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. Foodfrequency 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, B 6 , folate and B 12 ). 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.

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BackgroundThe 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.MethodsWe 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.ResultsAfter 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.ConclusionsOur findings suggest that larger density of local food destinations may is associated with better diet quality in adults.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3631-7) contains supplementary material, which is available to authorized users.

Markers of insulin resistance such as the adiponectin:leptin ratio (A:L) and the homeostasis model assessment ratio (HOMA-IR) are associated with obesity and hyperinsulinemia, both established risk factors for endometrial cancer, and may therefore be informative regarding endometrial cancer risk. This study investigated the association between endometrial cancer risk and markers of insulin resistance, namely adiponectin, leptin, the A:L ratio, insulin, fasting glucose, and the HOMA-IR. We analyzed data from 541 incident endometrial cancer cases and 961 frequency age-matched controls in a population-based case–control study in Alberta, Canada from 2002 to 2006. Participants completed interview-administered questionnaires were assessed for anthropometric measures, and provided 8-h fasting blood samples either pre- or postoperatively. Blood was analyzed for concentrations of leptin, adiponectin, and insulin by immunoassay, and fasting plasma glucose levels were determined by fluorimetric quantitative determination. Compared with the lowest quartile, the highest quartile of insulin and HOMA-IR was associated with 64% (95% confidence intervals (CI): 1.12–2.40) and 72% (95% CI: 1.17–2.53) increased risks of endometrial cancer, respectively, and the highest quartile of adiponectin was associated with a 45% (95% CI: 0.37–0.80) decreased risk after multivariable adjustments. Null associations were observed between fasting glucose, leptin and A:L, and endometrial cancer risk. This population-based study provides evidence for a role of insulin resistance in endometrial cancer etiology and may provide one possible pathway whereby obesity increases the risk of this common cancer. Interventions aimed at decreasing both obesity and insulin resistance may decrease endometrial cancer risk.

Background: Metabolic syndrome may predict endometrial cancer risk better than diabetes, hypertension, dyslipidemia, dysglycemia, or weight alone, but few studies have examined this issue.Methods: We conducted a population-based case-control study in Alberta, Canada (2002) that included 515 incident endometrial cancer cases and 962 frequency age-matched controls. Data were collected through in-person interviews, anthropometric measurements, and 8-hour fasting bloods drawn either pre-or postsurgery. Bloods were analyzed using quantitative colorimetric or absorbance-based assays (ELISA), specific to metabolic syndrome markers. Metabolic syndrome was defined using harmonized guidelines requiring presence of !3 of the following risk factors: waist circumference !88 cm, triglycerides !150 mg/dL, high-density lipoprotein cholesterol <50 mg/dL, treatment of previously diagnosed hypertension, and fasting blood glucose !100 mg/dL. OR and 95% CIs for endometrial cancer risk with presence of metabolic syndrome and individual metabolic syndrome components were estimated using logistic regression analysis.Results: Metabolic syndrome was significantly more prevalent among cases (62%) than controls (38%). A statistically significant increased risk for endometrial cancer was observed for metabolic syndrome (OR ¼ 1.53; 95% CI: 1.17-2.00), as well as for some of the individual components of metabolic syndrome including waist circumference !88 cm (OR ¼ 1.57; 95% CI: 1.18-2.08), hypertension (OR ¼ 1.57; 95% CI: 1.18-2.09), and fasting blood glucose !100 mg/dL (OR ¼ 1.31; 95% CI: 1.03-1.67). Some evidence for effect modification by menopausal status and body mass index was also found.Conclusion: Metabolic syndrome is clearly associated with increased endometrial cancer risk. Impact: Targeting the entire metabolic syndrome may optimize endometrial cancer risk reduction. Cancer Epidemiol Biomarkers Prev; 20(11); 2384-95. Ó2011 AACR.

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.

BackgroundMost sedentary behavior measures focus on occupational or leisure-time sitting. Our aim was to develop a comprehensive measure of adult sedentary behavior and establish its measurement properties.MethodThe SIT-Q was developed through expert review (n = 7), cognitive interviewing (n = 11) and pilot testing (n = 34). A convenience sample of 82 adults from Calgary, Alberta, Canada, participated in the measurement property study. Test-retest reliability was assessed by intraclass correlation coefficients (ICCs) comparing two administrations of the SIT-Q conducted one month apart. Convergent validity was established using Spearman’s rho, by comparing the SIT-Q estimates of sedentary behaviour with values derived from a 7-Day Activity Diary.ResultsThe SIT-Q exhibited good face validity and acceptability during pilot testing. Within the measurement property study, the ICCs for test-retest reliability ranged from 0.31 for leisure-time computer use to 0.86 for occupational sitting. Total daily sitting demonstrated substantial correlation (ICC = 0.65, 95% CI: 0.49, 0.78). In terms of convergent validity, correlations varied from 0.19 for sitting during meals to 0.76 for occupational sitting. For total daily sitting, estimates derived from the SIT-Q and 7 Day Activity Diaries were moderately correlated (ρ = 0.53, p < 0.01).ConclusionThe SIT-Q has acceptable measurement properties for use in epidemiologic studies.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2458-14-899) contains supplementary material, which is available to authorized users.