Socioeconomic status and hypertension: a meta-analysis.

Higher socioeconomic status is associated with lower in-hospital cardiac arrest: How can we address this socioeconomic inequality?

The Impact of Socioeconomic Status on Prostate Cancer Treatment and Survival in the Southern Netherlands

BackgroundDental health and care among children and adolescents are a major neglected area of public health, leading to both physical and mental health consequences in the long term. Several demographics, economic, and social factors influence dental service utilization, with Socio-Economic Status (SES) being a significant determinant. SES plays an important role in the utilization of dental services for children and adolescents. This systematic review and meta-analysis aim to explore the association between SES and dental service utilization in this population.MethodsUsing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched PubMed, Web of Science, and Scopus for relevant articles published between January 2000 and September 2024. We selected global studies that examined the association between SES and dental service utilization among children and adolescents. Different subgroup analysis based on socioeconomic indicators (household income, parental educational level and/ or occupational level, household assets, SES index, and annual household consumption expenditure), economic classification of the country (high, upper-middle, or lower-middle), nature of the dental insurance system and type of outcome measure. Pooled Odd Ratio (OR) and 95% confidence intervals (CIs) were calculated for the outcome using a random-effects model. Furthermore, meta-regression and sensitivity analysis were conducted to identify the sources for heterogeneity.ResultsA total of 48 studies met the inclusion criteria for this review. The meta-analysis revealed that children and adolescents from higher SES were about twice as likely to utilize dental services (OR = 2.10, 95% CI: 1.32–2.89) compared to those from lower SES backgrounds. The subgroup analysis indicated that various factors influenced the association between SES and dental service utilization among children and adolescents. These included specific SES indicators—household income (OR = 1.65, 95% CI: 1.37–1.94), parental occupation and/or education level (OR = 3.30, 95% CI: 1.12–5.47), and household assets (OR = 1.47, 95% CI: 1.15–1.78)—as well as the economic classification of the country, with higher-income countries (OR = 2.57, 95% CI: 1.24–3.90) and upper-middle-income countries (OR = 1.52, 95% CI: 1.26–1.78) showing stronger associations. The type of dental insurance system also influenced the outcomes, with significant associations found in countries with universal coverage (OR = 1.73, 95% CI: 1.19–2.26), means-tested systems (OR = 1.70, 95% CI: 1.40–2.00), and mixed public-private systems (OR = 1.47, 95% CI: 1.09–1.85). Additionally, the type of outcome measure also played a role, with recent dental service use (OR = 2.21, 95% CI: 1.18–3.23) and preventive dental service use (OR = 2.01, 95% CI: 1.19–2.84) demonstrating significant effects.ConclusionThe findings provide evidence that children and adolescents with low SES are associated with lower utilization of dental services. Interventions focused on these groups targeting specific barriers to care are needed to improve equitable dental service utilization.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12903-025-06742-4.

Socioeconomic status (SES) is recognizably linked with incident heart failure (HF) risk and the association of SES with geography presents a potential target for geographical location of preventive health services. To better inform policy we sought to quantify the independent association between SES and incident HF and investigate differences by type of SES measure. MEDLINE and EMBASE were searched up to August 2018. Observational studies and randomized trials reporting adjusted HF incidence by stratified socioeconomic measures were included. Effect sizes reflected HF incidence in the lowest vs. highest SES stratum and were pooled using a random-effects model. Low SES referred to the lowest resource stratum, the definition of which varied across studies: meta-analysis was only performed where strata were comparable. Statistical heterogeneity was assessed using the I2 statistic. Eleven studies comprising 6308006 individuals and 104217 HF events found that low SES was associated with an increase in risk of incident HF ranging between 43% and 87% depending on SES measure, with an overall estimate of 62% [hazard ratio (HR) 1.62, 95% confidence interval (CI) 1.50-1.76]. By individual measure, HRs of 1.66 (95% CI 1.3-2.11), 1.87 (95% CI 1.33-2.62), and 1.54 (95% CI 1.22-1.95) were observed for education, income, and occupation, respectively. For area-level indexes, HRs were 1.43 (95% CI 1.2-1.69) (Carstairs index) and 1.61 (95% CI 1.56-1.65) (index of multiple deprivation). Low SES assessed by all common measures confers independent risk for incident HF. These findings carry implications for the design and delivery of HF prevention programmes.

