Housing-based Socioeconomic Status Research Articles

Disparities in Influenza, Pneumococcal, COVID-19 Vaccine Coverage in High-Risk Adults Aged 19 to 64 Years in Southeastern Minnesota, 2010-2021

Despite effective vaccines against influenza, pneumococcus, and COVID-19, uptake has been suboptimal. Although disparities in vaccination by race and ethnicity have been observed, what is the role of other sociodemographic factors in US vaccine uptake? We conducted a population-based study using the Rochester Epidemiology Project (REP), a comprehensive medical records linkage system, to assess effects of sociodemographic factors including race, ethnicity, individual-level socioeconomic status (SES) via the housing-based socioeconomic status index, education, population density (urban or nonurban), and marital status with uptake of influenza, pneumococcal, and COVID-19 vaccination in high-risk adults. Adults at high risk of invasive pneumococcal disease residing in four counties in southeastern Minnesota who were aged 19 to 64 years were identified. Vaccination data were obtained from the Minnesota Immunization Information Connection and REP from January 1, 2010, through December 31,2021. We identified 45,755 residents. Most were White (82%), non-Hispanic (94%), married (56%), and living in an urban setting (81%), with three-quarters obtaining at least some college education (74%). Although 45.1%were up to date on pneumococcal vaccines, 60.1%had completed the primary COVID-19 series. For influenza and COVID-19, higher SES, living in an urban setting, older age, and higher education positively correlated with vaccination. Magnitude of differences in race, education, and SES widened with booster vaccines. This high-risk population is undervaccinated against preventable respiratory diseases, especially influenza and pneumococcus. Although national data reported improvement of disparities in COVID-19 vaccination uptake observed early in the pandemic, our data demonstrated gaps related to race, education level, SES, and age that widened with booster vaccines. Communities with high social vulnerabilities often show increased risk of severe disease outcomes, yet demonstrate lower uptake of preventive services. This highlights the need to understand better vaccine compliance and access in rural, lower SES, less-educated, Black, Hispanic, and younger populations, each of which were associated independently with decreased vaccination.

Socioeconomic status, race, and preadolescent acne: A population-based retrospective cohort analysis in a mixed rural-urban community of the United States (Olmsted County, Minnesota).

There is limited information about the potential relationship of socioeconomic status (SES) with acne in preadolescents. Our objective was to assess the possible relationship between SES and preadolescent acne. A population-based retrospective cohort study was conducted to identify Olmsted County, Minnesota, residents with an initial acne diagnosis between 7 and ≤12 years old during 2010 to 2018 using the Rochester Epidemiology Project. For each acne case, we randomly selected 2 sex- and age-matched controls without an acne diagnosis from the county. Individual HOUsing-based SocioEconomic Status index (HOUSES) derived from real property data was used to evaluate SES, represented as four quartiles with higher quartile representing higher SES. A total of 604 patients met the criteria. HOUSES distribution significantly differed between cases and controls (p=.001); a higher proportion of acne cases were in quartile 4 (42.2% vs. 32.7%), indicating higher SES. Race and ethnicity did not significantly differ between cases and controls. Among cases and controls, 74.5% and 72.3% were White, respectively. Study limitations include its retrospective design, only patients who visited a physician were included, and Olmsted County residents are largely non-Hispanic White. Preadolescents diagnosed with acne have a higher SES than those without diagnosed acne, highlighting a potential disparity in access to care and appropriate diagnosis.

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.

Artificial intelligence (AI) models may propagate harmful biases in performance and hence negatively affect the underserved. We aimed to assess the degree to which data quality of electronic health records (EHRs) affected by inequities related to low socioeconomic status (SES), results in differential performance of AI models across SES. This study utilized existing machine learning models for predicting asthma exacerbation in children with asthma. We compared balanced error rate (BER) against different SES levels measured by HOUsing-based SocioEconomic Status measure (HOUSES) index. As a possible mechanism for differential performance, we also compared incompleteness of EHR information relevant to asthma care by SES. Asthmatic children with lower SES had larger BER than those with higher SES (eg, ratio = 1.35 for HOUSES Q1 vs Q2-Q4) and had a higher proportion of missing information relevant to asthma care (eg, 41% vs 24% for missing asthma severity and 12% vs 9.8% for undiagnosed asthma despite meeting asthma criteria). Our study suggests that lower SES is associated with worse predictive model performance. It also highlights the potential role of incomplete EHR data in this differential performance and suggests a way to mitigate this bias. The HOUSES index allows AI researchers to assess bias in predictive model performance by SES. Although our case study was based on a small sample size and a single-site study, the study results highlight a potential strategy for identifying bias by using an innovative SES measure.

