60 research outputs found
Reduced impact of parental adiposity as a risk factor for excess body weight with greater distance run.
<p>The parental adiposity index is the linear combination of the mothers' and fathers' adiposities that most strongly predicted the runners' adiposity within the <3 km/day group. In the analyses, the coefficient (slope) for the <3 km/day category is always one because it was the category of runners used to define the index. Significance levels above each bar refer to the significance of the parent-offspring relationship within each distance category. The inheritance x exercise interaction tests whether the parent-offspring relationships differed by the offsprings' running distance. When the coefficients (slopes) for other running categories (3β6, 6β9, β₯9 km/day) are less than one, this means that exercise has attenuated the parental contribution. Specifically, the coefficient estimates the reduction in the effect of the parents' adiposities on their offsprings' BMIs and body circumferences.</p
Survival analyses of all related mortality, i.e., underlying or contributing causes of death, vs. categories of physical activity adjusted for medication use and BMI<sub>starting walking</sub>.
<p>Semi-hazard ratios (95% confidence intervals) ratios relative to <1.07 MET-hours/d from competing risk regression analyses. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078777#pone-0078777-t002" target="_blank">table 2</a> for adjustments.</p
Sample characteristics by MET-hours/week/d run.
*<p>Calculated as the age at death or December 31, 2008. β All variables show an association with MET-hours/week at Pβ€0.05. β‘ coded Aβ=β1, Bβ=β2, Cβ=β3, Dβ=β4, β₯Eβ=β5.</p
Effect of parental adiposity on runners' pre-exercise BMI, waist circumference, and chest circumference, showing no significant association with exercise.
<p>The inheritance x exercise interaction tests whether the parent-offspring relationships differed by the offsprings' running distance. Parental adiposity was strongly related to pre-exercise BMI in male runners (P<10<sup>β15</sup> all categories) and female runners who currently ran <3 (P<10<sup>β15</sup>), 3β6 and (P<10<sup>β15</sup>), 6β9 (P<10<sup>β11</sup>), and >9 km/day (P<10<sup>β7</sup>), pre-exercise waist circumference in male and female runners who currently ran <3 (P<10<sup>β15</sup> and P<10<sup>β9</sup>, respectively), 3β6 (P<10<sup>β15</sup> and P<10<sup>β10</sup>, respectively), 6β9 (P<10<sup>β13</sup> and P<0.0001, respectively), and β₯9 km/day (P<10<sup>β15</sup> and Pβ=β0.006, respectively), and pre-exercise chest circumference in male and female runners who currently ran <3 (P<10<sup>β15</sup> and Pβ=β0.0003, respectively), 3β6 (P<10<sup>β15</sup> and P<10<sup>β6</sup>, respectively), 6β9 (P<10<sup>β6</sup> and Pβ=β0.03, respectively), and β₯9 km/day (P<10<sup>β12</sup> and P<10<sup>β4</sup>, respectively). The analyses are restricted to the 96.7% of men and 94.3% of women who provided a weight for when they had first started running 12 or more miles per week.</p
Percentile plot showing the slope for BMI vs. years of education (Y-axis) at each percentile of the BMI distribution (X-axis).
<p>For example, each addition year of education in Study 1 females was associated with a BMI decrease of (slopeΒ±SE) β0.117Β±0.018 kg/m<sup>2</sup> at the 10<sup>th</sup> percentile of their BMI distribution (A), β0.117Β±0.016 kg/m<sup>2</sup> at their 25<sup>th</sup> percentile (B), β0.165Β±0.020 kg/m<sup>2</sup> at their 50<sup>th</sup> percentile (C, the median), β0.245Β±0.029 kg/m<sup>2</sup> at their 75<sup>th</sup> percentile (D), and β0.300Β±0.046 kg/m<sup>2</sup> at their 90<sup>th</sup> percentile (E, compare with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0027657#pone-0027657-g001" target="_blank">Figure 1</a>). The dashed lines designate one standard error. Data adjusted for age, race, physical activity, and diet. Study 1 included additional adjustment for parental adiposity.</p
Multivariate regression to determine the linear combinations of reported obesity of the mother and father that best predicts body mass index (BMI) and body circumferences in runners who averaged <3 km/day.
<p>Adjusted for age, education, and alcohol intake. Significance levels coded:</p><p>*P<0.05,</p>β <p>P<0.01,</p>β‘<p>P<0.001,</p>Β§<p>P<0.0001.</p
Percentile plot showing the slope for BMI vs. the dietary index (high-meat/low-fruit content, Y-axis) at each percentile of the BMI distribution (X-axis).
<p>The exact definitions of the dietary indices are described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0027657#s4" target="_blank">Methods</a> Section. The dashed lines designate one standard error. Data adjusted for age, race, and education. Study 1 included additional adjustment for parental adiposity.</p
Odds reduction in women's medication use to control for hypertension and high cholesterol per METhr/d energy expenditure by running (National Runners' Health Study) or walking (National Walkers' Health Study).
<p>See legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041906#pone-0041906-g001" target="_blank">Figure 1</a> for model.</p
Slopes for plasma total cholesterol concentrations versus GRS<sub>Total cholesterol</sub> and plasma triglyceride concentrations versus GRS<sub>Triglycerides</sub> (Y-axis) by the percentiles of the lipid distribution (X-axis).
<p>Lighter lines designate Β± one standard error.</p
Survival analyses of underlying cause of death vs. categories of physical activity adjusted for medication use and BMI<sub>baseline</sub>.
*<p>Hazard ratios (95% confidence intervals) from Cox proportional hazard analyses. β Semi-hazard ratios (95% confidence intervals) from competing risk regression analyses. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078777#pone-0078777-t002" target="_blank">table 2</a> for adjustments. Hazard and semi-hazard ratios relative to <1.07 MET-hours/d.</p
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