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

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.

[1]  J. Martínez,et al.  Leisure-time physical activity, sedentary behaviors, sleep, and cardiometabolic risk factors at baseline in the PREDIMED-PLUS intervention trial: A cross-sectional analysis , 2017, PloS one.

[2]  N. Owen,et al.  Sitting Less and Moving More: Improved Glycaemic Control for Type 2 Diabetes Prevention and Management , 2016, Current Diabetes Reports.

[3]  J. Lefevre,et al.  Independent Associations between Sedentary Time, Moderate-To-Vigorous Physical Activity, Cardiorespiratory Fitness and Cardio-Metabolic Health: A Cross-Sectional Study , 2016, PloS one.

[4]  M. M. Rahman,et al.  Worldwide trends in diabetes since 1980 : pooled analysis of 751 population-based measurement studies with over 4 . 4 million participants , 2016 .

[5]  Eivind Aadland,et al.  Reliability of Objectively Measured Sedentary Time and Physical Activity in Adults , 2015, PloS one.

[6]  T. Olds,et al.  Reconsidering the Sedentary Behaviour Paradigm , 2014, PloS one.

[7]  T. Perry,et al.  Breaking prolonged sitting reduces postprandial glycemia in healthy, normal-weight adults: a randomized crossover trial. , 2013, The American journal of clinical nutrition.

[8]  L. J. Gray,et al.  Associations of objectively measured sedentary behaviour and physical activity with markers of cardiometabolic health , 2013, Diabetologia.

[9]  Thierry Troosters,et al.  Validity of physical activity monitors during daily life in patients with COPD , 2013, European Respiratory Journal.

[10]  A. Kriska,et al.  Daily physical activity predicts degree of insulin resistance: a cross-sectional observational study using the 2003–2004 National Health and Nutrition Examination Survey , 2013, International Journal of Behavioral Nutrition and Physical Activity.

[11]  S. Blair,et al.  Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy , 2012, BDJ.

[12]  K. Khunti,et al.  Risk identification and interventions to prevent type 2 diabetes in adults at high risk: summary of NICE guidance , 2012, BMJ : British Medical Journal.

[13]  S. Sebire,et al.  Sedentary time, breaks in sedentary time and metabolic variables in people with newly diagnosed type 2 diabetes , 2012, Diabetologia.

[14]  K. Knutson,et al.  Sleep duration and cardiometabolic risk: a review of the epidemiologic evidence. , 2010, Best practice & research. Clinical endocrinology & metabolism.

[15]  A. Stadlmayr,et al.  A European Evidence-Based Guideline for the Prevention of Type 2 Diabetes , 2010, Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme.

[16]  P. O S I T I O N S T A T E M E N T,et al.  Diagnosis and Classification of Diabetes Mellitus , 2011, Diabetes Care.

[17]  J. Holst,et al.  Pathophysiology and aetiology of impaired fasting glycaemia and impaired glucose tolerance: does it matter for prevention and treatment of type 2 diabetes? , 2009, Diabetologia.

[18]  M. Kenward,et al.  Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls , 2009, BMJ : British Medical Journal.

[19]  U. Ekelund,et al.  Objectively Measured Moderate- and Vigorous-Intensity Physical Activity but Not Sedentary Time Predicts Insulin Resistance in High-Risk Individuals , 2009, Diabetes Care.

[20]  M. Tremblay,et al.  A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review , 2008, The international journal of behavioral nutrition and physical activity.

[21]  J. Shaw,et al.  Objectively Measured Sedentary Time, Physical Activity, and Metabolic Risk , 2007, Diabetes Care.

[22]  J. Tuomilehto,et al.  The validity of the Finnish Diabetes Risk Score for the prediction of the incidence of coronary heart disease and stroke, and total mortality , 2005, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[23]  J. Holloszy Exercise-induced increase in muscle insulin sensitivity. , 2005, Journal of applied physiology.

[24]  J. Levy,et al.  Use and abuse of HOMA modeling. , 2004, Diabetes care.

[25]  M. Hamilton,et al.  Suppression of skeletal muscle lipoprotein lipase activity during physical inactivity: a molecular reason to maintain daily low‐intensity activity , 2003, The Journal of physiology.

[26]  R. Eckel,et al.  Exercise training, without weight loss, increases insulin sensitivity and postheparin plasma lipase activity in previously sedentary adults. , 2003, Diabetes care.

[27]  Gregory J. Welk,et al.  Physical Activity Assessments for Health-Related Research , 2002 .

[28]  P. Neufer,et al.  Effects of muscle activity and fiber composition on glucose transport and GLUT-4. , 1993, The American journal of physiology.

[29]  N. Owen,et al.  Interrupting prolonged sitting reduces resting blood pressure in adults with type 2 diabetes , 2015 .

[30]  Catrine Tudor-Locke,et al.  Fully automated waist-worn accelerometer algorithm for detecting children's sleep-period time separate from 24-h physical activity or sedentary behaviors. , 2014, Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme.

[31]  L. Mâsse,et al.  Physical activity in the United States measured by accelerometer. , 2008, Medicine and science in sports and exercise.