Validation of Total Water Intake from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Doubly Labeled Water.

BACKGROUND: Although prior evidence indicates that water intake is important for health, the ability to accurately measure community-dwelling intake is limited. Only a few studies have evaluated self-reported water intake against an objective recovery biomarker. OBJECTIVES: The aim was to compare preformed water intakes (all sources including food) by multiple Automated Self-Administered 24-h recalls (ASA24s), food frequency questionnaires (FFQs), and 4-d food records (4DFRs) against a recovery biomarker, doubly labeled water (DLW), to assess measurement error. METHODS: Over 1 y, 1082 women and men (50%), aged 50 to 74 y, were asked to complete 6 ASA24s, 2 FFQs, 2 unweighted 4DFRs, and an administration of DLW (n = 686). Geometric means of water intake by self-report tools were compared with DLW. Attenuation factors and correlation coefficients between self-reported and the recovery biomarker (DLW) were estimated. RESULTS: Mean water intakes by DLW were 2777 mL/d (interquartile range, 2350 to 3331) in women and 3243 mL/d (interquartile range, 2720 to 3838) in men. Compared with DLW, water intake was underestimated by 18% to 31% on ASA24s and 43% to 44% on 4DFRs. Estimated geometric means from FFQs differed from DLW by -1% to +13%. For a single ASA24, FFQ, and 4DFR, attenuation factors were 0.28, 0.27, and 0.32 and correlation coefficients were 0.46, 0.48, and 0.49, respectively. Repeated use of 6 ASA24s, 2 FFQs, and 2 4DFRs improved attenuation factors to 0.43, 0.32, and 0.39 and correlation coefficients to 0.58, 0.53, and 0.54, respectively. CONCLUSIONS: FFQs may better estimate population means for usual water intake compared with ASA24 and 4DFR. Similar attenuation factors and correlation coefficients across all self-report tools indicate that researchers have 3 feasible options if the goal is understanding intake-disease relationships. The findings are useful for planning future nutrition studies that set policy priorities for populations and to understand the health impact of water. This trial was registered at clinicaltrials.gov as NCT03268577.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45-86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Examining the association between meal context and diet quality: an observational study of meal context in older adults.

BACKGROUND: Though a healthy diet is widely associated with reduced risks for chronic disease and mortality, older adults in the U.S. on average do not meet dietary recommendations. Given that few studies have examined the association between meal context on older adult diet quality, the aims of this study were (1) to compare the dietary quality of foods consumed in different meal contexts, as measured by the Healthy Eating Index 2015 (HEI-2015): meal location, the presence of others, and the use of electronic screens; and (2) to examine which components of the HEI-2015 drove differences in HEI-2015 total scores by meal context. METHODS: Interactive Diet and Activity Tracking in AARP study participants (50-74 years) completed the Automated Self-Administered 24-h Dietary Assessment tool (ASA24, version 2011) that included foods and beverages consumed and three meal contexts: "at home" versus "away from home," "alone" versus "with company," and "with screen time" versus "without screen time." A population ratio approach was used to estimate HEI-2015 total and component scores for all food items consumed by meal context. Mean HEI-2015 scores (range: 0-100) for the three meal context variables were compared using t-tests. Where there were significant differences in total scores, additional t-tests were used to explore which HEI-2015 components were the primary drivers. All tests were stratified by sex and adjusted for multiple comparisons. RESULTS: HEI-2015 scores were lower for meals consumed away vs. at home (mean difference (SE), males: - 8.23 (1.02); females: - 7.29 (0.93); both p < 0.0001) and for meals eaten with vs. without company (mean difference (SE), males: - 6.61 (1.06); females: - 7.34 (1.18); both p < 0.0001). There was no difference comparing with vs. without screen time. When HEI-2015 component scores were examined, fewer total fruits, whole grains, and dairy were consumed away from home or with company; more total vegetables and greens and beans, and less added sugars were consumed with company. CONCLUSIONS: Our findings suggest an association between the behavior cues of meal location and companions and dietary choices among older adults. Future studies can explore the individual and interactive effects of meal context on diet quality and subsequent health outcomes.

