Abstract
Introduction: To improve the management of overweight and obesity in the primary care setting, an analysis of patient perceptions of weight status and predictors of weight loss attempts for those with overweight and obesity is needed. Methods: Primary care patients (n=949) across 5 health systems in the Mid-Atlantic region of the U.S. were surveyed in 2015; data analysis was performed in 2018. Survey data was combined with data via the electronic health record to understand patients’ perceptions of weight, factors associated with weight loss efforts, and provider counseling practices. Results: Most participants with overweight or obesity perceived themselves as weighing too much and reported trying to lose weight. Furthermore, most participants with obesity reported receiving advice to lose weight by a provider in the past 12 months. However, less than half of patients with overweight reported receiving advice to lose weight, maintain weight, or develop healthy eating and physical activity patterns from a health professional in the past 12 months. Among participants with overweight and obesity, multivariable logistic regression analysis demonstrated that the perception of being overweight and receiving healthcare advice to lose weight had the highest odds of reporting attempted weight loss (OR=5.5, 95% CI=2.7, 11.2 and OR=3.9, 95% CI=1.9, 7.9, respectively). Conclusions: The findings emphasize the importance of provider attention to weight management counseling and identifies patients with overweight as needing increased attention by providers.
| Original language | English (US) |
|---|---|
| Pages (from-to) | e105-e114 |
| Journal | American journal of preventive medicine |
| Volume | 59 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2020 |
Bibliographical note
Funding Information:REDCap is a secure, web-based application designed to support data capture for research studies, providing an intuitive interface for validated data entry, audit trails for tracking data manipulation and export procedures, automated export procedures for seamless data downloads to common statistical packages, and procedures for importing data from external sources. This work was funded through a Patient-Centered Outcomes Research Institute (PCORI) Award (PCORI CDRN # 1306-04912) for development of the National Patient-Centered Clinical Research Network, known as PCORnet. The views presented in this article are solely the responsibility of the authors and do not necessarily represent the views of PCORI, its Board of Governors or Methodology Committee, or other participants in PCORnet. Additionally, this work was supported in part by the National Center for Advancing Translational Sciences, NIH, through Grant UL1 TR002014. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. All authors contributed to the design of the work. WLB, JMC, SJH, JK, MRL, KMMcT, and NC contributed to the acquisition of the data. SDR analyzed the data. All authors interpreted the data for this work. SJ drafted and revised the manuscript. All other authors provided critical revisions. All authors have approved the manuscript for publication. No financial disclosures were reported by the authors of this paper.
Funding Information:
This work was funded through a Patient-Centered Outcomes Research Institute ( PCORI ) Award (PCORI CDRN # 1306-04912 ) for development of the National Patient-Centered Clinical Research Network, known as PCORnet. The views presented in this article are solely the responsibility of the authors and do not necessarily represent the views of PCORI , its Board of Governors or Methodology Committee, or other participants in PCORnet. Additionally, this work was supported in part by the National Center for Advancing Translational Sciences , NIH , through Grant UL1 TR002014 . The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH .
Publisher Copyright:
© 2020 American Journal of Preventive Medicine
