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Background: The 2008 Physical Activity Guidelines for Americans recommends that adults accumulate moderate-to-vigorous physical activity (MVPA) in bouts of ≥10 minutes for substantial health benefits. To what extent the same amount of MVPA accumulated in bouts versus sporadically reduces mortality risk remains unclear., Methods and Results: We analyzed data from the National Health and Nutrition Examination Survey 2003-2006 and death records available through 2011 (follow-up period of ≈6.6 years; 700 deaths) to examine the associations between objectively measured physical activity accumulated with and without a bout criteria and all-cause mortality in a representative sample of US adults 40 years and older (n=4840). Physical activity data were processed to generate minutes per day of total and bouted MVPA. Bouted MVPA was defined as MVPA accumulated in bouts of a minimum duration of either 5 or 10 minutes allowing for 1- to 2-minute interruptions. Hazard ratios for all-cause mortality associated with total and bouted MVPA were similar and ranged from 0.24 for the third quartile of total to 0.44 for the second quartile of 10-minute bouts. The examination of jointly classified quartiles of total MVPA and tertiles of proportion of bouted activity revealed that greater amounts of bouted MVPA did not result in additional risk reductions for mortality., Conclusions: These results provide evidence that mortality risk reductions associated with MVPA are independent of how activity is accumulated and can impact the development of physical activity guidelines and inform clinical practice., (© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)

Introduction/purpose: To assess the utility of measurement methods that may be more accurate and precise than traditional questionnaire-based estimates of habitual physical activity and sedentary behavior we compared the measurement properties of a past year questionnaire (AARP) and more comprehensive measures: an internet-based 24-h recall (ACT24), and a variety of estimates from an accelerometer (ActiGraph)., Methods: Participants were 932 adults (50-74 yr) in a 12-month study that included reference measures of energy expenditure from doubly labeled water (DLW) and active and sedentary time via activPAL., Results: Accuracy at the group level (mean differences) was generally better for both ACT24 and ActiGraph than the AARP questionnaire. The AARP accuracy for energy expenditure ranged from -4% to -13% lower than DLW, but its accuracy was poorer for physical activity duration (-48%) and sedentary time (-18%) versus activPAL. In contrast, ACT24 accuracy was within 3% to 10% of DLW expenditure measures and within 1% to 3% of active and sedentary time from activPAL. For ActiGraph, accuracy for energy expenditure was best for the Crouter 2-regression method (-2% to -7%), and for active and sedentary time the 100 counts per minute cutpoint was most accurate (-1% to 2%) at the group level. One administration of the AARP questionnaire was significantly correlated with long-term average from the reference measures (ρTX = 0.16-0.34) overall, but four ACT24 recalls had higher correlations (ρTX = 0.48-0.60), as did 4 d of ActiGraph assessment (ρTX = 0.54-0.87)., Conclusions: New exposure assessments suitable for use in large epidemiologic studies (ACT24, ActiGraph) were more accurate and had higher correlations than a traditional questionnaire. Use of better more comprehensive measures in future epidemiologic studies could yield new etiologic discoveries and possibly new opportunities for prevention.

Background: A limited number of studies have evaluated self-reported dietary intakes against objective recovery biomarkers., Objective: The aim was to compare dietary intakes of multiple Automated Self-Administered 24-h recalls (ASA24s), 4-d food records (4DFRs), and food-frequency questionnaires (FFQs) against recovery biomarkers and to estimate the prevalence of under- and overreporting., Design: Over 12 mo, 530 men and 545 women, aged 50-74 y, were asked to complete 6 ASA24s (2011 version), 2 unweighed 4DFRs, 2 FFQs, two 24-h urine collections (biomarkers for protein, potassium, and sodium intakes), and 1 administration of doubly labeled water (biomarker for energy intake). Absolute and density-based energy-adjusted nutrient intakes were calculated. The prevalence of under- and overreporting of self-report against biomarkers was estimated., Results: Ninety-two percent of men and 87% of women completed ≥3 ASA24s (mean ASA24s completed: 5.4 and 5.1 for men and women, respectively). Absolute intakes of energy, protein, potassium, and sodium assessed by all self-reported instruments were systematically lower than those from recovery biomarkers, with underreporting greater for energy than for other nutrients. On average, compared with the energy biomarker, intake was underestimated by 15-17% on ASA24s, 18-21% on 4DFRs, and 29-34% on FFQs. Underreporting was more prevalent on FFQs than on ASA24s and 4DFRs and among obese individuals. Mean protein and sodium densities on ASA24s, 4DFRs, and FFQs were similar to biomarker values, but potassium density on FFQs was 26-40% higher, leading to a substantial increase in the prevalence of overreporting compared with absolute potassium intake., Conclusions: Although misreporting is present in all self-report dietary assessment tools, multiple ASA24s and a 4DFR provided the best estimates of absolute dietary intakes for these few nutrients and outperformed FFQs. Energy adjustment improved estimates from FFQs for protein and sodium but not for potassium. The ASA24, which now can be used to collect both recalls and records, is a feasible means to collect dietary data for nutrition research., (Published by Oxford University Press on behalf of the American Society for Nutrition 2018.)