Introduction: Disparities in breast cancer (BC) incidence and outcomes exist across racial/ethnic groups in the U.S. and by socioeconomic status (SES). The extent to which lower SES independently impacts breast cancer outcomes in different racial/ethnic groups is not fully described. Our purpose was to determine the impact of SES on cancer-specific mortality among women with metastatic breast cancer. Method: We conducted a large, population-based retrospective cohort study of women ages 18+ years diagnosed with de novo metastatic breast cancer using the Surveillance, Epidemiology and End Results Census Tract-level SES and Rurality Database (2000-2015). SES was described using the Yost index, a validated time-dependent composite score that reflects SES based on several components including education and income, with the 1st quintile representing the lowest and 5th quintile being the highest SES. Information on demographic and clinical characteristics, including hormone receptor (HR) status, cancer treatment, survival and cause of death were collected from cancer registry data. We determined associations between SES and BC-specific mortality in Fine and Gray regression models. Multivariable adjusted subdistribution hazard ratios (SHR) and 95% confidence intervals (CI) were calculated accounting for competing risks of death. We determined associations between SES and BC mortality overall and calculated stratum specific SHR estimates by racial/ethnic groups and HR status. Results: In an overall cohort of 33,976 women with de novo metastatic BC, the majority were non-Hispanic white (67%), 17% were Black, 0.4% were American Indian/Alaskan Native, 6% were Asian/Pacific Islander and 10% were Hispanic. Compared to women in the highest SES quintile, women in the lowest SES were more likely to be uninsured or on Medicaid (25% vs. 7%) and have HR-negative disease (24% vs. 18%) but were similar with respect to treatment with surgery, radiation and chemotherapy. Overall, metastatic BC patients in the lowest SES quintile had a significantly increased risk of BC mortality compared to the highest SES quintile (adjusted SHR 1.27, 95% CI 1.22-1.32); however, these impacts of SES differed across racial/ethnic groups and by HR status. Risk estimates for the association between low SES (1st quintile) and BC mortality were lower among HR-positive white women (SHR 1.19, 95% CI 1.12-1.26) and minimal among Asian/Pacific Islander women (SHR 1.05, 95% CI 0.88-1.25). The greatest increased risk was observed among HR-negative Black women (SHR 1.38, 95% CI 1.00-1.90) with metastatic BC. Conclusion: Independent of race/ethnicity, lower SES is significantly associated with BC-specific mortality among women with de novo metastatic disease. However, when stratifying these effects by racial/ethnic groups and HR status, the impact of SES appears to be greater among Black women with HR-negative metastatic BC. Citation Format: Hsiao- Ching Huang, Mary H. Smart, Huiwen Deng, Ashwini Zolekar, Colin C. Hubbard, Kent F. Hoskins, Naomi Y. Ko, Gregory S. Calip. Differences in impact of socioeconomic status on cancer: Specific survival in metastatic breast cancer by race/ethnicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 776.

This study explores the impact of socioeconomic status (SES) on diabetes prevalence through a meta-analysis. We systematically searched PubMed, Cochrane Library, and Google Scholar databases, and used random-effects models to calculate pooled odds ratios (ORs) and 95% confidence intervals (CIs). We conducted heterogeneity tests, publication bias analysis, sensitivity analysis, and assessed the quality of literature using GRADE. Results showed that individuals with low SES had a significantly higher risk of diabetes compared to those with high SES (OR=1.61, 95%CI: 1.10-2.69). Blue-collar workers (OR=1.72, 95%CI: 1.10-2.69) and manual laborers (OR=1.85, 95%CI: 1.32-2.59) also had significantly higher diabetes risk compared to white-collar workers and non-manual laborers. No significant differences were found in analyses of education and income levels. This meta-analysis examined the impact of SES on diabetes prevalence, and while some individual factors did not show statistical significance, an overall association between SES and diabetes risk was observed.

