Bottom Income Quartile Research Articles

Operative Management of Rotator Cuff Tears: Identifying Disparities in Access on a National Level.

The purpose of this study was to identify nationwide disparities in the rates of operative management of rotator cuff tears based on race, ethnicity, insurance type, and socioeconomic status. Patients diagnosed with a full or partial rotator cuff tear from 2006-2014 were identified in the Healthcare Cost and Utilization Project's National Inpatient Sample database using International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Bivariate analysis using chi-square tests and adjusted, multivariable logistic regression models were used to evaluate differences in the rates of operative versus non-operative management for rotator cuff tears. This study included 46,167 patients. When compared with white patients, adjusted analysis showed that minority race and ethnicity were associated with lower rates of operative management for Black [adjusted odds ratio (AOR): 0.31, 95% confidence interval (CI): 0.29-0.33; p < 0.001], Hispanic [AOR: 0.49, 95% CI: 0.45-0.52; p < 0.001], Asian or Pacific Islander [AOR: 0.72, 95% CI: 0.61-0.84; p < 0.001], and Native American patients [AOR: 0.65, 95% CI: 0.50-0.86; p = 0.002]. In comparison to privately insured patients, our analysis also found that self-payers [AOR: 0.08, 95% CI: 0.07-0.10; p < 0.001], Medicare beneficiaries [AOR: 0.76, 95% CI: 0.72-0.81; p < 0.001], and Medicaid beneficiaries [AOR: 0.33, 95% CI: 0.30-0.36; p < 0.001] had lower odds of receiving surgical intervention. Additionally, relative to those in the bottom income quartile, patients in all other quartiles experienced nominally higher rates of operative repair; these differences were statistically significant for the second quartile [AOR: 1.09, 95% CI: 1.03-1.16; p = 0.004]. There are significant nationwide disparities in the likelihood of receiving operative management for rotator cuff tear patients of differing race/ethnicity, payer status, and socioeconomic status. Further investigation is needed to fully understand and address causes of these discrepancies to optimize care pathways.

Waves of inequality: Income differences in intensive care due to Covid-19 in Sweden

Abstract Background Individuals in lower social strata were overall more likely to develop severe Covid-19 during the pandemic. However, specific conditions in terms of preparedness, knowledge and the properties of the virus itself changed during the course of the pandemic. Socioeconomic inequalities in Covid-19 may therefore shift over time. This study examines the relationship between income and intensive care (ICU) episodes due to Covid-19 in Sweden during three distinct waves. Methods This study uses Swedish register data on the total adult population and estimate the relative risk (RR) of ICU episodes due to Covid-19 by income quartile for each month between March 2020 and May 2022, and for each wave, using Poisson regression analyses. Results The first wave had modest income-related inequalities, while the second wave had a clear income gradient, with the lowest income quartile having an increased risk compared to the high-income group (RR: 1·55 [1·36 - 1·77]). In the third wave, the overall need for ICU decreased, but relative risks increased, particularly the top and bottom income quartiles (RR: 3·72 [3·50 - 3·96]). Inequalities in the third wave were partly explained by differential vaccination coverage by income quartile, although substantial inequalities remained after adjustment for vaccination status (RR: 2·39 [2·20 - 2·59]). Conclusions The study highlights the importance of considering the changing mechanisms that connect income and health during a novel pandemic. Health inequalities per income group increased for each subsequent wave. As the aetiology of Covid-19 became better understood those with more resources could better protect themselves from infection. Understanding the social dynamic of infectious diseases can help prepare for possible future pandemics. Key messages • Health inequalities in severe covid-19 infections increased as the pandemic progressed. • Understanding the social dynamic of infectious diseases can help prepare for possible future pandemics.

