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Increasingly studies have identified socioeconomic factors adversely affecting healthcare outcomes for a multitude of diseases. To date, however, there has not been a study correlating socioeconomic details from nationwide databases on the prevalence of advanced coronary artery disease. We seek to identify whether socioeconomic factors contribute t...
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Citations
... Regardless of the mechanism, there is a strong association between SES and health, because SES is considered a major social basis for inequality and an important predictor of health at all ages. SES appears to have a significant impact on a multitude of diseases, including cardiovascular disease, 82 respiratory disease, 83 neurological disorders, 84,85 and other chronic conditions such as obesity 86 and cancer. 84,87 Socioeconomically disadvantaged individuals have higher overall mortality rates than those of higher SES. ...
Objectives: To document the relationship between socioeconomic status (SES) and sleep health in African populations.
Methods: Observational cross-sectional or cohort studies examining the association between SES indicators and sleep outcomes in participants from African countries were included. The search was performed in the MEDLINE, Embase, and Web of Science Core Collection electronic databases in June 2021. Selection, confounding, attrition/exclusion, detection, and selective reporting bias were assessed using the OHAT Risk of Bias Tool. Random effects meta-analysis was used for summarizing the effect estimates.
Results: Forty-three reports were selected, having sampled 153,372 Africans from 26 countries. Education was the most frequent SES indicator and composite measures of sleep quality or disturbances was the most common sleep outcome. Low educational attainment was significantly associated with lower odds of short sleep (odds ratio [OR]=0.65, 95% confidence intervals [0.50, 0.84], p = .001) and higher odds of insomnia (OR=1.53, [1.18, 1.99], p = .001) or poor sleep quality (OR=1.60, [1.17, 2.18], p = .003). Low levels of income/assets were related to higher odds of insomnia (OR=1.38, [1.02, 1.86], p = .04) and low occupational/employment status was linked to lower odds of short sleep duration (OR=0.49, [0.30, 0.79], p = .004).
Conclusions: Socioeconomic disadvantage was a significant predictor of insomnia and poor sleep quality, while it was associated with longer sleep duration. Significant heterogeneity in terms of exposure and outcomes, scarcity of longitudinal designs, lack of objective outcome measurement, and low representation of rural samples and participants from low-income countries limit the quality of evidence.
... These living conditions in turn determine how an individual handles his health, with different patterns of health outcomes appearing through time, as documented by epidemiological studies. Literature demonstrated that people with high education and income, like white-collar workers, reported fewer chronic diseases than those with physical occupations like blue-collar workers [6][7][8] . Furthermore, people with higher levels of education and higher incomes have a lower prevalence of sleep disorders, mood disorders, musculoskeletal impairment, and chronic diseases, such as diabetes, morbid obesity, or cardiovascular diseases [6][7][8] . ...
... Literature demonstrated that people with high education and income, like white-collar workers, reported fewer chronic diseases than those with physical occupations like blue-collar workers [6][7][8] . Furthermore, people with higher levels of education and higher incomes have a lower prevalence of sleep disorders, mood disorders, musculoskeletal impairment, and chronic diseases, such as diabetes, morbid obesity, or cardiovascular diseases [6][7][8] . ...
To this day, no consensus has been established on the definition and the conceptualization of the socioeconomic status (SES), since all the available studies on the relation between SES and health did not use the same conceptual framework and operationalization to assess SES. While literature reported that SES markers (such as income, social support networks, education, employment or occupation) influence the health of populations by shaping living conditions; empirical research does not tell us which SES markers affect more strongly the sleep components of the individuals, as well as which sleep disorders (SD) are affected and how. Even though several original studies have tried to assess how changes in socioeconomic status of parents may affect the psychosocial environment and mental health of an individual directly or through his community, no systematic reviews on the influence of SES on children's sleep are available. This systematic review make an update on the different measures of SES and sleep disturbances used for pediatric population across the different regions of the world. Recommendations for a future standardization of SES measures is proposed, for a better understanding of its influence on sleep disturbances.
