Application of a novel socioeconomic measure using individual housing data in asthma research: an exploratory study

Sex differences in sociodemographic, clinical, and laboratory variables in childhood asthma: A birth cohort study

BACKGROUND

There are marked sex differences in the prevalence and severity of asthma, both during childhood and adulthood. There is a relative lack of comprehensive studies exploring sexdifferences in pediatric asthma cohorts.

OBJECTIVE

To identify the most relevant sex differences in sociodemographic, clinical, and laboratory variables in a well-characterized large pediatric asthma cohort.

METHODS

We performed a cross-sectional analysis of the Mayo Clinic Olmsted County Birth Cohort. In the full birth cohort, we used a natural language-processing algorithm based on the Predetermined Asthma Criteria for asthma ascertainment. In a stratified random sample of 300 children, we obtained additional pulmonary function tests and laboratory data. We identified the significant sex differences among available sociodemographic, clinical, and laboratory variables.

RESULTS

Boys were more frequently diagnosed with having asthma than girls and were younger at the time of asthma diagnosis. There were no sex differences in relation to socioeconomic status. We identified a male predominance in the presence of a tympanostomy tube and a female predominance in the history of pneumonia. A higher percentage of boys had a forced expiratory volume in 1 second/forced vital capacity ratio less than 0.85. Blood eosinophilia and atopic sensitization were also more common in boys. Finally, boys had higher levels of serum periostin than girls.

CONCLUSION

This study described significant sex differences in a large pediatric asthma cohort. Overall, boys had earlier and more severe asthma than girls. Differences in blood eosinophilia and serum periostin provide insights into possible mechanisms of the sex bias in childhood asthma.

Rural Health Disparities in Allergy, Asthma, and Immunologic Diseases: The Current State and Future Direction for Clinical Care and Research

Rural health disparities are well documented and continue to jeopardize the long-term health and wellness for the millions of individuals who live in rural America. The disparities observed between urban and rural residents encompass numerous morbidity and mortality measures for several chronic diseases and have been referred to as the "rural mortality penalty." Although the unmet health needs of rural communities are widely acknowledged, little is known about rural health disparities in allergies, asthma, and immunologic diseases. Furthermore, the intersection between rural health disparities and social determinants of health has not been fully explored. To achieve a more complete understanding of the factors that perpetuate rural health disparities, greater research efforts followed by improved practice and policy are needed that account for the complex social context within rural communities rather than a general comparison between urban and rural environments or focusing on biomedical factors. Moreover, research efforts must prioritize community inclusion throughout rural areas through meaningful engagement of stakeholders in both clinical care and research. In this review, we examine the scope of health disparities in the rural United States and the impact of social determinants of health. We then detail the current state of rural health disparities in the field of allergy, asthma, and immunology. To close, we offer future considerations to address knowledge gaps and unmet needs for both clinical care and research in addressing rural health disparities.

Paired Indoor and Outdoor Nitrogen Dioxide Associated With Childhood Asthma Outcomes in a Mixed Rural-Urban Setting: A Feasibility Study

INTRODUCTION

Nitrogen dioxide (NO₂) is known to be a trigger for asthma exacerbation. However, little is known about the role of seasonal variation in indoor and outdoor NO₂ levels in childhood asthma in a mixed rural-urban setting of North America.

METHODS

This prospective cohort study, as a feasibility study, included 62 families with children (5-17 years) that had diagnosed persistent asthma residing in Olmsted County, Minnesota. Indoor and outdoor NO₂ concentrations were measured using passive air samples over 2 weeks in winter and 2 weeks in summer. We assessed seasonal variation in NO₂ levels in urban and rural residential areas and the association with asthma control status collected from participants' asthma diaries during the study period.

RESULTS

Outdoor NO₂ levels were lower (median: 2.4 parts per billion (ppb) in summer, 3.9 ppb in winter) than the Environmental Protection Agency (EPA) annual standard (53 ppb). In winter, a higher level of outdoor NO₂ was significantly associated with urban residential living area (P = .014) and lower socioeconomic status (SES) (P = .027). For both seasons, indoor NO₂ was significantly higher (P < .05) in rural versus urban areas and in homes with gas versus electric stoves (P < .05). Asthma control status was not associated with level of indoor or outdoor NO₂ in this cohort.

CONCLUSIONS

NO₂ levels were low in this mixed rural-urban community and not associated with asthma control status in this small feasibility study. Further research with a larger sample size is warranted for defining a lower threshold of NO₂ concentration with health effect on asthma in mixed rural-urban settings.