Association of Household Income at Diagnosis With Financial Toxicity, Health Utility, and Survival in Patients With Head and Neck Cancer

While several studies have documented a link between socioeconomic status and survival in head and neck cancer, nearly all have used ecologic, community-based measures. Studies using more granular patient-level data are lacking. To determine the association of baseline annual household income with financial toxicity, health utility, and survival. This was a prospective cohort of adult patients with head and neck cancer treated at a tertiary cancer center in Toronto, Ontario, between September 17, 2015, and December 19, 2019. Data analysis was performed from April to December 2021. Annual household income at time of diagnosis. The primary outcome of interest was disease-free survival. Secondary outcomes included subjective financial toxicity, measured using the Financial Index of Toxicity (FIT) tool, and health utility, measured using the Health Utilities Index Mark 3. Cox proportional hazards models were used to estimate the association between household income and survival. Income was regressed onto log-transformed FIT scores using linear models. The association between income and health utility was explored using generalized linear models. Generalized estimating equations were used to account for patient-level clustering. There were 555 patients (mean [SD] age, 62.7 [10.7] years; 109 [20%] women and 446 [80%] men) included in this cohort. Two-year disease-free survival was worse for patients in the bottom income quartile (<$30 000: 67%; 95% CI, 58%-78%) compared with the top quartile (≥$90 000: 88%; 95% CI, 83%-93%). In risk-adjusted models, patients in the bottom income quartile had inferior disease-free survival (adjusted hazard ratio, 2.13; 95% CI, 1.22-3.71) and overall survival (adjusted hazard ratio, 2.01; 95% CI, 0.94-4.29), when compared with patients in the highest quartile. The average FIT score was 22.6 in the lowest income quartile vs 11.7 in the highest quartile. In adjusted analysis, low-income patients had 12-month FIT scores that were, on average, 134% higher (worse) (95% CI, 16%-253%) than high-income patients. Similarly, health utility scores were, on average, 0.104 points lower (95% CI, 0.026-0.182) for low-income patients in adjusted analysis. In this cohort study, patients with head and neck cancer with a household income less than CAD$30 000 experienced worse financial toxicity, health status, and disease-free survival. Significant disparities exist for Ontario's patients with head and neck cancer.

The association between preventive health and outpatient spending and life expectancy by income quartile

BackgroundTo describe the relationship between longevity and local access to preventive healthcare at the county level.MethodsWe used Medicare outpatient reimbursement data from the 2010 Dartmouth Health Atlas and longevity data from Chetty et al. (2016) to identify the cross-sectional associations between county longevity, access to outpatient care, and the quality of primary care.ResultsWe find that the cost of outpatient care is inversely correlated with area life expectancy for individuals in the bottom income quartile. Much of this correlation is driven by men in the bottom income quartile. We also find that disaggregating a preventive care index produces significant relationships between components of the index and longevity where none were previously found.ConclusionsThese results counter prior assertions that local health costs are not associated with life expectancy. Additionally, the results also suggest that the local cost of outpatient care and the quality of that care may influence the longevity of low-income populations, especially for low-income men.

Annual household income and its association with financial toxicity, health utility, and survival in head and neck cancer.

e18040 Background: While several studies have documented a link between socioeconomic status and survival in head and neck cancer, nearly all have used ecologic, community-based measures. Studies using more granular patient level data are lacking. We sought to determine the association between baseline annual household income with financial toxicity, health utility and survival. Methods: This was a prospective cohort of adult head and neck cancer patients treated at tertiary cancer center between September 17, 2015, and December 19, 2019. Our primary exposure was annual household income at time of diagnosis. Outcomes of interest included disease-free survival, financial toxicity, measured using the FIT tool, and health utility, measured using the Health Utilities Index Mark 3. Cox proportional hazards models were used to estimate the relationship between household income and survival. Income was regressed onto log-transformed FIT scores using linear models. The association between income and health utility was explored using generalized linear models. A generalized estimating equations approach was incorporated to account for patient level clustering. Results: There were 555 patients included in this cohort. Two-year disease-free survival was worse for patients in the bottom income quartile (&lt; $30,000 - 67% [95%CI 58-78])) compared to the top quartile (≥$90,000 - 88% [95%CI 83-93]). In risk adjusted models, patients in the bottom income quartile had inferior disease-free survival (aHR 2.13 [95%CI 1.22-3.71]) but not overall survival (aHR 2.01 [95%CI 0.94-4.29]). The average FIT score was 22.6 in the lowest income quartile vs. 11.7 in the highest quartile. In adjusted analysis, low-income patients had 12-month FIT scores that were, on average, 134% higher (worse) [95%CI 16%-253%] than high-income patients. Similarly, health utility scores were, on average, 0.106 [95%CI 0.029-0.184] points lower for low-income patients. Conclusions: Head and neck cancer patients with a household income &lt; $30,000 experienced worse financial toxicity, health status and disease-free survival. Significant disparities exist for Ontario’s head and neck cancer patients.