Background: Multiple myeloma (MM) incidence and outcomes differ across racial/ethnic groups in the United States. Interactions between socioeconomic status (SES) with ethnicity in MM incidence and survival outcomes are not well understood. Our objective was to evaluate disparities in cancer-specific survival of patients diagnosed with MM by race/ethnicity. Methods: We conducted a population-based retrospective cohort study of patients ages 20+ years diagnosed with MM between 2000 and 2015 using Surveillance, Epidemiology and End Results, Census Tract-level SES and Rurality Database. SES was defined using the National Cancer Institute's time-dependent composite score developed by Yost et al. (2001). Yost index quintiles were where the 1st and 5th quintiles representing the lowest and highest SES categories respectively. Cumulative incidence functions were used to analyze cancer-specific survival across strata racial/ethnic and SES and equality of functions was determined using Gray's test. Subdistribution hazard ratios (SHR) and 95% confidence intervals (CI) were calculated using the Fine and Gray regression models adjusted for age, sex, year of diagnosis, marital status, insurance status, and treatment with chemotherapy. Race-specific risk estimates were stratified by age (<65 and 65+ years). Results: Overall, 58,095 MM patients were included in our analysis among whom 63.0% were non-Hispanic White, 19.5% were Black, 0.3% were American Indian/Alaskan Native, 5.8% were Asian/Pacific Islander and 11.4% were Hispanic. Compared to White MM patients (median age 69 years), Black (64 years), American Indian/Alaskan Native (64 years), Asian/Pacific Islander (67 years) and Hispanic (64 years) patients were younger on average. A higher proportion of Black (42.8%) and Hispanic (27.9%) MM patients were in the lowest SES quintile compared to White (10.6%), American Indian/Alaskan Native (15.2%), and Asian/Pacific Islander (8.9%) MM patients. Cumulative incidence functions for cancer-specific survival were significantly different across SES quintiles (P < 0.0001) and racial/ethnic groups (P < 0.0001). Overall, MM patients in the lowest SES quintile had a significantly increased risk of MM-specific mortality (SHR: 1.28, 95% CI 1.21-1.36) compared to patients in the highest quintile. Risk estimates comparing the lowest to the highest quintile of SES were higher among Black (SHR 1.39, 95% CI 1.08-1.77), Hispanic (SHR: 1.78, 95% CI 1.21-2.63), and White (SHR 1.44, 95% CI 1.23-1.69) MM patients ages <65 years at diagnosis. Conclusion: Low SES level is independently associated with poor MM-specific survival. However, the impacts of SES on MM-specific survival differ by race/ethnicity and age with the greatest increased risk observed in younger Black, Hispanic, and White patients. Citation Format: Huiwen Deng, Ashwini Zolekar, Hsiao-Ching Huang, Mary H. Smart, Colin C. Hubbard, Brian C. Chiu, Pritesh R. Patel, Karen Sweiss, Gregory S. Calip. Racial differences in the impact of socioeconomic status on cancer-specific survival in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2628.

Introduction: Breast cancer survivors have an increased risk of contralateral breast cancer (CBC), among whom minority breast cancer patients are at increased risk of this adverse outcome. Studies evaluating CBC risk by race/ethnicity frequently aggregate Asian/Pacific Islanders (API) into a single group or exclude them. The purpose of this study was to determine the impact of socioeconomic status (SES) on the risk of CBC among subgroups of API breast cancer survivors. Method: We conducted a population-based retrospective cohort study of women ages 18+ years diagnosed with unilateral Stage I-III breast cancer using the Surveillance, Epidemiology and End Results Census Tract-level SES and Rurality Database (2000-2016). Women included in the study received cancer-directed surgery and the primary outcome of interest was asynchronous CBC occurring. SES was classified using the Yost index, a validated time-dependent composite score with the 1st quintile representing the lowest and 5th quintile being the highest SES. API women were categorized into Chinese, Japanese, Filipina, Hawaiian, Korean, Vietnamese, Indian/Pakistani, and other Asian/Pacific Islanders. We determined overall associations between SES and the risk of CBC using Fine and Gray regression models accounting for competing risks comparing API women to Non-Hispanic White (NHW) women. Multivariable adjusted subdistribution hazard ratios (SHR) and 95% confidence intervals (CI) were estimated and stratified by API subgroups. Results: From a cohort of 44,362 API female breast cancer patients included, one quarter of the cohort were Filipina (25%), 18% were Chinese, 14% were Japanese, 8% were Indian/Pakistani, and 17% were other API. API women living in the lowest SES areas were more likely to be uninsured or have Medicaid coverage (21% vs. 6%) and have Stage lll first primary breast cancer (14% vs. 10%) compared to API women living in the highest SES areas. Overall, API breast cancer patients as an aggregate group did not have significantly increased risk of CBC compared to NHW patients. In stratified subgroups, risk estimates for CBC were higher among Chinese women (SHR 1.24, 95% CI 1.08-1.41), Filipina (SHR 1.37, 95% CI 1.23-1.52), and Hawaiian women (SHR 1.67, 95% CI 1.37-2.08) when compared to NHW women after adjusting for demographics and baseline clinical characteristics. Lower SES was not associated with increased CBC risk among API women overall. However, the risk of CBC is significantly lower among Chinese and Vietnamese women and higher among Filipina women who lived in areas lower SES quintile compared to women who lived in area with the highest SES quintile when examining impact of SES within API subgroups. Conclusion: Chinese, Filipina, and Hawaiian women have higher risk of CBC when compared to NHW. When disaggregated API women into subgroups, the impact of SES on the risk of CBC differs significantly across API subgroups. Citation Format: Hsiao- Ching Huang, Jenny S. Guadamuz, Kent F. Hoskins, Naomi Y. Ko, Gregory S. Calip. Impact of socioeconomic status on the risk of contralateral breast cancer among Asian/Pacific Islander subgroups [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3630.