An Innovative Individual-Level Socioeconomic Measure Predicts Critical Care Outcomes in Older Adults: A Population-Based Study.

Little is known about the impact of socioeconomic status (SES) as a key element of social determinants of health on intensive care unit (ICU) outcomes for adults. We assessed whether a validated individual SES index termed HOUSES (HOUsing-based SocioEconomic status index) derived from housing features was associated with short-term outcomes of critical illness including ICU mortality, ICU-free days, hospital-free days, and ICU readmission. We performed a population-based cohort study of adult patients living in Olmsted County, Minnesota, admitted to 7 intensive care units at Mayo Clinic from 2011 to 2014. We compared outcomes between the lowest SES group (HOUSES quartile 1 [Q1]) and the higher SES group (HOUSES Q2-4). We stratified the cohort based on age (<50 years old and ≥50 years old). Among 4134 eligible patients, 3378 (82%) patients had SES successfully measured by the HOUSES index. Baseline characteristics, severity of illness, and reason for ICU admission were similar among the different SES groups as measured by HOUSES except for larger number of intoxications and overdoses in younger patients from the lowest SES. In all adult patients, there were no overall differences in mortality, ICU-free days, hospital-free days, or ICU readmissions in patients with higher SES compared to lower SES. Among older patients (>50 years), those with higher SES (HOUSES Q2-4) compared to those with lower SES (HOUSES Q1) had lower mortality rates (hazard ratio = 0.72; 95% CI: 0.56-0.93; adjusted P = .01), increased ICU-free days (mean 1.08 days; 95% CI: 0.34-1.84; adjusted P = .004), and increased hospital-free days (mean 1.20 days; 95% CI: 0.45-1.96; adjusted P = .002). There were no differences in ICU readmission rates (OR = 0.74; 95% CI: 0.55-1.00; P = .051). Individual-level SES may be an important determinant or predictor of critical care outcomes in older adults. Housing-based socioeconomic status may be a useful tool for enhancing critical care research and practice.

The relationship of 25-hydroxyvitamin D concentrations and individual-level socioeconomic status

Socioeconomic status (SES), defined as the ability to access desired resources, is associated with behaviors that may affect vitamin D status. Most studies of the effect of vitamin D status on outcomes do not account for individual-level SES. The ability to adjust for SES in epidemiologic studies, when data on conventional SES measures have not been obtained, would be advantageous. We identified all serum 25(OH)D measurements in adults age 18 years and older residing in Olmsted County, MN, a mixed urban-rural setting, between January 1, 2005 and December 31, 2011, through the Rochester Epidemiology Project. The first 25(OH)D measurement was considered the index measurement for each subject. SES was determined for each subject by the HOUsing-based SocioEconomic Status (HOUSES) index, derived from real property data. The HOUSES index is an aggregated z-score of assessed housing value, area of living space, number of bedrooms, and number of bathrooms, with higher scores indicating higher SES. Multivariable analyses were adjusted for age, BMI, sex, race, season of 25(OH)D measurement, and Charlson comorbidity index. HOUSES was matched for 10,378 of 11,002 subjects (94 %) with 25(OH)D measurements available. The mean (SD) age was 54.3 (17.1) years with 26.9 % ≥65 years; 77.3 % were women, and 12.1 % were non-white. The mean 25(OH)D concentration was 30.0 (12.9) ng/mL, and 598 (5.8 %) had a 25(OH)D value <12 ng/mL. The mean (SD) HOUSES was -1.55 (3.09),-0.97 (3.34), 0.14 (3.52), 0.24 (3.51) for serum 25(OH)D categories of <12, 12–19, 20–50, and >50 ng/mL, respectively (P = 0.12 for trend). 25(OH)D increased by 0.43 (95 % CI 0.36-0.50) ng/mL for each unit increase in HOUSES in univariate analysis and by 0.28 (0.21-0.35; P < 0.001) ng/mL in multivariable analysis. This represents a change of 4 ng/mL across the entire range of observed HOUSES, an effect similar in magnitude to the seasonal variation of 25(OH)D values. SES was independently associated with serum 25(OH)D concentrations in a dose-response manner after adjustment for important covariates. HOUSES is a useful tool to assess the role of individual-level SES in health outcomes when other SES measures are unavailable and to control for confounding by SES in examining the effect of 25(OH)D on clinical and metabolic outcomes.