Income disparity in school readiness and the mediating role of perinatal maternal mental health: a longitudinal birth cohort study.

There is compelling evidence for gradient effects of household income on school readiness. Potential mechanisms are described, yet the growth curve trajectory of maternal mental health in a child's early life has not been thoroughly investigated. We aimed to examine the relationships between household incomes, maternal mental health trajectories from antenatal to the postnatal period, and school readiness. Prospective data from 505 mother-child dyads in a birth cohort in Singapore were used, including household income, repeated measures of maternal mental health from pregnancy to 2-years postpartum, and a range of child behavioural, socio-emotional and cognitive outcomes from 2 to 6 years of age. Antenatal mental health and its trajectory were tested as mediators in the latent growth curve models. Household income was a robust predictor of antenatal maternal mental health and all child outcomes. Between children from the bottom and top household income quartiles, four dimensions of school readiness skills differed by a range of 0.52 (95% Cl: 0.23, 0.67) to 1.21 s.d. (95% CI: 1.02, 1.40). Thirty-eight percent of pregnant mothers in this cohort were found to have perinatal depressive and anxiety symptoms in the subclinical and clinical ranges. Poorer school readiness skills were found in children of these mothers when compared to those of mothers with little or no symptoms. After adjustment of unmeasured confounding on the indirect effect, antenatal maternal mental health provided a robust mediating path between household income and multiple school readiness outcomes (χ2 126.05, df 63, p < 0.001; RMSEA = 0.031, CFI = 0.980, SRMR = 0.034). Pregnant mothers with mental health symptoms, particularly those from economically-challenged households, are potential targets for intervention to level the playing field of their children.

Higher complication rates after management of lower extremity fractures in lower socioeconomic classes: Are risk adjustment models necessary?

Introduction Alternative payment models, such as bundled payments, have been proposed to control rising costs in orthopaedic trauma surgery. Without risk adjustment models, concerns exist about the financial burden incurred by so called “safety-net hospitals” that serve patients of lower socioeconomic status. The purpose of this study was to determine whether lower socioeconomic status was associated with increased complications and subsequently higher resource utilization following surgical treatment of high-energy lower extremity fractures. Methods The National Inpatient Sample database was queried for patients who underwent surgical fixation of the femur and tibia between 2005–2014. The top and bottom income quartiles were compared. Demographics, medical comorbidities, length of stay (LOS), complications, in-hospital mortality were compared between patients of top and bottom income quartiles. Multivariate logistic regression analysis was then performed to identify factors independently associated with complications, mortality, and increased resource utilization. Results Patients with femur fracture in the bottom income quartile had longer length of stay (6.9 days vs 6.5 days, p &lt; 0.001) and a higher mortality rate (1.9% vs 1.7%, p = 0.034). Patients with tibia fracture in the bottom income quartile had greater complication rates (7.3% vs 6.1%, p &lt; 0.001), longer length of stay (5.3 days vs. 4.5 days, p &lt; 0.001), and higher mortality (0.3% vs. 0.2%, p &lt; 0.001). Conclusions Lower income status is associated with increased in-hospital mortality and longer length of stay in patients following lower extremity fractures. Risk adjustment models should consider the role of socioeconomic status in patient resource utilization to ensure continued access to orthopedic trauma care for all patients.

The demographics of assisted reproductive technology births in a Nordic country.

