Hours spent and energy expended in physical activity domains: Results from The Tomorrow Project cohort in Alberta, Canada

<p>Abstract</p> <p>Background</p> <p>Knowledge of adult activity patterns across domains of physical activity is essential for the planning of population-based strategies that will increase overall energy expenditure and reduce the risk of obesity and related chronic diseases. We describe domain-specific hours of activity and energy expended among participants in a prospective cohort in Alberta, Canada.</p> <p>Methods</p> <p>The <it>Past Year Total Physical Activity Questionnaire </it>was completed by 15,591 <it>Tomorrow Project</it>^®participants, between 2001 and 2005 detailing physical activity type, duration, frequency and intensity. Domain-specific hours of activity and activity-related energy expenditure, expressed as a percent of total energy expenditure (TEE) (Mean (SD); Median (IQR)) are reported across <it>inactive </it>(<1.4), <it>low active </it>(1.4 to 1.59), <it>active </it>(1.6 to 1.89) and <it>very active </it>(≥ 1.9) Physical Activity Level (PAL = TEE:REE) categories.</p> <p>Results</p> <p>In <it>very active </it>women and amongst all men except those classified as <it>inactive</it>, activity-related energy expenditure comprised primarily occupational activity. Amongst <it>inactive </it>men and women in <it>active, low active </it>and <it>inactive </it>groups, activity-related energy expenditure from household activity was comparable to, or exceeded that for occupational activity. Leisure-time activity-related energy expenditure decreased with decreasing PAL categories; however, even amongst the most active men and women it accounted for less than 10 percent of TEE. When stratified by employment status, leisure-time activity-related energy expenditure was greatest for retired men [mean (SD): 10.8 (8.5) percent of TEE], compared with those who were fully employed, employed part-time or not employed. Transportation-related activity was negligible across all categories of PAL and employment status.</p> <p>Conclusion</p> <p>For the <it>inactive </it>portion of this population, active non-leisure activities, specifically in the transportation and occupational domains, need to be considered for inclusion in daily routines as a means of increasing population-wide activity levels. Environmental and policy changes to promote active transport and workplace initiatives could increase overall daily energy expenditure through reducing prolonged sitting time.</p

Co-consumption of vegetables and fruit, whole grains, and fiber reduces the cancer risk of red and processed meat in a large prospective cohort of adults from Alberta’s tomorrow project

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. We examined whether co-consumption of red and processed meat with key foods items and food constituents recommended for cancer prevention (vegetables and fruit, whole grains, and fiber) mitigates cancer incidence. In a prospective cohort of 26,218 adults aged 35–69 years at baseline, dietary intake was collected through 124-item past-year food frequency questionnaire. Incidence of all-cause and 15 cancers previously linked to red and processed meat intake was obtained through data linkage with a cancer registry (average follow-up 13.5 years). Competing risk Cox Proportional Hazard models estimated cancer risk and Accelerated Failure Time models estimated time-to-cancer occurrence for different combinations of intake levels while considering mortality from vital statistics and established confounders. Co-consumption of low vegetables and fruit intake with high processed meat was associated with higher incidence of all-cause and 15 cancers (men: HR = 1.85, 1.91; women: HR = 1.44, 1.49) and accelerated time-to-cancer occurrence (men: 6.5 and 7.1 years and women: 5.6 and 6.3 years, respectively), compared to high vegetables and fruit with low processed meat intake. Less pronounced and less consistent associations were observed for whole grains and fiber and for red meat. The findings provide initial evidence toward refining existing cancer prevention recommendations to optimize the intake and combination of foods in the general adult population

Strategies to Address Misestimation of Energy Intake Based on Self-Report Dietary Consumption in Examining Associations Between Dietary Patterns and Cancer Risk

Solbak, N. M., Al Rajabi, A., Akawung, A. K., Lo Siou, G., Kirkpatrick, S. I., & Robson, P. J. (2019). Strategies to Address Misestimation of Energy Intake Based on Self-Report Dietary Consumption in Examining Associations Between Dietary Patterns and Cancer Risk. Nutrients, 11(11), 2614. https://doi.org/10.3390/nu11112614The objective of this study was to determine the influence of strategies of handling misestimation of energy intake (EI) on observed associations between dietary patterns and cancer risk. Data from Alberta’s Tomorrow Project participants (n = 9,847 men and 16,241 women) were linked to the Alberta Cancer Registry. The revised-Goldberg method was used to characterize EI misestimation. Four strategies assessed the influence of EI misestimation: Retaining individuals with EI misestimation in the cluster analysis (Inclusion), excluding before (ExBefore) or after cluster analysis (ExAfter), or reassigning into ExBefore clusters using the nearest neighbor method (InclusionNN). Misestimation of EI affected approximately 50% of participants. Cluster analysis identified three patterns: Healthy, Meats/Pizza and Sweets/Dairy. Cox proportional hazard regression models assessed associations between the risk of cancer and dietary patterns. Among men, no significant associations (based on an often-used threshold of p < 0.05) between dietary patterns and cancer risk were observed. In women, significant associations were observed between the Sweets/Dairy and Meats/Pizza patterns and all cancer risk in the ExBefore (HR (95% CI): 1.28 (1.04–1.58)) and InclusionNN (HR (95% CI): 1.14 (1.00–1.30)), respectively. Thus, strategies to address misestimation of EI can influence associations between dietary patterns and disease outcomes. Identifying optimal approaches for addressing EI misestimation, for example, by leveraging biomarker-based studies could improve our ability to characterize diet-disease associations.Funder 1, Alberta’s Tomorrow Project is funded by the Alberta Cancer Foundation || Funder 2, the Canadian Partnership Against Cancer|| Funder 3, the Alberta Cancer Prevention Legacy Fund (administered by the Government of Alberta) || Funder 4, the University of Toronto and substantial in-kind funding from Alberta Health Services. Although funding has been provided by several organizations, the analyses and interpretation of the data presented in this paper are those of the authors alon

