J. E. McLaughlin

Relationship of leisure-time physical activity and occupational activity to the prevalence of obesity

OBJECTIVE: To assess the interaction between leisure-time physical activity (LTPA) and occupational activity (OA) on the prevalence of obesity.DESIGN: Secondary data analysis of a population based cross-sectional US national sample (NHANES III).SUBJECTS: A total of 4889 disease-free, currently employed adults over age 20 y.MEASUREMENTS: Subjects body mass index (BMI) was categorized as (1) obese (BMI≥30 kg/m2), or (2) non-obese (BMI<30 kg/m2). LTPA was divided into four categories: (1) no LTPA; (2) irregular LTPA; (3) regular moderate intensity LTPA; and (4) regular vigorous intensity LTPA. OA was grouped as (1) high OA and (2) low OA. Age, gender, race–ethnicity, smoking status, urbanization classification, alcohol consumption and income were statistically controlled.RESULTS: In all, 16.8% (s.e. 0.7) of the total subject population were obese (15.1% (s.e. 1.1) of men and 19.1% (s.e. 1.1) of women). Logistic regression revealed that compared to those who engage in no LTPA and have low levels of OA, the likelihood of being obese is 42% (95% CI 0.35, 0.96) lower for those who engage in no LTPA and have high OA, 48% (95% CI 0.32, 0.83) lower for those who have irregular LTPA and have high levels of OA, and about 50% lower for all those who have regular LTPA through moderate or vigorous activity levels regardless of OA level.CONCLUSION: When considering disease free adults above 20 y of age employed in high and low activity occupations, a high level of occupational activity is associated with a decreased likelihood of being obese.

Test of the Classic Model for Predicting Endurance Running Performance

PURPOSE To compare the classic physiological variables linked to endurance performance (VO2max, %VO2max at lactate threshold (LT), and running economy (RE)) with peak treadmill velocity (PTV) as predictors of performance in a 16-km time trial. METHODS Seventeen healthy, well-trained distance runners (10 males and 7 females) underwent laboratory testing to determine maximal oxygen uptake (VO2max), RE, percentage of maximal oxygen uptake at the LT (%VO2max at LT), running velocity at LT, and PTV. Velocity at VO2max (vVO2max) was calculated from RE and VO2max. Three stepwise regression models were used to determine the best predictors (classic vs treadmill performance protocols) for the 16-km running time trial. RESULTS Simple Pearson correlations of the variables with 16-km performance showed vVO2max to have the highest correlation (r = -0.972) and %VO2max at the LT the lowest (r = 0.136). The correlation coefficients for LT, VO2max, and PTV were very similar in magnitude (r = -0.903 to r = -0.892). When VO2max, %VO2max at LT, RE, and PTV were entered into SPSS stepwise analysis, VO2max explained 81.3% of the total variance, and RE accounted for an additional 10.7%. vVO2max was shown to be the best predictor of the 16-km performance, accounting for 94.4% of the total variance. The measured velocity at VO2max (PTV) was highly correlated with the estimated velocity at vVO2max (r = 0.8867). CONCLUSIONS Among well-trained subjects heterogeneous in VO2max and running performance, vVO2max is the best predictor of running performance because it integrates both maximal aerobic power and the economy of running. The PTV is linked to the same physiological variables that determine vVO2max.