STUDY QUESTIONWhat are the socio-demographic characteristics of families in Norway who have children after assisted reproductive technology (ART), and have these characteristics changed over time?SUMMARY ANSWERParents who conceive through ART in Norway tend to be advantaged families, and their socio-demographic profile has not changed considerably over the period 1985–2014.WHAT IS KNOWN ALREADYA small number of studies show that couples who conceive through ART tend to be socio-economically advantaged.STUDY DESIGN, SIZE, DURATIONNorwegian Population Register, the Medical Birth Register and the national data bases were linked to study all live births in Norway between 1985 and 2014.PARTICIPANTS/MATERIALS, SETTING, METHODSThe sample consisted of 1 757 768 live births. Simple bivariate analyses were performed to describe the socio-demographic characteristics of parents who conceived through ART and changes in these characteristics over the time period 1985–2014. We used linear probability models to estimate the association between parental income and giving birth after ART from 2000 to 2014, before and after adjustment for maternal age at delivery, education and area of residence.MAIN RESULTS AND THE ROLE OF CHANCEParents conceiving through ART were more likely to be older, with the highest levels of income and education, and married. Their socio-demographic profiles did not change considerably during the period 1985–2014. In the unadjusted model, parents belonging to the top income quartile were 4.2 percentage points more likely (95% CI: 4.1 to 4.3) to have conceived through ART than parents who belonged to the bottom income quartile. Adjustment for maternal age only partially reduced the income disparities (for the top income quartile by 35% (β = 2.7 with 95% CI: 2.5 to 2.8)). Additional adjustment for maternal education, marital status and area of residence did not further attenuate the associations.LIMITATIONS, REASONS FOR CAUTIONThe data does not enable us to tell whether the lower numbers of children conceived through ART amongst more disadvantaged individuals is caused by lower success rates with ART treatment, lower demand of ART services or barriers faced in access to ART. The study focuses on Norway, a context characterised by high subsidisation of ART services.WIDER IMPLICATIONS OF THE FINDINGSEven though in Norway access to ART services is highly subsidised, the results highlight important and persisting social inequities in use of ART. The results also indicate that children born after ART grow up in resourceful environments, which will benefit their development and well-being.STUDY FUNDING/COMPETING INTEREST(S)This work was supported by European Research Council agreement n. 803959 (to A.G.), by Economic and Social Research Council grant ES/M001660/1 and by the Research Council of Norway through its Centres of Excellence funding scheme, project number 262700. The authors have no conflict of interest to declare.TRIAL REGISTRATION NUMBERNot applicable.

Low Socioeconomic Status Is Associated With Increased Complication Rates: Are Risk Adjustment Models Necessary in Cervical Spine Surgery?

Study Design:Retrospective cohort study.Objectives:The objective of this study was to determine whether lower socioeconomic status was associated with increased resource utilization following anterior discectomy and fusion (ACDF).Methods:The National Inpatient Sample database was queried for patients who underwent a primary, 1- to 2-level ACDF between 2005 and 2014. Trauma, malignancy, infection, and revision surgery were excluded. The top and bottom income quartiles were compared. Demographics, medical comorbidities, length of stay, complications, and hospital cost were compared between patients of top and bottom income quartiles.Results:A total of 69 844 cases were included. The bottom income quartile had a similar mean hospital stay (2.04 vs 1.77 days, P = .412), more complications (2.45% vs 1.77%, P < .001), and a higher mortality rate (0.18% vs 0.11%, P = .016). Multivariate analysis revealed bottom income quartile was an independent risk factor for complications (odds ratio = 1.135, confidence interval = 1.02-1.26). Interestingly, the bottom income quartile experienced lower mean hospital costs ($17 041 vs $17 958, P < .001).Conclusion:Patients in the lowest income group experienced more complications even after adjusting for comorbidities. Therefore, risk adjustment models, including socioeconomic status, may be necessary to avoid potential problems with access to orthopedic spine care for this patient population.