Diabetic Ketoacidosis in Pregnancy: Clinical Risk Factors, Presentation, and Outcomes

CONTEXT

Diabetic ketoacidosis (DKA) in pregnancy is an obstetric emergency with risk of maternofetal death.

OBJECTIVE

This work aimed to evaluate DKA events in pregnant women admitted to our inpatient obstetric service, and to examine associated clinical risk factors, presentation, and pregnancy outcomes.

METHODS

A retrospective cohort study was conducted at the Mayo Clinic, Rochester, Minnesota, USA, and included women aged 17 to 45 years who were treated for DKA during pregnancy between January 1, 2004 and December 31, 2021. Main outcome measures included maternal and fetal death along with a broad spectrum of maternal and fetal pregnancy outcomes.

RESULTS

A total of 71 DKA events were identified in 58 pregnancies among 51 women, 48 (82.8%) of whom had type 1 diabetes. There were no maternal deaths, but fetal demise occurred in 10 (17.2%) pregnancies (6 miscarriages and 4 stillbirths). Maternal social stressors were frequently present (n = 30, 51.0%), and glycemic control was suboptimal (median first trimester glycated hemoglobin A1c = 9.0%). Preeclampsia was diagnosed in 17 (29.3%) pregnancies. Infants born to women with DKA were large for gestational age (n = 16, 33.3%), suffered from neonatal hypoglycemia (n = 29, 60.4%) and required intensive care unit admission (n = 25, 52.1%).

CONCLUSION

DKA is associated with a high rate of maternofetal morbidity and fetal loss. Prenatal education strategies for women with diabetes mellitus should include a strong focus on DKA prevention, and clinicians and patients should have a high index of suspicion for DKA in all pregnant women who present with symptoms that could be attributed to this condition.

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

OBJECTIVE

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.

MATERIALS AND METHODS

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.

RESULTS

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).

DISCUSSION

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.

CONCLUSION

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.

Risk of pneumonia in asthmatic children using inhaled corticosteroids: a nested case-control study in a birth cohort

BACKGROUND

Inhaled corticosteroids (ICSs) are important in asthma management, but there are concerns regarding associated risk of pneumonia. While studies in asthmatic adults have shown inconsistent results, this risk in asthmatic children is unclear.

OBJECTIVE

Our aim was to determine the association of ICS use with pneumonia risk in asthmatic children.

METHODS

A nested case-control study was performed in the Mayo Clinic Birth Cohort. Asthmatic children (<18 years) with a physician diagnosis of asthma were identified from electronic medical records of children born at Mayo Clinic from 1997 to 2016 and followed until 31 December 2017. Pneumonia cases defined by Infectious Disease Society of America were 1:1 matched with controls without pneumonia by age, sex and asthma index date. Exposure was defined as ICS prescription at least 90 days prior to pneumonia. Associations of ICS use, type and dose (low, medium and high) with pneumonia risk were analysed using conditional logistic regression.

RESULTS

Of the 2108 asthmatic children eligible for the study (70% mild intermittent and 30% persistent asthma), 312 children developed pneumonia during the study period. ICS use overall was not associated with risk of pneumonia (adjusted OR: 0.94, 95% CI: 0.62 to 1.41). Poorly controlled asthma was significantly associated with the risk of pneumonia (OR: 2.03, 95% CI: 1.35 to 3.05; p<0.001). No ICS type or dose was associated with risk of pneumonia.

CONCLUSION

ICS use in asthmatic children was not associated with risk of pneumonia but poorly controlled asthma was. Future asthma studies may need to include pneumonia as a potential outcome of asthma management.

Association of a housing based individual socioeconomic status measure with diabetic control in primary care practices

AIMS

Socioeconomic status (SES) is an important variable that impacts healthcare outcomes. However, grouped SES data is not always representative of all members and it is difficult to obtain individual level data. A validated individual housing-based measure termed HOUSES is available, but has not been studied in diabetes. We hypothesize that patients in the lowest HOUSES quartile are associated with worse diabetic control as measured by the D5.

METHODS

A retrospective cohort study of 5463 patients with diabetes in 5 patient centered medical home practices in southeast Minnesota was conducted. HOUSES is a validated, standardized housing-based SES measure constructed from publicly available county assessor's office data. Diabetic control was assessed by the D5 (HgbA1c < 8, BP < 140/90, statin use, nonsmoking status, and antiplatelet therapy).