... Health disparities among different race/ethnicity groups are often related to differences in demographic, clinical, economic, psychosocial, and other social determinants of health. The inverse association of socioeconomic status (SES) with all phases of the progression of CVD is well established, from the onset of risk factors through mortality due to CVD [41][42][43][44][45]. Immigration status and acculturation processes may also impact CVD risk among Asian and Pacific Islander populations [46]. ...
Background: Cardiovascular disease (CVD) remains the leading cause of death in the US. CVD incidence is influenced by many demographic, clinical, cultural, and psychosocial factors, including race and ethnicity. Despite recent research, there remain limitations on understanding CVD health among Asians and Pacific Islanders (APIs), particularly some subgroups and multi-racial populations. Combining diverse API populations into one study group and difficulties in defining API subpopulations and multi-race individuals have hampered efforts to identify and address health disparities in these growing populations.
Methods: The study cohort was comprised of all adult patients at Kaiser Permanente Hawai’i and Palo Alto Medical Foundation in California during 2014–2018 (n = 684,363). EHR-recorded ICD-9 and ICD-10 diagnosis codes were used
to indicate coronary heart disease (CHD), stroke, peripheral vascular disease (PVD), and overall CVD. Self-reported race and ethnicity data were used to construct 12 mutually exclusive single and multi-race groups, and a Non-Hispanic White (NHW) comparison group. Logistic regression models were used to derive prevalence estimates, odds ratios, and confidence intervals for the 12 race/ethnicity groups.
Results: The prevalence of CHD and PVD varied 4-fold and stroke and overall CVD prevalence varied 3-fold across API subpopulations. Among Asians, the Filipino subgroup had the highest prevalence of all three CVD conditions and overall CVD. Chinese people had the lowest prevalence of CHD, PVD and overall CVD. In comparison to Native Hawaiians, Other Pacific Islanders had significantly higher prevalence of CHD. For the multi-race groups that included Native Hawaiians and Other Pacific Islanders, the prevalence of overall CVD was significantly higher than that for either single-race Native Hawaiians or Other Pacific Islanders. The multi-race Asian + White group had significantly higher overall CVD prevalence than both the NHW group and the highest Asian subgroup (Filipinos).
Conclusions: Study findings revealed significant differences in overall CVD, CHD, stroke, and PVD among API subgroups. In addition to elevated risk among Filipino, Native Hawaiian, and Other Pacific Islander groups, the study identified particularly elevated risk among multi-race API groups. Differences in disease prevalence are likely mirrored in other cardiometabolic conditions, supporting the need to disaggregate API subgroups in health research.
... The stress related to individual's socioeconomic status alone may impact his or her health 8 . There is a strong association between SES and health 9 . Low socioeconomic status is a global problem and major social determinant of health 10 . ...
Background: Socioeconomic status (SES) is an important determinant of health, and one of the major factors that determine treatment and rehabilitation outcomes of debilitating chronic conditions such as stroke and osteoarthritis (OA). Aim of the Study: This study determined and compared SES of stroke survivors and people living with osteoarthritis (PLWOA) in Port Harcourt Metropolis, Rivers State. Material and Methods: The study design was comparative cross-sectional. A multistage sampling technique was used to select 78 stroke survivors and 186 PLWOA from the two strata making up Port Harcourt Metropolis-Port Harcourt City Local Government Area (PHALGA) and Obio-Akpor Local Government Area (OBALGA). Kuppuswamy's socioeconomic scale was used to measure the current SES of the two groups from June 2019 to January 2020. Data were analyzed using the IBM SPSS version 24. Chi-square test statistic was used to compare the proportion of stroke survivors with low, middle and high SES and that of PLWOA. P-value ≤ 0.05 was considered statistically significant. Results: Results revealed that majority of stroke survivors and PLWOA were males, 55 (70.5%) and 106 (57%) respectively and within 51-60years of age. The proportions of stroke survivors with low, middle and high SES were 26.1%, 56.5% and 17.4% compared to 41.7%, 49.7% and 8.1% respectively of those of PLWOA. The difference observed between these proportions was statistically significant (Chi-square = 10.272, P-value = 0.006). Conclusion: The study concluded that most stroke survivors and PLWOA in Port Harcourt metropolis were of middle SES, and that low SES was higher in PLWOA than in stroke survivors.
