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Dietary intake during a pragmatic cluster-randomized weight loss trial in an underserved population in primary care

Domaine:

healthcare

Type de record:

paper
Créateur:
ApoMarNewMye
Éditeur:
fig
Hôte:avatar
Abstract Background Currently there are limited data as to whether dietary intake can be improved during pragmatic weight loss interventions in primary care in underserved individuals. Methods Patients with obesity were recruited into the PROPEL trial, which randomized 18 clinics to either an intensive lifestyle intervention (ILI) or usual care (UC). At baseline and months 6, 12, and 24, fruit and vegetable (F/V) intake and fat intake was determined. Outcomes were analyzed by repeated-measures linear mixed-effects multilevel models and regression models, which included random cluster (clinic) effects. Secondary analyses examined the effects of race, sex, age, and food security status. Results A total of 803 patients were recruited. 84.4% were female, 67.2% African American, 26.1% received Medicaid, and 65.5% made less than $40,000. No differences in F/V intake were seen between the ILI and UC groups at months 6, 12, or 24. The ILI group reduced percent fat at months 6, 12, and 24 compared to UC. Change in F/V intake was negatively correlated with weight change at month 6 whereas change in fat intake was positively associated with weight change at months 6, 12, and 24 for the ILI group. Conclusions The pragmatic weight loss intervention in primary care did not increase F/V intake but did reduce fat intake in an underserved population with obesity. F/V intake was negatively associated with weight loss at month 6 whereas percent fat was positively correlated with weight loss throughout the intervention. Future efforts better targeting both increasing F/V intake and reducing fat intake may promote greater weight loss in similar populations. Trial registration NCT Registration: NCT02561221

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doi.orgspringernature.figshare.com

Tags

MedicineBiotechnologySociologyFOS: SociologyImmunologyFOS: Clinical medicineScience PolicyComputational Biology

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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