RESULTS

In the lowest HOUSES quartile, more patients had an uncontrolled D5 (56.4%) than any of the other quartiles (49.2%, 49.8%, 49.6% respectively, p < 0.001). A multivariate analysis shows the adjusted odds of D5 control for patients in the 2nd, 3rd or 4th HOUSES quartiles as opposed to the 1st quartile are 1.28, 1.21, and 1.20, respectively.

CONCLUSION

Lower SES as represented by the first quartile of HOUSES index, is associated with lower odds of D5 control and thus worse diabetic outcomes. Using the HOUSES index to identify these individuals in a patient centered medical home might prove useful in deciding where to focus diabetic control efforts.

Miller N, L. Pecina J, D. Decker M, I. Wi C, Garrison GM. Association of Early and Late Hospital Readmissions with a Novel Housing-Based Socioeconomic Measure

Background

While socioeconomic status has been linked to hospital readmissions for several conditions, reliable measures of individual socioeconomic status are often not available. HOUSES, a new measure of individual socioeconomic status based upon objective public data about one's housing unit, is inversely associated with overall hospitalization rate but it has not been studied with respect to readmissions.

Purpose

To determine if patients in the lowest HOUSES quartile are more likely to be readmitted within 30 days (short-term) and 180 days (long-term).

Methods

A retrospective cohort study of 11 993 patients having 21 633 admissions was conducted using generalized linear mixed-effects models.

Results

HOUSES quartile did not show any significant association with early readmission. However, when compared to the lowest HOUSES quartile, the second quartile (OR = 0.90, 95%CI 0.83-0.98) and the third quartile (OR = 0.91, 95%CI 0.83-0.99) were associated with lower odds of late readmission while the highest quartile (OR = 0.91, 95%CI 0.82-1.01) was not statistically different.

Conclusion

HOUSES was associated with late readmission, but not early readmission. This may be because early readmissions are influenced by medical conditions and hospital care while late readmissions are influenced by ambulatory care and home-based factors. Since HOUSES relies on public county assessor data, it is generally available and may be used to focus interventions on those at highest risk for late readmission.

Role of Geographic Risk Factors and Social Determinants of Health in COVID-19 Epidemiology: Longitudinal Geospatial Analysis in a Midwest Rural Region

Background:

Studies examining the role of geographic factors in coronavirus disease-2019 (COVID-19) epidemiology among rural populations are lacking.

Methods:

Our study is a population-based longitudinal study based on rural residents in four southeast Minnesota counties from March through October 2020. We used a kernel density estimation approach to identify hotspots for COVID-19 cases. Temporal trends of cases and testing were examined by generating a series of hotspot maps during the study period. Household/individual-level socioeconomic status (SES) was measured using the HOUSES index and examined for association between identified hotspots and SES.

Results:

During the study period, 24,243 of 90,975 residents (26.6%) were tested for COVID-19 at least once; 1498 (6.2%) of these tested positive. Compared to other rural residents, hotspot residents were overall younger (median age: 40.5 vs 43.2), more likely to be minorities (10.7% vs 9.7%), and of higher SES (lowest HOUSES [SES] quadrant: 14.6% vs 18.7%). Hotspots accounted for 30.1% of cases (14.5% of population) for rural cities and 60.8% of cases (27.1% of population) for townships. Lower SES and minority households were primarily affected early in the pandemic and higher SES and non-minority households affected later.

Conclusion:

In rural areas of these four counties in Minnesota, geographic factors (hotspots) play a significant role in the overall burden of COVID-19 with associated racial/ethnic and SES disparities, of which pattern differed by the timing of the pandemic (earlier in pandemic vs later). The study results could more precisely guide community outreach efforts (e.g., public health education, testing/tracing, and vaccine roll out) to those residing in hotspots.

Impact of socioeconomic status on depression clinical outcomes at six months in a Midwestern, United States community

INTRODUCTION

Lower socioeconomic status (SES) has been associated with poor healthcare outcomes in depression. However, reliable individual-level SES data rarely exists for clinical research. The HOUSES index relies on publicly available data allowing for evaluation of individual-level SES on patient outcomes.

HYPOTHESIS

Primary care patients with depression within the lower SES quartile (Quartile 1 vs. Quartile 4, of the HOUSES index) would experience worse clinical outcomes of their symptoms six months after diagnosis.

STUDY DESIGN

A retrospective cohort study which followed 4313 adult primary care patients that were diagnosed with depression during the study period of 2008-2015. The outcome measures were the six month PHQ-9 scores.

