Relationships between obesity management and depression management in a university-based family medicine center

J Am Assoc Nurse Pract. 2015 May;27(5):256-61. doi: 10.1002/2327-6924.12174. Epub 2014 Sep 13.

Abstract

Purpose: The purpose of this study is to describe and examine relationships among sociodemographics, obesity, and depression management in Appalachian adults.

Data sources: This study was conducted in a primary care center and used a cross-sectional, quantitative, nonexperimental descriptive, and predictive design. Data were obtained from a random sample of 240 adult records that were stratified by gender. Analysis included exploration of all variables for descriptive information followed by bivariate analyses to determine significant relationships between variables, and regression analysis using variables with significant relation to obesity and depression management.

Conclusions: Obesity was prevalent (48%) though less than 1% had documented diagnosis. Over 98% of the 65 participants diagnosed with depression did not have documentation of use of a depression screening tool. Diagnosis of depression correlated significantly with elevated body mass index (BMI) and diagnosis of obesity. Gender bias was evident with males having more documentation of weight-loss discussions and planning, and women receiving more referrals to behavioral health for counseling.

Implications for practice: Innovations to enhance the diagnosis of obesity could lead to consistent provider-led management. Implementation studies of valid depression screening tools in the electronic medical record could enhance the identification of depressive symptoms and could promote health equity.

Keywords: Appalachia; Obesity; depression; primary care; research; screening.

MeSH terms

  • Adult
  • Aged
  • Cross-Sectional Studies
  • Depression / therapy*
  • Disease Management*
  • Electronic Health Records / statistics & numerical data
  • Female
  • Humans
  • Male
  • Middle Aged
  • Obesity / psychology*
  • Obesity / therapy*
  • Prevalence
  • Primary Health Care / methods
  • Statistics as Topic / methods