Evidence map›Paper›PMID 30125001›Full record

Trial reportMilitary medicine2019

Characteristics Associated With Participation in a Behavioral Weight Loss Randomized Control Trial in the U.S. Military.

Margaret C Fahey, Marion E Hare, Gerald W Talcott, Mehmet Kocak, Ann Hryshko-Mullen, Robert C Klesges, Rebecca A Krukowski

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Military medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. A Postpartum Weight Loss-focused Stepped-care Intervention in a Military Population: A Randomized Controlled Trial.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Margaret C FaheyDepartment of Psychology, University of Memphis, 400 Innovation Drive Memphis, TN.
Marion E HareDepartment of Preventive Medicine, University of Tennessee Health Science Center, 66 N Pauline Street Memphis, TN.
Gerald W TalcottUniversity of Tennessee Health Science Center, Fit Blue Study Wilford Hall Ambulatory Surgical Center, 2200 Bergquist Dr., Ste. 1 Lackland AFB, TX.
Mehmet KocakDepartment of Preventive Medicine, University of Tennessee Health Science Center, 66 N Pauline Street Memphis, TN.
Ann Hryshko-MullenDefense Institute for Medical Operations, Joint Base San Antonio-Lackland Air Force Base, 1320 Truemper Road, San Antonio, TX.
Robert C KlesgesDepartment of Preventive Medicine, University of Tennessee Health Science Center, 66 N Pauline Street Memphis, TN.
Rebecca A KrukowskiDepartment of Preventive Medicine, University of Tennessee Health Science Center, 66 N Pauline Street Memphis, TN.
University of Tennessee Health Science Center · USWilford Hall Medical Center · USUniversity of Memphis · USUniversity of Virginia · US

Funding

Dissemination of the Look Ahead Weight Management Treatment in the MilitaryR01DK097158 · NIDDK · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI KRUKOWSKI, REBECCA A. · 2012 to 2016
$2.9M
NIDDK NIH HHS R01 DK097158
6 · The paper itself

Abstract

introductionEffective recruitment and subsequent enrollment of diverse populations is often a challenge in randomized controlled trials, especially those focused on weight loss. In the civilian literature, individuals identified as racial and ethnic minorities, men, and younger and older adults are poorly represented in weight loss interventions. There are limited weight loss trials within military populations, and to our knowledge, none reported participant characteristics associated with enrollment. There may be unique motives and barriers for active duty personnel for enrollment in weight management trials. Given substantial costs and consequences of overweight and obesity in the U.S. military, identifying predictors and limitations to diverse enrollment can inform future interventions within this population. The study aims to describe the recruitment, screening, and enrollment process of a military weight loss intervention. Demographic and lifestyle characteristics of military personnel lost between screening and randomization are compared to characteristics of personnel randomized in the study and characteristics of the Air Force in general. MATERIALS AND

methodsThe Fit Blue study, a randomized controlled behavioral weight loss trial for active duty personnel, was approved by the Institutional Review Board of the Wilford Hall Ambulatory Surgical Center in San Antonio, TX, USA and acknowledged by the Institutional Review Board at the University of Tennessee Health Science Center. Logistic regressions compared participant demographics, anthropometric data, and health behaviors between personnel that attended a screening visit but were not randomized and those randomized. Multivariable models were constructed for the likelihood of being randomized using a liberal entry and stay criteria of 0.10 for the p-values in a stepwise variable selection algorithm. Descriptive statistics compared the randomized Fit Blue cohort demographics to those of the U.S. Air Force.

