Socioeconomic Status Risk Factors Research Articles

A network analysis of cardiovascular risk factors in patients with heart disease: the role of socioeconomic status and sex.

Diverse risk factors influence the development and prognosis of coronary heart disease (CHD) independently and mutually. Low socio-economic status (SES) seems to exacerbate these risk factors' influences. Additionally, sex differences have been identified for individual risk factors. Network analysis could provide in-depth insight into the interrelatedness of the risk factors, their predictability, and into the moderating role of sex, to ultimately contribute to more refinement in prevention and cardiac rehabilitation (CR). 1682 participants (78% male; Mage = 69.2 ± 10.6) with CHD completed questionnaires on psychosocial factors and health behaviors. Cardiometabolic data were retrieved through medical records. An SES index was created based on self-reported occupation and education, and area (i.e., postal code)-based median family income. Using R, we conducted a mixed graphical model network analysis on all risk factors combined with and without the moderating role of sex. SES belonged to the more influential risk factors with moderate to high levels of expected influence and degree centrality, indicating it plays a considerable role in the risk factor network. When considering the moderating role of sex, relationships between SES and most risk factors were found to be stronger for women (b = 0.06 - 0.48). The current study provided an insight into an interrelated network of psychosocial and medical risk factors among CHD patients. With SES belonging to the more influential risk factors and female sex influencing the strength of all the SES-risk factor relationships, CR and prevention techniques could be more refined by accounting for both influences.

Geographic Variation and Risk Factor Association of Early Versus Late Onset Colorectal Cancer

The proportion of patients diagnosed with colorectal cancer (CRC) at age < 50 (early-onset CRC, or EOCRC) has steadily increased over the past three decades relative to the proportion of patients diagnosed at age ≥ 50 (late-onset CRC, or LOCRC), despite the reduction in CRC incidence overall. An important gap in the literature is whether EOCRC shares the same community-level risk factors as LOCRC. Thus, we sought to (1) identify disparities in the incidence rates of EOCRC and LOCRC using geospatial analysis and (2) compare the importance of community-level risk factors (racial/ethnic, health status, behavioral, clinical care, physical environmental, and socioeconomic status risk factors) in the prediction of EOCRC and LOCRC incidence rates using a random forest machine learning approach. The incidence data came from the Surveillance, Epidemiology, and End Results program (years 2000-2019). The geospatial analysis revealed large geographic variations in EOCRC and LOCRC incidence rates. For example, some regions had relatively low LOCRC and high EOCRC rates (e.g., Georgia and eastern Texas) while others had relatively high LOCRC and low EOCRC rates (e.g., Iowa and New Jersey). The random forest analysis revealed that the importance of community-level risk factors most predictive of EOCRC versus LOCRC incidence rates differed meaningfully. For example, diabetes prevalence was the most important risk factor in predicting EOCRC incidence rate, but it was a less important risk factor of LOCRC incidence rate; physical inactivity was the most important risk factor in predicting LOCRC incidence rate, but it was the fourth most important predictor for EOCRC incidence rate. Thus, our community-level analysis demonstrates the geographic variation in EOCRC burden and the distinctive set of risk factors most predictive of EOCRC.

Socioeconomic Classes among Oldest-Old Women in South Korea: A Latent Class Analysis.

Oldest-old women are known to live at the intersection of multiple socioeconomic disadvantages in South Korean society. This study classified oldest-old Korean women into several socioeconomically homogeneous classes based on various socioeconomic status (SES) risks and compared health characteristics among the identified classes. This cross-sectional study utilized the 2019 Korean Community Health Survey, including data from 11,053 women (≥80 years). Latent class analysis determined the number of underlying socioeconomic classes based on nine selected SES variables. Four distinct socioeconomic classes were identified: “Urban, living alone, recipient of NBLSS, moderate education, leisure activity” (Class 1), “Rural, traditional house, living with others, not financially deprived, low education, employed” (Class 2), “Urban, living with family, financially affluent, not employed, no barriers to healthcare” (Class 3), “Rural, traditional house, living alone, financially deprived, uneducated, employed, barriers to healthcare” (Class 4). Depressive symptoms, subjective stress, and the prevalence of sleep disorder and diabetes were higher in Class 1 compared to other classes. Health-related quality of life, perceived health, and self-rated oral health were the poorest in Class 4. Class 3 reported the best health status. Understanding the intersecting SES risk factors in this group can aid in developing targeted interventions.

