower utilization of maternal health care. Relatively less attention had been paid to inequalities in structural circumstances that contribute to reduced utilization of maternal health care. More importantly, scholarship concerning the impact of the rural-urban divide on socioeconomic disparities in the utilization of maternal health care is virtually nonexistent in Tanzania. METHODS:Drawing from the Demographic Health Survey (2015-2016) conducted in Tanzania, our study includes a total of 3,595 women aged between 15-49 years old, who had given birth in five years before the month of the interview and living in both rural and urban Tanzania. The maternal health care utilization was assessed by four variables (i.e., antenatal care, skilled delivery assistance, the before and after discharging postnatal care). The independent variables were wealth, education, residence, parity, occupation, age, and the head of the household's sex. We used bivariate statistics and logistic regression to examine the rural-urban differences in the influence of education and wealth on maternal health care utilization. RESULTS:Significantly lower use of maternal health care in rural than urban areas demonstrated a stark rural-urban divide in Tanzania. We documented socioeconomic inequalities in maternal health care utilization in the form of lower odds of the utilization of such services among women with lower levels of education and household wealth. The educational inequalities in the utilization of skilled delivery assistance (or = 0.37, 95% CI: 0.16, 0.86; p = 0.021) and (before discharge) postnatal care (or = 0.60, 95% CI: 0.38, 0.95; p = 0.030) were significantly wider in rural than urban areas. The differences in the odds of the utilization of skilled delivery assistance between women in poorer wealth quintile and women in richer household wealth quintile were also significantly wider in rural areas than in urban areas. However, the statistically significant rural-urban divides in the impacts of socioeconomic status on antenatal care and (after discharge) postnatal care were not observed. CONCLUSION:This study establishes the need for consideration of the rural-urban context in the formulation of policies to reduce disparities in maternal health care utilization in Tanzania.

Project description:BackgroundMultimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes.MethodsIn this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status.FindingsOf 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56-69) in 2015, and 5766 (48·8%) participants were male. 7320 (61·9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2·93, 95% CI 2·71-3·15), among women (2·70, 2·04-3·57), within a higher socioeconomic group (for quartile 4 [highest group] 1·50, 1·24-1·82), and higher educational level (5·17, 3·02-8·83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1·29, 95% CI 1·27-1·31), and number of days spent in hospital as an inpatient (1·38, 1·35-1·41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1·29, 95% CI 1·26-1·32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes.InterpretationConcerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection.FundingNone.

Project description:BackgroundEvidence of multimorbidity has come mainly from high-income regions, while disparities among racial groups have been less explored. This study examined racial differences in multimorbidity in the multiracial cohort of the Longitudinal Study of Adult Health (Estudo Longitudinal de Saúde do Adulto), ELSA-Brasil.MethodsThe study examined baseline (2008-2010) data for 14 099 ELSA-Brasil participants who self-reported being white, mixed-race, or black. A list of 16 morbidities was used to evaluate multimorbidity, operationalised by simple count into ≥ 2, ≥ 3, ≥ 4, ≥ 5 and ≥ 6 morbidities, in addition to evaluating the number of coexisting conditions. Prevalence ratios (PR) were estimated from logistic models and a quantile model was used to examine racial differences graphically in the distribution quantiles for the number of morbidities.ResultsOverall prevalence of multimorbidity (≥ 2 morbidities) was 70% and, after controlling for age and sex, was greater among mixed-race and black participants - by 6% (PR: 1.06; 95% CI: 1.03-1.08) and 9% (PR: 1.09; 95% CI: 1.06-1.12), respectively - than among white participants. As the cutoff value for defining multimorbidity was raised, so the strength of the association increased, especially among blacks: if set at ≥ 6 morbidities, the prevalence was 27% greater for those of mixed-race (PR: 1.27; 95% CI: 1.07-1.50) and 47% greater for blacks (PR: 1.47; 95% CI: 1.22-1.76) than for whites. The disparities were smaller in the lower morbidity distribution quantiles and larger in the upper quantiles, indicating a heavier burden of disease, particularly on blacks.ConclusionsMultimorbidity was common among adults and older adults in a Brazilian cohort, but important racial inequalities were found. Raising the cutoff point for defining multimorbidity revealed stronger associations between race/skin colour and multimorbidity, indicating a higher prevalence of multimorbidity among mixed-race and black individuals than among whites and that the former groups coexisted more often with more complex health situations (with more coexisting morbidities). Interventions to prevent and manage the condition of multimorbidity that consider the social determinants of health and historically discriminated populations in low- and middle-income regions are necessary.

