Living in "Cold Spot" Communities Is Associated with Poor Health and Health Quality

J Am Board Fam Med. 2018 May-Jun;31(3):342-350. doi: 10.3122/jabfm.2018.03.170421.


Purpose: Little is known about incorporating community data into clinical care. This study sought to understand the clinical associations of cold spots (census tracts with worse income, education, and composite deprivation).

Methods: Across 12 practices, we assessed the relationship between cold spots and clinical outcomes (obesity, uncontrolled diabetes, pneumonia vaccination, cancer screening-colon, cervical, and prostate-and aspirin chemoprophylaxis) for 152,962 patients. We geocoded and linked addresses to census tracts and assessed, at the census tract level, the percentage earning less than 200% of the Federal Poverty Level, without high school diplomas, and the social deprivation index (SDI). We labeled those census tracts in the worst quartiles as cold spots and conducted bivariate and logistic regression.

Results: There was a 10-fold difference in the proportion of patients in cold spots between the highest (29.1%) and lowest practices (2.6%). Except for aspirin, all outcomes were influenced by cold spots. Fifteen percent of low-education cold-spot patients had uncontrolled diabetes compared with 13% of noncold-spot patients (P < .05). In regression, those in poverty, low education, and SDI cold spots were less likely to receive colon cancer screening (odds ratio [CI], 0.88 [0.83-0.93], 0.87 [0.82-0.92], and 0.89 [0.83-0.95], respectively) although cold-spot patients were more likely to receive cervical cancer screening.

Conclusion: Living in cold spots is associated with worse chronic conditions and quality for some screening tests. Practices can use neighborhood data to allocate resources and identify those at risk for poor outcomes.

Keywords: Cancer Screening; Censuses; Health Resources; Health Services; Health Status; Logistic Regression; Poverty.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Ambulatory Care / statistics & numerical data*
  • Blood Glucose
  • Chronic Disease / epidemiology
  • Cross-Sectional Studies
  • Diabetes Mellitus / blood
  • Diabetes Mellitus / drug therapy
  • Diabetes Mellitus / epidemiology
  • Early Detection of Cancer / statistics & numerical data
  • Female
  • Health Status Disparities*
  • Humans
  • Male
  • Middle Aged
  • Obesity / epidemiology
  • Pneumonia / prevention & control
  • Primary Health Care / statistics & numerical data*
  • Residence Characteristics / statistics & numerical data*
  • Socioeconomic Factors*
  • Vaccination / statistics & numerical data
  • Virginia / epidemiology
  • Young Adult


  • Blood Glucose