RESULTS

At six months, a higher HOUSES quartile was associated with greater odds of remission of depressive symptoms (RDS) and lower odds of persistent depressive symptoms (PDS), after controlling for covariates. Patients in Quartile 4 had 27% more likelihood of RDS and a 24% lower likelihood of PDS at six months compared to a Quartile 1 patient.

LIMITATIONS

As a retrospective study only can observe associations but not causation. Only one institution participated and not all treatments were readily available, limiting the generalizability of these findings.

CONCLUSIONS

Lower SES as demonstrated by a lower HOUSES quartile (Quartile 1 versus 4) was associated with lower odds of RDS and increased odds of PDS at six months. HOUSES index is a useful tool for identifying patients at risk for worse clinical outcomes and may help health care systems plan resource allocation for depression care.

Role of Geographic Risk Factors in COVID-19 Epidemiology: Longitudinal Geospatial Analysis

Objective

To perform a geospatial and temporal trend analysis for coronavirus disease 2019 (COVID-19) in a Midwest community to identify and characterize hot spots for COVID-19.

Participants and Methods

We conducted a population-based longitudinal surveillance assessing the semimonthly geospatial trends of the prevalence of test confirmed COVID-19 cases in Olmsted County, Minnesota, from March 11, 2020, through October 31, 2020. As urban areas accounted for 84% of the population and 86% of all COVID-19 cases in Olmsted County, MN, we determined hot spots for COVID-19 in urban areas (Rochester and other small cities) of Olmsted County, MN, during the study period by using kernel density analysis with a half-mile bandwidth.

Results

As of October 31, 2020, a total of 37,141 individuals (30%) were tested at least once, of whom 2433 (7%) tested positive. Testing rates among race groups were similar: 29% (black), 30% (Hispanic), 25% (Asian), and 31% (white). Ten urban hot spots accounted for 590 cases at 220 addresses (2.68 cases per address) as compared with 1843 cases at 1292 addresses in areas outside hot spots (1.43 cases per address). Overall, 12% of the population residing in hot spots accounted for 24% of all COVID-19 cases. Hot spots were concentrated in neighborhoods with low-income apartments and mobile home communities. People living in hot spots tended to be minorities and from a lower socioeconomic background.

Conclusion

Geographic and residential risk factors might considerably account for the overall burden of COVID-19 and its associated racial/ethnic and socioeconomic disparities. Results could geospatially guide community outreach efforts (eg, testing/tracing and vaccine rollout) for populations at risk for COVID-19.

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

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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).

RESULTS

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).

CONCLUSION

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.

HOUSES Index as an Innovative Socioeconomic Measure Predicts Graft Failure Among Kidney Transplant Recipients

BACKGROUND

Despite extensive evaluation processes to determine candidacy for kidney transplantation, variability in graft failure exists. The role of patient socioeconomic status (SES) in transplantation outcomes is poorly understood because of limitations of conventional SES measures.

METHODS

This population-based retrospective cohort study assessed whether a validated objective and individual-level housing-based SES index (HOUSES) would serve as a predictive tool for graft failure in patients (n = 181) who received a kidney transplant in Olmsted County, MN (January 1, 1998 to December 8, 2016). Associations were assessed between HOUSES (quartiles: Q1 [lowest] to Q4 [highest]) and graft failure until last follow-up date (December 31, 2016) using Cox proportional hazards. The mean age (SD) was 46.1 (17.2) years, 109 (60.2%) were male, 113 (62.4%) received a living kidney donor transplant, and 40 (22.1%) had a graft failure event.

RESULTS

Compared with Q1, patients with higher HOUSES (Q2-Q4) had significantly lower graft failure rates (adjusted hazard ratio, 0.47; 95% confidence interval, 0.24-0.92; P < 0.029), controlling for age, sex, race, previous kidney transplantation, and donor type.

CONCLUSIONS

Although criteria for kidney transplant recipients are selective, patients with higher HOUSES had lower graft failure rates. Thus, HOUSES may enable transplantation programs to identify a target group for improving kidney transplantation outcomes.

An innovative housing-related measure for individual socioeconomic status and human papillomavirus vaccination coverage: A population-based cross-sectional study

BACKGROUND

Human papillomavirus (HPV) is a known cause of anogenital (eg, cervical) and oropharyngeal cancers. Despite availability of effective HPV vaccines, US vaccination-completion rates remain low. Evidence is conflicting regarding the association of socioeconomic status (SES) and HPV vaccination rates. We assessed the association between SES, defined by an individual validated Housing-based Index of Socioeconomic Status (HOUSES), and HPV vaccination status.