MP12-05 THE IMPACT OF SOCIOECONOMIC STATUS ON THE SURVIVAL OF MEN WITH EARLY-ONSET PROSTATE CANCER

Category:Ankle; TraumaIntroduction/Purpose:Socioeconomic status has been recognized throughout the medical literature, both within orthopedics and beyond, as a factor that influences outcomes after surgery, and can result in substandard care. Within the foot and ankle subspecialty, there is limited data regarding socioeconomic status and post-operative outcomes, with the current literature focusing on outcomes for diabetic feet. However, ankle fractures are among the most common fractures encountered by orthopedic surgeons. While a few studies have explored the impact of ankle fractures on employment and disability status, the effect of socioeconomic status on return to work post operatively has not yet been investigated. The purpose of this study was to determine the impact of low socioeconomic status on return to work.Methods:We retrospectively reviewed 592 medical charts of patients with CPT code 27766, 27792, 27814, 27822, 27823, 27827, 27829, 27826, 27828 from 2015-2018. Included were patients >18 yrs of age who sustained an acute ankle fracture, were employed prior to the injury, and with information on return to work after ankle surgery, zip code, race, ethnicity and insurance status. Excluded were patients who were not employed prior to their injury. Socioeconomic status was either defined by insurance status - Medicaid/Medicare, commercial, or workman’s compensation -, or by assessing socioeconomic status (SES) using medial household per capita income by zip code as generated and reported by the US National Census Bureau’s 2013-2017 American Community Survey 5-Year Estimates. The national dataset was divided into quartiles with the lowest quartile defined as low SES. Patients who had income that fell within this income category were classified as low SES.Results:174 patients were included with an average follow-up of 10.2months. 22/174 (12.6%) patients didn’t return to work post-operatively. Univariate analysis identified non-sedentary work to decrease the likelihood of return to work (HR:0.637; p=0.03). Patients with a low SES were more prevalent in the no return group compared to the return to work group (86% vs 60%; p=0.028). 95% of patients with low SES were a minority compared to 56% with average/high SES (p<0.005). Patients with low SES had a higher BMI (p=0.026), a longer hospitalization (p=0.04) and more wound complications (p=0.032). Insurance type didn’t affect return to work (p=0.158). Patients with workman’s compensation had a longer follow-up time and a longer time to return to work compared to other insurances (p<0.005 for each comparison).Conclusion:Low socioeconomic status based on income, not insurance type, affected return to work after an ankle fracture ORIF. Patients with workman’s compensation took a longer time to return to work compared to other insurance types. These findings warrants the need to consider socioeconomic status when allocating resources to treat these patients.