Inverse association between changes in energetic cost of walking and vertical accelerations in non-metastatic breast cancer survivors.

PURPOSE: With accelerometry, the utility to detect changes in physical activity are predicated on the assumption that walking energetics and gait mechanics do not change. The present work examined associations between changes (∆) in walking energetics, exercise self-efficacy, and several accelerometer-derived metrics. METHODS: Secondary analyses were performed among a sub-sample (n = 29) of breast cancer survivors participating in a larger randomized trial. During 4 min of treadmill walking (0.89 m s-1, 0% grade), indirect calorimetry quantified steady-state energy expenditure (EE), wherein, participants were fitted with a heart rate monitor and hip-worn triaxial accelerometer. Exercise self-efficacy was measured using a 9-item questionnaire, while vector magnitude (VM) and individual planes (e.g., mediolateral, vertical, and anteroposterior) of the movement were extracted for data analyses. Evaluations were made at baseline and after 3 months. RESULTS: From baseline to 3 months, the energetic cost of walking (kcals min-1) significantly decreased by an average of - 5.1% (p = 0.001; d = 0.46). Conversely, VM significantly increased (p = 0.007; d = 0.53), exclusively due to greater vertical accelerations (acc) (+ 5.7 ± 7.8 acc; p = 0.001; d = 0.69). Changes in vertical accelerations were inversely and positively associated with ∆walking EE (r = - 0.37; p = 0.047) and ∆exercise self-efficacy (r = 0.39; p = 0.034), respectively. CONCLUSION: Hip-worn accelerometers do not appear well-suited to correctly detect changes in ease of walking as evidenced by reduced energetic cost. Further research should determine if a divergence between measured EE and vertical accelerations could contribute to erroneous inferences in free-living physical activity.

Reporting accelerometer methods in physical activity intervention studies: a systematic review and recommendations for authors.

OBJECTIVE: This systematic review assessed the completeness of accelerometer reporting in physical activity (PA) intervention studies and assessed factors related to accelerometer reporting. DESIGN: The PubMed database was used to identify manuscripts for inclusion. Included studies were PA interventions that used accelerometers, were written in English and were conducted between 1 January 1998 and 31 July 2014. 195 manuscripts from PA interventions that used accelerometers to measure PA were included. Manuscript completeness was scored using 12 questions focused on 3 accelerometer reporting areas: accelerometer information, data processing and interpretation and protocol non-compliance. Variables, including publication year, journal focus and impact factor, and population studied were evaluated to assess trends in reporting completeness. RESULTS: The number of manuscripts using accelerometers to assess PA in interventions increased from 1 in 2002 to 29 in the first 7 months of 2014. Accelerometer reporting completeness correlated weakly with publication year (r=0.24, p<0.001). Correlations were greater when we assessed improvements over time in reporting data processing in manuscripts published in PA-focused journals (r=0.43, p=0.002) compared to manuscripts published in non-PA-focused journals (r=0.19, p=0.021). Only 7 of 195 (4%) manuscripts reported all components of accelerometer use, and only 132 (68%) reported more than half of the components. CONCLUSIONS: Accelerometer reporting of PA in intervention studies has been poor and improved only minimally over time. We provide recommendations to improve accelerometer reporting and include a template to standardise reports.

Self-reported pediatric measures of physical activity, sedentary behavior, and strength impact for PROMIS: item development.

BACKGROUND: Children's activity level is commonly assessed in clinical research, but rigorous assessment tools for children are scarce. Our objectives were to improve pediatric activity self-report measures using qualitative methods to develop item pools that measure these concepts. METHODS: On the basis of the items generated from our conceptual framework development, we applied cognitive interviews and comprehensibility reviews to ensure children readily understood the items. RESULTS: Our methods resulted in 129 unique items-physical activities (80 items), sedentary behaviors (23 items), and strengthening activities (26 items)-that were comprehensible to children between the ages of 8 and 18 years. Comprehensibility review resulted in the deletion of 4 items. CONCLUSIONS: The resultant item pools reflect children's experiences and understanding of the concepts of physical activities, sedentary behaviors, and strengthening activities. The item pools will undergo calibration using item response theory to support computer-adaptive test administration of self- and proxy-reported outcomes.