METHODS

We conducted a cross-sectional study of children/adolescents 9-17 years as of December 31, 2016, living in southeastern Minnesota by using a health-record linkage system to identify study-eligible children/adolescents, vaccination dates, and home addresses matched to HOUSES data. We analyzed the relationship between HPV vaccination status and HOUSES using multivariable Poisson regression models stratifying by age, sex, race, ethnicity, and county.

RESULTS

Of 20,087 study-eligible children/adolescents, 19,363 (96.4%) were geocoded and HOUSES measures determined. In this cohort, 57.9% did not receive HPV vaccination, 15.8% initiated (only), and 26.3% completed the series. HPV vaccination-initiation and completion rates increased over higher SES HOUSES quartiles (P < .001). Rates of HPV vaccination initiation versus unvaccinated increased across HOUSES quartiles in multivariable analysis adjusted for age, sex, race, ethnicity, and county (1st quartile, referent; 2nd quartile, 0.97 [0.87-1.09]; 3rd quartile, 1.05 [0.94-1.17]; 4th quartile, 1.15 [1.03-1.28]; test for trend, P = .002). HOUSES was a stronger predictor of HPV vaccination completion versus unvaccinated (1st quartile referent; 2nd quartile, 1.06 [0.96-1.16]; 3rd quartile, 1.12 [1.03-1.23]; 4th quartile, 1.32 [1.21-1.44]; test for trend, P < .001). Significant interactions were shown for HPV vaccination initiation by HOUSES for sex (P = .009) and age (P = .006).

CONCLUSION

The study showed disparities in HPV vaccination by SES, with the highest HOUSES quartiles associated with increased rates of initiating and even greater likelihood of completing the series. HOUSES data may be used to target and tailor HPV vaccination interventions to undervaccinated populations.

Mobile home residence as a risk factor for adverse events among children in a mixed rural-urban community: A case for geospatial analysis

Background:

Given the significant health effects, we assessed geospatial patterns of adverse events (AEs), defined as physical or sexual abuse and accidents or poisonings at home, among children in a mixed rural–urban community.

Methods:

We conducted a population-based cohort study of children (<18 years) living in Olmsted County, Minnesota, to assess geographic patterns of AEs between April 2004 and March 2009 using International Classification of Diseases, Ninth Revision codes. We identified hotspots by calculating the relative difference between observed and expected case densities accounting for population characteristics (; hotspot ≥ 0.33) using kernel density methods. A Bayesian geospatial logistic regression model was used to test for association of subject characteristics (including residential features) with AEs, adjusting for age, sex, and socioeconomic status (SES).

Results:

Of the 30,227 eligible children (<18 years), 974 (3.2%) experienced at least one AE. Of the nine total hotspots identified, five were mobile home communities (MHCs). Among non-Hispanic White children (85% of total children), those living in MHCs had higher AE prevalence compared to those outside MHCs, independent of SES (mean posterior odds ratio: 1.80; 95% credible interval: 1.22–2.54). MHC residency in minority children was not associated with higher prevalence of AEs. Of addresses requiring manual correction, 85.5% belonged to mobile homes.

Conclusions:

MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural–urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.

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.

Agreement between area- and individual-level income measures in a population-based cohort: Implications for population health research

Socioeconomic status is an important determinant of health, the measurement of which is of great significance to population health research. However, individual-level socioeconomic factors are absent from much health administrative data, resulting in widespread use of area-level measures in their place. This study aims to clarify the role of individual- and area-level socioeconomic status in Ontario, Canada, through comparison of income measures.

Using data from four cycles (2005–2012) of the Canadian Community Health Survey, we assessed concordance between individual- and area-level income quintiles using percent agreement and Kappa statistics. Individual-level characteristics were compared at baseline. Cumulative adult premature mortality was calculated for 5-years following interview. Rates were calculated separately for area-level and individual-level income, and jointly for each combination of income groups. Multivariable negative binomial models were fit to estimate associations between area- and individual-level income quintile and premature mortality after adjustment for basic demographics (age, sex, interview cycle) and key risk factors (alcohol, smoking, physical activity, and body mass index).

Agreement between individual- and area-level income measures was low. Kappa statistics for same and similar (i.e. ±1 quintile) measures were 0.11 and 0.48, indicating low and moderate agreement, respectively. Socioeconomic disparities in premature mortality were greater for individual-level income than area-level income. When rates were stratified by both area- and individual-level income quintiles simultaneously, individual-level income gradients persisted within each area-level income group. The association between income and premature mortality was significant for both measures, including after full adjustment.