Towards refining WCRF/AICR cancer prevention recommendations for red and processed meat intake: Insights from Alberta\u27s Tomorrow Project cohort

Current cancer prevention recommendations advise limiting red meat intake to \u3c500g/week and avoiding consumption of processed meat, but do not differentiate the source of processed meat. We examined the associations of processed meat derived from red vs. non-red meats with cancer risk in a prospective cohort of 26,218 adults who reported dietary intake using the Canadian Diet History Questionnaire. Incidence of cancer was obtained through data linkage with Alberta Cancer Registry with median (IQR) follow-up of 13.3 (5.1) years. Multivariable Cox proportional hazards regression models were adjusted for covariates and stratified by age and gender. The median (IQR) consumption (g/week) of red meat, processed meat from red meat and processed meat from non-red meat were 267.9 (269.9), 53.6 (83.3), and 11.9 (31.8), respectively. High intakes (4th Quartile) of processed meat from red meat was associated with increased risk of gastro-intestinal cancer Adjusted Hazard Ratio (AHR) (95% CI): 1.68 (1.09-2.57) and colorectal cancers AHR (95% CI): 1.90 (1.12-3.22), respectively in women. No statistically significant associations were observed for intakes of red meat or processed meat from non-red meat. Results suggests that the carcinogenic effect associated with processed meat intake may be limited to processed meat derived from red meats. The findings provide preliminary evidence toward refining cancer prevention recommendations for red and processed meat intake

Evaluating the feasibility of administering a combination of online dietary assessment tools in a cohort of adults in Alberta, Canada

Purpose: Evidence suggests that combining tools, such as 24-hour recalls and food frequency questionnaires, may allow more accurate assessment of diet in epidemiologic studies. Webbased technology should make this approach more feasible than in the past, but it is important to explore response rates and acceptability of such an approach in real-world settings. We sought to determine the feasibility of using a combination of online tools (Automated SelfAdministered 24-hour (ASA24) Dietary Assessment Tool and Diet History Questionnaire-II (DHQ-II)) in a sub-set of participants in Alberta’s Tomorrow Project (ATP); a prospective cohort of 55,000 adults >35y in Alberta, Canada. Methods: Invitations to the feasibility study were mailed to 550 ATP participants. Those who consented (n=331) were asked to complete a health questionnaire, four ASA24 recalls (approximately three weeks apart over a four month period, with staggered start dates between June and December 2016), followed by the DHQ-II, and an evaluation survey. Results: The majority of participants [mean (SD) age =57.1 (10.1)] were women (70.7%), urban residents (84.8%) and non-smokers (95.7%). Of the 229 participants who completed at least one ASA24, roughly equal proportions completed one (24.8%), two (24.5%), three (24.5%) and four recalls (26.2%). One third (n=102) of consenting participants did not respond to any ASA24 recall requests, with “lack of time” given as the primary reason. Only 41% of consenting participants (n=136) completed the DHQ-II; of these, 40% (n=55) completed all four recalls. Median (25th-75th percentile) completion times were 46 (26-64) minutes for the first ASA24 recall and 50 (40-90) minutes for the DHQ-II. Conclusions: Over half of participants completed at least two or more ASA24 recalls, and those who completed a greater number of recalls also completed the DHQ-II, demonstrating that the approach is feasible in the ATP cohort. However, response rates may be sensitive to the timing and frequency of recall administration. Future investigations will (i) evaluate the dietary data collected from each tool; (ii) explore methods of combining the data to optimize assessment of diet in the cohort, while accounting for the fact that not all participants will complete the entire dietary assessment protocol

Administering a combination of online dietary assessment tools, the Automated Self-Administered 24-Hour Dietary Assessment Tool, and Diet History Questionnaire II, in a cohort of adults in Alberta\u27s Tomorrow Project

