Race, Ethnicity and Nativity, Family Structure, Socioeconomic Status and Welfare Dependency

2000 ◽  
Vol 34 (3) ◽  
pp. 739 ◽  
Author(s):  
Hiromi Ono ◽  
Rosina M. Becerra
Keyword(s):  
Socioeconomic Status ◽  
Family Structure ◽  
Welfare Dependency ◽  
Race Ethnicity

Treatment disparities in female breast cancer patients according to race, ethnicity and socioeconomic status

2013 ◽  
Author(s):  
Christopher S. Bartlett ◽  
Tulay Koru-Sengul ◽  
Feng Miao ◽  
Stacey L. Tannenbaum ◽  
David J. Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Socioeconomic Status ◽  
Cancer Patients ◽  
Female Breast Cancer ◽  
Breast Cancer Patients ◽  
Female Breast ◽  
Treatment Disparities ◽  
Race Ethnicity

scholarly journals AB0142 SOCIOECONOMIC STATUS (SES) AND MEDICATION USE IN RHEUMATOID ARTHRITIS (RA): A SCOPING REVIEW

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1098.2-1099
Author(s):  
O. Russell ◽  
S. Lester ◽  
R. Black ◽  
C. Hill
Keyword(s):  
Rheumatoid Arthritis ◽  
Socioeconomic Status ◽  
Scoping Review ◽  
Research Training ◽  
Medication Use ◽  
Study Group ◽  
Knowledge Gaps ◽  
Coverage Area ◽  
Race Ethnicity ◽  
The Impact

Background:Socioeconomic status (SES) influences disease outcomes in rheumatoid arthritis (RA) patients. (1, 2) Differences in medication use could partly explain this association. (3) A scoping review was used to identify research conducted on this topic and determine what knowledge gaps remain.Objectives:To determine what research has been conducted on this topic, how this research has defined SES and medication use, and establish what knowledge gaps remain.Methods:MEDLINE, EMBASE and PsychInfo were searched from their inception until May 2019 for studies which assessed SES and medication use as outcome variables. Studies were included if they measured medication use and incorporated an SES measure as a comparator variable.SES was defined using any of the “PROGRESS” framework variables (4) including patients’ stated gender, age, educational attainment, employment, occupational class, personal income, marital status, health insurance coverage, area- (neighbourhood) level SES, or patients’ stated race and/or ethnicity. Medication use was broadly defined as either prescription or dispensation of a medicine, medication adherence, or delays in treatment. Data was extracted on studies’ primary objectives, measurement of specific SES measures, patients’ medication use, and whether studies assessed for differences in patients’ medication use according to SES variables.Results:1464 studies were identified by this search from which 74 studies were selected for inclusion, including 52 published articles. Studies’ publication year ranged from 1994-2019, and originated from 20 countries; most commonly from the USA.Studies measured a median of 4 SES variables (IQR 3-6), with educational achievement, area level SES and race/ethnicity the most frequently recorded.Likelihood of disease modifying antirheumatic drug (DMARD) prescription was the most frequent primary objective recorded.96% of studies reported on patients’ use of DMARDs, with glucocorticoids and analgesics being reported in fewer studies (51% and 23% respectively.)Most included studies found at least one SES measure to be significantly associated with differences in patients’ medication use. In some studies, however, this result was not necessarily drawn from the primary outcome and therefore may not have been adjusted for covariates.70% of published studies measuring patients’ income (n=14 of 20) and 58% of those that measured race/ethnicity (n=14 of 24) documented significant differences in patients’ medication use according to these SES variables, although the direction of this effect – whether it led to ‘greater’ or ‘lesser’ medication use – varied between studies.Conclusion:Multiple definitions of SES are used in studies of medication use in RA patients. Despite this, most identified studies found evidence of a difference in medication use by patient groups that differed by an SES variable, although how medication use differed was found to vary between studies. This latter observation may relate to contextual factors pertaining to differences in countries’ healthcare systems. Further prospective studies with clearly defined SES and medication use measures may help confirm the apparent association between SES and differences in medication use.References:[1]Jacobi CE, Mol GD, Boshuizen HC, Rupp I, Dinant HJ, Van Den Bos GA. Impact of socioeconomic status on the course of rheumatoid arthritis and on related use of health care services. Arthritis Rheum. 2003;49(4):567-73.[2]ERAS Study Group. Socioeconomic deprivation and rheumatoid disease: what lessons for the health service? ERAS Study Group. Early Rheumatoid Arthritis Study. Annals of the rheumatic diseases. 2000;59(10):794-9.[3]Verstappen SMM. The impact of socio-economic status in rheumatoid arthritis. Rheumatology (Oxford). 2017;56(7):1051-2.[4]O’Neill J, Tabish H, Welch V, Petticrew M, Pottie K, Clarke M, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014;67(1):56-64.Acknowledgements:This research was supported by an Australian Government Research Training Program Scholarship.Disclosure of Interests:None declared

scholarly journals Conceptual causal models of socioeconomic status, family structure, family functioning and their role in public health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Frederik Booysen ◽  
Ferdi Botha ◽  
Edwin Wouters
Keyword(s):  
Public Health ◽  
Socioeconomic Status ◽  
Family Functioning ◽  
Family Structure ◽  
Empirical Studies ◽  
Social Determinant ◽  
Causal Models ◽  
Family Socioeconomic Status ◽  
The Family ◽  
Social Determinant Of Health