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.

The Physical Activity Monitor component was introduced into the 2003-2004 National Health and Nutrition Examination Survey (NHANES) to collect objective information on physical activity including both movement intensity counts and ambulatory steps. Because of an error in the accelerometer device initialization process, the steps data were missing for all participants in several primary sampling units, typically a single county or group of contiguous counties, who had intensity count data from their accelerometers. To avoid potential bias and loss in efficiency in estimation and inference involving the steps data, we considered methods to accurately impute the missing values for steps collected in the 2003-2004 NHANES. The objective was to come up with an efficient imputation method that minimized model-based assumptions. We adopted a multiple imputation approach based on additive regression, bootstrapping and predictive mean matching methods. This method fits alternative conditional expectation (ace) models, which use an automated procedure to estimate optimal transformations for both the predictor and response variables. This paper describes the approaches used in this imputation and evaluates the methods by comparing the distributions of the original and the imputed data. A simulation study using the observed data is also conducted as part of the model diagnostics. Finally, some real data analyses are performed to compare the before and after imputation results. Published 2016. This article is a U.S. Government work and is in the public domain in the USA., (Published 2016. This article is a U.S. Government work and is in the public domain in the USA.)

Background: Moderate-to-vigorous-intensity physical activity is recommended to maintain and improve health, but the mortality benefits of light activity and risk for sedentary time remain uncertain., Objectives: Using accelerometer-based measures, we 1) described the mortality dose-response for sedentary time and light- and moderate-to-vigorous-intensity activity using restricted cubic splines, and 2) estimated the mortality benefits associated with replacing sedentary time with physical activity, accounting for total activity., Design: US adults (n = 4840) from NHANES (2003-2006) wore an accelerometer for ≤7 d and were followed prospectively for mortality. Proportional hazards models were used to estimate adjusted HRs and 95% CIs for mortality associations with time spent sedentary and in light- and moderate-to-vigorous-intensity physical activity. Splines were used to graphically present behavior-mortality relation. Isotemporal models estimated replacement associations for sedentary time, and separate models were fit for low- (<5.8 h total activity/d) and high-active participants to account for nonlinear associations., Results: Over a mean of 6.6 y, 700 deaths occurred. Compared with less-sedentary adults (6 sedentary h/d), those who spent 10 sedentary h/d had 29% greater risk (HR: 1.29; 95% CI: 1.1, 1.5). Compared with those who did less light activity (3 h/d), those who did 5 h of light activity/d had 23% lower risk (HR: 0.77; 95% CI: 0.6, 1.0). There was no association with mortality for sedentary time or light or moderate-to-vigorous activity in highly active adults. In less-active adults, replacing 1 h of sedentary time with either light- or moderate-to-vigorous-intensity activity was associated with 18% and 42% lower mortality, respectively., Conclusions: Health promotion efforts for physical activity have mostly focused on moderate-to-vigorous activity. However, our findings derived from accelerometer-based measurements suggest that increasing light-intensity activity and reducing sedentary time are also important, particularly for inactive adults., (© 2016 American Society for Nutrition.)

Purpose: Develop strategic priorities to guide future physical activity surveillance in the United States., Methods: The Centers for Disease Control and Prevention and the American College of Sports Medicine convened a scientific roundtable of physical activity and measurement experts. Participants summarized the current state of aerobic physical activity surveillance for adults, focusing on practice and research needs in three areas: 1) behavior, 2) human movement, and 3) community supports. Needs and challenges for each area were identified. At the conclusion of the meeting, experts identified one overarching strategy and five strategic priorities to guide future surveillance., Results: The identified overarching strategy was to develop a national plan for physical activity surveillance similar to the U.S. National Physical Activity Plan for promotion. The purpose of the plan would be to enhance coordination and collaboration within and between sectors, such as transportation and public health, and to address specific strategic priorities identified at the roundtable. These strategic priorities were used 1) to identify and prioritize physical activity constructs; 2) to assess the psychometric properties of instruments for physical activity surveillance; 3) to provide training and technical assistance for those collecting, analyzing, or interpreting surveillance data; 4) to explore accessing data from alternative sources; and 5) to improve communication, translation, and dissemination about estimates of physical activity from surveillance systems., Conclusion: This roundtable provided strategic priorities for physical activity surveillance in the United States. A first step is to develop a national plan for physical activity surveillance that would provide an operating framework from which to execute these priorities.