... Although studies have shown that lower socioeconomic status (SES) is associated with poorer outcomes in CAD, the association between SES and PAD has been less extensively studied [123][124][125]. The association between SES and PAD is multifaceted and requires investigation into intersections of SES with treatment, postoperative outcomes, and health at presentation in patients with PAD. ...
Peripheral artery disease (PAD), the pathophysiologic narrowing of arterial blood vessels of the lower leg due to atherosclerosis, is a highly prevalent disease that affects over 6 million individuals aged ≥ 40 in the United States, with sharp increases in prevalence with age. Morbidity and mortality rates in patients with PAD range from 30% to 70% during the 5–15-year period after diagnosis and PAD is associated with poor health outcomes and reduced functionality and quality of life. Despite advances in medical, endovascular, and open surgical techniques, there is striking variation in care among population subgroups defined by sex, race/ethnicity, and socioeconomic status, with concomitant differences in preoperative medication optimization, amputation risk, and overall health outcomes. We reviewed studies from 1995 to 2021 to provide a comprehensive analysis of the current impact of disparities on the treatment and management of PAD and offer action items that require strategic partnership with primary care providers, researchers, patients, and their communities. With new technologies and collaborative approaches, optimal management across all population subgroups is possible.
... There is a robust body of literature where a number of factors related to economic well-being, employment status, neighborhood environment, and educational attainment associated with cardiovascular disease prevalence and outcomes at the individual level have been identified (10)(11)(12)(13)(14)(15)(16)(17)(18)(19) and the community level (4,20,21). Integrated metrics of community distress and socioeconomic status have also been linked to cardiovascular disease (4,(18)(19)(20). However, in prior studies where the relationship between measures of community vulnerability and prevalence of cardiovascular disease have been examined are based on considerably larger geographic regions such as counties which limits the degree of precision when estimating the impact of these non-traditional risk factors. ...
Background
: Social determinants of health are implicated in the geographic variation in cardiovascular diseases (CVDs). The social vulnerability index (SVI) is an estimate of a neighborhood's potential for deleterious outcomes when faced with natural disasters or disease outbreaks. We sought to investigate the association of the SVI with cardiovascular risk factors and the prevalence of coronary heart disease (CHD) in the United States at the census tract level.
Methods
: We linked census tract SVI with prevalence of census tract CVD risk factors (smoking, high cholesterol, diabetes, high blood pressure, low physical activity and obesity), and prevalence of CHD obtained from the behavioral risk factor surveillance system. We evaluated the association between SVI, its sub-scales, CVD risk factors and CHD prevalence using linear regression.
Results
: Among 72,173 census tracts, prevalence of all cardiovascular risk factors increased linearly with SVI. A higher SVI was associated with a higher CHD prevalence (R²=0.17, P<0.0001). The relationship between SVI and CHD was stronger when accounting for census-tract median age (R²=0.57, P<0.0001). A multivariable linear regression model including 4 SVI themes separately explained considerably more variation in CHD prevalence than the composite SVI alone (50.0% vs 17.3%). Socioeconomic status and household composition and disability were the SVI themes most closely associated with cardiovascular risk factors and CHD prevalence.
Conclusions
: In the United States, social vulnerability can explain significant portion of geographic variation in CHD and its risk factors. Neighborhoods with high social vulnerability are at disproportionately increased risk of CHD and its risk factors.
CONDENSED ABSTRACT
: Social determinants of health are implicated in the geographic variation in cardiovascular diseases (CVDs). We investigated the association of social vulnerability index (SVI) with cardiovascular risk factors and the prevalence of coronary heart disease (CHD) in the United States at the census tract level. We show that cardiovascular risk factors and CHD were more common with higher SVI. A multivariable linear regression model including 4 SVI themes separately explained considerably more variation in CHD prevalence than the composite SVI alone (50.0% vs 17.3%). Socioeconomic status and household composition/disability were the SVI themes most closely associated with cardiovascular risk factors and CHD prevalence.