Background: Evidence suggests that combining tools that gather short- and long-term dietary data may be the optimal approach for the assessment of diet–disease associations in epidemiologic studies. Online technology can reduce the associated burdens for researchers and participants, but feasibility must be demonstrated in real-world settings before wide-scale implementation. Objective: The objective of this study was to determine the feasibility and acceptability of combining web-based tools (the Automated Self-Administered 24-hour Dietary Assessment Tool [ASA24-2016] and the past-year Diet History Questionnaire II [DHQ-II]) in a subset of participants in Alberta\u27s Tomorrow Project, a prospective cohort. Design: For this feasibility study, invitations were mailed to 550 randomly selected individuals enrolled in Alberta\u27s Tomorrow Project. Consented participants (n = 331) were asked to complete a brief sociodemographic and health questionnaire, four ASA24-2016 recalls, the DHQ-II, and an evaluation survey. Participants/setting: The study was conducted from March 2016 to December 2016 in Alberta, Canada. The majority of participants, mean age (SD) = 57.4 (9.8) years, were women (70.7%), urban residents (85.5%), and nonsmokers (95.7%). Main outcome measures: Primary outcomes were number of ASA24-2016 recalls completed, response rate of DHQ-II completion, and time to complete each assessment. Statistical analyses: The Wilcoxon signed rank sum test was used to assess differences in completion time. Results: One-third (n = 102) of consenting participants did not complete any ASA24-2016 recalls. The primary reason to withdraw from the feasibility study was a lack of time. Among consenting participants, 51.9% (n = 172), 41.1% (n = 136), and 36.5% (n = 121) completed at least two ASA24-2016 recalls, the DHQ-II, and at least two ASA24-2016 recalls plus the DHQ-II, respectively. Median (25th to 75th percentile) completion times for participants who completed all recalls were 39 minutes (25 to 53 minutes) for the first ASA24-2016 recall and 60 minutes (40 to 90 minutes) for the DHQ-II. Conclusions: Findings indicate combining multiple ASA24-2016 recalls and the DHQ-II is feasible in this subset of Alberta\u27s Tomorrow Project participants. However, optimal response rates may be contingent on providing participant support. Completion may also be sensitive to timing and frequency of recall administration

The effect of different methods to identify, and scenarios used to address energy intake misestimation on dietary patterns derived by cluster analysis

Background: All self-reported dietary intake data are characterized by measurement error, and validation studies indicate that the estimation of energy intake (EI) is particularly affected. Methods: Using self-reported food frequency and physical activity data from Alberta’s Tomorrow Project participants (n = 9847 men 16,241 women), we compared the revised-Goldberg and the predicted total energy expenditure methods in their ability to identify misreporters of EI. We also compared dietary patterns derived by k-means clustering under different scenarios where misreporters are included in the cluster analysis (Inclusion); excluded prior to completing the cluster analysis (ExBefore); excluded after completing the cluster analysis (ExAfter); and finally, excluded before the cluster analysis but added to the ExBefore cluster solution using the nearest neighbor method (InclusionNN). Results: The predicted total energy expenditure method identified a significantly higher proportion of participants as EI misreporters compared to the revised-Goldberg method (50% vs. 47%, p \u3c 0.0001). k-means cluster analysis identified 3 dietary patterns: Healthy, Meats/Pizza and Sweets/Dairy. Among both men and women, participants assigned to dietary patterns changed substantially between ExBefore and ExAfter and also between the Inclusion and InclusionNN scenarios (Hubert and Arabie’s adjusted Rand Index, Kappa and Cramer’s V statistics \u3c 0.8). Conclusions: Different scenarios used to account for EI misreporters influenced cluster analysis and hence the composition of the dietary patterns. Continued efforts are needed to explore and validate methods and their ability to identify and mitigate the impact of EI misestimation in nutritional epidemiology

The Comparative Reliability and Feasibility of the Past-Year Canadian Diet History Questionnaire II: Comparison of the Paper and Web Versions

Advances in technology-enabled dietary assessment include the advent of web-based food frequency questionnaires, which may reduce costs and researcher burden but may introduce new challenges related to internet connectivity and computer literacy. The purpose of this study was to evaluate the intra- and inter-version reliability, feasibility and acceptability of the paper and web Canadian Diet History Questionnaire II (CDHQ-II) in a sub-sample of 648 adults (aged 39–81 years) recruited from Alberta’s Tomorrow Project. Participants were randomly assigned to one of two groups: (1) paper, web, paper; or (2) web, paper, web over a six-week period. With few exceptions, no statistically significant differences in mean nutrient intake were found in the intra- and inter-version reliability analyses. The majority of participants indicated future willingness to complete the CDHQ-II online, and 59% indicated a preference for the web over the paper version. Findings indicate that, in this population of adults drawn from an existing cohort, the CDHQ-II may be administered in paper or web modalities (increasing flexibility for questionnaire delivery), and the nutrient estimates obtained with either version are comparable. We recommend that other studies explore the feasibility and reliability of different modes of administration of dietary assessment instruments prior to widespread implementation