To determine the number and distribution of days required to produce stable group-level estimates of a 7 d mean for common accelerometer-derived activity measures. Data from the 2003-2006 NHANES were used in this analysis. The sample included 986 youth (6-19 year) and 2532 adults (⩾20 year) with 7 d of  ⩾10 h of wear. Accelerometer measures included minutes of inactive, light physical activity, moderate-to-vigorous physical activity (MVPA); and total activity counts/d. Twenty-five alternative protocols were bootstrapped with 50 000 samples drawn for each protocol. Alternative protocols included: 1-6 random days, Saturday plus 1-5 random weekdays (WD), Sunday plus 1-5 random WD, 1 random weekend day (WE) plus 1-5 WD, and both WE plus 1-4 random WD. Relative difference was calculated between the 7 d mean and alternative protocol mean (((alternative protocol mean - 7 d mean)/7 d mean) (*) 100). Adult MVPA is used as an example; however, similar trends were observed across age groups and variables except adult inactive time, which was stable across protocols. The 7 d mean for adult MVPA was 44.1(0.9) min d(-1). The mean bias for any 1-6 random days ranged from  -0.0(0.3) to 0.0(0.2) min d(-1) with a relative difference of  -0.1 to 0.0%. For protocols with non-random components, bias ranged from  -1.4(0.2) to 0.6(0.1) min d(-1) with relative difference ranging from  -7.2 to 3.1%. Simulation data suggest that stable estimates of group-level means can be obtained from as few as one randomly selected monitoring day from a sampled week. On the other hand, estimates using non-random selection of weekend days may be significantly biased. Purposeful sampling that disproportionally forces inclusion of weekend data in analyses should be discouraged.

This paper examined how many older adults (65+years) are meeting physical activity (PA) Guidelines (PAG; 150min/week of moderate-to-vigorous PA) using data from three leading national surveys (NHANES, BRFSS and NHIS). The proportion of individuals meeting aerobic PAG was determined for the most recent cycle available for each survey (NHANES 2011-12, NHIS and BRFSS 2013). We also assessed whether PAG adherence has changed over time. Predicted margins from multinomial logistic regression were computed after adjusting for age, race/ethnicity and gender and sample weights. The proportion of older adults meeting PAG was 27.3% for NHANES, 35.8% for NHIS and 44.3% for BRFSS. Across all surveys, men reported higher levels of activity than women, Non-Hispanic whites reported higher levels than Non-Hispanic blacks and Hispanics, activity declined with age and was lower in those with functional limitations, all P<0.05. The proportion of older adults meeting PAG in the NHIS survey, the only survey where PA questions remained the same over time, increased from 25.7% in 1998 to 35.8% in 2013 (P<0.01). Point-estimates for activity levels are different between surveys but they consistently identify sub-groups who are less active. Although older adults are reporting more activity over time, adherence to aerobic and strength training PAG remains low in this population and there is a need for effective interventions to prevent age-related declines in PA and address health disparities among older adults., (Published by Elsevier Inc.)

Introduction: Although decline in muscle mass and quality and resulting declines in muscle strength are associated with aging, more research is needed in general populations to assess the utility of handgrip strength as an indicator of muscle strength and cardiovascular disease risk., Methods: Data from 4,221 participants aged ≥20 years in the 2011-2012 cycle of National Health and Nutrition Examination Survey were analyzed during 2014-2015. Standing isometric relative handgrip strength (calculated as maximal absolute handgrip strength from both hands divided by BMI) was used to predict cardiovascular biomarkers, including blood pressure (measured systolic and diastolic blood pressure); serum lipids (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides); and plasma insulin and glucose., Results: Results from regression analyses showed that higher relative grip strength was significantly associated with lower systolic blood pressure, triglycerides, and plasma insulin and glucose, and higher high-density lipoprotein cholesterol in male and female participants (p<0.05 for all). Secondary descriptive analyses found that absolute handgrip strength increased significantly with increasing weight status, but relative handgrip strength decreased significantly with increasing weight status., Conclusions: Results suggest that increased relative handgrip strength may be associated with a better profile of cardiovascular health biomarkers among U.S. adults. Relative grip strength, which both adjusts for the confounding of mass and assesses concomitant health risks of increased body size and low muscle strength, may be a useful public health measure of muscle strength., (Published by Elsevier Inc.)

Objectives: Population-referenced total activity counts per day (TAC/d) percentiles provide public health practitioners a standardized measure of physical activity (PA) volume obtained from an accelerometer that can be compared across populations. The purpose of this study was to describe the application of TAC/d population-referenced percentiles to characterize the PA levels of population groups relative to US estimates., Methods: A total of 679 adults participating in the 2011 NYC Physical Activity Transit survey wore an ActiGraph accelerometer on their hip for seven consecutive days. Accelerometer-derived TAC/d was classified into age- and gender-specific quartiles of US population-referenced TAC/d to compare differences in the distributions by borough (N=5)., Results: Males in Brooklyn, Manhattan, and Staten Island had significantly greater TAC/d than US males. Females in Brooklyn and Queens had significantly greater levels of TAC/d compared to US females. The proportion of males in each population-referenced TAC/d quartile varied significantly by borough (χ(2)(12)=2.63, p=0.002), with disproportionately more men in Manhattan and the Bronx found to be in the highest and lowest US population-referenced TAC/d quartiles, respectively. For females, there was no significant difference in US population-reference TAC/d quartile by borough (χ(2)(12)=1.09, p=0.36)., Conclusions: These results demonstrate the utility of population-referenced TAC/d percentiles in public health monitoring and surveillance. These findings also provide insights into the PA levels of NYC residents relative to the broader US population, which can be used to guide health promotion efforts., (Published by Elsevier Inc.)

