Validity and reproducibility of an interviewer-administered food frequency questionnaire for healthy French-Canadian men and women

OBJECTIVE: To evaluate the validity (study 1) and the reproducibility (study 2) of an interviewer-administered food frequency questionnaire (FFQ). METHOD: The FFQ was designed at Laval University and contains 91 items and 33 subquestions. Study 1: The FFQ was compared against a 3-day food record (2 week-days and 1 weekend-day), at week 0, 6 and 12 of a nutritional intervention. Study 2: In order to evaluate the reproducibility of the FFQ, 2 registered dietitians administered the FFQ 4-weeks apart among subjects who were not part of the nutritional intervention. RESULTS: Study 1: Mean values for intake of most nutrients assessed by the FFQ and by the 3-day food record were not statistically different. Energy-adjusted correlation coefficients for major macronutrients ranged from 0.36 for proteins to 0.60 for carbohydrates (p ≤ 0.01). Agreement analysis revealed that on average, 35% of the subjects were classified in the same quartile when nutrients were assessed by either the 3-day food record or the FFQ. Study 2: Significant associations were observed between dietary measurements derived from the two FFQs administered 4 weeks apart. Correlation coefficients for the reproducibility of macronutrients ranged from 0.66 for carbohydrates to 0.83 for lipids after energy adjustment. On average, 46% of the subjects were classified in the same quartile when nutrient intakes were assessed by either FFQ. CONCLUSION: These data indicated that the FFQ developed has a good validity and is reproducible

Underreporting of dietary intake by body mass index in premenopausal women participating in the Healthy Women Study

Underreporting patterns by the level of obesity have not been fully assessed yet. The purpose of this study was to examine the differential underreporting patterns on cardiovascular risk factor, macronutrient, and food group intakes by the level of Body Mass Index (BMI). We analyzed cross-sectional baseline nutritional survey data from the population-based longitudinal study, the Healthy Women Study (HWS) cohort. Study subjects included 538 healthy premenopausal women participating in the HWS. Nutrient and food group intakes were assessed by the one-day 24-hour dietary recall and a semi-quantitative food frequency questionnaire, respectively. The ratio of reported energy intake (EI) to estimated basal metabolic rate (BMR) was used as a measure of relative energy reporting status and categorized into tertiles. Overweight group (BMI≥25kg/m2) had a higher ratio of EI to BMR (EI/BMR) than normal weight group (BMI<25kg/m2). Normal weight and overweight groups showed similar patterns in cardiovascular risk factors, nutrient intake, and food group intake by the EI/BMR. Fat and saturated fat intakes as a nutrient density were positively associated with the EI/BMR. Proportion of women who reported higher consumption (≥4 times/wk) of sugar/candy, cream and red meat groups was greater in higher tertiles of the EI/BMR in both BMI groups. Our findings suggest similar patterns of underreporting of cardiovascular risk factors, and macronutrient and food group intakes in both normal and overweight women

Prevalence of Obesity and the Relationship between the Body Mass Index and Body Fat: Cross-Sectional, Population-Based Data

Background: Anthropometric measures such as the body mass index (BMI) and waist circumference are widely used as convenient indices of adiposity, yet there are limitations in their estimates of body fat. We aimed to determine the prevalence of obesity using criteria based on the BMI and waist circumference, and to examine the relationship between the BMI and body fat.Methodology/Principal Findings: This population-based, cross-sectional study was conducted as part of the Geelong Osteoporosis Study. A random sample of 1,467 men and 1,076 women aged 20&ndash;96 years was assessed 2001&ndash;2008. Overweight and obesity were identified according to BMI (overweight 25.0&ndash;29.9 kg/m2; obesity 30.0 kg/m2) and waist circumference (overweight men 94.0–101.9 cm; women 80.0–87.9 cm; obesity men 102.0 cm, women $88.0 cm); body fat mass was assessed using dual energy X-ray absorptiometry; height and weight were measured and lifestyle factors documented by self-report. According to the BMI, 45.1% (95%CI 42.4&ndash;47.9) of men and 30.2% (95%CI 27.4&ndash;33.0) of women were overweight and a further 20.2% (95%CI 18.0&ndash;22.4) of men and 28.6% (95%CI 25.8&ndash;31.3) of women were obese. Using waist circumference, 27.5% (95%CI 25.1&ndash;30.0) of men and 23.3% (95%CI 20.8&ndash;25.9) of women were overweight, and 29.3% (95%CI 26.9&ndash;31.7) of men and 44.1% (95%CI 41.2&ndash;47.1) of women, obese. Both criteria indicate that approximately 60% of the population exceeded recommended thresholds for healthy body habitus. There was no consistent pattern apparent between BMI and energy intake. Compared with women, BMI overestimated adiposity in men, whose excess weight was largely attributable to muscular body builds and greater bone mass. BMI also underestimated adiposity in the elderly. Regression models including gender, age and BMI explained 0.825 of the variance in percent body fat.Conclusions/Significance: As the BMI does not account for differences in body composition, we suggest that gender- and age-specific thresholds should be considered when the BMI is used to indicate adiposity.<br /

