Area-level Socioeconomic Characteristics Research Articles

Importance of Patient Health Insurance Coverage and Out-of-Pocket Costs for Genomic Testing in Oncologists' Treatment Decisions.

Use of genomic testing, especially multimarker panels, is increasing in the United States. Not all tests and related treatments are covered by health insurance, which can result in substantial patient out-of-pocket (OOP) costs. Little is known about oncologists' treatment decisions with respect to patient insurance coverage and OOP costs for genomic testing. We identified 1,049 oncologists who used multimarker tumor panels from the 2017 National Survey of Precision Medicine in Cancer Treatment. Separate multivariable ordinal logistic regressions examined associations of oncologist-, practice-, and area-level characteristics and oncologists' ratings of importance (very, somewhat, or a little/not important) of insurance coverage and OOP costs for genomic testing in treatment decisions, adjusting for oncologist years of experience, sex, race and ethnicity, specialty, use of next-generation sequencing (NGS) tests, region, tumor boards, patient insurance mix, and area-level socioeconomic characteristics. Among oncologists, 47.3%, 32.7%, and 20.0% reported that patient insurance coverage for genomic testing was very, somewhat, or a little/not important, respectively, in treatment decisions. In addition, 56.9%, 28.0%, and 15.2% reported that OOP costs for testing were very, somewhat, or a little/not important, respectively. In adjusted analyses, oncologists who used NGS tests were more likely to report patient insurance and OOP costs as important (odds ratio [OR], 2.00 [95% CI, 1.16 to 3.45] and OR, 2.12 [95% CI, 1.22 to 3.68], respectively) in treatment decisions compared with oncologists who did not use these tests, as were oncologists who treated solid tumors, rather than only hematological cancers. More years of experience and higher percentages of Medicaid or self-paid/uninsured patients in the practice were associated with reporting insurance coverage (OR, 1.43 [95% CI, 1.09 to 1.89]) and OOP costs (OR, 1.51 [95% CI, 1.13 to 2.01]) as important. Oncologists in practices with molecular tumor boards for genomic tests were less likely to report coverage (OR, 0.63 [95% CI, 0.47 to 0.85]) and OOP costs (OR, 0.72 [95% CI, 0.53 to 0.97]) as important than their counterparts in practices without these tumor boards. Most oncologists rate patient health insurance and OOP costs for genomic tests as important considerations in subsequent treatment recommendations. Modifiable factors associated with these ratings can inform interventions to support patient-physician decision making about care.

Climatic exposures in childhood and the risk of schizophrenia from childhood to early adulthood

BackgroundSeason of birth is a risk factor of schizophrenia, and it is possible that cumulative exposure to climatic factors during childhood affects the risk of schizophrenia. We conducted a cohort study among 365,482 persons born in Finland in 1990–1995 to examine associations of 10-year cumulative exposure to global solar radiation and ambient temperature in childhood with schizophrenia. MethodsData on schizophrenia diagnoses and sociodemographic factors from the Finnish population register and health care register were linked to daily meteorological data using residential information. The study population was followed from age 10 until the first schizophrenia diagnosis, death, emigration or December 31, 2017, whichever came first. Hazard ratios (HR) for the risk of schizophrenia were estimated using Cox proportional hazards model. ResultsCompared to the lowest quintile of global solar radiation or ambient temperature, growing up in the second highest quintile (Q4) was associated with greater risk of schizophrenia. These hazard ratios were attenuated after adjustment for parental mental disorder, parental education, parental income, area-level socioeconomic characteristics and urbanicity (HR = 1.29, 95 % CI 1.06–1.58 for radiation; HR = 1.24, 95 % CI, 1.02–1.52 for temperature). Continuous linear terms evaluated in secondary models suggested a greater risk of schizophrenia at greater childhood exposure to global radiation and ambient temperature, but these associations did not remain in fully adjusted models. ConclusionsWe found no consistent evidence that cumulative exposure to sunlight and ambient temperature in childhood is associated with the risk of developing schizophrenia. Studies in other populations residing in different latitudes are needed.