Project description:BackgroundThe magnitude of socioeconomic health inequalities differs across age groups. It is less clear whether socioeconomic health inequalities differ across age groups by other factors that are known to affect the relation between socioeconomic position and health, like the indicator of socioeconomic position, the health outcome, gender, and as to whether socioeconomic health inequalities are measured in absolute or in relative terms. The aim is to investigate whether absolute and relative socioeconomic health inequalities differ across age groups by indicator of socioeconomic position, health outcome and gender.MethodsThe study sample was derived from the baseline measurement of the LifeLines Cohort Study and consisted of 95,432 participants. Socioeconomic position was measured as educational level and household income. Physical and mental health were measured with the RAND-36. Age concerned eleven 5-years age groups. Absolute inequalities were examined by comparing means. Relative inequalities were examined by comparing Gini-coefficients. Analyses were performed for both health outcomes by both educational level and household income. Analyses were performed for all age groups, and stratified by gender.ResultsAbsolute and relative socioeconomic health inequalities differed across age groups by indicator of socioeconomic position, health outcome, and gender. Absolute inequalities were most pronounced for mental health by household income. They were larger in younger than older age groups. Relative inequalities were most pronounced for physical health by educational level. Gini-coefficients were largest in young age groups and smallest in older age groups.ConclusionsAbsolute and relative socioeconomic health inequalities differed cross-sectionally across age groups by indicator of socioeconomic position, health outcome and gender. Researchers should critically consider the implications of choosing a specific age group, in addition to the indicator of socioeconomic position and health outcome, as findings on socioeconomic health inequalities may differ between them.

Project description:BackgroundVery little is known about socioeconomic related inequalities in multimorbidity, especially in developing countries. Traditionally, studies on health inequalities have mainly focused on a single disease condition or different conditions in isolation. This paper examines socioeconomic inequality in multimorbidity in illness and disability in South Africa between 2005 and 2008.MethodsData were drawn from the 2005, 2006, 2007, and 2008 rounds of the nationally representative annual South African General Household Surveys (GHS). Indirectly standardised concentration indices were used to assess socioeconomic inequality. A proxy index of socioeconomic status was constructed, for each year, using a selected set of variables that are available in all the GHS rounds. Multimorbidity in illness and disability were constructed using data on nine illnesses and six disabilities contained in the GHS.ResultsMultimorbidity affects a substantial number of South Africans. Most often, based on the nine illness conditions and six disability conditions considered, multimorbidity in illness and multimorbidity in disability are each found to involve only two conditions. In 2008 in South Africa, the multimorbidity that affected the greatest number of individuals (0.6% of the population) combined high blood pressure (BP) with at least one other illness. The combination of sexually transmitted diseases (STDs) and other condition or conditions is the least reported (i.e. 0.02% of the population). Between 2005 and 2008, multimorbidity in illness and disability is more prevalent among the poor; in disabilities this is yet more consistent. The concentration index of multiple illnesses in 2005 and 2008 are -0.0009 and -0.0006 respectively. The corresponding values for multiple disabilities are -0.0006 and -0.0006 respectively.ConclusionWhile there is a dearth of information on the socioeconomic distribution of multimorbidity in many developing countries, this paper has shown that its distribution in South Africa indicates that the poor bear a greater burden of multimorbidity. This is more so for disability than for illness. This paper argues that, given the high burden and skewed socioeconomic distribution of multimorbidity, there is a need to design policies to address this situation. Further, there is a need to design surveys that specifically assess multimorbidity.

Project description:BackgroundWe aimed to estimate multimorbidity trajectories and quantify socioeconomic inequalities based on childhood and adulthood socioeconomic position (SEP) in the risks and rates of multimorbidity accumulation across adulthood.Methods and findingsParticipants from the UK 1946 National Survey of Health and Development (NSHD) birth cohort study who attended the age 36 years assessment in 1982 and any one of the follow-up assessments at ages 43, 53, 63, and 69 years (N = 3,723, 51% males). Information on 18 health conditions was based on a combination of self-report, biomarkers, health records, and prescribed medications. We estimated multimorbidity trajectories and delineated socioeconomic inequalities (based on childhood and adulthood social class and highest education) in multimorbidity at each age and in longitudinal trajectories. Multimorbidity increased with age (0.7 conditions at 36 years to 3.7 at 69 years). Multimorbidity accumulation was nonlinear, accelerating with age at the rate of 0.08 conditions/year (95% CI 0.07 to 0.09, p < 0.001) at 36 to 43 years to 0.19 conditions/year (95% CI 0.18 to 0.20, p < 0.001) at 63 to 69 years. At all ages, the most socioeconomically disadvantaged had 1.2 to 1.4 times greater number of conditions on average compared to the most advantaged. The most disadvantaged by each socioeconomic indicator experienced an additional 0.39 conditions (childhood social class), 0.83 (adult social class), and 1.08 conditions (adult education) at age 69 years, independent of all other socioeconomic indicators. Adverse adulthood SEP was associated with more rapid accumulation of multimorbidity, resulting in 0.49 excess conditions in partly/unskilled compared to professional/intermediate individuals between 63 and 69 years. Disadvantaged childhood social class, independently of adulthood SEP, was associated with accelerated multimorbidity trajectories from age 53 years onwards. Study limitations include that the NSHD cohort is composed of individuals of white European heritage only, and findings may not be generalizable to the non-white British population of the same generation and did not account for other important dimensions of SEP such as income and wealth.ConclusionsIn this study, we found that socioeconomically disadvantaged individuals have earlier onset and more rapid accumulation of multimorbidity resulting in widening inequalities into old age, with independent contributions from both childhood and adulthood SEP.

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Socioeconomic inequalities in health in the context of multimorbidity: A Korean panel study.

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