Housing-Based Socioeconomic Status (HOUSES) Index as a Recruitment Tool for Integrating Under-represented Populations in Clinical Research

While minority children are in general under-represented in clinical research, the role of socioeconomic status (SES) on recruitment for research is poorly understood. This cross-sectional study utilized a large pediatric birth cohort (n=8,196), who participated in a prospective study for childhood asthma between 2016-2017 (n=300). SES was based on the HOUSES index, an individual-level housing-based SES, with a higher HOUSES score indicating a higher SES. HOUSES as a standardized z-score from the entire Olmsted county MN population was assigned to the study cohort. The distribution of the HOUSES index (in quartiles) and race/ethnicity was compared between invited children (IC) and accrued children (AC). We invited 793 eligible children (mean [SD] age: 13.4 years [2.7], 55% males) of which 300 (AC) were enrolled (13.1 years [2.5], 53% males). Compared to the all invited children (IC), those from racial/ethnic minorities were under-represented in the final study cohort (e.g., frequency of Blacks in IC was 6%, while 3% in AC vs. 78% and 81% for Whites), as were low SES families (e.g., 23% in IC vs 21% in AC for HOUSES Q1 vs. 27% vs 31% for Q4). In Caucasian children, a higher HOUSES was associated with a higher participation whereas African American children with lower HOUSES tended to participate in the study. HOUSES may add to race and ethnicity information for predicting research participation in childhood asthma studies. HOUSES could be a useful tool for recruitment planning and community engagement to integrate minority children in clinical research.

Socioeconomic Status, Race/Ethnicity, and Health Disparities in Children and Adolescents in a Mixed Rural-Urban Community—Olmsted County, Minnesota

ObjectiveTo characterize disparities in childhood health outcomes by socioeconomic status (SES) and race/ethnicity in a mixed rural-urban US community. MethodsThis was a retrospective population-based study of children 18 years and younger residing in Olmsted County, Minnesota, in 2009. The prevalence rates of childhood health outcomes were determined using International Classification of Diseases, Ninth Revision codes. Socioeconomic status was measured using the HOUsing-based SocioEconomic Status index (HOUSES), derived from real property data. Adjusting for age and sex, logistic regression models were used to examine the relationships among HOUSES, race/ethnicity, and prevalence of childhood health outcomes considering an interaction between HOUSES and race/ethnicity. Odds ratios were calculated using the lowest SES quartile and non-Hispanic white participants as the reference groups. ResultsOf 31,523 eligible children, 51% were male and 86% were of non-Hispanic white race/ethnicity. Overall, lower SES was associated with higher prevalence of bronchiolitis, urinary tract infection, asthma, mood disorder, and accidents/adverse childhood experiences (physical and sexual abuse) in a dose-response manner (P<.04). Prevalence rates of all childhood conditions considered except for epilepsy were significantly different across races/ethnicities (P<.002). Racial/ethnic disparities for asthma and mood disorder were greater with higher SES. ConclusionSignificant health disparities are present in a predominantly affluent, non-Hispanic white, mixed rural-urban community. Socioeconomic status modifies disparities by race/ethnicity in clinically less overt conditions. Interpretation of future health disparity research should account for the nature of disease.

An Individual Housing-Based Socioeconomic Status Measure Predicts Advance Care Planning and Nursing Home Utilization.

Socioeconomic status (SES) is an important determinant of disparities in health care and may play a role in end-of-life care and decision-making. The SES is difficult to retrospectively abstract from current electronic medical records and data sets. Using a validated SES measuring tool derived from home address, the HOUsing-based SocioEconomic Status index, termed HOUSES we wanted to determine whether SES is associated with differences in end-of-life care and decision-making. This cross-sectional study utilized a cohort of Olmsted County adult residents admitted to 7 intensive care units (ICUs) at Mayo Rochester between June 1, 2011, and May 31, 2014. Multiple variables that reflect decision-making and care at end of life and during critical illness were evaluated, including presence of advance directives and discharge disposition. The SES was measured by individual housing-based SES index (HOUSES index; a composite index derived from real property as a standardized z-score) at the date of admission to the ICU which was then divided into 4 quartiles. The greater HOUSES, the higher SES, outcomes were adjusted for age, 24-hour Acute Physiology and Chronic Health Evaluation III score, sex, race/ethnicity, and insurance. Among the eligible 4134 participants, the addresses of 3393 (82%) were successfully geocoded and formulated into HOUSES. The adjusted odds ratios comparing HOUSES 1 versus 2, 3, and 4 demonstrated lower likelihood of advance directives -0.77(95% CI: 0.63-0.93) and lower likelihood of discharge to home -0.60(95% CI: 1.0.5-0.72). Lower SES, derived from a composite index of housing attributes, was associated with lower rates of advance directives and lower likelihood of discharge to home.

