Activity energy expenditure (AEE) is the modifiable component of total energy expenditure (TEE) derived from all activities, both volitional and nonvolitional. Because AEE may affect health, there is interest in its estimation in free-living people. Physical activity questionnaires (PAQs) could be a feasible approach to AEE estimation in large populations, but it is unclear whether or not any PAQ is valid for this purpose. Our aim was to explore the validity of existing PAQs for estimating usual AEE in adults, using doubly labeled water (DLW) as a criterion measure. We reviewed 20 publications that described PAQ-to-DLW comparisons, summarized study design factors, and appraised criterion validity using mean differences (AEE_PAQ − AEE_DLW, or TEE_PAQ − TEE_DLW), 95% limits of agreement, and correlation coefficients (AEE_PAQ versus AEE_DLW or TEE_PAQ versus TEE_DLW). Only 2 of 23 PAQs assessed most types of activity over the past year and indicated acceptable criterion validity, with mean differences (TEE_PAQ − TEE_DLW) of 10% and 2% and correlation coefficients of 0.62 and 0.63, respectively. At the group level, neither overreporting nor underreporting was more prevalent across studies. We speculate that, aside from reporting error, discrepancies between PAQ and DLW estimates may be partly attributable to 1) PAQs not including key activities related to AEE, 2) PAQs and DLW ascertaining different time periods, or 3) inaccurate assignment of metabolic equivalents to self-reported activities. Small sample sizes, use of correlation coefficients, and limited information on individual validity were problematic. Future research should address these issues to clarify the true validity of PAQs for estimating AEE.

Background and objective: Despite assumed similarities in Canadian and US dietary habits, some differences in food availability and nutrient fortification exist. Food-frequency questionnaires designed for the USA may therefore not provide the most accurate estimates of dietary intake in Canadian populations. Hence, we undertook to evaluate and modify the National Cancer Institute's Diet History Questionnaire (DHQ) and nutrient database.Methods: Of the foods queried on the DHQ, those most likely to differ in nutrient composition were identified. Where possible these foods were matched to comparable foods in the Canadian Nutrient File. Nutrient values were examined and modified to reflect the Canadian content of minerals (calcium, iron, zinc) and vitamins (A, C, D, thiamin, riboflavin, niacin, B₆, folate and B₁₂). DHQs completed by 13 181 Alberta Cohort Study participants aged 35–69 years were analysed to estimate nutrient intakes using the original US and modified versions of the DHQ databases. Misclassification of intake for meeting the Dietary Reference Intake (DRI) was determined following analysis with the US nutrient database.Results: Twenty-five per cent of 2411 foods deemed most likely to differ in nutrient profile were subsequently modified for folate, 11% for vitamin D, 10% for calcium and riboflavin, and between 7 and 10% for the remaining nutrients of interest. Misclassification with respect to meeting the DRI varied but was highest for folate (7%) and vitamin A (7%) among men, and for vitamin D (7%) among women over 50 years of age.Conclusion: Errors in nutrient intake estimates owing to differences in food fortification between the USA and Canada can be reduced in Canadian populations by using nutrient databases that reflect Canadian fortification practices.

Background: Metabolic syndrome may predict endometrial cancer risk better than diabetes, hypertension, dyslipidemia, dysglycemia, or weight alone, but few studies have examined this issue.