Area-level socioeconomic status is an inappropriate proxy for missing individual-level data. The low agreement between area- and individual-level income measures and differences in demographic profile indicate that the two socioeconomic status measures do not capture the same population groups. However, our findings demonstrate that both individual- and area-level income measures are associated with premature mortality, and describe unique socioeconomic inequities.

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Area- and individual-level income measures may not capture the same groups.

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Area-level socioeconomic status is not a valid proxy for individual-level data.

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Area- and individual-level income are independently meaningful for health outcomes.

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Measures can be used together to fully contextualize socioeconomic status.

Long-term incidence of glioma in Olmsted County, Minnesota, and disparities in postglioma survival rate: a population-based study

Background

We assessed glioma incidence and disparities in postglioma survival rate in the Olmsted County, Minnesota, population.

Methods

This population-based study assessed the incidence of pathologically confirmed primary gliomas between January 1, 1995, and December 31, 2014. Age- and sex-adjusted incidence rates per 100 000 person-years were calculated and standardized to the US white 2010 population. We compared incidence trends of glioma during our study period with previously published Olmsted County data from 1950 to 1990. We assessed postglioma survival rates among individuals with different socioeconomic status (SES), which was measured by a validated individual HOUsing-based SES index (HOUSES).

Results

We identified 135 incident glioma cases (93% white) with 20 pediatric (50% female) and 115 adult cases (44% female). Overall incidence rate during our study period, 5.51 per 100 000 person-years (95% CI: 4.56-6.46), showed no significant changes and was similar to that seen in 1950 to 1990, 5.5 per 100 000 person-years. The incidence of pediatric (age < 20 years) glioma was 2.49 (95% CI: 1.40-3.58), whereas adult glioma incidence was 6.47 (95% CI: 5.26-7.67). Among those with grade II to IV gliomas, individuals with lower SES (< median HOUSES) had significantly lower 5-year survival rates compared to those with higher SES, adjusted hazard ratio 1.61 (95% CI: 1.01-2.85).

Conclusion

In a well-defined North American population, long-term glioma incidence appears stable since 1950. Significant socioeconomic disparities exist for postglioma survival.

Prenatal socioeconomic status and social support are associated with neonatal brain morphology, toddler language and psychiatric symptoms

Few studies have assessed the association of parental socioeconomic status (SES) with brain measures in neonates, at a time when exposure to the postnatal environment is minimal. Social support may buffer the adverse consequences of SES, and has been associated with better cognitive - emotional development in children. We studied the association of prenatal SES and social support with neonatal brain structure, and toddler cognition, and psychiatric symptoms. In a sample of 37 healthy neonates, we correlated a measure of SES and marital/partner status (an index of social support) with morphological features of the cerebral surface measured on high-resolution MRI scans between the 1^st - 6^th weeks of postnatal life. We then assessed how SES relates to cognitive and behavioral outcomes at age 24-months. We found that neonates born to mothers with lower SES had greater local volumes at the surface of the right occipital lobe, left temporal pole, and left inferior frontal and anterior cingulate regions. Partner status moderated the associations of SES on neonatal brain morphology. Lower SES was associated with poorer language scores and less severe ADHD and ODD symptoms. In summary, SES was associated with neonatal brain structure and language and behavioral outcomes at toddler age. Future studies with a greater sample size and longitudinal MRI scans will help to determine whether prenatal SES continues to relate to early brain development in the same or different brain regions.

Epidemiology of Children With Multiple Complex Chronic Conditions in a Mixed Urban-Rural US Community

OBJECTIVES

Children with multiple complex chronic conditions (MCCs) represent a small fraction of our communities but a disproportionate amount of health care cost and mortality. Because the temporal trends of children with MCCs within a geographically well-defined US pediatric population has not been previously assessed, health care planning and policy for this vulnerable population is limited.

METHODS

In this population-based, repeated cross-sectional study, we identified and enrolled all eligible children residing in Olmsted County, Minnesota, through the Rochester Epidemiology Project, a medical record linkage system of Olmsted County residents. The pediatric complex chronic conditions classification system version 2 was used to identify children with MCCs. Five-year period prevalence and incidence rates were calculated during the study period (1999-2014) and characterized by age, sex, ethnicity, and socioeconomic status (SES) by using the housing-based index of socioeconomic status, a validated individual housing-based SES index. Age-, sex-, and ethnicity-adjusted prevalence and incidence rates were calculated, adjusting to the 2010 US total pediatric population.