BackgroundLow socioeconomic status (SES) has been linked to worse survival in patients with colorectal cancer (CRC); however, the impact of SES on early‐onset CRC remains undescribed.Materials and MethodsRetrospective analysis of data from the National Cancer Database (NCDB) between 2004 and 2016 was conducted. We combined income and education to form a composite measure of SES. Logistic regression and χ2 testing were used to examine early‐onset CRC according to SES group. Survival rates and Cox proportional hazards models compared stage‐specific overall survival (OS) between the SES groups.ResultsIn total, 30,903 patients with early‐onset CRC were identified, of whom 78.7% were White; 14.5% were Black. Low SES compared with high SES patients were more likely to be Black (26.3% vs. 6.1%) or Hispanic (25.3% vs. 10.5%), have T4 tumors (21.3% vs. 17.8%) and/or N2 disease (13% vs. 11.1%), and present with stage IV disease (32.8% vs. 27.7%) at diagnosis (p < .0001, all comparisons). OS gradually improved with increasing SES at all disease stages (p < .001). In stage IV, the 5‐year survival rate was 13.9% vs. 21.7% for patients with low compared with high SES. In multivariable analysis, SES (low vs. high group; adjusted hazard ratio [HRadj], 1.35; 95% confidence interval [CI], 1.26–1.46) was found to have a significant effect on survival (p < .0001) when all of the confounding variables were adjusted. Insurance (not private vs. private; HRadj, 1.38; 95% CI, 1.31–1.44) mediates 31% of the SES effect on survival.ConclusionPatients with early‐onset CRC with low SES had the worst outcomes. Our data suggest that SES should be considered when implementing programs to improve the early detection and treatment of patients with early‐onset CRC.Implications for PracticeLow socioeconomic status (SES) has been linked to worse survival in patients with colorectal cancer (CRC); however, the impact of SES on early‐onset CRC remains undescribed. In this retrospective study of 30,903 patients with early‐onset CRC in the National Cancer Database, a steady increase in the yearly rate of stage IV diagnosis at presentation was observed. The risk of death increased as socioeconomic status decreased. Race and insurance status were independent predictors for survival. Implementation of programs to improve access to care and early diagnostic strategies among younger adults, especially those with low SES, is warranted.

Clinical Impact and Outcomes of Socioeconomic Status on Patients with Sickle Cell Disease: A Pilot Study and Literature Review

Fragility fractures, especially of the hip, cause substantial excess mortality and impairment in health-related quality of life (HRQoL). This systematic review and meta-analysis aimed to investigate the association between socio-economic status (SES) and post-fracture mortality and HRQoL. PubMed, EMBASE and CINAHL databases were searched from inception to the last week of November 2018 for studies reporting an association between SES and post-fracture mortality and/or HRQoL among people aged ≥ 50years. Risk ratios (RRs) were meta-analyzed using a standard inverse-variance-weighted random effects model. Studies using individual-level and area-based SES measures were analyzed separately. A total of 24 studies from 15 different countries and involving more than one million patients with hip fractures were included. The overall risk of mortality within 1-year post-hip fracture in individuals with low SES was 24% higher than in individuals with high SES (RR 1.24, 95% CI 1.19 to 1.29) for individual-level SES measures, and 14% (RR 1.14, 95% CI 1.09 to 1.19) for area-based SES measures. The quality of the evidence for the outcome mortality was moderate. Using individual SES measures, we estimated the excess HRQoL loss to be 5% (95% CI - 1 to 10%) among hip fracture patients with low SES compared with high SES. We found a consistently increased risk of post-hip fracture mortality with low SES across SES measures and across countries with different political structures and different health and social care infrastructures. The impact of SES on post-fracture HRQoL remains uncertain due to sparse and low-quality evidence.