The neighbourhood environment may play an important role in diet quality. Most previous research has examined the associations between neighbourhood food environment and diet quality, and neighbourhood socioeconomic status and diet quality separately. This study investigated the independent and joint effects of neighbourhood food environment and neighbourhood socioeconomic status in relation to diet quality in Canadian adults. We undertook a cross-sectional study with n = 446 adults in Calgary, Alberta (Canada). Individual-level data on diet and socio-demographic and health-related characteristics were captured from two self-report internet-based questionnaires, the Canadian Diet History Questionnaire II (C-DHQ II) and the Past Year Physical Activity Questionnaire (PAQ). Neighbourhood environment data were derived from dissemination area level Canadian Census data, and Geographical Information Systems (GIS) databases. Neighbourhood was defined as a 400 m network-based ‘walkshed’ around each participant’s household. Using GIS we objectively-assessed the density, diversity, and presence of specific food destination types within the participant’s walkshed. A seven variable socioeconomic deprivation index was derived from Canadian Census variables and estimated for each walkshed. The Canadian adapted Healthy Eating Index (C-HEI), used to assess diet quality was estimated from food intakes reported on C-DHQ II. Multivariable linear regression was used to test for associations between walkshed food environment variables, walkshed socioeconomic status, and diet quality (C-HEI), adjusting for individual level socio-demographic and health-related covariates. Interaction effects between walkshed socioeconomic status and walkshed food environment variables on diet quality (C-HEI) were also tested. After adjustment for covariates, food destination density was positively associated with the C-HEI (β 0.06, 95 % CI 0.01-0.12, p = 0.04) though the magnitude of the association was small. Walkshed socioeconomic status was not significantly associated with the C-HEI. We found no statistically significant interactions between walkshed food environment variables and socioeconomic status in relation to the C-HEI. Self-reported physical and mental health, time spent in neighbourhood, and dog ownership were also significantly (p < .05) associated with diet quality. Our findings suggest that larger density of local food destinations may is associated with better diet quality in adults.

Objective: To evaluate the Canadian Diet History Questionnaire I (C-DHQ I) food list and to adapt the US DHQ II for Canada using Canadian dietary survey data.Design: Twenty-four-hour dietary recalls reported by adults in a national Canadian survey were analysed to create a food list corresponding to C-DHQ I food questions. The percentage contribution of the food list to the total survey intake of seventeen nutrients was used as the criterion to evaluate the suitability of the C-DHQ I to capture food intake in Canadian populations. The data were also analysed to identify foods and to modify portion sizes for the C-DHQ II.Setting: The Canadian Community Health Survey (CCHS) – Cycle 2.2 Nutrition (2004).Subjects: Adults (n20 159) who completed 24 h dietary recalls during in-person interviews.Results: Four thousand five hundred and thirty-three foods and recipes were grouped into 268 Food Groups, of which 212 corresponded to questions on the C-DHQ I. Nutrient intakes captured by the C-DHQ I ranged from 79 % for fat to 100 % for alcohol. For the new C-DHQ II, some food questions were retained from the original US DHQ II while others were added based on foods reported in CCHS and foods available on the Canadian market since 2004. Of 153 questions, 143 were associated with portion sizes of which fifty-three were modified from US values. Sex-specific nutrient profiles for the C-DHQ II nutrient database were derived using CCHS data.Conclusions: The C-DHQ I and II are designed to optimize the capture of foods consumed by Canadian populations.

Dietary patterns derived by cluster analysis are commonly reported with little information describing how decisions are made at each step of the analytical process. Using food frequency questionnaire data obtained in 2001–2007 on Albertan men (n = 6,445) and women (n = 10,299) aged 35–69 years, the authors explored the use of statistical approaches to diminish the subjectivity inherent in cluster analysis. Reproducibility of cluster solutions, defined as agreement between 2 cluster assignments, by 3 clustering methods (Ward's minimum variance, flexible beta, K means) was evaluated. Ratios of between- versus within-cluster variances were examined, and health-related variables across clusters in the final solution were described. K means produced cluster solutions with the highest reproducibility. For men, 4 clusters were chosen on the basis of ratios of between- versus within-cluster variances, but for women, 3 clusters were chosen on the basis of interpretability of cluster labels and descriptive statistics. In comparison with those in other clusters, men and women in the “healthy” clusters by greater proportions reported normal body mass index, smaller waist circumference, and lower energy intakes. The authors’ approach appeared helpful when choosing the clustering method for both sexes and the optimal number of clusters for men, but additional analyses are required to understand why it performed differently for women.