An Exploration of Milk Product Health Beliefs and Dietary Calcium Intake in Young Adults.

Purpose: Milk products (fluid milk, cheese, yogurt) typically provide a rich source of calcium and other nutrients, yet consumption is declining in Canada. This study examined milk product health beliefs among young adults and the association between these beliefs and dietary calcium intake. Methods: Seventy-nine participants (25 ± 4 y; 40 males) completed a milk product health belief questionnaire to determine a milk product health belief score (MPHBS) and a 3-day food record to assess dietary intake. Results: Despite generally positive views, young adults were uncertain about milk products in relation to health, weight management, and ethical concerns. Females would be more likely than males to increase milk product intake if they were confident that milk products are ethically produced. There was no significant association between MPHBS and dietary calcium intake. Energy-adjusted dietary calcium intake was positively associated with intakes of vitamin A (r = 0.3, P < 0.05), riboflavin (r = 0.5, P < 0.01), vitamin B12 (r = 0.5, P = < 0.01), vitamin D (r = 0.4, P < 0.01), phosphorus (r = 0.4, P < 0.01), zinc (r = 0.3, P < 0.01), and with milk and alternatives servings (r = 0.8, P < 0.01). Conclusion: Nutrition education efforts focused on increasing calcium-rich food consumption will help consumers to be better informed when making dietary choices.

Parent reported nutritional risk and laboratory indices of cardiometabolic risk and in preschool-aged children.

BACKGROUND: Eating habits formed during childhood may contribute to the increasing prevalence of cardiometabolic disorders. Assessing nutritional risk in young children may help to prevent later cardiometabolic disease. The objective of this study was to determine whether parent-reported nutritional risk in preschool-aged children was associated with laboratory indices of cardiometabolic risk, namely leptin and insulin. METHODS: In this cross-sectional study, the relationship between nutritional risk as determined by the parent-completed NutriSTEP® questionnaire was assessed and compared to the serum leptin and insulin concentrations, hormones involved in regulation of food intake and biomarkers of adiposity and cardiometabolic risk. The community-based primary care research network for children in Toronto, Canada (TARGet Kids!) was used. The participants were children aged 3-5 years recruited from TARGet Kids! A total of 1856 children were recruited from seven primary care practices. Of these, 1086 children completed laboratory testing. Laboratory data for leptin and insulin were available for 714 and 1054 of those individuals, respectively. RESULTS: The total NutriSTEP® score was significantly associated with serum leptin concentrations (p=0.003); for each unit increase in the total NutriSTEP® score, there was an increase of 0.01 ng/mL (95% confidence interval [CI] 0.004-0.018) in serum leptin concentrations after adjusting for potential confounders. The total NutriSTEP® score was not significantly associated with serum insulin concentration. CONCLUSIONS: Parent reported nutritional risk is associated with serum leptin, but not insulin, concentrations in preschool-aged children. The NutriSTEP® questionnaire may be an effective tool for predicting future cardiometabolic risk in preschool-aged children.

Predicted and measured resting metabolic rate in young, non-obese women.

PURPOSE: Measured resting metabolic rate (RMR) was compared with predicted RMR in a sample of young, non-obese women. METHODS: In 52 women aged 19 to 30 with a body mass index of 16 to 29 kg/m2, RMR was measured with a MedGem indirect calorimeter and predicted with five commonly used equations: the Harris-Benedict (1919), Mifflin (1989), Owen (1985), Schofield (weight) (1985), and Schofield (weight and height) (1985) equations. Measured RMR and predicted RMR were compared through the use of various measures. RESULTS: In comparison with the measured RMR, the RMR predicted with four of the five equations was significantly higher (by 16 to 225 kcal/day, p < 0.001). At the group level, the Owen equation performed best and captured the greatest proportion of individuals (65%) for whom predicted RMR differed from measured RMR by less than 10%. With the other four equations, residuals exceeded 10% for more than two-thirds of participants. For the Harris-Benedict, Mifflin, and Owen equations, every 100 kcal/day increase in measured RMR was associated with a 6% to 8% decrease in error. The optimal prediction range (within 10% of the measured RMR) was different for each: Owen equation 1105 to 1400 kcal/day, Mifflin equation 1280 to 1595 kcal/day, and Harris-Benedict equation 1345 to 1630 kcal/day. CONCLUSIONS: Prediction equations should be modified according to the amount of corresponding percentage error. Where possible, RMR should be measured. Barring this, the Owen equation should be used for young, non-obese women.

Body mass, vitamin D and alcohol intake, lactose intolerance, and television watching influence bone mineral density of young, healthy Canadian women.