Associations between Family Income and Child Development: Mediation by Antenatal Maternal Mental Health

Background: Socioeconomic gradients in numerous measures of child health and development exist. Programs to promote equity for children require a clear understanding of pathways underlying the associations between socioeconomic status and child outcomes. Methods: We used a prospective birth cohort study consisting of 1247 mother-child dyads and assessed maternal mood symptoms at four time points during antenatal and postnatal visits. Child outcomes from ages 2 to 6 included socio-emotional health, school readiness, intelligence, and executive function. We performed latent growth curve analysis to examine the maternal mood trajectory formed by repeated measures, then we conducted structural equation models (SEM) to determine outcome prediction by family income and the mood trajectory. Findings: Family income was a robust predictor of maternal mood and child developmental skills. Between children from the bottom and top family income quartiles, school readiness and IQ differed by a standard deviation of 0·78 (95% CI 0·65-1·07) to 1·18 (95% CI 0·96-1·40). There was a high occurrence (38·2%) of suboptimal maternal mental health. Children of mothers with little or no symptoms were significantly better in many areas of development compared to those of mothers with either clinical or sub-clinical levels of symptoms. While antenatal mood and its mood trajectory to 24-months postpartum are strong correlates of child outcomes, only antenatal mood exerted broad-ranging mediating effects on the associations of family income and all measured child outcomes, accounting for 13·3-56·5% of the total effects. Interpretations: Perinatal maternal symptoms of depression and anxiety are modifiable risks and are thus potential leverage points for intervention to alleviate socioeconomic gradients in child development. Funding Statement: Singapore National Medical Research Council Translational and Clinical Research Flagship Programme (NMRC/TCR/004-NUS/2008, 012-NUHS/2014), Health Services Research Grant (HSR-NIG 011/2015), and the Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR). Declaration of Interests: Professor C.Y.S. is part of the Epigen Academic Consortium that has received academic research funding from Abbot Nutrition, Nestec, and Danone outside of this submitted work. All other co-authors do not have any conflict of interest. Ethics Approval Statement: Ethics were approved by the Singapore National Healthcare Group and SingHealth Institutional Review Boards. All mothers gave informed consent before taking part in this study.

The socioeconomic determinants for transsphenoidal pituitary surgery: a review of New York State from 1995 to 2015.

Prolonged length of stay (pLOS), disease-related complications, and 30-day readmissions are important quality metrics under the Affordable Care Act. The purpose of our study was to investigate the effect of patient-level and hospital-level factors on these outcomes for patients admitted for transsphenoidal pituitary surgery. The Statewide Planning and Research Cooperative System (SPARCS) database was queried to investigate 30-day readmissions and pLOS for transsphenoidal pituitary surgery in New York from 1995 to 2015. Multivariate logistic regression, adjusting for patient and hospital characteristics, was performed to assess the effect of these variables on the outcomes of interest. A total of 9950 patients underwent transsphenoidal pituitary surgery; 7122 (72%), 2394 (24%), and 434 (4%) patients were treated at high-volume, medium-volume, and low-volume centers, respectively. Patient factors associated with treatment at high-volume centers (HVCs) included: top income quartile, private insurance, urban residence, and white or Asian race (p < 0.05). Patient variables associated with treatment at low-volume centers (LVCs) included: age >65 years, elevated Charlson comorbidity index (CCI) scores, bottom income quartile, Medicaid and Medicare insurance, rural residence, black race, and Hispanic ethnicity (p < 0.05). Variables predictive of prolonged hospitalizations in our multivariable model included black race, Hispanic ethnicity, Medicaid insurance, low income, female gender, LVC, and comorbidities (panhypopituitarism, hypothyroidism, diabetes insipidus [DI], visual disturbances, CCI) while predictors of readmissions included Asian race, female gender, and comorbidities (Cushing syndrome, DI, CCI). Patients undergoing transsphenoidal pituitary surgery at HVCs have shorter hospitalizations, fewer postoperative electrolyte abnormalities, and lower charges; however, socioeconomic factors may influence access to quality care.

Socioeconomic status and diagnosis, treatment, and mortality in men with prostate cancer. Nationwide population-based study.