Association between birth in the stroke belt and late‐life cognition with assessment of socioeconomic and cardiovascular risk factors: The Study of Healthy Aging in African Americans (STAR)

AbstractBackgroundThe Southeastern U.S. (“Stroke Belt”) is known for high rates of cardiovascular diseases and cognitive impairment. Due to the high proportion of Black Americans born in the Stroke Belt and their elevated risk of cognitive impairment, we examined the relationship of birth in a Stroke Belt state with late‐life cognition in The Study of Healthy Aging in African Americans (STAR).MethodSTAR evaluated cognition in African Americans (N=764) ages 50+ who were long‐term Kaiser Permanente Northern California members. Participants completed Multiphasic Health Check‐ups (1964‐1985) at which early adulthood cardiovascular risk factors (CVRF) of body mass index, blood pressure, glucose, and total cholesterol were measured. At STAR wave 1 (2018), participants self‐reported birth state (all participants resided in northern California by the 1980s), childhood and young adulthood socioeconomic status (SES), and completed cognitive assessments using the Spanish and English Neuropsychological Assessment Scales (SENAS). We used linear regression to estimate the association between Stroke Belt birth state with cognition adjusting for birth year, gender, and parental education and evaluating SES and CVRF as potential mediators.ResultAfter exclusions for missing data, 27% (n=197) of 728 participants were born in a Stroke Belt state and mean age at cognitive assessment was 69 years (SD=9). Birth in a Stroke Belt state was associated with worse late‐life executive function (β(95% CI): ‐0.18(‐0.33, ‐0.02)) and semantic memory (β(95% CI): ‐0.37(‐0.53, ‐0.21)), but not verbal episodic memory, compared to individuals born elsewhere. Having 2+ SES risk factors (β(95% CI): ‐0.77(‐0.97, ‐0.56)) or 2+ CVRF (β(95% CI): ‐0.20(‐0.37, ‐0.03)) was associated with significantly worse executive function compared to having no SES or cardiovascular risk factors, respectively. Additionally, having 2+ SES risk factors (β(95% CI): ‐0.64(‐0.85, ‐0.43)) was associated with worse semantic memory. Associations of birth in a Stroke Belt state with executive function (β(95% CI): ‐0.07(‐0.23, 0.08)) and semantic memory (β(95% CI): ‐0.30(‐0.47, ‐0.14)) were attenuated after adjusting for SES and cardiovascular risk factors simultaneously (as well as individually).ConclusionBirth in a Stroke Belt state has lasting influence on cognitive function that is only partially mediated by childhood and early adulthood SES and cardiovascular risk factors.

Geospatial analysis of salmonellosis and its association with socioeconomic status in Texas

ObjectiveThe study’s objective was to find the association between salmonellosis and socioeconomic status (SES) in hot spot areas and statewide counties.DesignA retrospective cohort study.SettingThe data were recorded regarding salmonellosis in...

Socioeconomic status variables contribute to the disparities in female triple negative breast cancer outcome in the United States, 2011-2015: A population study based on NCI Surveillance, Epidemiology and End Results (SEER) database.

6521 Background: Cancer disparities pertinent to socioeconomic status (SES) still exist in the American healthcare system. How SES variables impact the outcome of triple negative breast cancer (TNBC) needs identification. Methods: We enrolled 22,434 women diagnosed with invasive TNBC in 2011 – 2015 from the SEER 18 program. The primary outcome was to identify SES risk factors for TNBC cause specific survival (TNBCCSS)and overall survival (OS) via the Cox Proportional Hazard Regression Model. SES information was collected: race, insurance status, marital status, and percentage of families with incomes below the poverty level and adults with less than high school graduate (&lt;HSG) in a county of the patient’s residency; all analyses were also adjusted for clinicopathological characteristics. We categorized rates of poverty and &lt;HSG as quartiles. Results: 18,578 (82.8%) women were insured or insured/ no specifics (NS), and 3,360 (15.0%) received Medicaid upon TNBC diagnosis; only 496 (2.2%) patients were uninsured. The TNBCCSS rates of insured, insured/ NS, Medicaid, and uninsured cohorts were 86.6%, 83.6%, 77.4% and 73.2%, respectively. In multivariable adjusted analyses, the TNBC cause specific mortality risk of patients who were uninsured or receiving Medicaid was significantly higher than that of women who were insured (Hazard ratio [HR] = 1.60, 95% confidence interval [CI]: 1.34-1.92 and HR = 1.29, 95% CI: 1.18-1.41, respectively). Women residing in a county with a high poverty rate (the 3rd quartile [rate of 11.1 – &lt;14.3%]) had significantly worse TNBC cause specific mortality risk as compared to women with residency of the lowest poverty rate (HR = 1.25, 95% CI: 1.10-1.41). Single and widowed cohorts had better HR of TNBCCSS compared with the married population (HR = 0.86, 95% CI: 0.79-0.95 and HR = 0.82, 95% CI: 0.73-0.93, respectively). Notably, we observed a synergistic effect among race, insurance status and TNBC OS: black women receiving Medicaid had significantly lower HR compared with their non-Hispanic white counterparts (HR = 0.86, 95% CI: 0.74-0.98). Rate of &lt;HSG was marginally correlated with the TNBCCSS. Conclusions: SES variables contribute to the disparities in TNBC survival. TNBC cause specific mortality risk of patients without insurance or with Medicaid at the time of TNBC diagnosis is 60% and 29% higher compared with insured women (Table). Race and insurance status act synergistically upon TNBC OS.[Table: see text]

The Effect of Socioeconomic Status on Treatment and Mortality in Non-Small Cell Lung Cancer Patients

