Literature DB >> 29158249

Objectively Measured Physical Activity and Sedentary Time Are Associated With Cardiometabolic Risk Factors in Adults With Prediabetes: The PREVIEW Study.

Nils Swindell1, Kelly Mackintosh2, Melitta McNarry2, Jeffrey W Stephens2, Diewertje Sluik3, Mikael Fogelholm4, Mathijs Drummen5, Ian MacDonald6, J Alfredo Martinez7, Teodora Handjieva-Darlenska8, Sally D Poppitt9, Jennie Brand-Miller10, Thomas M Larsen11, Anne Raben11, Gareth Stratton2.   

Abstract

OBJECTIVE: The aim of the present cross-sectional study was to examine the association among physical activity (PA), sedentary time (ST), and cardiometabolic risk in adults with prediabetes. RESEARCH DESIGN AND METHODS: Participants (n = 2,326; 25-70 years old, 67% female) from eight countries, with a BMI >25 kg ⋅ m-2 and impaired fasting glucose (5.6-6.9 mmol ⋅ L-1) or impaired glucose tolerance (7.8-11.0 mmol ⋅ L-1 at 2 h), participated. Seven-day accelerometry objectively assessed PA levels and ST.
RESULTS: Multiple linear regression revealed that moderate-to-vigorous PA (MVPA) was negatively associated with HOMA of insulin resistance (HOMA-IR) (standardized β = -0.078 [95% CI -0.128, -0.027]), waist circumference (WC) (β = -0.177 [-0.122, -0.134]), fasting insulin (β = -0.115 [-0.158, -0.072]), 2-h glucose (β = -0.069 [-0.112, -0.025]), triglycerides (β = -0.091 [-0.138, -0.044]), and CRP (β = -0.086 [-0.127, -0.045]). ST was positively associated with HOMA-IR (β = 0.175 [0.114, 0.236]), WC (β = 0.215 [0.026, 0.131]), fasting insulin (β = 0.155 [0.092, 0.219]), triglycerides (β = 0.106 [0.052, 0.16]), CRP (β = 0.106 [0.39, 0.172]), systolic blood pressure (BP) (β = 0.078 [0.026, 0.131]), and diastolic BP (β = 0.106 [0.39, -0.172]). Associations reported between total PA (counts ⋅ min-1), and all risk factors were comparable or stronger than for MVPA: HOMA-IR (β = -0.151 [-0.194, -0.107]), WC (β = -0.179 [-0.224, -0.134]), fasting insulin (β = -0.139 [-0.183, -0.096]), 2-h glucose (β = -0.088 [-0.131, -0.045]), triglycerides (β = -0.117 [-0.162, -0.071]), and CRP (β = -0.104 [-0.146, -0.062]).
CONCLUSIONS: In adults with prediabetes, objectively measured PA and ST were associated with cardiometabolic risk markers. Total PA was at least as strongly associated with cardiometabolic risk markers as MVPA, which may imply that the accumulation of total PA over the day is as important as achieving the intensity of MVPA.
© 2017 by the American Diabetes Association.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 29158249     DOI: 10.2337/dc17-1057

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  8 in total

1.  Sedentary behavior moderates the relationship between physical activity and cardiometabolic risk in young Latino children.

Authors:  Jamil A Malik; Jennifer Coto; Elizabeth R Pulgaron; Amber Daigre; Janine E Sanchez; Ronald B Goldberg; Dawn K Wilson; Alan M Delamater
Journal:  Transl Behav Med       Date:  2021-08-13       Impact factor: 3.046

2.  Frequency of Interruptions to Sitting Time: Benefits for Postprandial Metabolism in Type 2 Diabetes.

Authors:  Ashleigh R Homer; Frances C Taylor; Paddy C Dempsey; Michael J Wheeler; Parneet Sethi; Melanie K Townsend; Megan S Grace; Daniel J Green; Neale D Cohen; Robyn N Larsen; Bronwyn A Kingwell; Neville Owen; David W Dunstan
Journal:  Diabetes Care       Date:  2021-04-26       Impact factor: 17.152

3.  Activity Tracker-Based Metrics as Digital Markers of Cardiometabolic Health in Working Adults: Cross-Sectional Study.

Authors:  Yuri Rykov; Thuan-Quoc Thach; Gerard Dunleavy; Adam Charles Roberts; George Christopoulos; Chee-Kiong Soh; Josip Car
Journal:  JMIR Mhealth Uhealth       Date:  2020-01-31       Impact factor: 4.773

4.  Editorial: FIN Special Issue on PREVIEW.

Authors:  Jennie C Brand-Miller; Anne Raben
Journal:  Front Nutr       Date:  2021-12-22

5.  Contributions of changes in physical activity, sedentary time, diet and body weight to changes in cardiometabolic risk.

Authors:  Eivind Andersen; Hidde P van der Ploeg; Willem van Mechelen; Cindy M Gray; Nanette Mutrie; Femke van Nassau; Judith G M Jelsma; Annie S Anderson; Marlene N Silva; Hugo V Pereira; Alex McConnachie; Naveed Sattar; Marit Sørensen; Øystein B Røynesdal; Kate Hunt; Glyn C Roberts; Sally Wyke; Jason M R Gill
Journal:  Int J Behav Nutr Phys Act       Date:  2021-12-20       Impact factor: 6.457

6.  Physical activity intensity profiles associated with cardiometabolic risk in middle-aged to older men and women.

Authors:  Paddy C Dempsey; Eivind Aadland; Tessa Strain; Olav M Kvalheim; Kate Westgate; Tim Lindsay; Kay-Tee Khaw; Nicholas J Wareham; Søren Brage; Katrien Wijndaele
Journal:  Prev Med       Date:  2022-02-04       Impact factor: 4.018

7.  Association between physical activity and insulin resistance using the homeostatic model assessment for insulin resistance independent of waist circumference.

Authors:  Tae Kyung Yoo; Byeong Kil Oh; Mi Yeon Lee; Ki-Chul Sung
Journal:  Sci Rep       Date:  2022-04-09       Impact factor: 4.379

8.  Trends in adherence to recommended physical activity and its effects on cardiometabolic markers in US adults with pre-diabetes.

Authors:  Xiaolin Qu; Kun Chen; Jigang Chen; Junhui Zhang
Journal:  BMJ Open Diabetes Res Care       Date:  2022-09
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.