Patients with high socioeconomic status (SES) have better cancer outcomes than patients with low SES. This has also been shown in Sweden, a country with tax‐financed health care aiming to provide care on equal terms to all residents. The association between income and educational level and diagnostics and treatment as outlined in national guidelines and prostate cancer (Pca) and all‐cause mortality was assessed in 74,643 men by use of data in the National Prostate Cancer Register of Sweden and a number of other health care registers and demographic databases. In multivariable logistic regression analysis, men with high income had higher probability of Pca detected in a health‐check‐up, top versus bottom income quartile, odds ratio (OR) 1.60 (95% CI 1.45–1.77) and lower probability of waiting more than 3 months for prostatectomy, OR 0.77 (0.69–0.86). Men with the highest incomes also had higher probability of curative treatment for intermediate and high‐risk cancer, OR 1.77 (1.61–1.95) and lower risk of positive margins, (incomplete resection) at prostatectomy, OR 0.80 (0.71–0.90). Similar, but weaker associations were observed for educational level. At 6 years of follow‐up, Pca mortality was modestly lower for men with high income, which was statistically significant for localized high‐risk and metastatic Pca in men with no comorbidities. All‐cause mortality was less than half in top versus bottom quartile of income (12% vs. 30%, p < 0.001) among men above age 65. Our findings underscore the importance of adherence to guidelines to ensure optimal and equal care for all patients diagnosed with cancer.

The association between income and life expectancy revisited: deindustrialization, incarceration and the widening health gap.

The health gap between the top and the bottom of the income distribution is widening rapidly in the USA, but the lifespan of America's poor depends substantially on where they live. We ask whether two major developments in American society, deindustrialization and incarceration, can explain variation among states in life expectancy of those in the lowest income quartile. Life expectancy estimates at age 40 of those in the bottom income quartile were used to fit panel data models examining the relationship with deindustrialization and incarceration between 2001 and 2014 for all US states. A one standard deviation (s.d.) increase in deindustrialization (mean = 11.2, s.d. = 3.5) reduces life expectancy for the poor by 0.255 years [95% confidence interval (CI): 0.090-0.419] and each additional prisoner per 1000 residents (mean = 4.0, s.d. = 1.5) is associated with a loss of 0.468 years (95% CI: 0.213-0.723). Our predictors explain over 20% of the state-level variation in life expectancy among the poor and virtually the entire increase in the life expectancy gap between the top and the bottom income quartiles since the turn of the century. In the USA between 2001 and 2014, deindustrialization and incarceration subtracted roughly 2.5 years from the lifespan of the poor, pointing to their role as major health determinants. Future research must remain conscious of the upstream determinants and the political economy of public health. If public policy responses to growing health inequalities are to be effective, they must consider strengthening industrial policy and ending hyper-incarceration.

An empirical analysis of household education expenditures in Turkey

Using Turkish Household Budget Surveys from 2003, 2007 and 2012, this paper investigates the determinants of household education expenditures within an Engel curve framework. In particular, we estimate Tobit regressions of real educational expenditures by income groups using a number of household characteristics (i.e. rural residence, employment status, age, educational attainment of the household head, household size, share of female students and primary school students in the household, and total number of students in the household) to examine if and to what extent the determinants of educational expenditures differ by income groups; income elasticities of educational spending evolves over time; and children from middle-class and poor families can benefit enough from educational opportunities. The estimated expenditure elasticities have lower values for the top- and the bottom-income quartiles while they have larger values for the middle-income quartiles. The results also show that for all income groups the expenditure elasticity of education increases over time, indicating that Turkish households allocates greater share of their budgets to education expenditures.

The Association Between Income and Life Expectancy in the United States, 2001-2014.