Association between an individual housing-based socioeconomic index and inconsistent self-reporting of health conditions: a prospective cohort study in the Mayo Clinic Biobank

ObjectiveUsing surveys to collect self-reported information on health and disease is commonly used in clinical practice and epidemiological research. However, the inconsistency of self-reported information collected longitudinally in repeated surveys...

Individual housing-based socioeconomic status predicts risk of accidental falls among adults

PurposeAccidental falls are a major public health concern among people of all ages. Little is known about whether an individual-level housing-based socioeconomic status measure is associated with the risk of accidental falls. MethodsAmong 12,286 Mayo Clinic Biobank participants residing in Olmsted County, Minnesota, subjects who experienced accidental falls between the biobank enrollment and September 2014 were identified using ICD-9 codes evaluated at emergency departments. HOUSES (HOUsing-based Index of SocioEconomic Status), a socioeconomic status measure based on individual housing features, was also calculated. Cox regression models were utilized to assess the association of the HOUSES (in quartiles) with accidental fall risk. ResultsSeven hundred eleven (5.8%) participants had at least one emergency room visit due to an accidental fall during the study period. Subjects with higher HOUSES were less likely to experience falls in a dose-response manner (hazard ratio: 0.58; 95% confidence interval: 0.44–0.76 for comparing the highest to the lowest quartile). In addition, the HOUSES was positively associated with better health behaviors, social support, and functional status. ConclusionsThe HOUSES is inversely associated with accidental fall risk requiring emergency care in a dose-response manner. The HOUSES may capture falls-related risk factors through housing features and socioeconomic status-related psychosocial factors.

A new socioeconomic status measure for vaccine research in children using individual housing data: a population-based case-control study.

BackgroundWe recently developed HOUSES, an individual housing-based socioeconomic status (SES) measurement for health disparities research. We assessed whether HOUSES was associated with risk of pertussis and pertussis vaccine up-to-date status in children.MethodsThe study utilized a previous population-based case-control study cohort assembled during the 2004–2005 pertussis outbreak. We collected data on pertussis vaccine status (up-to-date status) at the time of the index date. Using a z-score for housing value, actual square footage, and numbers of bedrooms and bathrooms, HOUSES was formulated in continuous variable and categorized into quartiles. Vaccine up-to-date status was compared among subjects with different SES as measured by HOUSES using a chi-square test and logistic regression models.ResultsOf the 391 eligible pediatric subjects (median age of 13.1 years with male sex of 55 %), 363 (93 %) were successfully geocoded to formulate HOUSES index. HOUSES was not associated with the risk of pertussis (p = 0.82). Pertussis vaccine up-to-date statuses were 79, 86, 83, and 94 % for children in the first (the lowest SES), second, third, and fourth quartiles of HOUSES, respectively (p = 0.03). HOUSES as a continuous variable was associated with pertussis vaccine up-to-date status (adjusted OR: 1.15 per increment of one unit of HOUSES, 95 % CI: 1.04–1.27, p = 0.008).ConclusionWhile HOUSES is not associated with the risk of pertussis, it predicts vaccine up-to-date status among children with different SES. HOUSES may be a useful tool for vaccine delivery research among children.

A novel socioeconomic measure using individual housing data in cardiovascular outcome research.

Background: To assess whether the individual housing-based socioeconomic status (SES) measure termed HOUSES was associated with post-myocardial infarction (MI) mortality. Methods: The study was designed as a population-based cohort study, which compared post-MI mortality among Olmsted County, Minnesota, USA, residents with different SES as measured by HOUSES using Cox proportional hazards models. Subjects’ addresses at index date of MI were geocoded to real property data to formulate HOUSES (a z-score for housing value, square footage, and numbers of bedrooms and bathrooms). Educational levels were used as a comparison for the HOUSES index. Results: 637 of the 696 eligible patients with MI (92%) were successfully geocoded to real property data. Post-MI survival rates were 60% (50–72), 78% (71–85), 72% (60–87), and 87% (81–93) at 2 years for patients in the first (the lowest SES), second, third, and fourth quartiles of HOUSES, respectively (p < 0.001). HOUSES was associated with post-MI all-cause mortality, controlling for all variables except age and comorbidity (p = 0.036) but was not significant after adjusting for age and comorbidity (p = 0.24). Conclusions: Although HOUSES is associated with post-MI mortality, the differential mortality rates by HOUSES were primarily accounted for by age and comorbid conditions. HOUSES may be useful for health disparities research concerning cardiovascular outcomes, especially in overcoming the paucity of conventional SES measures in commonly used datasets.