The Relationship Between Time of Day of Physical Activity and Obesity in Older Women.

BACKGROUND Physical activity is important for maintaining healthy weight. The time of day when exercise is performed-a highly discretionary aspect of behavior-may impact weight control, but evidence is limited. Thus, we examined the association between the timing of physical activity and obesity risk in women. METHODS A cross-sectional analysis was conducted among 7157 Women's Health Study participants who participated in an ancillary study begun in 2011 that is measuring physical activity using accelerometers. The exposure was percentage of total accelerometer counts accumulated before 12:00 noon and the outcome was obesity. RESULTS Mean (±SD) BMI among participants was 26.1 (±4.9) kg/m2 and 1322 women were obese. The mean activity counts per day was 203,870 (±95,811) of which a mean 47.1% (±11.5%) were recorded in the morning. In multivariable-adjusted models, women who recorded < 39% (lowest quartile) of accelerometer counts before 12:00 noon had a 26% higher odds of being obese, compared with those recording ≥ 54% (highest quartile) of counts before noon (Ptrend = 0.02). CONCLUSIONS These study findings-that women who are less active during morning hours may be at higher risk of obesity-if confirmed can provide a novel strategy to help combat the important health problem of obesity.

[1]  Bryan K. Smith,et al.  American College of Sports Medicine Position Stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. , 2009, Medicine and science in sports and exercise.

[2]  I-Min Lee,et al.  Patterns of accelerometer-assessed sedentary behavior in older women. , 2013, JAMA.

[3]  A. Ashworth,et al.  The relationship between obesity and exposure to light at night: cross-sectional analyses of over 100,000 women in the Breakthrough Generations Study. , 2014, American journal of epidemiology.

[4]  K. Reid,et al.  Timing and Intensity of Light Correlate with Body Weight in Adults , 2014, PloS one.

[5]  W. Campbell,et al.  Exercise patterns, ingestive behaviors, and energy balance , 2014, Physiology & Behavior.

[6]  Leena Choi,et al.  Validation of accelerometer wear and nonwear time classification algorithm. , 2011, Medicine and science in sports and exercise.

[7]  S. Veasey,et al.  Daytime sleepiness in obesity: mechanisms beyond obstructive sleep apnea--a review. , 2012, Sleep.

[8]  E. Rimm,et al.  Validity of Self‐Reported Waist and Hip Circumferences in Men and Women , 1990, Epidemiology.

[9]  Catrine Tudor-Locke,et al.  A Catalog of Rules, Variables, and Definitions Applied to Accelerometer Data in the National Health and Nutrition Examination Survey, 2003–2006 , 2012, Preventing chronic disease.

[10]  L. Deldicque,et al.  Training in the fasted state improves glucose tolerance during fat‐rich diet , 2010, The Journal of physiology.

[11]  David R Bassett,et al.  Accelerometer-based physical activity: total volume per day and standardized measures. , 2015, Medicine and science in sports and exercise.

[12]  A. di Blasio,et al.  Effects of the time of day of walking on dietary behaviour, body composition and aerobic fitness in post-menopausal women. , 2010, The Journal of sports medicine and physical fitness.