Epidemiology of COVID-19 Among Healthcare Workers In Ontario, Canada During The First Pandemic Wave

Aim and Objectives: This study aims to describe and compare COVID-19 cases among healthcare workers, long-term care residents, and the general population in Ontario, Canada, considering baseline characteristics, trends over time, and socioeconomic status.
 Methods: This study used test-confirmed COVID-19 case reports between March 13th, 2020 to June 15th, 2020, reported by Ontario’s Public Health Units to the Ontario Ministry of Health Public Health Case and Contact Management Solution (CCM). Cases were stratified into three sub-populations based on risk group characteristics identified in CCM data: healthcare workers, long-term care residents, and the general population. The residential postal codes of the cases reported to CCM were linked to area-level socioeconomic characteristics of material deprivation from the Ontario Marginalization Index (ON-MARG). Demographic characteristics and case outcomes were captured in CCM data for each case.
 Results: COVID-19 cases among healthcare workers were more concentrated between working ages of 20–59 and in females, compared to the general population and long-term care cases. Additionally, hospitalization and mortality were low among healthcare workers compared to the other sub-populations. Over time, COVID-19 cases decreased among healthcare workers. For both healthcare workers and the general population, more cases were observed in areas of high material deprivation, and this disparity between high- and low- income areas increased over time.
 Conclusion: Healthcare workers are a known high-risk group for COVID-19. For the surveillance of this disease, it is important to understand how they compare to other population groups regarding infection, hospitalization, and mortality. Our analysis shows clear socioeconomic gradients in the distribution of the disease. Thus, focusing our efforts on identifying and testing healthcare workers that work or live in lower socioeconomic areas would benefit the residents and workers in these areas and support the ongoing COVID-19 response.

Incidence of type 1 diabetes by socio-demographic characteristics among South Australian children: Whole-of-population study.

To describe and compare the incidence of type 1 diabetes (T1D) in South Australia by individual and area-level socio-economic characteristics among children aged ≤11 years. This is a whole-of-population, data linkage study (n = 231 685) conducted in South Australia, and included children born from 2002 to 2013, hospitalisation followed from 2002 to 2014. The study used de-identified, linked administrative hospitalisation, birth and perinatal data from the South Australian Early Childhood Data Project. Incidence was calculated by identifying T1D cases from T1D-related hospitalisations using International Classification of Disease, 10th Revision, Australian Modification diagnosis codes (E10, E101-E109). Overall, 333 children aged ≤11 years (173 boys) were identified as having T1D. The T1D incidence rate was 23.0 per 100 000 person-years (95% confidence interval (CI): 20.7-25.7), with no sex difference. T1D incidence was higher among children whose mothers were Caucasian, private patients and whose parents were employed. For example, T1D incidence was 26.0 per 100 000 (95% CI: 22.8-29.5) among children with both parents employed, compared to 20.0 per 100 000 (95% CI: 12.3-30.6) among children with both parents unemployed. There was no clear gradient in the association between area-level socio-economic position and T1D, with highest incidence for the fourth quintile (26.5 per 100 000 (95% CI: 20.9-33.1)). The most advantaged area (19.4 per 100 000 (95% CI: 13.8-26.5)) had lower incidence than the most disadvantaged area (23.5 per 100 000 (95% CI: 18.9-28.9)). T1D incidence rates differed depending on the measures of socio-economic characteristics. Individual-level indicators showed higher incidence among more advantaged children; however, there was no clear area-level socio-economic patterning of T1D.

Basic sanitation and self-reported health in Brazilian capitals: a multilevel analysis.

