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A novel housing-based socioeconomic measure predicts hospitalisation and multiple chronic conditions in a community population
  1. Paul Y Takahashi1,
  2. Euijung Ryu2,
  3. Matthew A Hathcock2,
  4. Janet E Olson2,
  5. Suzette J Bielinski2,
  6. James R Cerhan2,
  7. Jennifer Rand-Weaver3,
  8. Young J Juhn4
  1. 1Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
  2. 2Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
  3. 3Olmsted Planning Department, Rochester, Minnesota, USA
  4. 4Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
  1. Correspondence to Dr Paul Y Takahashi, Division of Primary Care Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905,USA; takahashi.paul{at}


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.


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