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

BACKGROUND: We 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. METHODS: The 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. RESULTS: Of 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). CONCLUSION: While 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 housing-based socioeconomic measure predicts hospitalisation and multiple chronic conditions in a community population.

BACKGROUND: Socioeconomic status (SES) is an important predictor for outcomes of chronic diseases. However, it is often unavailable in clinical data. We sought to determine whether an individual housing-based SES index termed HOUSES can influence the likelihood of multiple chronic conditions (MCC) and hospitalisation in a community population. METHODS: Participants were residents of Olmsted County, Minnesota, aged >18 years, who were enrolled in Mayo Clinic Biobank on 31 December 2010, with follow-up until 31 December 2011. Primary outcome was all-cause hospitalisation over 1 calendar-year. Secondary outcome was MCC determined through a Minnesota Medical Tiering score. A logistic regression model was used to assess the association of HOUSES with the Minnesota tiering score. With adjustment for age, sex and MCC, the association of HOUSES with hospitalisation risk was tested using the Cox proportional hazards model. RESULTS: Eligible patients totalled 6402 persons (median age, 57 years; 25th-75th quartiles, 45-68 years). The lowest quartile of HOUSES was associated with a higher Minnesota tiering score after adjustment for age and sex (OR (95% CI) 2.4 (2.0 to 3.1)) when compared with the highest HOUSES quartile. Patients in the lowest HOUSES quartile had higher risk of all-cause hospitalisation (age, sex, MCC-adjusted HR (95% CI) 1.53 (1.18 to 1.98)) compared with those in the highest quartile. CONCLUSIONS: Low SES, as assessed by HOUSES, was associated with increased risk of hospitalisation and greater MCC health burden. HOUSES may be a clinically useful surrogate for SES to assess risk stratification for patient care and clinical research.

Role of individual-housing-based socioeconomic status measure in relation to smoking status among late adolescents with asthma.

PURPOSE: We aimed to assess whether smoking status among individuals in late adolescence (19-22 years) with asthma was associated with socioeconomic status (SES) defined by HOUSES, an individual-housing-based SES measure. METHODS: A population-based cross-sectional study was conducted among the 1988-1989 Olmsted County, Minnesota Birth Cohort, with physician-diagnosed asthma and that lived in the community during the study period (November 1, 2008-October 31, 2012). Using a z score for housing value, actual square footage, and numbers of bedrooms and bathrooms, HOUSES was formulated and categorized into quartiles. Smoking status (both current and past smoker) was compared among subjects with different SES as measured by HOUSES using logistic regression, adjusting for age and sex. RESULTS: Among 289 eligible subjects, 287 (99%) were successfully geo-coded to real property data for HOUSES. Of the 257 subjects whose smoke exposure was recorded, 70 (27%) had a history of smoking (either past or current). An inverse association was observed between HOUSES and smoking status after accounting for age, gender, and General Medical Examination status (adjusted OR = 0.39, 95% CI = 0.18-0.87 for comparing highest vs. lowest HOUSES in quartile; overall P = .02). CONCLUSIONS: A significant proportion of individuals with asthma in late adolescence was smokers during the study period, disproportionally affecting those with lower SES.

Ethnicity, Socioeconomic Status, and Health Disparities in a Mixed Rural-Urban US Community-Olmsted County, Minnesota.

OBJECTIVE: To characterize health disparities in common chronic diseases among adults by socioeconomic status (SES) and ethnicity in a mixed rural-urban community of the United States. PATIENTS AND METHODS: We conducted a cross-sectional study to assess the association of the prevalence of the 5 most burdensome chronic diseases in adults with SES and ethnicity and their interaction. The Rochester Epidemiology Project medical records linkage system was used to identify the prevalence of coronary heart disease, asthma, diabetes, hypertension, and mood disorder using International Classification of Diseases, Ninth Revision codes recorded from January 1, 2005, through December 31, 2009, among all adult residents of Olmsted County, Minnesota, on April 1, 2009. For SES measurements, an individual HOUsing-based index of SocioEconomic Status (HOUSES) derived from real property data was used. Logistic regression models were used to examine the association of the prevalence of chronic diseases with ethnicity and HOUSES score and their interaction. RESULTS: We identified 88,010 eligible adults with HOUSES scores available, of whom 48,086 (54.6%) were female and 80,699 (91.7%) were non-Hispanic white; the median (interquartile range) age was 45 years (30-58 years). Overall and in the subgroup of non-Hispanic whites, SES measured by HOUSES was inversely associated with the prevalence of all 5 chronic diseases independent of age, sex, and ethnicity (P<.001). While an association of ethnicity with disease prevalence was observed for all the chronic diseases, SES modified the effect of ethnicity for clinically less overt conditions (interaction P<.05 for each condition [diabetes, hypertension, and mood disorder]) but not for coronary heart disease, a clinically more overt condition. CONCLUSION: In a mixed rural-urban setting with a predominantly non-Hispanic white population, health disparities in chronic diseases still exist across SES. The extent to which SES modifies the effect of ethnicity on the risk of chronic diseases may depend on the nature of the disease.

A novel measure of socioeconomic status using individual housing data to assess the association of SES with rheumatoid arthritis and its mortality: a population-based case-control study.

OBJECTIVES: To assess whether HOUSES (HOUsing-based index of socioeconomic status (SES)) is associated with risk of and mortality after rheumatoid arthritis (RA). DESIGN: We conducted a population-based case-control study which enrolled population-based RA cases and their controls without RA. SETTING: The study was performed in Olmsted County, Minnesota. PARTICIPANTS: Study participants were all residents of Olmsted County, Minnesota, with RA identified using the 1987 American College of Rheumatology criteria for RA from 1 January 1988, to 31 December 2007, using the auspices of the Rochester Epidemiology Project. For each patient with RA, one control was randomly selected from Olmsted County residents of similar age and gender without RA. PRIMARY AND SECONDARY OUTCOME MEASURE: The disease status was RA cases and their matched controls in relation to HOUSES as an exposure. As a secondary aim, post-RA mortality among only RA cases was an outcome event. The associations of SES measured by HOUSES with the study outcomes were assessed using logistic regression and Cox models. HOUSES, as a composite index, was formulated based on a summed z-score for housing value, square footage and number of bedrooms and bathrooms. RESULTS: Of the eligible 604 participants, 418 (69%) were female; the mean age was 56±15.6 years. Lower SES, as measured by HOUSES, was associated with the risk of developing RA (0.5±3.8 for controls vs -0.2±3.1 for RA cases, p=0.003), adjusting for age, gender, calendar year of RA index date, smoking status and BMI. The lowest quartile of HOUSES was significantly associated with increased post-RA mortality compared to higher quartiles of HOUSES (HR 1.74; 95% CI 1.10 to 2.74; p=0.017) in multivariate analysis. CONCLUSIONS: Lower SES, as measured by HOUSES, is associated with increased risk of RA and mortality after RA. HOUSES may be a useful tool for health disparities research concerning rheumatological outcomes when conventional SES measures are unavailable.

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.