This study aimed to analyze the association between the contextual determinants related to basic sanitation and self-reported health in Brazilian capitals. The sample consisted of 27,017 adults (≥18 years) residing in the 27 Brazilian capitals in 2013, from the National Health Survey (PNS). The association between self-reported health and sanitation (sewage system, water supply and garbage collection) was analyzed using Bayesian multilevel models, controlling for individual factors (first level of the model) and area-level socioeconomic characteristics (second level). We found a consistent association between better self-reported health and better sanitation levels, even after controlling for individual and contextual characteristics. At the contextual level, lower odds of poor self-reported health was observed among those living in areas with medium (OR = 0.59, 95%CI 0.57 - 0.61) or high (OR = 0.61, 95%CI 0.57 - 0.66) sewage system level; medium (OR = 0.77, 95%CI 0.71 - 0.83) coverage of water supply; and high (OR = 0.78, 95%CI 0.69 - 0.89) garbage collection level. The positive association between better sanitation conditions and health, independently of the individual factors and the socioeconomic characteristics of the place of residence, confirms the need to consider sanitation in the planning of health policies.

Exploring and visualizing the small-area-level socioeconomic factors, alcohol availability and built environment influences of alcohol expenditure for the City of Toronto: a spatial analysis approach.

Many Canadians continue to drink alcohol in excess of the recommended low-risk guidelines. In this study, we visualized the geographic variation of licensed premises alcohol expenditures in Toronto and examined the effects of area-level socioeconomic characteristics, alcohol availability and built environment influences on alcohol expenditures at the Dissemination Area (DA) level. Dissemination Area average total household expenditures on alcohol from licensed premises, from the 2010 Survey of Household Spending, was the main outcome variable. Moran's I and Local Moran's I were used to quantify geographic variation and determine hot spots and cold spots of expenditure. We used DA-level socioeconomic characteristics from the 2006 Census of Canada, and the density of licensed premises and other built environment characteristics from the 2008 DMTI Spatial and 2010 CanMap datasets to predict alcohol expenditures in multivariate spatial regression models. The results indicated that the most significant area-level predictors of alcohol expenditure were the percentage of individuals in management or finance occupations and the percentage with postsecondary education (one-unit increases associated with 78.6% and 35.0% increases in expenditures respectively). Presence of subway lines in the immediate and neighbouring areas was also significant (one-unit increases resulted in 5% and 28% increases respectively). Alcohol outlet density was also positively associated with alcohol expenditures. The associations identified between licensed premises alcohol expenditures and small-area-level characteristics highlight the potential importance of small-area-level factors in understanding alcohol use. Understanding the small-area-level characteristics of expenditures and geographic variation of alcohol expenditures may provide avenues for alcohol use reduction initiatives and policies.

The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?

BackgroundCountry averages for health outcomes hide important within-country variations. This paper probes into the geographic Belgian pattern of all-cause mortality and wishes to investigate the contribution of individual and area socio-economic characteristics to geographic mortality differences in men aged 45–64 during the period 2001–2011.MethodsData originate from a linkage between the Belgian census of 2001 and register data on mortality and emigration during the period 2001–2011. Mortality rate ratios (MRRs) are estimated for districts and sub-districts compared to the Belgian average mortality level using Poisson regression modelling. Individual socio-economic position (SEP) indicators are added to examine the impact of these characteristics on the observed geographic pattern. In order to scrutinize the contribution of area-level socio-economic characteristics, random intercepts Poisson modelling is performed with predictors at the individual and the sub-district level. Random intercepts and slopes models are fitted to explore variability of individual-level SEP effects.ResultsAll-cause MRRs for middle-aged Belgian men are higher in the geographic areas of the Walloon region and the Brussels-Capital Region (BCR) compared to those in the Flemish region. The highest MRRs are observed in the inner city of the BCR and in several Walloon cities. Their disadvantage can partially be explained by the lower individual SEP of men living in these areas. Similarly, the relatively low MRRs observed in the districts of Halle-Vilvoorde, Arlon and Virton can be related to the higher individual SEP. Among the area-level characteristics, both the percentage of men employed and the percentage of labourers in a sub-district have a protective effect on the individual MRR, regardless of individual SEP. Variability in individual-level SEP effects is limited.ConclusionsIndividual SEP partly explains the observed mortality gap in Belgium for some areas. The percentage of men employed and the percentage of labourers in a sub-district have an additional effect on the individual MRR aside from that of individual SEP. However, these socio-economic factors cannot explain all of the observed differences. Other mechanisms such as public health policy, cultural habits and environmental influences contribute to the observed geographic pattern in all-cause mortality among middle-aged men.Electronic supplementary materialThe online version of this article (doi:10.1186/s13690-016-0135-y) contains supplementary material, which is available to authorized users.

