Body metrics are associated with clinical, free-living, and self-report measures of mobility in a cohort of adults with obesity and multiple sclerosis.

BACKGROUND: Obesity is associated with multiple sclerosis (MS) onset and may contribute to more rapid disability accumulation. Whether obesity impacts mobility in MS is uncertain. Some studies find that obesity in MS is associated with poorer mobility; other studies find no relationship. Discrepant findings may be due to differences in measurement and methodology. In the present study, we employ a comprehensive battery of anthropometric and mobility measures in a sample of people with MS and obesity. METHODS: Participants with MS (N = 74) completed a battery of adiposity measurements (weight, height, waist circumference, and full body dual-energy x-ray absorptiometry [DXA] scans). They also completed validated clinical, free-living (accelerometry), and self-report measures of mobility. Spearman's Rho correlations were used to examine the associations between mobility and obesity measures with Benjamini and Hochberg correction for multiple comparisons. Multiple linear regression was used to examine if adiposity predicted mobility outcomes in people with MS when controlling for age and disease duration. RESULTS: The majority of participants (n = 70) were diagnosed with relapsing-remitting MS and reported mild MS-related disability on the Patient Determined Disease Steps (M = 0.77, SD = 1.1). Median BMI was 35.8 (SD = 5.4). Higher percentage body fat (measured via DXA) was associated with poorer self-reported physical functioning (rs = -0.52, p <0.001), less moderate-to-vigorous physical activity (rs = -0.24, p = 0.04), and worse performance on the Six Minute Walk Test (6MWT; rs = -0.44, p <0.001), the Timed 25 Foot Walk (T25FW; rs = 0.45, p <0.001), and the Timed Up and Go test (TUG; rs = 0.35, p = .003). Higher BMI and waist-to-height ratio (WtHR) were associated with worse outcomes on the 6MWT (BMI; rs = -0.35, p <0.01, WtHR; rs = -0.43, p <0.001), T25FW (BMI; rs = 0.32, p <0.01, WtHR; rs = 0.38, p <0.001), and the SF-36 (BMI; rs = -0.29, p <0.005, WtHR; rs = -0.31, p <0.05). Percentage body fat accounted for an additional 17 % of the variance in the T25FW and 6MWT performance, after controlling for age and disease duration. CONCLUSION: Higher BMI, WtHR, and percentage body fat were associated with lower levels of mobility (T25FW and 6MWT) in people with MS who have class I, class II, and class III obesity. Higher percentage body fat was associated with significantly worse performance on clinical, free-living, and self-report measures of mobility in people with MS even when accounting for participant age and disease duration. These findings suggest that people with MS and obesity may show improved mobility with weight loss.

Resting energy expenditure in adolescents with Down syndrome: a comparison of commonly used predictive equations.

BACKGROUND: Adolescents with Down syndrome (DS) are two to three times more likely to be obese than their typically developing peers. When preventing or treating obesity, it is useful for clinicians to understand an individual's energy intake needs. Predictive resting energy expenditure (REE) equations are often recommended for general use in energy intake recommendations; however, these predictive equations have not been validated in youth with DS. The aim of this study was to compare the accuracy of seven commonly used predictive equations for estimating REE in adolescents who are typically developing to REE measured by indirect calorimetry in adolescents with DS. METHODS: Adolescents with DS participated in a 90-min laboratory visit before 10:00 a.m. after a 12-h overnight fast and a 48-h abstention from aerobic exercise. REE was measured via indirect calorimetry, and estimated REE was derived using the Institute of Medicine, Molnar, Muller and World Health Organization equations. Mean differences between the measured and predicted REE for each equation were evaluated with equivalency testing, and P-values were adjusted for multiple comparisons using the Holm method. RESULTS: Forty-six adolescents with DS (age: 15.5 ± 1.7 years, 47.8% female, 73.9% non-Hispanic White) completed the REE assessment. Average measured REE was 1459.5 ± 267.8 kcal/day, and the Institute of Medicine equations provided the most accurate prediction of REE with a 1.7 ± 11.2% (13.9 ± 170.3 kcal/day) overestimation. This prediction was not statistically different from the measured REE [P-value = 0.582; 95% confidence interval (CI): -64.5, 36.7], and the difference between the measured and predicted REE was statistically equivalent to zero (P-value = 0.024; 90% CI: -56.1, 28.3). CONCLUSIONS: The results suggest that the Institute of Medicine equation may be useful in predicting REE in adolescents with DS. Future research should confirm these results in a larger sample and determine the utility of the Institute of Medicine equation for energy intake recommendations during a weight management intervention.