The purposes of this study were to use the National Health and Nutrition Examination Study (2011-12) data to determine nationally representative combined handgrip strength ranges and percentile information by sex and age group, examine trends in strength across age by sex, and to determine the relative proportion of children and adults falling into established health benefit zones (HBZ). Results indicate that mean strength was greater among men than women and increased linearly for children and in a quadratic fashion among adults for both sexes. Grip strength peaked in the 30- to 39-year age group for both men (216.4 lbs) and women (136.5 lbs) with subsequent age groups showing gradual decline, p < 0.0001. Relative and absolute increases in grip strength were greater for men than for women, but relative decrease from peak strength was less among women than men. Although absolute strength was greater among men than women, HBZ data indicated that a higher percentage of men than women overall and at each age group fell into the needs improvement zone, with differences particularly pronounced during adolescence and older adulthood. These data provide the first nationally representative population estimates of combined handgrip strength and percentile information from childhood through senescence and suggest consideration of HBZ information in conjunction with grip strength to improve surveillance data interpretation and intervention planning.

Purpose: This study aimed to describe the scope of accelerometry data collected internationally in adults and to obtain a consensus from measurement experts regarding the optimal strategies to harmonize international accelerometry data., Methods: In March 2014, a comprehensive review was undertaken to identify studies that collected accelerometry data in adults (sample size, n ≥ 400). In addition, 20 physical activity experts were invited to participate in a two-phase Delphi process to obtain consensus on the following: unique research opportunities available with such data, additional data required to address these opportunities, strategies for enabling comparisons between studies/countries, requirements for implementing/progressing such strategies, and value of a global repository of accelerometry data., Results: The review identified accelerometry data from more than 275,000 adults from 76 studies across 36 countries. Consensus was achieved after two rounds of the Delphi process; 18 experts participated in one or both rounds. The key opportunities highlighted were the ability for cross-country/cross-population comparisons and the analytic options available with the larger heterogeneity and greater statistical power. Basic sociodemographic and anthropometric data were considered a prerequisite for this. Disclosure of monitor specifications and protocols for data collection and processing were deemed essential to enable comparison and data harmonization. There was strong consensus that standardization of data collection, processing, and analytical procedures was needed. To implement these strategies, communication and consensus among researchers, development of an online infrastructure, and methodological comparison work were required. There was consensus that a global accelerometry data repository would be beneficial and worthwhile., Conclusions: This foundational resource can lead to implementation of key priority areas and identification of future directions in physical activity epidemiology, population monitoring, and burden of disease estimates.

The risk of obesity is reduced when youth engage in recommended levels of physical activity (PA). For that reason, public health organizations in the U.S. have encouraged communities to implement programs and policies designed to increase PA in youth, and many communities have taken on that challenge. However, the long-term effects of those programs and policies on obesity are largely unknown. The Healthy Communities Study is a large-scale observational study of U.S. communities that is examining the characteristics of programs and policies designed to promote healthy behaviors (e.g., increase PA and improve diet) and determining their association with obesity-related outcomes. The purpose of this paper is to describe the methods used to measure PA in children and the personal and community factors that may influence it. The study used both self-reported and objective measures of PA, and measured personal, family, and home influences on PA via three constructs: (1) PA self-schema; (2) parental support; and (3) parental rules regarding PA. Neighborhood and community factors related to PA were assessed using three measures: (1) child perceptions of the neighborhood environment; (2) availability of PA equipment; and (3) attributes of the child's street segment via direct observation. School influences on children's PA were assessed via three constructs: (1) school PA policies; (2) child perceptions of the school PA environment; and (3) school outdoor PA environment. These measures will enable examination of the associations between characteristics of community PA programs and policies and obesity-related outcomes in children and youth., (Copyright © 2015 American Journal of Preventive Medicine. All rights reserved.)

The use of accelerometers in physical activity (PA) research has increased exponentially over the past 20 yr. The first commercially available accelerometer for assessing PA, the Caltrac, was worn on the waist and estimated PA energy expenditure in kilocalories. Around 1995, the emphasis shifted to measuring minutes of moderate-to-vigorous PA (MVPA), especially for bouts of 10 min or longer. Recent studies, however, show that light-intensity PA and intermittent (nonbout) MVPA also have important health benefits. The total volume of PA performed is an important variable because it takes the frequency, intensity, and duration of activity bouts and condenses them down into a single metric. The total volume of PA is appropriate for many research applications and can enhance comparisons between studies. In the future, machine learning algorithms will provide improved accuracy for activity type recognition and estimation of PA energy expenditure. However, in the current landscape of objectively measured PA, total activity counts per day (TAC/d) is a proxy for the total volume of PA. TAC/d percentiles for age- and gender-specific groups have been developed from the National Health and Nutrition Examination Survey ActiGraph data (2003-2006), providing a novel way to assess PA. The use of TAC/d or standardized units of acceleration could harmonize PA across studies. TAC/d should be viewed as an additional metric, not intended to replace other metrics (e.g., sedentary time, light-intensity PA, moderate PA, and vigorous PA) that may also be related to health. As future refinements to wearable monitors occur, researchers should continue to consider metrics that reflect the total volume of PA in addition to existing PA metrics.