Area-Level Socioeconomic Characteristics, Prevalence and Trajectories of Cardiometabolic Risk

This study examines the relationships between area-level socioeconomic position (SEP) and the prevalence and trajectories of metabolic syndrome (MetS) and the count of its constituents (i.e., disturbed glucose and insulin metabolism, abdominal obesity, dyslipidemia, and hypertension). A cohort of 4,056 men and women aged 18+ living in Adelaide, Australia was established in 2000–2003. MetS was ascertained at baseline, four and eight years via clinical examinations. Baseline area-level median household income, percentage of residents with a high school education, and unemployment rate were derived from the 2001 population Census. Three-level random-intercepts logistic and Poisson regression models were performed to estimate the standardized odds ratio (SOR), prevalence risk ratio (SRR), ratio of SORs/SRRs, and (95% confidence interval (CI)). Interaction between area- and individual-level SEP variables was also tested. The odds of having MetS and the count of its constituents increased over time. This increase did not vary according to baseline area-level SEP (ratios of SORs/SRRs ≈ 1; p ≥ 0.42). However, at baseline, after adjustment for individual SEP and health behaviours, median household income (inversely) and unemployment rate (positively) were significantly associated with MetS prevalence (SOR (95%CI) = 0.76 (0.63–0.90), and 1.48 (1.26–1.74), respectively), and the count of its constituents (SRR (95%CI) = 0.96 (0.93–0.99), and 1.06 (1.04–1.09), respectively). The inverse association with area-level education was statistically significant only in participants with less than post high school education (SOR (95%CI) = 0.58 (0.45–0.73), and SRR (95%CI) = 0.91 (0.88–0.94)). Area-level SEP does not predict an elevated trajectory to developing MetS or an elevated count of its constituents. However, at baseline, area-level SEP was inversely associated with prevalence of MetS and the count of its constituents, with the association of area-level education being modified by individual-level education. Population-level interventions for communities defined by area-level socioeconomic disadvantage are needed to reduce cardiometabolic risks.

Dietary Intakes by Different Markers of Socioeconomic Status: A Cross-Sectional Study

Previous studies show that diet quality varies by socioeconomic gradient. We compared the influence of individual- and area-level socioeconomic characteristics on food choice behavior and dietary nutrient intakes in a cross-sectional survey. Daily nutrient intakes were calculated from a food frequency questionnaire. Participants comprised 4007 people (1915 men, 2092 women) aged 35 to 74 years. Socioeconomic measures included the area-based deprivation NZDep2001, gross household income, education level and the occupation-based New Zealand Socioeconomic Index (NZSEI96). Results: Nutrients expressed as their percentage contribution to total energy intakes and adjusted for age, gender and ethnicity, showed that intakes of cholesterol were higher in the lower income groups, and fibre, alcohol and calcium were lower compared to the highest income group. Similarly adjusted nutrients expressed as their contribution to total energy intakes showed lower alcohol intakes in the lower NZDep2001 classes compared to the highest NZDep2001 class. Lower fruit, cheese, wine, and spirit servings were found in both the lower income and NZDep2001 groups. Lower vegetables, milk and cereal servings were found in the lowest income group compared with the highest. Higher chicken, eggs and bread servings were found in the lowest NZDep2001 group compared to the highest NZDep2001 group. Few statistically significant associations were observed with the NZSEI96 or education. Conclusion: Income was more strongly associated with nutrient intakes and NZDep2001 with food group selections. Lower fruit, cheese, wine and spirit servings in the lower SES strata showed independent associations with income and NZDep2001. However, NZDep2001 and income appear to be measuring different elements of dietary intakes and food group servings, with income being associated with lower vegetable, milk and cereal servings, and increased dietary cholesterol and lower fibre, and calcium intakes and NZDep2001 with increased chicken, eggs and bread servings. More in depth, research into area-level determinants of diet is warranted.