Attentional Processing of Food Cues in Overweight and Obese Individuals

The incentive sensitization model of obesity hypothesizes that obese individuals in the western world have acquired an enhanced attention bias to food cues, because of the overwhelming exposure to food. This article gives an overview of recent studies regarding attention to food and obesity. In general, an interesting approach-avoidance pattern in food-related attention has been found in overweight/obese individuals in a number of studies. However, it should be noted that study results are contradictory. This might be due to methodological issues, such as the choice of attention measurements, possibly tapping different underlying components of information processing. Although attention research is challenging, researchers are encouraged to further explore important issues, such as the exact circumstances in which obese persons demonstrate enhanced attention to food, the directional relationship between food-related attention bias, overeating and weight gain, and the underlying involvement of the reward system. Knowledge on these issues could help improve treatment programs

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

<p>Abstract</p> <p>Background</p> <p>Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.</p> <p>Methods</p> <p>Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired <it>t</it>-tests and/or coefficients of variation.</p> <p>Results</p> <p>The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.</p> <p>Conclusion</p> <p>Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.</p

Total energy expenditure is repeatable in adults but not associated with short-term changes in body composition

Low total energy expenditure (TEE, MJ/d) has been a hypothesized risk factor for weight gain, but repeatability of TEE, a critical variable in longitudinal studies of energy balance, is understudied. We examine repeated doubly labeled water (DLW) measurements of TEE in 348 adults and 47 children from the IAEA DLW Database (mean ± SD time interval: 1.9 ± 2.9 y) to assess repeatability of TEE, and to examine if TEE adjusted for age, sex, fat-free mass, and fat mass is associated with changes in weight or body composition. Here, we report that repeatability of TEE is high for adults, but not children. Bivariate Bayesian mixed models show no among or within-individual correlation between body composition (fat mass or percentage) and unadjusted TEE in adults. For adults aged 20-60 y (N = 267; time interval: 7.4 ± 12.2 weeks), increases in adjusted TEE are associated with weight gain but not with changes in body composition; results are similar for subjects with intervals >4 weeks (N = 53; 29.1 ± 12.8 weeks). This suggests low TEE is not a risk factor for, and high TEE is not protective against, weight or body fat gain over the time intervals tested

Energy compensation and adiposity in humans

Understanding the impacts of activity on energy balance is crucial. Increasing levels of activity may bring diminishing returns in energy expenditure because of compensatory responses in non-activity energy expenditures.1-3 This suggestion has profound implications for both the evolution of metabolism and human health. It implies that a long-term increase in activity does not directly translate into an increase in total energy expenditure (TEE) because other components of TEE may decrease in response-energy compensation. We used the largest dataset compiled on adult TEE and basal energy expenditure (BEE) (n = 1,754) of people living normal lives to find that energy compensation by a typical human averages 28% due to reduced BEE; this suggests that only 72% of the extra calories we burn from additional activity translates into extra calories burned that day. Moreover, the degree of energy compensation varied considerably between people of different body compositions. This association between compensation and adiposity could be due to among-individual differences in compensation: people who compensate more may be more likely to accumulate body fat. Alternatively, the process might occur within individuals: as we get fatter, our body might compensate more strongly for the calories burned during activity, making losing fat progressively more difficult. Determining the causality of the relationship between energy compensation and adiposity will be key to improving public health strategies regarding obesity

Daily energy expenditure through the human life course

Total daily energy expenditure (“total expenditure”) reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass–adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span