Socioeconomic inequalities in health in the context of multimorbidity: A Korean panel study.
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SUBMITTER: Ki M
PROVIDER: S-EPMC5351993 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo document socioepidemiological theories used to explain the relationship between socioeconomic disadvantage and multimorbidity.DesignScoping review.MethodsA search strategy was developed and then applied to multiple electronic databases including Medline, Embase, PsychInfo, Web of Science, Scielo, Applied Social Sciences, ERIC, Humanities Index and Sociological Abstracts. After the selection of studies, data were extracted using a data charting plan. The last search was performed on the 28 September 2021. Extracted data included: study design, country, population subgroups, measures of socioeconomic inequality, assessment of multimorbidity and conclusion on the association between socioeconomic variables and multimorbidity. Included studies were further assessed on their use of theory, type of theories used and context of application. Finally, we conducted a meta-narrative synthesis to summarise the results.ResultsA total of 64 studies were included in the review. Of these, 33 papers included theories as explanations for the association between socioeconomic position and multimorbidity. Within this group, 16 explicitly stated those theories and five tested at least one theory. Behavioural theories (health behaviours) were the most frequently used, followed by materialist (access to health resources) and psychosocial (stress pathways) theories. Most studies used theories as post hoc explanations for their findings or for study rationale. Supportive evidence was found for the role of material, behavioural and life course theories in explaining the relationship between social inequalities and multimorbidity.ConclusionGiven the widely reported social inequalities in multimorbidity and its increasing public health burden, there is a critical gap in evidence on pathways from socioeconomic disadvantage to multimorbidity. Generating evidence of these pathways will guide the development of intervention and public policies to prevent multimorbidity among people living in social disadvantage. Material, behavioural and life course pathways can be targeted to reduce the negative effect of low socioeconomic position on multimorbidity.
| S-EPMC8882654 | biostudies-literature
Project description:BackgroundThe burden of multimorbidity is likely higher in ethnic minority populations, as most individual diseases are more prevalent in minority groups. However, information is scarce. We examined ethnic inequalities in multimorbidity, and investigated to what extent they reflect differences in socioeconomic status (SES).MethodsWe included Healthy Life in an Urban Setting study participants of Dutch (N = 4582), South-Asian Surinamese (N = 3258), African Surinamese (N = 4267), Ghanaian (N = 2282), Turkish (N = 3879) and Moroccan (N = 4094) origin (aged 18-70 years). Educational level, employment status, income situation and multimorbidity were defined based on questionnaires. We described the prevalence and examined age-adjusted ethnic inequalities in multimorbidity with logistic regression analyses. To assess the contribution of SES, we added SES indicators to the age-adjusted model.ResultsThe prevalence of multimorbidity ranged from 27.1 to 53.4% in men and from 38.5 to 69.6% in women. The prevalence of multimorbidity in most ethnic minority groups was comparable to the prevalence among Dutch participants who were 1-3 decades older. After adjustment for SES, the odds of multimorbidity remained significantly higher in ethnic minority groups. For instance, age-adjusted OR for multimorbidity for the Turkish compared to the Dutch changed from 4.43 (3.84-5.13) to 2.34 (1.99-2.75) in men and from 5.35 (4.69-6.10) to 2.94 (2.54-3.41) in women after simultaneous adjustment for all SES indicators.ConclusionsWe found a significantly higher prevalence of multimorbidity in ethnic minority men and women compared to Dutch, and results pointed to an earlier onset of multimorbidity in ethnic minority groups. These inequalities in multimorbidity were not fully accounted for by differences in SES.
| S-EPMC6660190 | biostudies-literature
Project description:Socioeconomic status differentials in health are well documented. Less is known about the socioeconomic variation in health in older people, and in older women in particular. The aim of the study was to examine the association between socioeconomic status and health in older women in relation to two indicators of socioeconomic status and three measures of health, and further, to investigate whether socioeconomic differences in health increase or decrease with advancing age. Data from a cross-sectional population based health survey inviting all women ≥70 years were analysed; 6,380 women aged 70-103 years participated. Logistic regression was applied to analyse variation in health by socioeconomic status. Disadvantaged socioeconomic status (i.e. lower educational levels and previous manual or never been in paid work) was significantly associated with poorer health outcomes, whether measured as self-assessed health or depression. Limiting long-standing illness was significantly associated with never been in paid work. The associations were not attenuated by simultaneous adjustments for health behavioural factors, social support, and marital status. Additional adjustments for medical conditions did only alter the significant association between employment status and limiting long-standing illness. The analyses revealed that educational inequalities did not decrease with advancing age, whereas the results for employment varied across age groups. Our findings suggest an enduring relation between socioeconomic status and health in later life. The study adds to the understanding of the consistent associations between poorer health and social disadvantages at older age. We are not aware of any previous study showing the persistence of social inequalities in health upon adjustments for medical conditions.
| S-EPMC5547285 | biostudies-other
Project description:BackgroundExisting 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.MethodsDrawing 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.ResultsSignificantly 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.ConclusionThis 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.
| S-EPMC7652341 | biostudies-literature
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.