Self-reported pediatric measures of physical activity, sedentary behavior, and strength impact for PROMIS: conceptual framework.

PURPOSE: Children's physical activity (PA) levels are commonly assessed in pediatric clinical research, but rigorous self-report assessment tools for children are scarce, and computer adaptive test implementations are rare. Our objective was to improve pediatric self-report measures of activity using semistructured interviews with experts and children for conceptualization of a child-informed framework. METHODS: Semistructured interviews were conducted to conceptualize PA, sedentary behaviors, and strengthening activities. We performed systematic literature reviews to identify item-level concepts used to assess these 3 domains. RESULTS: We developed conceptual frameworks for each domain using words and phrases identified by children as relevant. CONCLUSIONS: Semistructured interview methods provide valuable information of children's perspectives and the ways children recall previous activities. Conceptualized domains of PA are based on the literature and expert views, which also reflect children's experiences and understanding, providing a basis for pediatric self-report instruments.

Patterns of neighborhood environment attributes related to physical activity across 11 countries: a latent class analysis.

BACKGROUND: Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants' response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA. METHODS: A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10-15 minutes walk of participants' residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants' response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country. RESULTS: A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, "Overall Activity Supportive (52% of sample)", "High Walkable and Unsafe with Few Recreation Facilities (16%)", "Safe with Active Transport Facilities (12%)", "Transit and Shops Dense with Few Amenities (15%)", and "Safe but Activity Unsupportive (5%)". Country representation differed by type (e.g., U.S. disproportionally represented "Safe but Activity Unsupportive"). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR=2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR=1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA. CONCLUSIONS: Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.

Perceived neighborhood environment and physical activity in 11 countries: do associations differ by country?

BACKGROUND: Increasing empirical evidence supports associations between neighborhood environments and physical activity. However, since most studies were conducted in a single country, particularly western countries, the generalizability of associations in an international setting is not well understood. The current study examined whether associations between perceived attributes of neighborhood environments and physical activity differed by country. METHODS: Population representative samples from 11 countries on five continents were surveyed using comparable methodologies and measurement instruments. Neighborhood environment × country interactions were tested in logistic regression models with meeting physical activity recommendations as the outcome, adjusted for demographic characteristics. Country-specific associations were reported. RESULTS: Significant neighborhood environment attribute × country interactions implied some differences across countries in the association of each neighborhood attribute with meeting physical activity recommendations. Across the 11 countries, land-use mix and sidewalks had the most consistent associations with physical activity. Access to public transit, bicycle facilities, and low-cost recreation facilities had some associations with physical activity, but with less consistency across countries. There was little evidence supporting the associations of residential density and crime-related safety with physical activity in most countries. CONCLUSION: There is evidence of generalizability for the associations of land use mix, and presence of sidewalks with physical activity. Associations of other neighborhood characteristics with physical activity tended to differ by country. Future studies should include objective measures of neighborhood environments, compare psychometric properties of reports across countries, and use better specified models to further understand the similarities and differences in associations across countries.

Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.