Despite the well-known benefits of youths engaging in 60 or more minutes of daily physical activity, physical inactivity remains a significant public health concern. The 2008 Physical Activity Guidelines for Americans (PAG) provides recommendations on the amount of physical activity needed for overall health; the PAG Midcourse Report (2013) describes effective strategies to help youths meet these recommendations. Public health professionals can be dynamic change agents where youths live, learn, and play by changing environments and policies to empower youths to develop regular physical activity habits to maintain throughout life. We have summarized key findings from the PAG Midcourse Report and outlined actions that public health professionals can take to ensure that all youths regularly engage in health-enhancing physical activity.

The technology and application of current accelerometer-based devices in physical activity (PA) research allow the capture and storage or transmission of large volumes of raw acceleration signal data. These rich data not only provide opportunities to improve PA characterisation, but also bring logistical and analytic challenges. We discuss how researchers and developers from multiple disciplines are responding to the analytic challenges and how advances in data storage, transmission and big data computing will minimise logistical challenges. These new approaches also bring the need for several paradigm shifts for PA researchers, including a shift from count-based approaches and regression calibrations for PA energy expenditure (PAEE) estimation to activity characterisation and EE estimation based on features extracted from raw acceleration signals. Furthermore, a collaborative approach towards analytic methods is proposed to facilitate PA research, which requires a shift away from multiple independent calibration studies. Finally, we make the case for a distinction between PA represented by accelerometer-based devices and PA assessed by self-report., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Systematic investigations into the structure of measurement error of physical activity questionnaires are lacking. We propose a measurement error model for a physical activity questionnaire that uses physical activity level (the ratio of total energy expenditure to basal energy expenditure) to relate questionnaire-based reports of physical activity level to true physical activity levels. The 1999-2006 National Health and Nutrition Examination Survey physical activity questionnaire was administered to 433 participants aged 40-69 years in the Observing Protein and Energy Nutrition (OPEN) Study (Maryland, 1999-2000). Valid estimates of participants' total energy expenditure were also available from doubly labeled water, and basal energy expenditure was estimated from an equation; the ratio of those measures estimated true physical activity level ("truth"). We present a measurement error model that accommodates the mixture of errors that arise from assuming a classical measurement error model for doubly labeled water and a Berkson error model for the equation used to estimate basal energy expenditure. The method was then applied to the OPEN Study. Correlations between the questionnaire-based physical activity level and truth were modest (r = 0.32-0.41); attenuation factors (0.43-0.73) indicate that the use of questionnaire-based physical activity level would lead to attenuated estimates of effect size. Results suggest that sample sizes for estimating relationships between physical activity level and disease should be inflated, and that regression calibration can be used to provide measurement error-adjusted estimates of relationships between physical activity and disease.

Background: To examine the benefits of physical activity (PA) on diseases with a long developmental period, it is important to determine reliability of long-term PA recall., Methods: We investigated 15-year reproducibility of PA recall. Participants were 3605 White and African-American adults in the Coronary Artery Risk Development in Young Adults study, aged 33-45 at the time of recall assessment. Categorical questions assessed PA before and during high school (HS) and overall PA level at Baseline, with the same timeframes recalled 15 years later. Moderate- and vigorous-intensity scores were calculated from reported months of participation in specific activities., Results: HS PA recall had higher reproducibility than overall PA recall (weighted kappa = 0.43 vs. 0.21). Correlations between 15-year recall and Baseline reports of PA were r = 0.29 for moderate-intensity scores, and r = 0.50 for vigorous-intensity. Recall of vigorous activities had higher reproducibility than moderate-intensity activities. Regardless of number of months originally reported for specific activities, most participants recalled either no activity or activity during all 12 months., Conclusion: PA recall from the distant past is moderately reproducible, but poor at the individual level, among young and middle aged adults.

