Longitudinal associations between body mass index, physical activity, and healthy dietary behaviors in adults: A parallel latent growth curve modeling approach

Background Physical activity (PA) and healthy dietary behaviors (HDB) are two well-documented lifestyle factors influencing body mass index (BMI). This study examined 7-year longitudinal associations between changes in PA, HDB, and BMI among adults using a parallel latent growth curve modeling (LGCM). Methods We used prospective cohort data collected by a private company (SimplyWell LLC, Omaha, NE, USA) implementing a workplace health screening program. Data from a total of 2,579 adults who provided valid BMI, PA, and HDB information for at least 5 out of 7 follow-up years from the time they entered the program were analyzed. PA and HDB were subjectively measured during an annual online health survey. Height and weight measured during an annual onsite health screening were used to calculate BMI (kgm2). The parallel LGCMs stratified by gender and baseline weight status (normal: BMI30) were fitted to examine the longitudinal associations of changes in PA and HDB with change in BMI over years. Results On average, BMI gradually increased over years, at rates ranging from 0.06 to 0.20 kgm 2year, with larger increases observed among those of normal baseline weight status across genders. The increases in PA and HDB were independently associated with a smaller increase in BMI for obese males (b = -1.70 and -1.98, respectively), and overweight females (b = -1.85 and -2.46, respectively) and obese females (b = -2.78 and -3.08,respectively). However, no significant associations of baseline PA and HDB with changes in BMI were observed. Conclusions Our study suggests that gradual increases in PA and HDB are independently associated with smaller increases in BMI in overweight and obese adults, but not in normal weight individuals. Further study is warranted to address factors that check increases in BMI in normal weight adults

Longitudinal associations between body mass index, physical activity, and healthy dietary behaviors in adults: A parallel latent growth curve modeling approach

<div><p>Background</p><p>Physical activity (PA) and healthy dietary behaviors (HDB) are two well-documented lifestyle factors influencing body mass index (BMI). This study examined 7-year longitudinal associations between changes in PA, HDB, and BMI among adults using a parallel latent growth curve modeling (LGCM).</p><p>Methods</p><p>We used prospective cohort data collected by a private company (SimplyWell LLC, Omaha, NE, USA) implementing a workplace health screening program. Data from a total of 2,579 adults who provided valid BMI, PA, and HDB information for at least 5 out of 7 follow-up years from the time they entered the program were analyzed. PA and HDB were subjectively measured during an annual online health survey. Height and weight measured during an annual onsite health screening were used to calculate BMI (kg·m²). The parallel LGCMs stratified by gender and baseline weight status (normal: BMI<25, overweight BMI 25–29.9, and obese: BMI>30) were fitted to examine the longitudinal associations of changes in PA and HDB with change in BMI over years.</p><p>Results</p><p>On average, BMI gradually increased over years, at rates ranging from 0.06 to 0.20 kg·m²·year, with larger increases observed among those of normal baseline weight status across genders. The increases in PA and HDB were independently associated with a smaller increase in BMI for obese males (b = -1.70 and -1.98, respectively), and overweight females (b = -1.85 and -2.46, respectively) and obese females (b = -2.78 and -3.08, respectively). However, no significant associations of baseline PA and HDB with changes in BMI were observed.</p><p>Conclusions</p><p>Our study suggests that gradual increases in PA and HDB are independently associated with smaller increases in BMI in overweight and obese adults, but not in normal weight individuals. Further study is warranted to address factors that check increases in BMI in normal weight adults.</p></div

Parameter estimates from the parallel latent growth curve model ^a.

<p>Parameter estimates from the parallel latent growth curve model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173986#t004fn002" target="_blank">^a</a>.</p

A schematic diagram depicting the parallel latent growth curve model controlling for baseline covariates.

<p>‘a’ denotes the paths examining the cross-sectional associations of baseline PA and HDB with baseline BMI (Intercept_(PA) → Intercept_(BMI); Intercept_(HDB) → Intercept_(BMI)). ‘b’ denotes the paths examining the prospective associations of baseline PA and HDB with change in BMI (Intercept_(PA) → Slope_(BMI); Intercept_(HDB) → Slope_(BMI)). ‘c’ denotes the parallel associations of changes in PA and HDB with change in BMI (Slope_(PA) → Slope_(BMI); Slope_(HDB) → Slope_(BMI)).</p

Estimated mean and 95% confidence intervals of latent growth parameters ^a.

<p>Estimated mean and 95% confidence intervals of latent growth parameters <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173986#t003fn002" target="_blank">^a</a>.</p

The model-data fit indices for the latent growth curve models by gender and weight status.

<p>The model-data fit indices for the latent growth curve models by gender and weight status.</p

Baseline characteristics of study sample by genders and weight status ^a.

<p>Baseline characteristics of study sample by genders and weight status <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173986#t001fn002" target="_blank">^a</a>.</p

Effect of misfit strain on the electrocaloric effect in epitaxial SrTiO 3 thin films

77.22.Ej Polarization and depolarization, 77.70.+a Pyroelectric and electrocaloric effects, 77.80.-e Ferroelectricity and antiferroelectricity,