OBJECTIVES: Smartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers. METHODS: We recruited 19 male farmers, aged 50-60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app. Eligibility criteria include personal use of an iOS or Android smartphone and >4 h of farming activities at least two days per week. We developed a study-specific database of 350 farming tasks that were provided in the app; 152 were linked to questions that were asked when the activity ended. We report eligibility, study compliance, number of activities, duration of activities by day and task, and responses to the follow-up questions. RESULTS: Of the 143 farmers we reached out to for this study, 16 were not reached by phone or refused to answer eligibility questions, 69 were ineligible (limited smartphone use and/or farming time), 58 met study criteria, and 19 agreed to participate. Refusals were mostly related to uneasiness with the app and/or time commitment (32 of 39). Participation declined gradually over time, with 11 farmers reporting activities through the 24-week study period. We obtained data on 279 days (median 554 min/day; median 18 days per farmer) and 1,321 activities (median 61 min/activity; median 3 activities per day per farmer). The activities were predominantly related to animals (36%), transportation (12%), and equipment (10%). Planting crops and yard work had the longest median durations; short-duration tasks included fueling trucks, collecting/storing eggs, and tree work. Time period-specific variability was observed; for example, crop-related activities were reported for an average of 204 min/day during planting but only 28 min/day during pre-planting and 110 min/day during the growing period. We obtained additional information for 485 (37%) activities; the most frequently asked questions were related to "feed animals" (231 activities) and "operate fuel-powered vehicle (transportation)" (120 activities). CONCLUSIONS: Our study demonstrated feasibility and good compliance in collecting longitudinal activity data over 6 months using smartphones in a relatively homogeneous population of farmers. We captured most of the farming day and observed substantial heterogeneity in activities, highlighting the need for individual activity data when characterizing exposure in farmers. We also identified several areas for improvement. In addition, future evaluations should include more diverse populations.

Improving self-reports of active and sedentary behaviors in large epidemiologic studies.

Questionnaires that assess active and sedentary behaviors in large-scale epidemiologic studies are known to contain substantial errors. We present three options for improving measures of physical activity behaviors in large-scale epidemiologic studies, discuss the problems and prospects for each of these options, and highlight a new direction for measuring these behaviors in such studies.

Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

BACKGROUND: Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. OBJECTIVE: The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). DESIGN: Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. PARTICIPANTS/SETTING: From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. MAIN OUTCOME MEASURES: Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. STATISTICAL ANALYSES PERFORMED: Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. RESULTS: Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). CONCLUSIONS: ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov).

The International Prevalence Study on Physical Activity: results from 20 countries.

BACKGROUND: Physical activity (PA) is one of the most important factors for improving population health, but no standardised systems exist for international surveillance. The International Physical Activity Questionnaire (IPAQ) was developed for international surveillance. The purpose of this study was a comparative international study of population physical activity prevalence across 20 countries. METHODS: Between 2002-2004, a standardised protocol using IPAQ was used to assess PA participation in 20 countries [total N = 52,746, aged 18-65 years]. The median survey response rate was 61%. Physical activity levels were categorised as "low", "moderate" and "high". Age-adjusted prevalence estimates are presented by sex. RESULTS: The prevalence of "high PA" varied from 21-63%; in eight countries high PA was reported for over half of the adult population. The prevalence of "low PA" varied from 9% to 43%. Males more frequently reported high PA than females in 17 of 20 countries. The prevalence of low PA ranged from 7-41% among males, and 6-49% among females. Gender differences were noted, especially for younger adults, with males more active than females in most countries. Markedly lower physical activity prevalence (10% difference) with increasing age was noted in 11 of 19 countries for males, but only in three countries for women. The ways populations accumulated PA differed, with some reporting mostly vigorous intensity activities and others mostly walking. CONCLUSION: This study demonstrated the feasibility of international PA surveillance, and showed that IPAQ is an acceptable surveillance instrument, at least within countries. If assessment methods are used consistently over time, trend data will inform countries about the success of their efforts to promote physical activity.

Initial outcomes of the VERB campaign: tweens' awareness and understanding of campaign messages.