Objective: To assess primary care physicians' (PCPs) knowledge of energy balance related guidelines and the association with sociodemographic characteristics and clinical care practices., Method: As part of the 2008 U.S. nationally representative National Survey of Energy Balance Related Care among Primary Care Physicians (EB-PCP), 1776 PCPs from four specialties who treated adults (n=1060) or children and adolescents (n=716) completed surveys on sociodemographic information, knowledge of energy balance guidelines, and clinical care practices., Results: EB-PCP response rate was 64.5%. For PCPs treating children, knowledge of guidelines for healthy BMI percentile, physical activity, and fruit and vegetables intake was 36.5%, 27.0%, and 62.9%, respectively. For PCPs treating adults, knowledge of guidelines for overweight, obesity, physical activity, and fruit and vegetables intake was 81.4%, 81.3%, 70.9%, and 63.5%, respectively. Generally, younger, female physicians were more likely to exhibit correct knowledge. Knowledge of weight-related guidelines was associated with assessment of body mass index (BMI) and use of BMI-for-age growth charts., Conclusion: Knowledge of energy balance guidelines among PCPs treating children is low, among PCPs treating adults it appeared high for overweight and obesity-related clinical guidelines and moderate for physical activity and diet, and was mostly unrelated to clinical practices among all PCPs., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The focus of the PhenX (Phenotypes and eXposures) Toolkit is to provide researchers whose expertise lies outside a particular area with key measures identified by experts for uniform use in large-scale genetic studies and other extensive epidemiologic efforts going forward. The current paper specifically addresses the PhenX Toolkit research domain of physical activity and physical fitness (PA/PF), which are often associated with health outcomes. A Working Group (WG) of content experts completed a 6-month consensus process in which they identified a set of 14 high-priority, low-burden, and scientifically supported measures. During this process, the WG considered self-reported and objective measures that included the latest technology (e.g., accelerometers, pedometers, and heart-rate monitors). They also sought the input of measurement experts and other members of the research community during their deliberations. A majority of the measures include protocols for children (or adolescents), adults, and older adults or are applicable to all ages. Measures from the PA/PF domain and 20 other domains are publicly available and found at the PhenX Toolkit website, www.phenxtoolkit.org. The use of common measures and protocols across large studies enhances the capacity to combine or compare data across studies, benefiting both PA/PF experts and non-experts. Use of these common measures by the research community should increase statistical power and enhance the ability to answer scientific questions that previously might have gone unanswered., (Copyright © 2012 American Journal of Preventive Medicine. All rights reserved.)

Background/objectives: Adults often misreport dietary intake; the magnitude varies by the methods used to assess diet and classify participants. The objective was to quantify the accuracy of the Goldberg method for categorizing misreporters on a food frequency questionnaire (FFQ) and two 24-h recalls (24HRs)., Subjects/methods: We compared the Goldberg method, which uses an equation to predict total energy expenditure (TEE), with a criterion method that uses doubly labeled water (DLW), in a study of 451 men and women. Underreporting was classified using recommended cut points and calculated values. Sensitivity and specificity, positive predictive value (PPV) and negative predictive value and the area under the receiver operating characteristic curve (AUC) were calculated. Predictive models of underreporting were contrasted for the Goldberg and DLW methods., Results: AUCs were 0.974 and 0.972 on the FFQ, and 0.961 and 0.938 on the 24HR for men and women, respectively. The sensitivity of the Goldberg method was higher for the FFQ (92%) than the 24HR (50%); specificity was higher for the 24HR (99%) than the FFQ (88%); PPV was high for the 24HR (92%) and FFQ (88%). Simulation studies indicate attenuation in odds ratio estimates and reduction of power in predictive models., Conclusions: Although use of the Goldberg method may lead to bias and reduction in power in predictive models of underreporting, the method has high predictive value for both the FFQ and the 24HR. Thus, in the absence of objective measures of TEE or physical activity, the Goldberg method is a reasonable approach to characterize underreporting.

Background: A significant proportion of the average annual body weight (BW) gain in US adults (~0.5-1 kg/y) may result from modest episodes of positive energy balance during the winter holiday season., Objective: We tested whether holiday BW gain was reduced in participants with high baseline total energy expenditure (TEE) or whether it varied by BMI (in kg/m(2))., Design: In a secondary analysis of previously published data, ΔBW normalized over 90 d from mid-September/mid-October 1999 to mid-January/early March 2000 was analyzed by sex, age, and BMI in 443 men and women (40-69 y of age). TEE was measured by doubly labeled water. High or low energy expenditure was assessed as residual TEE after linear adjustment for age, height, and BW., Results: No correlations between ΔBW and TEE or TEE residuals were found. Sixty-five percent of men and 58% of women gained ≥0.5 kg BW, with ~50% of both groups gaining ≥1% of preholiday BW. Obese men (BMI ≥30) gained more BW than did obese women., Conclusions: A high preholiday absolute TEE or residual TEE did not protect against BW gain during the winter holiday quarter. It is not known whether higher than these typical TEE levels would protect against weight gain or if the observed gain may be attributed to increased food consumption and/or reduced physical activity during the holiday quarter.

Background: Sedentary behaviors predominate modern life, yet we do not fully understand the adverse effects of these behaviors on mortality after considering the benefits of moderate-vigorous physical activity (MVPA)., Objective: We tested the hypotheses that higher amounts of overall sitting time and television viewing are positively associated with mortality and described the independent and combined effects of these sedentary behaviors and MVPA on mortality., Design: In the NIH-AARP Diet and Health Study, we examined 240,819 adults (aged 50-71 y) who did not report any cancer, cardiovascular disease, or respiratory disease at baseline. Mortality was ascertained over 8.5 y., Results: Sedentary behaviors were positively associated with mortality after adjustment for age, sex, education, smoking, diet, race, and MVPA. Participants who reported the most television viewing (≥7 h compared with <1 h/d) were at greater risk of all-cause (HR: 1.61; 95% CI: 1.47, 1.76), cardiovascular (HR: 1.85; 95% CI: 1.56, 2.20), and cancer (HR: 1.22; 95% CI: 1.06, 1.40) mortality after adjustment for MVPA. Overall sitting was associated with all-cause mortality. Even among adults reporting high levels of MVPA (>7 h/wk), high amounts of television viewing (≥7 h/d) remained associated with increased risk of all-cause (HR: 1.47; 95% CI: 1.20, 1.79) and cardiovascular (HR: 2.00; 95% CI: 1.33, 3.00) mortality compared with those reporting the least television viewing (<1 h/d)., Conclusions: Time spent in sedentary behaviors was positively associated with mortality, and participation in high levels of MVPA did not fully mitigate health risks associated with prolonged time watching television. Adults should be encouraged to reduce time spent in sedentary behaviors, when possible, and to participate in MVPA at recommended levels. The NIH-AARP Diet and Health Study was registered at clinicaltrials.gov as NCT00340015.