The relationship between income and life expectancy is well established but remains poorly understood. To measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation. Income data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy. Pretax household earnings as a measure of income. Relationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas. The sample consisted of 1,408,287,218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61,175 per year). There were 4,114,380 deaths among men (mortality rate, 596.3 per 100,000) and 2,694,808 deaths among women (mortality rate, 375.1 per 100,000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% (P < .001 for the differences for both sexes). Third, life expectancy for low-income individuals varied substantially across local areas. In the bottom income quartile, life expectancy differed by approximately 4.5 years between areas with the highest and lowest longevity. Changes in life expectancy between 2001 and 2014 ranged from gains of more than 4 years to losses of more than 2 years across areas. Fourth, geographic differences in life expectancy for individuals in the lowest income quartile were significantly correlated with health behaviors such as smoking (r = -0.69, P < .001), but were not significantly correlated with access to medical care, physical environmental factors, income inequality, or labor market conditions. Life expectancy for low-income individuals was positively correlated with the local area fraction of immigrants (r = 0.72, P < .001), fraction of college graduates (r = 0.42, P < .001), and government expenditures (r = 0.57, P < .001). In the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.

Economic Opportunity, Health Behaviors, and Mortality in the United States.

We assessed whether economic opportunity was independently associated with health behaviors and outcomes in the United States. Using newly available, cross-sectional, county-level data from the Equality of Opportunity Project Database and vital statistics, we estimated associations between all-cause mortality rates (averaged over 2000-2012) and economic opportunity, adjusting for socioeconomic, demographic, and health system covariates. Our measure of economic opportunity was the county-average rank in the national income distribution attained by individuals born to families in the bottom income quartile. Secondary outcomes included rates of age- and race-specific mortality, smoking, obesity, hypertension, and diabetes. An increase in economic opportunity from the lowest to the highest quintile was associated with a 16.7% decrease in mortality. The magnitudes of association were largest for working-age adults and African Americans. Greater economic opportunity was also associated with health behaviors and risk factors. Economic opportunity is a robust, independent predictor of health. Future work should investigate underlying causal links and mechanisms.

OP14 Children’s and Adolescents’ Sedentary Behaviour in Relation to Household Socioeconomic Status, Income, and Area Deprivation: The 2008 Health Survey for England

BackgroundSedentary behaviour (sitting) is an emerging cardiometabolic risk factor in young people. Little is known about how household socioeconomic position (SEP) and sedentary behaviour are associated in children and adolescents....

Understanding livelihood strategy-poverty links: empirical evidence from central highlands of Ethiopia

The aim of this paper is to disclose livelihood strategy-poverty links and gain a better understanding by developing typologies of rural households. Based on qualitative and quantitative data, we group households into different typologies and explore interactions. We identified six main agronomic strategies, four dominant livelihood diversification strategies, and income quartiles (proxies for poverty) using cluster and principal component factor analysis. We found that nearly 82% of the surveyed farmers in the study area belong to the bottom income quartiles while about 18% are on the upper quartiles. Households in the bottom income quartiles engaged in casual off-farm work and cereal-dominated livelihood strategies that tend to pursue subsistence farming by growing cereals and oil crops. Contrarily, farmers in the upper income quartiles adapted intensive agronomic strategies by integrating root crops, legumes, and vegetables with livestock. This was largely attributed to access to key livelihood assets such as land, livestock, education, and institutional support in which the upper quartiles were more endowed. Improving availability of the key assets for the bottom income quartiles might be a way out of poverty and ensuring sustainable development. It is crucial to recognize local-level heterogeneities of rural households when targeting development interventions.

Commentary: Health policies in the US: can they increase or decrease the gap between subgroups of the population? The case of folic acid