RESULTS

Five-year prevalence and incidence rates of children with MCCs in Olmsted County increased from 1200 to 1938 per 100 000 persons and from 256 to 335 per 100 000 person-years, respectively, during the study period. MCCs tend to be slightly more prevalent among children with a lower SES and with a racial minority background.

CONCLUSIONS

Both 5-year prevalence and incidence rates of children with MCCs have significantly increased over time, and health disparities are present among these children. The clinical and financial outcomes of children with MCCs need to be assessed for formulating suitable health care planning given limited resources.

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

OBJECTIVE

To characterize disparities in childhood health outcomes by socioeconomic status (SES) and race/ethnicity in a mixed rural-urban US community.

METHODS

This 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.

RESULTS

Of 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.

CONCLUSION

Significant 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.

The Use of Geographic Data to Improve Asthma Care Delivery and Population Health

The authors examine uses of geographic data to improve asthma care delivery and population health and describe potential practice changes and areas for future research.

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

BACKGROUND:

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.

OBJECTIVE:

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.

DESIGN/SETTING/PARTICIPANTS:

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.

MEASUREMENTS:

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.

RESULTS:

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).

CONCLUSION:

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.

Urinary incontinence and sleep complaints in community dwelling older adults

Sleep disorder is associated with poor quality of life in old age. Therefore, it is imperative to identify contributing factors leading to sleep disorder. The current study aimed to examine the impact of urinary incontinence on sleep complaint after controlling for potential sociodemographic and health covariates. Materials and Methods: A cross-sectional study was conducted on a sample of 184 community dwelling older adults 60 years and older in Yazd, Iran, 2016. In order to obtain the sample a multistage proportional random sampling technique was employed. Sociodemographic characteristics, sleep complaint, and urinary incontinence were collected from medical records. Statistical analyses were performed using SPSS version 24. A multiple logistic regression analysis was used to examine the impact of urinary incontinence on sleep complaint after controlling for potential covariates. Findings: A total of 184 respondents with a mean age of 68.48±6.65 years (age range, 60-87 years) were included in the study. About 70% of the respondents were women, 72.8% were married, 68.5% were not formally educated, and 21.7% were living alone. The prevalence of sleep complaint and urinary incontinence were 27.2% (95% CI: 21-34) and 22.3% (95% CI: 17-29), respectively. The results of the multiple logistic regression analysis revealed respondents with urinary incontinence were four times more likely to suffer from sleep complaint than those without urinary incontinence after adjusting for potential covariates (AOR=4.04, 95% CI: 1.74-9.35, p<0.001). Conclusion: Based on the results of this present study, which showed that urinary incontinence independently contributed to sleep complaint among older adults, it is necessary to employ effective interventions for controlling urinary incontinence to reduce sleep complaints.

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

PURPOSE

Accidental 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.

METHODS

Among 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.

RESULTS

Seven 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.

CONCLUSIONS

The 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.

Asthma exacerbations and traffic: examining relationships using link-based traffic metrics and a comprehensive patient database

BACKGROUND

The Rochester Epidemiology Project (REP) is a unique community-based medical record data linkage system that provides individual patient address, diagnosis and visit information for all hospitalizations, as well as emergency department, urgent care and outpatient clinic visits for asthma. Proximity to traffic is known to be associated with asthma exacerbations and severity. Our null hypothesis was that there is no association between residential proximity to traffic and asthma exacerbations over eleven years of REP data.

METHODS

Spatial coordinates of the homes of 19,915 individuals diagnosed with asthma were extracted from the REP database. Three metrics of traffic exposure at residences were calculated from link-based traffic count data. We used exploratory statistics as well as logistic and Poisson regression to examine associations between three traffic metrics at the home address and asthma exacerbations.

RESULTS

Asthma exacerbations increased as traffic levels near the home increased. Proximity to traffic was a significant predictor of asthma exacerbations in logistic and Poisson regressions controlling for age, gender and block group poverty.

CONCLUSIONS

Over eleven years in a comprehensive county-wide data set of asthma patients, and after controlling for demographic effects, we found evidence that living in proximity to traffic increased the risk of asthma exacerbations.

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.

Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study

OBJECTIVES

Socioeconomic status (SES) is a well-established risk factor for many health outcomes. Recently, we developed an SES measure based on 4 housing-related characteristics (termed HOUSES) and demonstrated its ability to assess health disparities. In this study, we aimed to evaluate whether fewer housing-related characteristics could be used to provide a similar representation of SES.

