James D. LeCheminant

Dr. James D. LeCheminant


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 July 2017 in Journal of Diabetes Research
Verified
Journal Article
Open access
PDF file
KMKeilah E. Martinez
Keilah E. Martinez
LTLarry Tucker
Larry Tucker
Bruce W. BaileyBruce W. Bailey
Bruce W. Bailey
JLJames D. LeCheminant
James D. LeCheminant
This study aims to expand the evaluation of normal weight obesity (NWO) and its association with insulin resistance using an NHANES (1999–2006) sample of US adults. A cross-sectional study including 5983 men and women (50.8%) was conducted. Body fat percentage (BF%) was assessed using dual-energy X-ray absorptiometry. Expanded normal weight obesity (eNWO) categories, pairings of BMI and body fat percentage classifications, were created using standard cut-points for BMI and sex-specific median for BF%. Homeostatic model assessment-insulin resistance (HOMA-IR) levels were used to index insulin resistance. Mean ± SE values were BMI: 27.9 ± 0.2 (women) and 27.8 ± 0.1 (men); body fat percentage: 40.5 ± 0.2 (women) and 27.8 ± 0.2 (men); and HOMA-IR: 2.04 ± 0.05 (women) and 2.47 ± 0.09 (men). HOMA-IR differed systematically and in a dose-response fashion across all levels of the eNWO categories (F=291.3,P<0.0001). As BMI levels increased, HOMA-IR increased significantly, and within each BMI category, higher levels of body fat were associated with higher levels of HOMA-IR. Both high BMI and high BF% were strongly related to insulin resistance. Insulin resistance appears to increase incrementally according to BMI levels primarily and body fat levels secondarily. Including a precise measure of body fat with BMI adds little to the utility of BMI in the prediction of insulin resistance.

28 June 2012 in Scandinavian Journal of Medicine & Science in Sports
Verified
Journal Article
Closed access
PDF file
JLJames D. LeCheminant
James D. LeCheminant
THT. Hinman
T. Hinman
KPK. B. Pratt
K. B. Pratt
NEN. Earl
N. Earl
Bruce W. BaileyBruce W. Bailey
Bruce W. Bailey
LTL. A. Tucker
L. A. Tucker

15 April 2015 in PLOS ONE
Verified
Journal Article
Open access
PDF file
MLMichael J. Larson
Michael J. Larson
JLJames D. LeCheminant
James D. LeCheminant
KHKyle Hill
Kyle Hill
KCKaylie Carbine
Kaylie Carbine
TMTravis Masterson
Travis Masterson
ECEd Christenson
Ed Christenson
This study compared cognitive (attention, learning, and memory) and typing outcomes during slow treadmill walking or sitting. Seventy-five healthy individuals were randomly assigned to a treadmill walking group (n=37; 23 female) or sitting group (n=38; 17 female). The treadmill walking group completed a series of tests while walking at 1.5 mph. The sitting group performed the same tests while sitting at a standard desk. Tests performed by both groups included: the Rey Auditory Verbal Learning Test and a modified version of the Paced Auditory Serial Attention Test. In addition, typing performance was evaluated. Participants in the treadmill walking group performed worse on the Rey Auditory Verbal Learning Test for total learning than the sitting group; the main effect was significant (F(1,73)=4.75, p=0.03, ηp2=0.06); however, short- and long-delay recall performance did not differ between groups (p>0.05). For the Paced Auditory Serial Attention Test, total number of correct responses was lower in the treadmill walking group relative to the sitting group; the main effect was significant (F(1,73)=4.97, p=0.03, ηp2=0.06). The performance of both groups followed the same learning slope (Group x Trial interactions were not significant) for the Rey Auditory Verbal Learning Test and Paced Auditory Serial Attention Test. Individuals in the treadmill walking group performed significantly worse for all measures of typing (p<0.05). Walking on a treadmill desk may result in a modest difference in total learning and typing outcomes relative to sitting, but those declines may not outweigh the benefit of the physical activity gains from walking on a treadmill.