BACKGROUND: Assessing the immediate effects of mass-media campaigns provides early evidence of campaign reach into the defined target populations. Assessing these effects early in a multi-year campaign allows for better message targeting in subsequent years. DESIGN: Cross-sectional analysis of a population cohort. Data were collected annually; this paper reports on 1-year outcome data following a mass-media-led intervention to increase physical activity among children aged 9-13 years. The groups initially reached by the campaign and those that understood the campaign messages were identified. Analysis was carried out using logistic regression. PARTICIPANTS: Nationally representative cohort of 2729 children aged 9-13 years (tweens). INTERVENTION: National mass-communications campaign (VERB) from June 2002 to June 2003, using television, print, and radio as the primary communication channels. In addition, there were promotions in communities, in schools, and on the Internet. MAIN OUTCOME MEASURES: Prompted and unprompted awareness of the VERB campaign and understanding of the key campaign message. RESULTS: After 1 year, tweens' unprompted awareness of VERB was 17.3%; prompted awareness was 57%; 25.6% had no awareness of VERB. Prompted awareness did not differ by child's age, gender, or ethnicity but was associated with being from a middle- or high-income household, having a parent who was a college graduate, and being active on 7 or more days the previous week. Unprompted awareness was significantly associated with being a girl, being aged 12-14 years, being white, being from a moderate- or high-income household, having a parent with a college degree, and doing 7 or more sessions of physical activity during the week before the survey. The variables associated with high levels of understanding of the campaign message were similar to those for campaign awareness, except there were no differences in campaign understanding by age, and a significant association was found between campaign understanding and parental approval of physical activity. CONCLUSIONS: Measuring initial campaign impact identified the magnitude of immediate effects on population target groups achieved through a mass-media campaign. Campaign planners used the information to develop new messages and adjust media purchases in subsequent years of the VERB campaign.

Testing a hierarchy-of-effects model: pathways from awareness to outcomes in the VERB campaign 2002-2003.

BACKGROUND: The McGuire hierarchy-of-effects (HOE) model, used extensively in mass-media interventions to describe the mechanisms for understanding effects, has not been tested in physical activity campaigns. DESIGN: Data collected at baseline (2002) and follow-up (2003) surveys in the VERB evaluation were used in structural equation modeling to test pathways and hierarchies of campaign effects. SETTING/PARTICIPANTS: Population-based cohort of youth aged 9-13 years (N=2364) for whom complete baseline and follow-up data were available. MAIN OUTCOME MEASURES: Awareness of the VERB campaign, understanding of the VERB message, attitude toward being active, outcome expectations, and physical activity participation. RESULTS: Among youth aged 9-13 years (tweens) in the study cohort, significant paths were identified between awareness and understanding (0.72, p<0.001) and between understanding and being physically active (0.11, p<0.05). At baseline there was a high prevalence of positive attitudes and outcome expectations, and these were not influenced by change in understanding or awareness. Among inactive tweens only, the same paths were identified except that, in this subgroup, attitude was related to physical activity (0.13, p<0.05), and awareness was more strongly related to physical activity than it was for the whole sample (0.14, p<0.01). CONCLUSIONS: These findings provided limited support for the HOE model and suggest that increased awareness and understanding were the key proximal effects that led to behavior change. A distinct sequence of effects, which bypassed attitudes and outcome expectations, was found for these U.S. young people. The findings could inform the design of future campaigns to address youth physical activity.

Associations of Sedentary Time with Energy Expenditure and Anthropometric Measures.

PURPOSE: To investigate associations between accelerometer-determined sedentary time (ST) in prolonged (≥30 min) and nonprolonged (<30 min) bouts with physical activity energy expenditure (PAEE) from doubly labeled water. Additionally, associations between ST and body mass index (BMI) and waist circumference were examined. METHODS: Data from 736 women and 655 men age 43 to 82 yr were analyzed. Participants wore the Actigraph GT3X for 7 d on two occasions approximately 6 months apart, and the average of the measurements was used. Physical activity energy expenditure was estimated by subtracting resting metabolic rate and the thermic effect of food from doubly labeled water estimates of total daily energy expenditure. Cross-sectional associations were analyzed using isotemporal substitution modeling. RESULTS: Reallocation of prolonged ST to nonprolonged was not associated with increased PAEE and only significantly associated with lower BMI (ß = -0.57 kg·m; 95% confidence interval, -0.94 to -0.20) and waist circumference (ß = -1.61 cm; 95% confidence interval, -2.61 to -0.60) in men. Replacing either type of ST with light or moderate-to-vigorous physical activity was significantly associated with higher PAEE, and lower BMI and waist circumference in both women and men. CONCLUSIONS: Limiting time spent sedentary as well as decreasing ST accumulated in prolonged bouts may have beneficial effects on BMI and waist circumference. Replacing any type of ST with activities of light or higher intensity may also have a substantial impact on PAEE.