Treatment decisions for patients with non-small cell lung cancer (NSCLC) are based on patient and tumor characteristics, including socioeconomic status (SES) factors. The objective was to assess the contribution of SES factors to treatment and outcomes among patients with stage I NSCLC. The National Cancer Database was queried for operable patients with stage I NSCLC. Patients were divided into three treatment groups: primary resection (ie, surgery only); nonstandard treatments consisting of chemotherapy with or without radiation; and no therapy. The SES of patients who made up the treatment groups was assessed, and the 5-year survival of all groups was analyzed. The cohort included 69,168 patients with stage I NSCLC. Each of these patients had between zero and five SES risk factors. The factors associated with no surgery were low income, nonwhite race, low high school graduation rate, Medicaid or no insurance, rural residence, and distance less than 12.5 miles from treatment facility. Patients with several SES risk factors have linearly increasing odds of undergoing nonstandard treatments and quadratically increasing odds of having no therapy (for patients with five factors, to odds ratio 4.7; 95% confidence interval, 3.44 to 6.30). Surgery alone was associated with significantly longer 5-year survival (71.8%) compared with nonstandard treatments (22.7%) and no therapy (21.8%; P < .001). Socioeconomic status factors increase the risk of undergoing guideline discordant therapy for stage I NSCLC. As the number of SES factors increases, the odds of no therapy rises quadratically whereas the odds of nonstandard treatments rises constantly. The surgery only group had significantly longer survival than the nonstandard treatment and no therapy groups.

Timed Up and Go (TUG) Test: Normative Reference Values for Ages 20 to 59 Years and Relationships With Physical and Mental Health Risk Factors.

The Timed Up and Go (TUG) test is a reliable, cost-effective, safe, and time-efficient way to evaluate overall functional mobility. However, the TUG does not have normative reference values (NRV) for individuals younger than 60 years. The purpose of this study was to establish NRV for the TUG for individuals aged between 20 and 59 years and to examine the relationship between the TUG and demographic, physical, and mental health risk factors. Two hundred participants, 50 per decade (ages 20-29, 30-39, 40-49, 50-59 years) were selected at their primary care visit, and timed as they performed the TUG by standing up out of a chair, walking 3 m, turning around, walking back to the chair, and sitting down. Information regarding the risk factors socioeconomic status, body mass index, an index of multimorbidities, perceptions of overall physical and mental health was obtained and used as predictors of TUG time independent of age. TUG times were significantly different among the decades ( F = 6.579, P = .001) with slower times occurring with the 50-year-old decade compared with the 20s ( P = .001), 30s ( P = .001), and 40s ( P = .020). Slower TUG times were associated with lower SES, higher body mass index, more medical comorbidities, and worse perceived physical and mental health. Regression results indicated that perceived physical and mental health accounted for unique variance in the prediction of TUG time beyond age, gender, and socioeconomic status. This study provided TUG NRV for adults in their 20s, 30s, 40s, and 50s. The TUG may have utility for primary care providers as they assess and monitor physical activity in younger adults, especially those with physical and mental health risk factors.

The better the worse: risk factors for HIV infection among women in Kenya and Uganda – Demographic and Health Survey

The objective of the study was to investigate socio-economic status (SES) factors as risk factors for HIV among women in Kenya and Uganda. Individual data from cross-sectional, population based 2003-Kenya Demographic and Health Survey (KDHS) and 2004-Uganda AIDS Indicator Survey (AIS) were used and the probability of being HIV-positive was analysed. Contrary to the public health literature, women of high SES were also vulnerable to HIV risk. Both Ugandan and Kenyan women had similar SES risk factors to HIV and harmonising policies in the two countries to deal with the disadvantages of the social and cultural roles of women would help reduce vulnerability to HIV for women. Policies in both countries need to be broad based to cut across all socio-economic groups and deal with the complexity of HIV/AIDS. Nyanza region needs exceptional policies to deal with the high HIV prevalence and reduce risk through cultural practices like widow inheritance.

How Much Does Low Socioeconomic Status Increase the Risk of Prenatal and Postpartum Depressive Symptoms in First-Time Mothers?

To examine socioeconomic status (SES) as a risk factor for depressive symptoms in late pregnancy and the early postpartum period. A secondary objective was to determine whether SES was a specific risk factor for elevated postpartum depressive symptoms beyond its contribution to prenatal depressive symptoms. Quantitative, secondary analysis, repeated measures, descriptive design. Participants were recruited from paid childbirth classes serving upper middle class women and Medicaid-funded hospitals serving low-income clients in Northern California. A sample of 198 first-time mothers was assessed for depressive symptoms in their third trimester of pregnancy and at 1, 2, and 3 months postpartum. Depressive symptoms were measured with the Center for Epidemiological Studies-Depression (CES-D) Scale. Low SES was associated with increased depressive symptoms in late pregnancy and at 2 and 3 months, but not at 1 month postpartum. Women with four SES risk factors (low monthly income, less than a college education, unmarried, unemployed) were 11 times more likely than women with no SES risk factors to have clinically elevated depression scores at 3 months postpartum, even after controlling for the level of prenatal depressive symptoms. Although new mothers from all SES strata are at risk for postpartum depression, SES factors including low education, low income, being unmarried, and being unemployed increased the risk of developing postpartum depressive symptoms in this sample.