Physical activity, eating traits and weight in young adulthood: a cross-sectional and longitudinal study.

OBJECTIVE: To investigate the association between eating traits (e.g. dietary restraint or opportunistic eating) and weight - both cross-sectionally and longitudinally - and whether physical activity (PA) moderates these associations. METHODS: Two-hundred seventy young adults (21-35 years; BMI: 25.40 kg/m2 [SD = 3.90 kg/m2]; 48.90% female) participated in this 12-month observational cohort study. Cognitive Restraint (CR), Disinhibition (DI) and Hunger (HU) were measured using the Three-Factor Eating Questionnaire at baseline and 12 months. Participants were measured at quarterly intervals for objectively measured PA and anthropometrics. Cross-sectional and longitudinal models determined if eating traits were associated with weight or weight change, and whether these associations were moderated by PA. RESULTS: At baseline, higher CR (B = 0.429, p < 0.01) and DI (B = 0.942, p < 0.01) were associated with higher weight. The associations of DI (B = -0.008 p = 0.02) and HU (B = -0.006, p = 0.04) with weight were moderated by PA at baseline. The longitudinal model for CR determined PA altered the relationship between change in CR and weight change (B = 0.004, p < 0.01). CONCLUSIONS: Eating traits and PA are associated with weight and weight change. However, to elucidate how PA and eating traits directly affect weight changes, future weight loss interventions should investigate whether improving eating traits and concomitantly increasing PA amplify weight loss.

High respiratory quotient is associated with increases in body weight and fat mass in young adults.

BACKGROUND/OBJECTIVES: Metabolic disturbances, such as reduced rates of fat oxidation (high respiratory quotient (RQ)) or low energy expenditure (low resting metabolic rate (RMR)), may contribute to obesity. The objective was to determine the association between a high RQ or a low RMR and changes in body weight and body composition over 1 year. SUBJECTS/METHODS: We measured RQ and RMR in 341 adults using indirect calorimetry, along with body weight/body composition using dual-energy X-ray absorptiometery, energy expenditure using an arm-based activity monitor and energy intake using dietary recalls. Participants were classified into low, moderate or high RQ and RMR (adjusted for age, sex, race and body composition) groups according to tertiles by sex. Follow-up measurements were completed every 3 months. RESULTS: Individuals with a high RQ had larger gains in body weight and fat mass compared with individuals with a low/moderate RQ at month 3, and increases in fat mass were more than double among individuals with a high RQ at 12 months (1.3±3.0 vs 0.6±3.7 kg, P=0.03). Individuals with a low RMR did not gain more body weight nor fat mass compared with individuals with a moderate/high RMR. CONCLUSION: The primary finding is a high RQ is predictive of gains in body weight and fat mass over a 12-month period among young adults, with changes occurring as soon as 3 months. In addition, a low RMR was not associated with gains in body weight or fat mass over the same period.

Prospective association between body composition, physical activity and energy intake in young adults.

BACKGROUND/OBJECTIVES: Despite considerable research on the association between physical activity (PA) and body composition, there remains limited information on the directionality of the relationship. The present study examined the prospective associations among objectively measured PA, energy intake (EI) and body composition. SUBJECTS/METHODS: A convenience sample of 430 adults (49% male) between 21 and 35 years of age was followed over 1 year with repeated measurements taken every 3 months. BMI (kg/m(2)) and percent body fat (%BF) were calculated based on anthropometric measurements and dual energy X-ray absorptiometry. A multi-sensor device was worn over a period of 10 days to estimate total daily energy expenditure and time spent in different intensities. EI was calculated based on change in body composition and total daily energy expenditure. RESULTS: A total of 379 participants provided valid data. On average, participants experienced a significant weight gain of 1.2±4.3 kg during the 12-month observation period, which was associated with an increase in %BF (0.8±3.2 %). Average time spent in moderate-to-vigorous PA (MVPA) decreased significantly, whereas EI remained constant. Optimal linear mixed models, adjusting for age and sex, showed an inverse effect of MVPA on BMI and %BF, whereas EI only directly affected BMI (P<0.001). There was also a significant inverse effect of BMI and %BF on MVPA (P<0.001). CONCLUSIONS: Results of this study indicate an inverse reciprocal association between MVPA and measures of adiposity. Thus, primary preventive actions are warranted to avoid excess weight gain, which may result in a vicious cycle of weight gain and low PA.