STUDY SETTING AND PARTICIPANTS

We performed a cross-sectional study using parents/guardians of children aged 1-17 years from 2 US Midwestern counties (n=728 in Olmsted County, Minnesota, and n=701 in Jackson County, Missouri).

PRIMARY AND SECONDARY OUTCOME MEASURES

For each participant, housing-related characteristics used in the formulation of HOUSES (assessed housing value, square footage, number of bedrooms and number of bathrooms) were obtained from the local government assessor's offices, and additional SES measures and health outcomes with known associations to SES (obesity, low birth weight and smoking exposure) were collected from a telephone survey. Housing characteristics with the greatest contribution for predicting the health outcomes were added to formulate a modified HOUSES index.

RESULTS

Among the 4 housing characteristics used in the original HOUSES, the strongest contributions for predicting health outcomes were observed from assessed housing value and square footage (combined contribution ranged between 89% and 96%). Based on this observation, these 2 were used to calculate a modified HOUSES index. Correlation between modified HOUSES and other SES measures was comparable to the original HOUSES for both locations. Consistent with the original HOUSES formula, the strongest association with modified HOUSES was observed with smoking exposure (OR=0.24 with 95% CI 0.11 to 0.49 for comparing participants in highest HOUSES vs lowest group; overall p<0.001).

CONCLUSIONS

The modified HOUSES requires only 2 readily available housing characteristics thereby improving the feasibility of using this index as a proxy for SES in multiple communities, especially in the US Midwestern region.

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 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.

Usefulness of a home affluence scale administered to urban adolescents with asthma to estimate the family's socioeconomic status

PURPOSE

Measurement of socioeconomic status (SES) is traditionally based on education, income, and occupation. This information may not be readily available from adolescents participating in research.

METHODS

Using data from school-based randomized trial of an asthma intervention targeting urban adolescents, we compared percent poverty in zip code of residence (% poverty), median housing value, and parental income and education, to teen responses on the Home Affluence Scale for Children (HASC), which included home, car, and computer ownership for the family and eligibility for free school lunch. The association of HASC with measures of asthma control was also assessed.

RESULTS

Of 422 adolescents, 390 (92%) responded to HASC items (mean HASC = 2.5). HASC was associated with mother's education and household income (both P < .001), and significantly correlated with % poverty (P < .0001) and median home value (P = .003). The association of HASC <2.0 to indicators of uncontrolled asthma was in the direction hypothesized, especially for nighttime symptoms, odds ratio (95% confidence interval) = 1.59 (0.95-2.66) and restricted activity, odds ratio = 1.87 (1.12-3.12).

CONCLUSIONS

HASC correlates well with more traditional measures of SES, and the risk estimates for HASC less than 2.0 and indicators of uncontrolled asthma were mostly in the hypothesized direction. Methods of obtaining SES indicators from youth are needed for research studies.

Sauver JL. Health Care Utilization by Body Mass Index in a Pediatric Population

OBJECTIVE

We tested the hypothesis that the frequency of emergency department (ED) visits, outpatient clinic visits, and hospitalizations were higher among children with higher body mass index (BMI) categories, even after controlling for demographics, socioeconomic status, and presence of other chronic medical conditions.

METHODS

We obtained electronic height, weight, and utilization data for all residents of Olmsted County, Minnesota, aged 2 to 18 years on January 1, 2005 (n = 34,335), and calculated baseline BMI (kg/m(2)). At least 1 BMI measurement and permission to use medical record information was available for 19,771 children (58%); 19,528 with follow-up comprised the final cohort. BMIs were categorized into underweight/healthy weight (<85th percentile), overweight (85th to <95th percentile), and obese (≥95th percentile). Negative binomial models were used to compare the rate of utilization across BMI categories. Multivariable models were used to adjust for the effects of age, race, sex, socioeconomic status, and chronic medical conditions.

RESULTS

Compared to children with BMI <85th percentile, overweight and obese status were associated with increased ED visits (adjusted incident rate ratio [IRR] 1.16, 95% confidence interval [CI] 1.10, 1.23; and IRR 1.27, 95% CI 1.19, 1.35, respectively; P for trend <.0001), and outpatient clinic visits (IRR 1.05, 95% CI 1.02, 1.08; and IRR 1.07, 95% CI 1.04, 1.11, respectively; P for trend <.0001). No associations were observed between baseline BMI category and hospitalizations in the adjusted analyses.

CONCLUSIONS

Children who are overweight or obese utilize the ED and outpatient clinics more frequently than those who are underweight/healthy weight, but are not hospitalized more frequently.

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.