| S-EPMC7241981 | biostudies-literature
Project description:ObjectivesMultimorbidity, the co-occurrence of multiple long-term conditions, is common and increasing. Definitions and assessment methods vary, yielding differences in estimates of prevalence and multimorbidity severity. Sociodemographic characteristics are associated with complicating factors of multimorbidity. We aimed to investigate the prevalence of complex multimorbidity by sex and occupational groups throughout adulthood.DesignCross-sectional study.SettingThe third total county survey of The Nord-Trøndelag Health Study (HUNT), 2006-2008, Norway.ParticipantsIndividuals aged 25-100 years with classifiable occupational data and complete questionnaires and measurements.Outcome measureComplex multimorbidity defined as 'the co-occurrence of three or more chronic conditions affecting three or more different body (organ) systems within one person without defining an index chronic condition'.AnalysisLogistic regression models with age and occupational group were specified for each sex separately.Results38 027 of 41 193 adults (55% women) were included in our analyses. 54% of the participants were identified as having complex multimorbidity. Prevalence differences in percentage points (pp) of those in the low occupational group (vs the high occupational group (reference)) were 19 (95% CI, 16 to 21) pp in women and 10 (8 to 13) pp in men at 30 years; 12 (10 to 14) pp in women and 13 (11 to 15) pp in men at 55 years; and 2 (-1 to 4) pp in women and 7 (4 to 10) pp in men at 75 years.ConclusionComplex multimorbidity is common from early adulthood, and social inequalities persist until 75 years in women and 90 years in men in the general population. These findings have policy implications for public health as well as healthcare, organisation, treatment, education and research, as complex multimorbidity breaks with the specialised, fragmented paradigm dominating medicine today.
| S-EPMC7299021 | biostudies-literature
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.
| S-EPMC9270815 | biostudies-literature
Project description:ObjectivesThis study aimed to estimate the effects of positive personality traits (PTs) in income and self-rated dental and general health (SRDH and SRGH) associations in a large South Australian sample.MethodsCross-sectional analyses were conducted using self-reported data collected from 3578 adults (2015-2016). Multivariable regression models assessed the main effects and interactions of the Ten-Item Personality Inventory (TIPI) and income with SRDH and SRGH. Prevalence ratios (PR) of poor health ratings were estimated using Poisson regression.ResultsAmong all respondents, high-income individuals with stronger Conscientiousness scores had the lowest prevalence of poor SRGH (0.8%), while those with stronger Extraversion (2.9%) and Agreeableness scores (3.4%) had the lowest prevalence of poor SRDH. Poor SRGH was related to weak Conscientiousness (PR = 6.9, 95% CI [2.3-20.8]) and Emotional Stability scores (PR = 6.0, 95% CI [2.0-18.3]), while poor SRDH was associated with weak Extraversion (PR = 2.3, 95% CI [1.2-4.5]), Agreeableness (PR = 1.8, 95% CI [1.0-3.2]) and Conscientiousness scores (PR = 2.1, 95% CI [1.1-4.0]). Among low-income people, poor health ratings were less prevalent in those with stronger positive PTs scores versus weaker scores. Among low-income respondents, poor SRGH was lower in individuals with stronger versus weaker Conscientiousness scores (10.9% vs 16.2%), and poor SRDH showed lower prevalence in participants with stronger versus weaker Agreeableness scores (18.1% vs 22.6%).ConclusionFindings showed the association between PTs and the prevalence of poor SRDH and SRGH. Stronger positive PTs modified the self-rated health inequalities associated with low income in a representative sample of the South Australian population.
| S-EPMC10946537 | biostudies-literature
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.
| S-EPMC4696790 | biostudies-literature
Project description:Across Europe, excess body weight rates are particularly high among children and adolescents living in Southern European contexts. In Spain, current food policies appeal to voluntary self-regulation of the food industry and parents' responsibility. However, there is no research (within Spain) assessing the food environment surrounding schools. We examined the association between neighborhood-level socioeconomic status (NSES) and the spatial access to an unhealthy food environment around schools using both counts and distance measures, across the city of Madrid. We conducted a cross-sectional study citywide (n = 2443 census tracts). In 2017, we identified all schools (n = 1321) and all food retailers offering unhealthy food and beverages surrounding them (n = 6530) using publicly available data. We examined both the counts of retailers (within 400 m) and the distance (in meters) from the schools to the closest retailer. We used multilevel regressions to model the association of neighborhood-level socioeconomic status (NSES) with both measures, adjusting both models for population density. Almost all schools (95%) were surrounded by unhealthy retailers within 400 m (median = 17 retailers; interquartile range = 8-34). After adjusting for population density, NSES remained inversely associated with unhealthy food availability. Schools located in low-NSES areas (two lowest quintiles) showed, on average, 29% (IRR (Incidence Rate Ratio) = 1.29; 95% CI (Confidence Interval) = 1.12, 1.50) and 62% (IRR = 1.62; 95% CI = 1.35, 1.95) more counts of unhealthy retailers compared with schools in middle-NSES areas (ref.). Schools in high-NSES areas were farther from unhealthy food sources than those schools located in middle-NSES areas (β = 0.35; 95% CI = 0.14, 0.47). Regulating the school food environment (within and beyond school boundaries) may be a promising direction to prevent and reduce childhood obesity.
| S-EPMC6683257 | biostudies-literature