Context: Advances in device-based measures have led researchers to question the value of reported measures of physical activity or sedentary behavior. The premise of the Workshop on Measurement of Active and Sedentary Behaviors: Closing the Gaps in Self-Report Methods, held in July 2010, was that assessment of behavior by self-report is a valuable approach., Objective: To provide suggestions to optimize the value of reported physical activity and sedentary behavior, we 1) discuss the constructs that devices and reports of behavior can measure, 2) develop a framework to help guide decision-making about the best approach to physical activity and sedentary behavior assessment in a given situation, and 3) address the potential for combining reported behavior methods with device-based monitoring to enhance both approaches., Process: After participation in a workshop breakout session, coauthors summarized the ideas presented and reached consensus on the material presented here., Conclusions: To select appropriate physical activity assessment methods and correctly interpret the measures obtained, researchers should carefully consider the purpose for assessment, physical activity constructs of interest, characteristics of the population and measurement tool, and the theoretical link between the exposure and outcome of interest.

Background: Physical inactivity is a risk factor for obesity, cardiovascular disease, hypertension, and other chronic diseases that are increasingly prevalent in the U.S. and worldwide. Time at work represents a major portion of the day for employed people., Purpose: To determine how employment status (full-time, part-time, or not employed) and job type (active or sedentary) are related to daily physical activity levels in American adults., Methods: Cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) were collected in 2003-2004 and analyzed in 2010. Physical activity was measured using Actigraph uniaxial accelerometers, and participants aged 20-60 years with ≥4 days of monitoring were included (N=1826). Accelerometer variables included mean counts/minute during wear time and proportion of wear time spent in various intensity levels., Results: In men, full-time workers were more active than healthy nonworkers (p=0.004), and in weekday-only analyses, even workers with sedentary jobs were more active (p=0.03) and spent less time sedentary (p<0.001) than nonworkers. In contrast with men, women with full-time sedentary jobs spent more time sedentary (p=0.008) and had less light and lifestyle intensity activity than healthy nonworkers on weekdays. Within full-time workers, those with active jobs had greater weekday activity than those with sedentary jobs (22% greater in men, 30% greater in women)., Conclusions: In men, full-time employment, even in sedentary occupations, is positively associated with physical activity compared to not working, and in both genders job type has a major bearing on daily activity levels., (Copyright © 2011. Published by Elsevier Inc.)

Purpose: The purpose of this study was to examine the independent associations of self-reported and objectively measured (using accelerometers) moderate to vigorous physical activity (MVPA) with physiological and anthropometric biomarkers in a nationally representative sample of U.S. adults., Methods: Data from the cross-sectional National Health and Nutrition Examination Survey 2003-2006 data were analyzed. Adults 20 yr and older (N=5797) with self-reported PA and 4 d or more of accelerometer data were included in the analyses. Pregnant or lactating women were excluded. Outcomes were blood pressure, body mass index, waist circumference, triceps and subscapular skinfolds, cholesterol, triglyceride, C-reactive protein, homocysteine, and insulin resistance and hyperinsulinemia indices., Results: Objectively measured MVPA displayed stronger independent associations with the biomarkers than did self-reported MVPA, even after adjusting for sociodemographic and health factors (adjusted Wald F values=3.9-85.6, P<0.05-0.0001). Self-reported and objectively measured MVPA were independently associated with skinfold measures, HDL, and C-reactive protein when both were included in the model., Conclusions: Objectively measured MVPA displayed stronger associations with physiological and anthropometric biomarkers than self-reported MVPA. However, self-reported and objectively measured MVPA appear to capture distinct aspects of PA that are independently associated with certain biomarkers. Further understanding of the distinct contributions of self-reported and objectively measured PA to health outcomes could help to better identify optimal activity level and pattern., (© 2011 by the American College of Sports Medicine)