Study question Is there an association between neighbourhood socioeconomic status (SES) and cumulative ongoing pregnancy after 2.5 years of in vitro fertilization (IVF) treatment? Summary answer Low and middle neighbourhood SES is associated with lower odds of an ongoing pregnancy within 2.5 years of IVF treatment than high neighbourhood SES. What is known already Low SES is known to have a negative impact on general health and a variety of medical conditions, including perinatal health. However, not much data is available on the impact of SES on IVF treatment outcome. Study design, size, duration This is a retrospective observational study of 3720 couples undergoing IVF or IVF-ICSI treatment between 2006 and 2020. Participants/materials, setting, methods Neighbourhood SES was assigned to each couple based on the postal code of residence. Subsequently, SES was categorized into low (&amp;lt;p20), medium (p20-p80), and high (&amp;gt;p80). Multivariable logistic regression analyses were performed with cumulative ongoing pregnancy within 2.5 years as outcome variable, SES category, female age, BMI, smoking status (yes/no), and interaction terms for age*SES and BMI*SES were used as covariates. Main results and the role of chance There was no difference in ongoing pregnancy rates between SES groups after the first fresh embryo transfer or in the average number of IVF treatment cycles performed. However, the cumulative ongoing pregnancy rates differ significantly between SES groups (Low; 43.6%, medium; 50.9%, high; 54.1%). Low SES had significantly lower odds for achieving an ongoing pregnancy within 2.5 years (OR = 0.06 (95%CI 0.02-0.22)). The interaction terms age*SES and BMI*SES showed attenuation of this association with increasing age and BMI (OR = 1.07 (95%CI 1.022 – 1.12) and OR = 1.61 (95%CI 1.25 – 2.09), respectively). The associations with medium SES were similar, but less pronounced (OR = 0.16 (95%CI 0.05 – 0.50) with OR = 1.04 (95%Cl 1.00 – 1.09) and OR = 1.41 (1.12 – 1.77) for the interaction terms with female age and BMI respectively. Limitations, reasons for caution We were not able to perform additional analysis on individual characteristics like educational level, ethnicity or language proficiency due to lack of data. Wider implications of the findings In the Netherlands, health insurance is mandatory. Our study showed that even with equal access to fertility care, patients living in a low SES neighbourhood are disadvantaged. This underlines the importance of taking the whole wellbeing of the patient into account, before starting an IVF treatment. Trial registration number not applicable