... Hamidreza Roohafza (1) , Awat Feizi (2) , Mojgan Gharipour (3) , Azam Khani (4) , Minoo Dianatkhah (5) , Nizal Sarrafzadegan (6) , Masoumeh Sadeghi (7) Introduction Socioeconomic status (SES) is a term that refers to an individual's social position relative to other members of a society which can have either a positive or negative impact on a person's life. According to previous researches, the main factors that made SES were income, occupation, and education. ...
... According to previous researches, the main factors that made SES were income, occupation, and education. 1 There is some evidence based on many studies on different diseases which have found deep implications of SES for disease, [2][3][4] and there is a close relationship between SES and health that is assumed to begin early in life, perhaps even in the prenatal environment, and continue to accumulate throughout life. 5,6 The conditions in which people are born, live, grow, and age influence how people become sick, what risk factors they faced to, how they access to the services, and how they use those services. ...
Background:
Evaluation of socioeconomic status (SES) is an important aspect in community-based health studies and it is a major predictor of health and nutritional status as well as mortality and morbidity from many diseases. This study aimed to construct and validate socioeconomic status short-from questionnaire (SES-SQ) in Iranian population.
Methods:
This cross-sectional methodological study was conducted among 1437 Iranian general population. Face and content validity of the developed questionnaire was evaluated qualitatively. Internal consistency, construct validity using exploratory factor analysis (EFA) and latent class analysis (LCA), and convergent and known-group validity were also evaluated.
Results:
The SES-SQ consisted of 6 items. The overall Cronbach's alpha was 0.64, showing acceptable internal consistency. EFA resulted in two factors explaining 47.78% of total variance. Three SES classes (low/middle/high) were extracted by LCA. The score of SES-SQ ranged from 0 to 17; two cutoff scores of 4.5 and 8.5 were determined by receiver operating characteristic (ROC) analysis for differentiating low from middle and middle from high SES classes, respectively.
Conclusion:
An efficient, reliable, and valid short-form questionnaire was developed for evaluating SES in Iranian general population. The relevancy of questionnaire items is not lost over time.
... Socioeconomic status (SES) is known to have a powerful influence on patients' health. Studies have demonstrated strong association between SES and the prevalence and outcomes of cardiovascular disease, respiratory disease, mental disorders and cancer [1][2][3][4] . ...
Background
Socioeconomic status (SES) is likely to affect survival in breast cancer patients. Housing value is a reasonable surrogate for SES in Singapore where most residents own their own homes, which could be public (subsidised) or private housing. We evaluated effects of housing value and enhanced medical subsidies on patients’ presentation, treatment choices, compliance and survival in a setting of good access to healthcare.
Methods
A retrospective analysis of breast cancer patients treated in a tertiary hospital cluster from 2000 to 2016 was performed. Individual-level Housing value Index (HI) was derived from each patient's address and then grouped into 3 tiers: HI(high)(minimal subsidy), HI(med)(medium subsidy) and HI(low)(high subsidy). Cox regression was performed to evaluate the associations between overall survival (OS) and cancer-specific survival (CSS) with HI and various factors.
Findings
We studied a multiracial cohort of 15,532 Stage 0–IV breast cancer patients. Median age was 53.7 years and median follow-up was 7.7 years. Patients with lower HI presented with more advanced disease and had lower treatment compliance. On multivariable analysis, compared to HI(high) patients, HI(med) patients had decreased OS (HR=1.14, 95% CI 1.05–1.23) and CSS (HR=1.15, 95% CI 1.03–1.27), and HI(low) patients demonstrated reduced OS (HR=1.16, 95% CI 1.01–1.33). Ten-year non-cancer mortality was higher in lower HI-strata. Enhanced medical subsidy approximately halved treatment noncompliance rates but its receipt was not an independent prognostic factor for survival.