Walking behaviours from the 1965-2003 American Heritage Time Use Study (AHTUS).

BACKGROUND: The American Heritage Time Use Study (AHTUS) represents a harmonised historical data file of time use by adults, amalgamating surveys collected in 1965-66, 1975-76, 1985, 1992-94, and 2003. The objectives of time-use studies have ranged from evaluating household and other unpaid production of goods and services, to monitoring of media use, to comparing lifestyles of more and less privileged social groups, or to tracking broad shifts in social behaviour. The purpose of this paper is to describe the process and utility of identifying and compiling data from the AHTUS to describe a range of walking behaviours collected using time-use survey methods over almost 40 years in the USA. METHODS: This is a secondary data analysis of an existing amalgamated data set. Noting source survey-specific limitations in comparability of design, we determined age-standardized participation (and associated durations) in any walking, walking for exercise, walking for transport, walking the dog, sports/exercise (excluding walking), and all physical activity for those survey years for which sufficient relevant data details were available. RESULTS: Data processing revealed inconsistencies in instrument administration, coding various types of walking and in prompting other sport/exercise across surveys. Thus for the entire period, application of inferential statistics to determine trend for a range of walking behaviours could not be done with confidence. Focusing on the two most comparable survey years, 1985 and 2003, it appears that walking for exercise in America has increased in popularity on any given day (from 2.9 to 5.4% of adults) and accumulated duration amongst those who walk for exercise (from 30 to 45 mins/day). Dog walking has decreased in popularity over the same time period (from 9.4 to 2.6%). Associated duration amongst dog walkers was stable at 30 mins/day. CONCLUSION: The noted and sometimes substantial differences in methods between the various survey administrations preclude stringent interpretation of these trends in walking behaviours and the use of conventional application of inferential statistics to evaluate significance of time trends. Although the AHTUS offers the most comprehensive attempt at harmonization yet undertaken with these individual time-use surveys, we found that any noted cross-time changes in walking and physical activity behaviour are not easily interpreted in terms of conventional epidemiological approaches and could be true changes, artefact related to instrument and method changes, or both. Public health utilization of the AHTUS, could be enhanced with greater attention to methodological issues known to influence estimation of physical activity behaviour in population. This could be achieved with cross-disciplinary collaboration between groups of experts in the various stages of these surveys.

Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water.

PURPOSE: To compare the degree to which four accelerometer metrics-total activity counts per day (TAC per day), steps per day (steps per day), physical activity energy expenditure (PAEE) (kcal·kg·d), and moderate- to vigorous-intensity physical activity (MVPA) (min·d)-were correlated with PAEE measured by doubly labeled water (DLW). Additionally, accelerometer metrics based on vertical axis counts and triaxial counts were compared. METHODS: This analysis included 684 women and 611 men age 43 to 83 yr. Participants wore the Actigraph GT3X on the hip for 7 d twice during the study and the average of the two measurements was used. Each participant also completed one DLW measurement, with a subset having a repeat. PAEE was estimated by subtracting resting metabolic rate and the thermic effect of food from total daily energy expenditure estimated by DLW. Partial Spearman correlations were used to estimate associations between PAEE and each accelerometer metric. RESULTS: Correlations between the accelerometer metrics and DLW-determined PAEE were higher for triaxial counts than vertical axis counts. After adjusting for weight, age, accelerometer wear time, and fat free mass, the correlation between TAC per day based on triaxial counts and DLW-determined PAEE was 0.44 in women and 0.41 in men. Correlations for steps per day and accelerometer-estimated PAEE with DLW-determined PAEE were similar. After adjustment for within-person variation in DLW-determined PAEE, the correlations for TAC per day increased to 0.61 and 0.49, respectively. Correlations between MVPA and DLW-determined PAEE were lower, particularly for modified bouts of ≥10 min. CONCLUSIONS: Accelerometer measures that represent total activity volume, including TAC per day, steps per day, and PAEE, were more highly correlated with DLW-determined PAEE than MVPA using traditional thresholds and should be considered by researchers seeking to reduce accelerometer data to a single metric.