Heart failure (HF) is a cardiovascular disease (CVD) outcome that is associated with high morbidity and mortality as well as high healthcare costs.1 Given that HF is the end stage of most CVDs, both conditions share common risk factors such as type 2 diabetes (T2D), hypertension, smoking and obesity.2 Socioeconomic status (SES) has been recognized to have a measurable and significant effect on cardiovascular health. It has been reported that low SES may confer a cardiovascular risk that is equivalent to conventional risk factors.3 Low SES has been shown to be a powerful and independent predictor of HF development and adverse outcomes.4 Biological, behavioural and psychosocial risk factors prevalent in socioeconomically deprived individuals are known to accentuate the relationship between low SES and cardiovascular outcomes such as HF.3 These include lower levels of education, unhealthy lifestyles such as excessive alcohol consumption, limited access to health care and higher prevalence of comorbid conditions. The beneficial effects of regular physical activity (PA) and exercise in preventing vascular disease and promoting overall health are well established and documented. These benefits also extend to HF prevention.5 Though cardiorespiratory fitness (CRF) reflects habitual aerobic PA, it is a separate measure that captures the capacity of the cardiovascular and respiratory systems to supply oxygen to skeletal muscles during progressive PA or incremental exercise to volitional fatigue.6 The gold standard for CRF assessment is direct measurement of the highest attained oxygen consumption (VO2) during cardiopulmonary exercise testing. Similar to PA, high levels of CRF are strongly and independently associated with lower risk of vascular outcomes including HF.7, 8 The inverse associations between CRF and vascular outcomes have been reported to be stronger than that of traditional risk factors such as T2D and smoking; this has led to CRF being proposed as a vital sign.9 There is increasing evidence showing that higher levels of CRF can attenuate the adverse impact of other risk factors; for instance, we and others have previously shown that high CRF levels can attenuate the impact of risk factors associated with mortality,10 pneumonia11 and COVID-19 hospitalization.12 Given the evidence, we hypothesized that high CRF levels would attenuate the increased risk of HF due to low SES. To explore this, we aimed to evaluate the joint effects of SES and CRF on the risk of incident HF using a population-based prospective cohort of 1831 middle-aged Finnish men without a history of HF at baseline. We also evaluated the separate associations of SES and CRF with the risk of HF to confirm previous evidence of these associations. Reporting of the study conforms to broad EQUATOR guidelines13 and was conducted according to STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines for reporting observational studies in epidemiology (Appendix S1). The current analysis is based on the Kuopio Ischaemic Heart Disease (KIHD) risk factor study, a general population-based prospective cohort study comprising of a representative sample of men aged 42–61 years recruited in eastern Finland. A detailed description of the study design, recruitment methods, risk marker assessment and physical examinations have been described previously.8 Baseline measurements were performed between 01 March 1984 and 31 December 1989. The research protocol was approved by the Research Ethics Committee of the University of Eastern Finland and written informed consent was obtained from all the participants. A self-reported questionnaire was used to assess SES, which involved a summary index that combined factors such as income, education, occupational prestige, material standard of living and housing conditions. The composite SES index ranged from 0 to 25, with higher values indicating lower SES. Maximal oxygen uptake (VO2max) was used as a measure of CRF, which was assessed using a respiratory gas exchange analyser (Medical Graphics, MCG, St. Paul, Minnesota) during cycle ergometer exercise testing.14 We excluded men with a prevalent history of HF for the current analysis. We included all HF events that occurred from study entry through to 2018. The diagnostic classification of HF cases was coded according to the ICD-10 codes. Hazard ratios (HRs) with 95% confidence intervals (CIs) for HF were calculated using Cox proportional hazard models and these were adjusted for in three models: (Model 1) age; (Model 2) Model 1 plus systolic blood pressure (SBP), body mass index (BMI), heart rate, smoking status, history of T2D, history of coronary heart disease (CHD), total cholesterol, high-density lipoprotein cholesterol (HDL-C) and PA; and (Model 3) Model 2 plus mutual adjustment for each exposure. For consistency with previous reports,10, 15 the exposures (SES and CRF) were categorized into low and high levels based on their median cutoffs. The exposures were also modelled as continuous variables given evidence of linear relationships with HF risk using multivariable restricted cubic spline curves. Evaluation of the joint association of SES and CRF with HF risk was based on the following four combinations: high SES-low CRF; low SES- low CRF; high SES-high CRF and low SES-high CRF. Tests of interaction were used to formally assess if the risk of HF due to one exposure is modified by the other exposure and vice versa. To put our findings into clinical context, we also calculated the number needed to treat (NNT) associated with high SES-high CRF using the formula proposed by Altman and Anderson16: NNT (t) =1/[SB(t))HR – SB(t)], where SB(t) denotes the Kaplan–Meir survival probability in the reference group (High SES-Low CRF) at time t and HR refers to the Cox regression estimate comparing the exposure group with the reference group. Stata version MP 16 (Stata Corp, College Station) was employed for all analyses. The overall mean (standard deviation, SD) age, SES and CRF of study participants at baseline was 52 (5) years, 8.26 (4.24) and 30.8 (7.9) ml/kg/min, respectively (Table 1). There were significant differences in baseline characteristics between low and high CRF groups. Overall Mean (SD) or median (IQR) or n (%) High CRF Mean (SD) or median (IQR) or n (%) Low CRF Mean (SD) or median (IQR) or n (%) During a median (interquartile range) follow-up of 27.3 (18.6–31.2) years, 364 incident HF cases occurred. In an analysis adjusted for age, SBP, BMI, heart rate, smoking status, history of T2D, history of CHD, total cholesterol, HDL-C and PA, low compared with high SES was associated with an increased risk of HF 1.43 (95% CI: 1.15–1.79), which remained similar on further adjustment for CRF. On adjustment for the confounders as above, high CRF was associated with a decreased risk of HF compared with low CRF 0.70 (95% CI: 0.55–0.89), which remained similar on additional adjustment for SES. There was evidence of significant associations when both exposures were modelled as continuous variables (Table 2). Restricted cubic spline curves with adjustment for age, SBP, BMI, heart rate, smoking status, history of T2D, history of CHD, total cholesterol, HDL-C and PA showed that HF risk increased continuously with decreasing SES across the range 7–19 (p-value for nonlinearity =.83) (Figure 1A), whereas HF risk decreased continuously with increasing CRF across the range 18–58 ml/kg/min (p-value for nonlinearity =.79) (Figure 1B). The spline curves were qualitatively similar in subgroups of CRF and SES (Figure 2). In multivariable analysis, low SES-low CRF was associated with an increased HF risk 1.32 (95% CI: 1.01–1.74), high SES-high CRF with a decreased HF risk 0.62 (95% CI: 0.43–0.89), with no evidence of an association for low SES-high CRF and HF risk 1.01 (95% CI: 0.73–1.39) when compared with men with high SES-low CRF (Table 2). The association of SES with HF risk was not modified by CRF (p-value for interactions >.10) and neither was the association between CRF and HF risk modified by SES (p-value for interactions >.10), when both exposures were modelled as continuous or categorical variables (Figure 3). The absolute risk reduction of HF associated with high SES-high CRF was 0.21 during the entire duration of follow-up, which translated into a NNT of 10 (95% CI: 6–35) to prevent one HF. Our results based on a general population-based prospective cohort study of middle-aged to older Finnish men confirms the previously reported independent associations of low SES with increased HF risk and high CRF levels with lowered risk of HF. The associations were also potentially consistent with graded dose-response relationships. Evaluation of the joint associations of SES and CRF with HF risk showed that increased CRF levels appeared to attenuate the increased risk of HF associated with low SES. However, formal tests showed no significant evidence of interactive effects of SES and CRF on the long-term risk of HF, suggesting the effect of each exposure on HF risk may be independent of the other. Given the low sample size and event rates in the exposure categories, studies with larger samples are needed to confirm or refute potential interactive effects of SES and CRF on HF risk. Finally, our findings suggest that the NNT for high aerobic fitness levels and high SES to prevent a HF event over long-term follow-up ranged from 6 to 35 in approximately healthy middle-aged to older men. The interaction between SES and HF has been reported to be complex and the precise mechanisms accounting for the association between low SES and increased HF risk remain elusive.4 Socioeconomic differences in potential aetiological risk factors such as alcohol consumption, hypertension and systemic inflammation, have been reported to contribute to the risk. Social deprivation is also associated with lower rates of treatment, dose and adherence to therapy for, and delayed presentation of hypertension, diabetes and CHD,4 which consequently lead to HF. Psychosocial factors such as stress and depression, which are strongly associated with cardiovascular outcomes, also disproportionately affect individuals of low SES.3 Though CRF is determined by many non-modifiable factors such as age, sex and heritability, it remains a modifiable risk factor. The most established methods of increasing CRF are via exercise training and increased PA.9 Greater PA and exercise reduce HF risk through various mechanisms including (i) reducing the prevalence of standard and novel cardiovascular risk factors such as hypertension, obesity, blood glucose and coronary artery disease; (ii) preventing adverse changes in cardiac structure and function; (iii) promoting physiologic remodelling and (iv) improving cardiac, neurohormonal, skeletal muscle, pulmonary, renal and vascular performance.5 These findings may have important clinical implications. They add to the overwhelming evidence on the benefits of high CRF levels (via regular aerobic PA) on chronic diseases and their potential ability to attenuate the adverse effects of traditional risk factors. Despite guideline recommendations and population-wide strategies to promote PA levels, most populations do not achieve general PA recommendations. Populations at high cardiovascular risk including the socioeconomically deprived need more education on the substantial benefits of PA. Furthermore, there should be widened access to PA resources that are both feasible and attractive for these populations. This is the first evaluation of the separate and joint associations of SES and CRF with HF risk. We also assessed the nature of the dose-response relationships of the exposures with HF risk. Other strengths of this analysis included the use of a prospective cohort design with exclusion of men with pre-existing HF, the long-term follow-up duration of the cohort and the use of a gold standard measure of CRF. Limitations deserving consideration included the relatively low sample size due to the categorization of exposures, use of self-administered questionnaires in assessing SES, findings may only be generalizable to middle-aged and older northern European men and potential for biases such as residual confounding and regression dilution bias. In a general male Finnish population, both SES and CRF were each independently associated with HF risk, potentially consistent with graded dose-response relationships. High levels of CRF may attenuate the increased risk of HF due to low SES, but further study is needed to confirm if there are true interactive effects of SES and CRF on the long-term risk of HF. The authors thank the staff of the Kuopio Research Institute of Exercise Medicine and the Research Institute of Public Health and University of Eastern Finland, Kuopio, Finland for the data collection in the study. J.A.L. acknowledges support from The Finnish Foundation for Cardiovascular Research, Helsinki, Finland. These sources had no role in design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review or approval of the manuscript. No potential conflict of interest was reported by the authors. S.K.K.: Study design, data analysis and interpretation, drafting manuscript, and revising manuscript content and approving final version of manuscript; S.Y.J.: Study design and revising manuscript content and approving final version of manuscript; T.H.M: Study design and revising manuscript content and approving final version of manuscript; J.A.L.: Study design and conduct, responsibility for the patients and data collection, and revising manuscript content and approving final version of manuscript. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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