1 April 2020 in Journal of Obesity
Verified
Journal Article
Open access
PDF file
JFJames R. Fowler
James R. Fowler
LTLarry Tucker
Larry Tucker
Bruce W. BaileyBruce W. Bailey
Bruce W. Bailey
JLJames D. LeCheminant
James D. LeCheminant
This cross-sectional investigation studied differences in insulin resistance across levels of physical activity in 6,500 US adults who were randomly selected as part of the National Health and Nutrition Examination Survey (NHANES). Another important objective was to determine the influence of abdominal obesity on the physical activity and insulin resistance relationship. MET-minutes were utilized to quantify total activity based on participation in 48 different physical activities. Two strategies were employed to categorize levels of physical activity: one was based on relative MET-minutes (quartiles), and the other approach was based on the US physical activity guidelines. Insulin resistance was indexed using the homeostatic model assessment (HOMA). Abdominal obesity was indexed using waist circumference. Effect modification was tested by dividing waist circumferences into sex-specific quartiles and then evaluating the relationship between physical activity and HOMA-IR within each quartile separately. Results showed that relative physical activity level was associated with HOMA-IR after controlling for demographic and demographic and lifestyle covariates (F = 11.5, P<0.0001 and F = 6.0, P=0.0012, respectively). Adjusting for demographic and demographic and lifestyle covariates also resulted in significant relationships between guideline-based activity and HOMA-IR (F = 8.0, P<0.0001 and F = 4.9, P=0.0017, respectively). However, statistically controlling for differences in waist circumference with the other covariates nullified the relationship between total physical activity and HOMA-IR. Effect modification testing showed that when the sample was delimited to adults with abdominal obesity (Quartile 4), relative (F = 5.6, P=0.0019) and guideline-based physical activity (F = 3.7, P=0.0098) and HOMA-IR were significantly associated. Physical activity and HOMA-IR were not related within the other three quartiles. In conclusion, it appears that differences in physical activity may play a meaningful role in insulin resistance in those with abdominal obesity, but total activity does not seem to account for differences in insulin resistance among US adults with smaller waists.


19 June 2018 in Journal of Diabetes Research
Verified
Journal Article
Open access
PDF file
SFShelby A. Firouzi
Shelby A. Firouzi
LTLarry Tucker
Larry Tucker
JLJames D. LeCheminant
James D. LeCheminant
Bruce W. BaileyBruce W. Bailey
Bruce W. Bailey
The objective was to compare associations between sagittal abdominal diameter (SAD), waist circumference, and BMI to the oral glucose tolerance test (OGTT), along with fasting glucose, HbA1c, and HOMA-IR, in a nationally representative sample of 3582 US adults. The study also analyzed the effect of multiple covariates on the anthropometric and glucose metabolism associations. A cross-sectional design was used. SAD was assessed using an abdominal caliper. All other data were collected following strict NHANES protocols. The OGTT was the primary variable used to index glucose metabolism. Fasting glucose, HbA1c, and HOMA-IR were also evaluated. Results showed that mean ± SE values were as follows: SAD: 22.3 ± 0.1 cm, waist circumference: 98.0 ± 0.4 cm, BMI: 28.6 ± 0.2 kg/m2, OGTT: 113.9 ± 1.0 mg/dL, fasting glucose: 99.6 ± 0.3 mg/dL, HbA1c: 5.4 ± 0.01%, and HOMA-IR: 3.2 ± 0.1. Compared to waist circumference and BMI, SAD consistently emerged as the best predictor of glucose metabolism, before and after adjusting for the covariates, and with the sample stratified by gender, race, or age. SAD was not a better predictor of OGTT among normal-weight adults or non-Hispanic Black adults. Due to the ease of taking SAD measurements, we recommend that healthcare providers use this simple method to more precisely predict diabetes risk, especially among overweight and obese adults.