Effective on January 1, 1998, the Food and Drug Administration (FDA) amended the standards to identify several enriched grain products, bromated flour, vegetable macaroni and vegetable noodle products by requiring folic acid fortication. Specifically, the FDA required that these products be fortified with folic acid levels ranging from 0.43 to 1.4 mg/pound or 95 to 309 mg/100 g of product. Although this requirement affects the entire population, the purpose of this amendment was to ensure that women of childbearing age consume the US Public Health Service recommended daily allowance of at least 0.4 mg (400 mg) of folic acid daily to reduce their risk of having a child with spina bifida or other neural tube defects (NTDs). Spina bifida and anencephaly affect approximately 4000 children in the US prior to the folic acid fortification amendment. However, approximately 1000 of these cases have been prevented with folic acid fortification. As with most conditions in the US, estimates for NTDs vary by race and ethnicity, with Hispanics exhibiting the highest estimates and blacks and Asians the lowest. Moreover, NTDs varies by socioeconomic status defined using income and education with the least educated and those with low income exhibiting the highest estimates. Low folate levels not only affect children in utero, but also evidence suggests that low folate levels are associated with increased prevalence of cancer, cardiovascular disease, physical and mental functioning. Thus, despite the fact that the fortification was targeted to women of childbearing age, the FDA amendment could be a preventive paradox for population health by benefiting everyone. The latter could have implications for health disparities across subgroups of the population if differences exist across the outcomes benefiting from the fortification. Findings from existing studies on folic acid preand post-fortification suggest that there are disparities between groups. For instance, Ford and Bowman showed differences in red blood cell (RBC) folate concentrations between non-Hispanic blacks and nonHispanic whites with the highest differences among those with greater than a high school diploma regardless of gender. Conversely, differences between Mexican Americans and non-Hispanic whites were significant for men with at least 9 years of education and for women at the educational attainment extreme (<9 years of education and more than a high school diploma). Ganji and Kafai showed a decrease in prevalence of low RBC folate between 1988–94 and 1999–2002 across all racial/ ethnic and poverty-income ratio groups. However, nonHispanic blacks continue to exhibit a higher prevalence of low RBC folate through this period. Unlike previous studies examining trends between the preand post-fortification period, Dowd and Aiello focused on investigating the magnitude of the racial/ethnic and socioeconomic status (defined using poverty to income ratio) disparities assessed as absolute and relative differences. Using data from the National Health and Nutrition Examination Surveys (NHANES), Dowd and Aiello examined racial/ethnic and income disparities in folate status in US adults aged 25 years or older before (1991–1994) and after (1999–2002) enactment of the folic acid fortification. They found an increase in relative, but a decrease, in absolute difference before and after the fortification. Non-Hispanic blacks had 1.6 (95% CI: 1.4–1.9) greater odds of having low RBC folate (<362.6 nmol) levels compared with non-Hispanic whites in the pre-fortification period. This estimate was 3.7 (95% CI: 2.8–5.0) in the postfortification period. In the pre-fortification period, individuals in the bottom income quartile had a 1.3 (95% CI: 1.1–1.4) greater odds of having low RBC compared with those in the highest income quartile. Finally, in the post-fortification period, this estimate was 2.1 (95% CI: 1.6–2.7). The corresponding absolute differences were 233 (pre-) and 121 (post-fortification) Department of Health Sciences, Graduate Program in Public Health, Lehman College, CUNY, 250 Bedford Park Boulevard West, Gillet 336, Bronx, NY 10468, USA. E-mail: Luisa.Borrell@lehman.cuny.edu Published by Oxford University Press on behalf of the International Epidemiological Association

Opportunities for Low-Income Students at Top Colleges and Universities: Policy Initiatives and the Distribution of Students

Whether the nation's most selective and resource-intensive colleges and universities are successful in serving as "engines of opportunity" rather than "bastions of privilege" depends on the extent to which they increase the educational attainment of students from the most economically disadvantaged backgrounds (Bowen, Kurzweil, and Tobin, 2005). Less than 11 percent of first-year students matriculating at 20 highly selective institutions were from the bottom income quartile of the income distribution, leading to significant concerns from higher education leaders and policy makers about the role of higher education in reducing intergenerational inequality, particularly in an era of high returns to education. Responding to what Lawrence Summers described as the "manifest inadequacy of higher education's current contribution to equality of opportunity in America," Harvard University and other public and private universities have introduced new initiatives designed to encourage the enrollment of students from low-and moderateincome families. One question addressed in this paper is whether the population of low-income students with high observed academic achievement is sufficiently large that aggressive institutional policies will be an effective tool in increasing the representation of low-income students at the most highly ranked colleges and universities. Using data on test-taking outcomes, we also examine where students currently send scores (as a proxy for application) and then consider the extent to which differences in family income affect students'choice sets. While the problem of the underrepresentation of low-income students affects both public and private universities, the effect of outreach and financial aid policies on outcomes is likely to differ appreciably across institutions.