Area-level socioeconomic characteristics and incidence of metabolic syndrome: a prospective cohort study.

BackgroundThe evidence linking socioeconomic environments and metabolic syndrome (MetS) has primarily been based on cross-sectional studies. This study prospectively examined the relationships between area-level socioeconomic position (SEP) and the incidence of MetS.MethodsA prospective cohort study design was employed involving 1,877 men and women aged 18+ living in metropolitan Adelaide, Australia, all free of MetS at baseline. Area-level SEP measures, derived from Census data, included proportion of residents completing a university education, and median household weekly income. MetS, defined according to International Diabetes Federation, was ascertained after an average of 3.6 years follow up. Associations between each area-level SEP measure and incident MetS were examined by Poisson regression Generalised Estimating Equations models. Interaction between area- and individual-level SEP variables was also tested.ResultsA total of 156 men (18.7%) and 153 women (13.1%) developed MetS. Each percentage increase in the proportion of residents with a university education corresponded to a 2% lower risk of developing MetS (age and sex-adjusted incidence risk ratio (RR) = 0.98; 95% confidence interval (CI) =0.97-0.99). This association persisted after adjustment for individual-level income, education, and health behaviours. There was no significant association between area-level income and incident MetS overall. For the high income participants, however, a one standard deviation increase in median household weekly income was associated with a 29% higher risk of developing MetS (Adjusted RR = 1.29; 95%CI = 1.04-1.60).ConclusionsWhile area-level education was independently and inversely associated with the risk of developing MetS, the association between area-level income and the MetS incidence was modified by individual-level income.

Relationship between area-level socioeconomic characteristics and outdoor NO2concentrations in rural and urban areas of northern Spain

BackgroundSocioeconomic variables are associated with mortality and morbidity in a variety of diseases at both the individual and neighborhood level. Investigating whether low socioeconomic status populations are exposed to higher air pollution has been an important objective for the scientific community during the last decade. The goal of this study was to analyze the associations between outdoor nitrogen dioxide (NO2) concentrations in an area of Asturias (Spain) and two socioeconomic indexes—one based on occupation and the other on educational level—at the census-tract level.MethodsA map of NO2 concentration was obtained from a land-use regression model. To obtain a census-tract average value, NO2 was estimated at the centroids of all 50 × 50 m grids within a census tract. Standard socioeconomic variables were used from the Census of Population and Housing 2001. We analyzed the association between NO2 concentration and socioeconomic indicators for the entire area and stratified for more urban and more rural areas.ResultsA positive linear relationship was found between the levels of education and NO2 exposure in the urban area and the overall study area, but no association was found in the rural area. A positive association between socioeconomic index based upon occupation and NO2 concentration was found in urban areas; however, this association was reversed in the rural and overall study areas.ConclusionsThe strength and direction of the association between socioeconomic status and NO2 concentration depended on the socioeconomic indicator used and the characteristics of the study area (urban, rural). More research is needed with different scenarios to clarify the uncertain relationship among socioeconomic indexes, particularly in non-urban areas, where little has been documented on this topic.

Lost Letter Measure of Variation in Altruistic Behaviour in 20 Neighbourhoods

Altruistic behaviour varies across human populations and this variation is likely to be partly explained by variation in the ecological context of the populations. We hypothesise that area level socio-economic characteristics will determine the levels of altruism found in individuals living in an area and we use a lost letter experiment to measure altruism across 20 neighbourhoods with a wide range of income deprivation scores in London, UK. The results show a strong negative effect of neighbourhood income deprivation on altruistic behaviour, with letters dropped in the poorest neighbourhoods having 91% lower odds of being returned than letters dropped in the wealthiest neighbourhoods. We suggest that measures of altruism are strongly context dependant.