Mass community cycling events: who participates and is their behaviour influenced by participation?

BACKGROUND: Participation in mass physical activity events may be a novel approach for encouraging inactive or low active adults to trial an active behaviour. The public health applicability of this strategy has not been investigated thoroughly. The purpose of this study to was describe participants in a mass cycling event and examine the subsequent effect on cycling behaviour. METHODS: A sample of men and women aged 16 years and older (n = 918) who registered online for a mass cycling event reported cycling ability and number of times they rode a bicycle during the month before the event. One month after the event participants completed an online follow-up questionnaire and reported cycling ability, lifestyle physical activity, and number of times they rode a bicycle during the month after the event. McNemar's test was used to examine changes in self-rated cycling ability, and repeated measures mixed linear modeling was used to determine whether average number of monthly bicycle rides changed between pre-event and post-event assessment. RESULTS: Participants in the cycling event were predominantly male (72%), 83% rated themselves as competent or regular cyclists, and 68% rated themselves as more active than others of the same sex and age. Half of the survey respondents that rated their cycling ability as low before the event subsequently rated themselves as high one month after the event. Respondents with low pre-event self-rated cycling ability reported an average 4 sessions of bicycle riding the month before the event and an average 6.8 sessions of bicycle riding a month after the event. This increase in average sessions of bicycle riding was significant (p < .0001). Similarly, first-time participants in this particular cycling event significantly increased average sessions of cycling from 7.2 pre-event to 8.9 sessions one month after the event. CONCLUSION: Participants who were novice riders or first time participants significantly increased their number of bicycle rides in the month after the event. Further knowledge about the public health applicability of mass events is needed, and methods for attracting less active and novice individuals to participate remain to be developed.

Comparison of the 2001 BRFSS and the IPAQ Physical Activity Questionnaires.

PURPOSE: The 2001 Behavioral Risk Factor Surveillance System (BRFSS) physical activity module and the International Physical Activity Questionnaire (IPAQ) are used in population studies to determine the prevalence of physical activity. The comparability of the prevalence estimates has not been compared in U.S. adults. This study compares the physical activity prevalence estimates from the BRFSS and the IPAQ. METHODS: A telephone survey was administered to a random sample of 11,211 U.S. adults aged 18-99 yr who were enrolled in the National Physical Activity and Weight Loss Survey. Data were analyzed from 9945 adults who provided complete data on the BRFSS and the IPAQ. Prevalence estimates were computed (1) applying the BRFSS scoring scheme for both questionnaires (2). Kappa statistics were used to compare prevalence estimates generated from the BRFSS and the IPAQ. RESULTS: When scored using the BRFSS protocol, agreement between physical activity categories was fair (kappa = 0.34-0.49). Prevalence estimates were higher on the IPAQ than the BRFSS for the lowest category (inactive) by 0.1-3.9% and for the highest category (meets recommendations) by 0.2-9.7%. When scored using their own scoring, agreement between physical activity categories was lower (kappa = 0.26-0.39). The prevalence estimates on the IPAQ were higher than on the BRFSS for the lowest physical activity category by 0.2-13.3% and for the highest physical activity category by 0-16.4%. Differences in physical activity categories were observed for sex, age, income, education, and body mass index on both questionnaires. CONCLUSION: Because of differences in the physical activity prevalence estimates, direct comparison of the BRFSS and IPAQ prevalence estimates is not recommended.