resultsIn univariate analyses, older age (p < 0.02), having a college degree or higher (p < 0.007) and higher military rank (p < 0.02) were associated with completing the randomization process. The randomized cohort reported a lower percentage of total daily kilocalories for fat compared to the non-randomized cohort (p = 0.033). The non-randomized cohort reported more total minutes and intensity of physical activity (p = 0.073). In the multivariate model, only those with a college degree or higher were 3.2 times more likely to go onto randomization. (OR = 3.2, 95% CI = 2.0, 5.6, p < 0.0001). The Fit Blue study included a higher representation of personnel who identified as African American (19.4% versus 15.0%) and Hispanic/Latino (22.7% versus 14.3%) compared with the U.S. Air Force in general; however, men were underrepresented (49.4% versus 80.0%). TABLE I.Comparisons of Demographic Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized CohortFit Blue Randomized Participants (N = 248)Non-Randomized Cohort (N = 111)All Screened Participants (N = 359)p-ValueSex N (%)0.73 Male122 (49.2)52 (46.8)174 (48.5) Female126 (50.8)59 (53.2)183 (51.5)Age Mean (±SD) years34 (±7.5)32 (±6.7)33 (±7.3)0.02Race N (%)0.89 African American49 (19.8)22 (19.8)71 (19.8) Caucasian163 (65.7)75 (67.6)238 (66.3) Other36 (14.5)14 (12.2)50 (13.9)Ethnicity N (%)0.59 Hispanic/Latino56 (22.6)28 (25.2)84 (23.4) Non-Hispanic/Latino192 (77.4)83 (74.8)275 (76.6)Education N (%)<0.0001 Less than college degree123 (49.6)82 (73.9)205 (57.1) College degree or greater125 (50.4)29 (26.1)154 (42.9)Marital status N (%)0.83 Single/never married40 (16.1)20 (18)60 (16.7) Married/living as married169 (68.1)72 (64.9)241 (67.1) Separated/divorced39 (15.7)19 (17.1)58 (16.2)Number of additional adults in household N (%)0.82 046 (18.5)22 (19.8)68 (18.9) 1162 (65.3)73 (65.8)235 (65.5) 231 (12.5)14 (12.6)45 (12.5) 3 or more9 (3.6)2 (1.8)11 (3.1)Number of children in household N (%)0.56 091 (36.7)37 (33.3)128 (35.7) 159 (23.8)23 (20.7)82 (22.8) 257 (23)26 (23.4)83 (23.1) 3 or more41 (16.5)25 (22.5)66 (18.4)Years in service mean (± SD)12 (±6.6)11 (±6.1)12 (±6.4)0.20Military gradeaN (%)0.02 E1-E434 (13.7)19 (17.1)53 (14.8) E5-E6105 (42.3)58 (52.3)163 (45.4) E7-E952 (21)21 (18.9)73 (20.3) O1-O317 (6.9)9 (8.1)26 (7.2) O4-O639 (15.7)4 (3.6)43 (12)Branch0.68 Army4 (1.6)1 (0.9)5 (1.4) Air Force234 (94.4)105 (94.6)339 (94.4) Navy8 (3.2)5 (4.5)13 (3.6) Marine Corp2 (0.8)0 (0.0)2 (0.6)BMI (m2/kg) N (%)30.6 (±2.7)30.4 (±2.9)30.6 (±2.8)BMI category N (%)0.76 Overweight115 (46.4)52 (48.1)167 (46.9) Obese133 (53.6)56 (51.9)189 (53.1)aMilitary ranking; Enlisted (E) categories: E1-E4 (enlisted), E5-E6 (non-commissioned officers), E7-E9 (senior non-commissioned officers) and two Officer categories (O): O1-O3 (Company Grade Officer) and O4-O6 (Field Grade Officer); standard deviation (SD).Table II.Comparisons of Anthropometric Characteristics of Randomized Fit Blue Cohort to Screened Non-Randomized CohortFit Blue Randomized Participants (N = 248)Non-Randomized Cohort (N = 111)All Screened Participants (N = 359)p-ValuePhysical activity Total physical activity2525 (±3218)2840 (±2541)2621 (±3028)0.027 (mean (±SD) minutes per week) Total sedentary physical activity5046 (±239)472 (±221)494 (±234)0.35 (mean (±SD) minutes per week) Vigorous physical activity34 (±145)54 (±152)40 (±147)0.036 (mean (±SD) minutes per week)Dietary intake Total sweetened beverages (kcal per day)165 (±206)152.9 (±166)160.8 (±194)0.80 Fruit and vegetable consumption (cups per day)3 (±1)3 (±1)3 (±1)0.52 Dietary fat (% total kcal)35 (±4)34 (±4)35 (±4)0.033.

conclusionsAccounting for all influencing characteristics, higher educational status was the only independent predictor of randomization. Perhaps, highly educated personnel are more invested in a military career, and thus, more concerned with consequences of failing required fitness tests. Thus, it may be important for future weight loss interventions to focus recruitment on less-educated personnel. Results suggest that weight loss interventions within a military population offer a unique opportunity to recruit a higher prevalence of males and individuals who identify as racial or ethnic minorities which are populations commonly underrepresented in weight loss research.

Indexed as

Work EngagementAdultBehavior TherapyEducational StatusFemaleHumansLogistic ModelsMaleMilitary PersonnelRacial GroupsTexasWeight Reduction Programsbehavioral weight loss interventionenrollmentrecruitment

Identifiers

PMID30125001
PMCPMC6375808
OpenAlexW2885553769

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.