Who is eating where? Findings from the SocioEconomic Status and Activity in Women (SESAW) study

Foods prepared outside of the home have been linked to less-than-ideal nutrient profiles for health. We examine whether the locations where meals are prepared and consumed are associated with socio-economic predictors among women. A cross-sectional study using self-reported data. We examined multiple locations where meals are prepared and consumed: (i) at home; (ii) fast food eaten at home; (iii) fast food eaten at the restaurant; (iv) total fast food; (v) non-fast-food restaurant meals eaten at home; (vi) non-fast-food restaurant meals eaten at the restaurant; and (vii) all non-fast-food restaurant meals. Multilevel logistic regression was used to determine whether frequent consumption of meals from these sources varied by level of education, occupation, household income and area-level disadvantage. Metropolitan Melbourne, Australia. A total of 1328 women from forty-five neighbourhoods randomly sampled for the SocioEconomic Status and Activity in Women study. Those with higher educational qualifications or who were not in the workforce (compared with those in professional employment) were more likely to report frequent consumption of meals prepared and consumed at home. High individual- and area-level socio-economic characteristics were associated with a lower likelihood of frequent consumption of fast food and a higher likelihood of frequent consumption of meals from non-fast-food sources. The strength and significance of relationships varied by place of consumption. The source of meal preparation and consumption varied by socio-economic predictors. This has implications for policy makers who need to continue to campaign to make healthy alternatives available in out-of-home food sources.

Individual and area-level socioeconomic associations with fast food purchasing

BackgroundIt has been suggested that those with lower socioeconomic characteristics would be more likely to seek energy-dense food options such as fast food because of cheaper prices; however, to date...

A multilevel study of socio-economic inequalities in food choice behaviour and dietary intake among the Dutch population: the GLOBE study

To examine the influence of individual- and area-level socio-economic characteristics on food choice behaviour and dietary intake. The city of Eindhoven in the south-east Netherlands. A total of 1339 men and women aged 25-79 years were sampled from 85 areas (mean number of participants per area = 18.4, range 2-49). Information on socio-economic position (SEP) and diet was collected by structured face-to-face interviews (response rate 80.9%). Individual-level SEP was measured by education and household income, and area-level deprivation was measured using a composite index that included residents' education, occupation and employment status. Diet was measured on the basis of (1) a grocery food index that captured compliance with dietary guidelines, (2) breakfast consumption and (3) intakes of fruit, total fat and saturated fat. Multilevel analyses were performed to examine the independent effects of individual- and area-level socio-economic characteristics on the dietary outcome variables. After adjusting for individual-level SEP, few trends or significant effects of area deprivation were found for the dietary outcomes. Significant associations were found between individual-level SEP and food choice, breakfast consumption and fruit intake, with participants from disadvantaged backgrounds being less likely to report food behaviours or nutrient intakes consistent with dietary recommendations. The findings suggest that an individual's socio-economic characteristics play a more important role in shaping diet than the socio-economic characteristics of the area in which they live. In this Dutch study, no independent influence of area-level socio-economic characteristics on diet was detected, which contrasts with findings from the USA, the UK and Finland.

Life-course socioeconomic position, area deprivation, and coronary heart disease: findings from the British Women's Heart and Health Study.

We sought to determine whether residential area deprivation, over and above the effect of life-course socioeconomic status or position (SEP), is associated with coronary heart disease. We conducted a cross-sectional analysis of 4286 women aged 60 to 79 years from 457 British electoral wards. After adjustment for age and 10 indicators of individual life-course SEP, the odds of coronary heart disease was 27% greater among those living in wards with a deprivation score above the median compared with those living in a ward with a deprivation score equal to or below the median (odds ratio=1.27; 95% confidence interval=1.02, 1.57). Adverse area-level socioeconomic characteristics, over and above individual life-course SEP, are associated with increased coronary heart disease.