Interpretation
Despite good healthcare access, lower-HI patients have poorer survival from both cancer and non-cancer causes, possibly due to delayed health-seeking and poorer treatment compliance. Enhanced subsidies may mitigate socioeconomic disadvantages.
Funding
None.
... Additionally we found that membership of the lowest 25th percentile socioeconomic status was a significant negative predictor for overuse. Besides socioeconomic status being a well-established determinant for health and access to health services [38,39], associations with guideline compliance have also been found before [40,41]. ...
Background:
Bridging anticoagulation is used in vitamin-K antagonist (VKA) patients undergoing invasive procedures and involves complex risk assessment in order to prevent thromboembolic and bleeding outcomes.
Objectives:
Our aim was to assess guideline compliance and identify factors associated with bridging and especially, non-compliant bridging.
Methods:
A retrospective review of 256 patient records in 13 Dutch hospitals was performed. Demographic, clinical, surgical and care delivery characteristics were collected. Compliance to the American College of Chest Physicians ninth edition guideline (AT9) was assessed. Multilevel regression models were built to explain bridging use and predict non-compliance.
Results:
Bridging use varied from 15.0 to 83.3% (mean = 41.8%) of patients per hospital, whereas guideline compliance varied from 20.0 to 88.2% (mean = 68.5%) per hospital. Both established thromboembolic risk factors and characteristics outside thromboembolic risk assessment were associated with bridging use. Predictors for overuse were gastrointestinal surgery (OR 14.85, 95% CI 2.69-81.99), vascular surgery (OR 13.01, 95% CI 1.83-92.30), non-elective surgery (OR 8.67, 95% CI 1.67-45.14), lowest 25th percentile socioeconomic status (OR 0.33, 95% CI 0.11-1.02) and use of VKA reversal agents (OR 0.22, 95% CI 0.04-1.16).
Conclusion:
Bridging anticoagulation practice was not compliant with the AT9 in 31.5% of patients. The aggregated AT9 thromboembolic risk was inferior to individual thromboembolic risk factors and other characteristics in explaining bridging use. Therefor the AT9 risk seems less important for the decision making in everyday practice. Additionally, a heterogeneous implementation of the guideline between hospitals was found. Further research and interventions are needed to improve bridging anticoagulation practice in VKA patients.
... As for many other health outcomes [1][2][3][4], individuals with a lower education have a higher incidence and mortality of diseases in the circulatory system (here termed cardiovascular disease (CVD)) than individuals with a higher education [5][6][7][8][9][10]. Most studies aiming at explaining this inequality have focused on whether it could be due to educational differences in established CVD risk factors [11] such as smoking patterns, hypertension and serum lipids. ...
Aims:
Educational inequality in diseases in the circulatory system (here termed cardiovascular disease) is well documented but may be confounded by early life factors. The aim of this observational study was to examine whether the associations between education and all cardiovascular diseases, ischaemic heart disease and stroke, respectively, were explained by family factors shared by siblings.
Methods:
The study population included all individuals born in Denmark between 1950 and 1979 who had at least one full sibling born in the same period. Using Cox regression, data were analysed in conventional cohort and within-sibship analyses in which the association was examined within siblings discordant on education. Assuming that attenuation of associations in the within-sibship as compared with the cohort analyses would indicate confounding from factors shared within families.
Results:
A lower educational status was associated with a higher risk of cardiovascular disease, ischaemic heart disease and stroke. All associations attenuated in the within-sibship analyses, in particular in the analyses on ischaemic heart disease before age 45 years. For instance, in the cohort analyses, the hazard rate of ischaemic heart disease among women less than 45 years who had a primary school education was 94% (hazard ratio 1.94 (1.78-2.12) higher than among those with a vocational education, while it attenuated to 51% (hazard ratio 1.51 (1.34-1.71)) in the within-sibship analysis.
Conclusions:
Confounding from factors shared by siblings explained the associations between education and the cardiovascular disease outcomes but to varying degrees. This should be taken into account when planning interventions aimed at reducing educational inequalities in the development of cardiovascular disease, ischaemic heart disease and stroke.