OBJECTIVE: To report bone mineral density (BMD) in young, reportedly healthy Canadian women and to determine whether lifestyle factors that have been associated with bone health in older women are also associated with BMD in young women. METHOD: We recruited a convenience sample of 52 female undergraduate students in the Applied Human Nutrition program at the University of Guelph, Ontario, Canada. BMD was measured at the femoral neck, lumbar spine (L1 to L4), and whole body using a Discovery Wi (Hologic Inc.) dual-energy x-ray absorptiometer. Subjects completed a questionnaire to collect demographics, medical history, physical activity levels, and dietary habits; in addition, a subset of subjects (n = 31) completed a food frequency questionnaire to collect data on calcium and vitamin D intake. BMD data were examined using T- and Z-score classifications established by the World Health Organization (WHO); multiple regression analysis was used to predict BMD with biological and lifestyle variables. RESULTS: Mean BMD measured at the femoral neck, lumbar spine, and whole body was 0.863 ± 0.11, 1.019 ± 0.09, and 1.085 ± 0.07 g/cm(2), respectively. Body mass and body mass index were significantly positively correlated with BMD at all 3 sites. Television watching, lactose intolerance, number of alcoholic drinks consumed per week, and age were used to develop a linear regression model to predict whole-body BMD (r(2) = 0.727, p < 0.001). CONCLUSIONS: Based on criteria established by the WHO, women in this group presented with lower than expected BMD.

Dietary and total calcium intakes are associated with lower percentage total body and truncal fat in young, healthy adults.

OBJECTIVE: To investigate the relationship between different sources of calcium intake (dairy [milk products only], dietary [all dietary sources including dairy], nondairy dietary [all dietary sources excluding dairy], and total [dietary + supplemental]) and fat mass in young adults. METHODS: One hundred ninety-seven healthy Caucasian men and women aged 18 to 28 years from southwestern Ontario underwent whole-body dual-energy x-ray absorptiometry to determine total body fat mass (%FM) and truncal fat (%TF). Calcium intakes, determined using a food frequency questionnaire, were divided into quartiles for each of dairy, dietary, nondairy dietary, and total sources. Physical activity scores were collected on a subset of subjects (n = 167). Mean %FM and %TF were compared between the lowest (Q1) and highest (Q4) quartiles of calcium consumers for each calcium source. Calcium intakes between subjects with %FM ≥ 50th and <50th percentile were also compared. RESULTS: Mean calcium intakes were as follows: 568 mg/d dairy calcium, 312 mg/d nondairy dietary calcium, 881 mg/d dietary calcium, 68 mg/d supplemental calcium, and 948 mg/d total calcium. %FM was 3.9%-4.9% lower and %TF was 4.1%-5.0% lower (all P ≤ 0.05) for subjects in Q4 vs Q1, regardless of calcium source (dairy, dietary, and total). When adjusted for physical activity, lower %FM and %TF persisted (P ≤ 0.05) for subjects in Q4 (1113-1595 mg/d mean dietary and total calcium intakes) vs Q1 (116-393 mg/d mean dietary and total calcium intakes). Calcium intakes from dairy, dietary, and total sources for subjects with a %FM ≥ 50th percentile were significantly lower (all P ≤ 0.05); when adjusted for physical activity, dietary (P = 0.025) and total (P = 0.060) calcium intakes remained lower. IMPLICATIONS AND CONCLUSIONS: Our findings support a relationship, even after adjusting for physical activity, between higher dietary and total calcium intakes and lower total body and truncal fat in young adults. Results suggest an intake of approximately 1500 mg/d calcium could aid in the management of body and truncal fat. We recommend that young adults be encouraged to increase their total calcium intakes to at least the recommended daily allowance of 1000 mg/d for reasons extending beyond bone health.

Published predictive equations overestimate measured resting metabolic rate in young, healthy females.

OBJECTIVE: To compare resting metabolic rate (RMR) measured by indirect calorimetry versus RMR predicted by several published formulas in a sample of healthy young women. METHODS: RMR was measured using indirect calorimetry and predicted using 6 commonly used equations (Nelson, 1992; Mifflin, 1990; Owen, 1986; Schofield(Weight), 1985; Schofield(Weight and Height), 1985; Harris-Benedict, 1919) in 47 reportedly healthy young females (age = 22.8 ± 2.9 years; body mass index = 21.8 ± 2.1 kg/m(2)). Comparisons between measured versus predicted RMR were conducted using paired t tests, and agreement using Pearson's correlation coefficient, analysis of variance, and the method of Bland-Altman. RESULTS: All 6 equations overestimated measured RMR by 140-738 kcal/d (all p < 0.001). The proportion of subjects for whom measured versus predicted RMR differed by ±10% ranged from 74% (Nelson) to 100% (Harris-Benedict). The adjusted coefficients of determination (R(2)) between measured and predicted RMR ranged from 0.13 to 0.19 (all p < 0.05). Bland-Altman analysis R(2) values ranged from 0.03 (p = 0.233; Harris-Benedict) to 0.72 (p = 0.000; Owen). Given its continued popularity, we modified the Harris-Benedict equation (RMR(modified Harris-Benedict) (kcal/d) = 738 / (RMR(Harris-Benedict) - 738)). Doing so reduced the mean difference between measured and predicted RMR from +738 kcal/d to -0.53 kcal/d (p = 0.984). CONCLUSION: No equation performed well, and none should be used interchangeably with measured RMR. We recommend that a new equation be validated for, and prospectively tested in, young women. In the interim, RMR should be measured in this population or predicted using the modified Harris-Benedict equation that we developed.