AbstractSocial determinants of health frameworks are standard tools in public health. These frameworks for the most part omit a crucial factor: the family. Socioeconomic status moreover is a prominent social determinant of health. Insofar as family functioning is poorer in poor families and family structure and functioning are linked to health, it is critical to consider the pathways between these four constructs. In this correspondence, we reflect on how empirical studies of this conceptual nexus mirror two causal models. We conclude by reflecting on future directions for research in this field.

scholarly journals Do quality improvement initiatives for diabetes care address social inequities? Secondary analysis of a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e018826 ◽  
Author(s):  
Jacquie Boyang Lu ◽  
Kristin J Danko ◽  
Michael D Elfassy ◽  
Vivian Welch ◽  
Jeremy M Grimshaw ◽  
...  
Keyword(s):  
Systematic Review ◽  
Socioeconomic Status ◽  
Quality Improvement ◽  
Diabetes Care ◽  
Secondary Analysis ◽  
Place Of Residence ◽  
Disadvantaged Groups ◽  
Disadvantaged Populations ◽  
Patients With Diabetes ◽  
Race Ethnicity

BackgroundSocially disadvantaged populations carry a disproportionate burden of diabetes-related morbidity and mortality. There is an emerging interest in quality improvement (QI) strategies in the care of patients with diabetes, however, the effect of these interventions on disadvantaged groups remains unclear.ObjectiveThis is a secondary analysis of a systematic review that seeks to examine the extent of equity considerations in diabetes QI studies, specifically quantifying the proportion of studies that target interventions toward disadvantaged populations and conduct analyses on the impact of interventions on disadvantaged groups.Research design and methodsStudies were identified using Medline, HealthStar and the Cochrane Effective Practice and Organisation of Care database. Randomised controlled trials assessing 12 QI strategies targeting health systems, healthcare professionals and/or patients for the management of adult outpatients with diabetes were eligible. The place of residence, race/ethnicity/culture/language, occupational status, gender/sexual identity, religious affiliations, education level, socioeconomic status, social capital, plus age, disability, sexual preferences and relationships (PROGRESS-Plus) framework was used to identify trials that focused on disadvantaged patient populations, to examine the types of equity-relevant factors that are being considered and to explore temporal trends in equity-relevant diabetes QI trials.ResultsOf the 278 trials that met the inclusion criteria, 95 trials had equity-relevant considerations. These include 64 targeted trials that focused on a disadvantaged population with the aim to improve the health status of that population and 31 general trials that undertook subgroup analyses to assess the extent to which their interventions may have had differential impacts on disadvantaged subgroups. Trials predominantly focused on race/ethnicity, socioeconomic status and place of residence as potential factors for disadvantage in patients receiving diabetes care.ConclusionsLess than one-third of diabetes QI trials included equity-relevant considerations, limiting the relevance and applicability of their data to disadvantaged populations. There is a need for better data collection, reporting, analysis and interventions on the social determinants of health that may influence the health outcomes of patients with diabetes.PROSPERO registration numberCRD42013005165.

Race and Ethnicity in Medical Research: Requirements Meet Reality

2006 ◽  
Vol 34 (3) ◽  
pp. 520-525 ◽  
Author(s):  
Margaret A. Winker
Keyword(s):  
Socioeconomic Status ◽  
Medical Research ◽  
Socioeconomic Factors ◽  
Biomedical Research ◽  
Race And Ethnicity ◽  
Careful Consideration ◽  
Biomedical Literature ◽  
Genetics Research ◽  
Race Ethnicity ◽  
Policy And Procedure

Race and ethnicity are commonly reported variables in biomedical research, but how they were initially determined is often not described and the rationale for analyzing them is often not provided. JAMA improved the reporting of these factors by implementing a policy and procedure for doing so. However, still lacking are careful consideration of what is actually being measured when race/ethnicity is described, consistent terminology, hypothesis-driven justification for analyzing race/ethnicity, and a consistent and generalizable measurement of socioeconomic status. Furthermore, some studies continue to use race/ethnicity as a proxy for genetics. Research into appropriate measures of race/ethnicity and socioeconomic factors, as well as education of researchers regarding issues of race/ethnicity, is necessary to clarify the meaning of race/ethnicity in the biomedical literature.

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