Objective: This study examined the association between objectively measured sedentary activity and metabolic syndrome among older adults., Research Design and Methods: Data were from 1,367 men and women, aged ≥ 60 years who participated in the 2003-2006 National Health and Nutrition Examination Survey (NHANES). Sedentary time during waking hours was measured by an accelerometer (<100 counts per minute). A sedentary bout was defined as a period of time >5 min. A sedentary break was defined as an interruption in sedentary time (≥ 100 counts per minute). Metabolic syndrome was defined according to the Adult Treatment Panel (ATP) III criteria., Results: On average, people spent 9.5 h (65% of wear time) as sedentary. Compared with people without metabolic syndrome, people with metabolic syndrome spent a greater percentage of time as sedentary (67.3 vs. 62.2%), had longer average sedentary bouts (17.7 vs. 16.7 min), had lower intensity during sedentary time (14.8 vs. 15.8 average counts per minute), and had fewer sedentary breaks (82.3 vs. 86.7), adjusted for age and sex (all P < 0.01). A higher percentage of time sedentary and fewer sedentary breaks were associated with a significantly greater likelihood of metabolic syndrome after adjustment for age, sex, ethnicity, education, alcohol consumption, smoking, BMI, diabetes, heart disease, and physical activity. The association between intensity during sedentary time and metabolic syndrome was borderline significant., Conclusions: The proportion of sedentary time was strongly related to metabolic risk, independent of physical activity. Current results suggest older people may benefit from reducing total sedentary time and avoiding prolonged periods of sedentary time by increasing the number of breaks during sedentary time.

Individuals who smoke generally have a lower body mass index (BMI) than nonsmokers. The relative roles of energy expenditure and energy intake in maintaining the lower BMI, however, remain controversial. We tested the hypothesis that current smokers have higher total energy expenditure than never smokers in 308 adults aged 40-69 years old of which 47 were current smokers. Energy expenditure was measured by doubly labeled water during a two week period in which the subjects lived at home and performed their normal activities. Smoking status was determined by questionnaire. There were no significant differences in mean BMI (mean ± SD) between smokers and never smokers for either males (27.8+5.1 kg/m2 vs. 27.5+4.0 kg/m2) or females (26.5+5.3 kg/m2 vs. 28.1+6.6 kg/m2), although the difference in females was of similar magnitude to previous reports. Similarly, total energy expenditure of male smokers (3069+764 kcal/d) was not significantly different from that of never smokers (2854+468 kcal/d), and that of female smokers (2266+387 kcal/d) was not different from that of never smokers (2330+415 kcal/d). These findings did not change after adjustment for age, fat-free mass and self-reported physical activity. Using doubly labeled water, we found no evidence of increased energy expenditure among smokers, however, it should be noted that BMI differences in this cohort also did not differ by smoking status.

Purpose: This study compared the ActiGraph accelerometer model 7164 (AM1) with the ActiGraph GT1M (AM2) during self-paced locomotion., Methods: Participants (n = 116, aged 18-73 yr, mean body mass index = 26.1 kg x m(-2)) walked at self-selected slow, medium, and fast speeds around an indoor circular hallway (0.47 km). Both activity monitors were attached to a belt secured to the hip and simultaneously collected data in 60-s epochs. To compare differences between monitors, the average difference (bias) in count output and steps output was computed at each speed. Time spent in different activity intensities (light, moderate, and vigorous) based on the cut points of Freedson et al. was compared for each minute., Results: The mean +/- SD walking speed was 0.7 +/- 0.22 m x s(-1) for the slow speed, 1.3 +/- 0.17 m x s(-1) for medium, and 2.1 +/- 0.61 m x s(-1) for fast speeds. Ninety-five percent confidence intervals (95% CI) were used to determine significance. Across all speeds, step output was significantly higher for the AM1 (bias = 19.8%, 95% CI = -23.2% to -16.4%) because of the large differences in step output at slow speed. The count output from AM2 was a significantly higher (2.7%, 95% CI = 0.8%-4.7%) than that from AM1. Overall, 96.1% of the minutes were classified into the same MET intensity category by both monitors., Conclusions: The step output between models was not comparable at slow speeds, and comparisons of step data collected with both models should be interpreted with caution. The count output from AM2 was slightly but significantly higher than that from AM1 during the self-paced locomotion, but this difference did not result in meaningful differences in activity intensity classifications. Thus, data collected with AM1 should be comparable to AM2 across studies for estimating habitual activity levels.

Background: The 2003 Bureau of Labor Statistics American Time Use Survey (ATUS) contains 438 distinct primary activity variables that can be analyzed with regard to how time is spent by Americans. The Compendium of Physical Activities is used to code physical activities derived from various surveys, logs, diaries, etc to facilitate comparison of coded intensity levels across studies., Methods: This article describes the methods, challenges, and rationale for linking Compendium estimates of physical activity intensity (METs, metabolic equivalents) with all activities reported in the 2003 ATUS., Results: The assigned ATUS intensity levels are not intended to compute the energy costs of physical activity in individuals. Instead, they are intended to be used to identify time spent in activities broadly classified by type and intensity. This function will complement public health surveillance systems and aid in policy and health-promotion activities. For example, at least one of the future projects of this process is the descriptive epidemiology of time spent in common physical activity intensity categories., Conclusions: The process of metabolic coding of the ATUS by linking it with the Compendium of Physical Activities can make important contributions to our understanding of American's time spent in health-related physical activity.

Sedentary behaviors are linked to adverse health outcomes, but the total amount of time spent in these behaviors in the United States has not been objectively quantified. The authors evaluated participants from the 2003-2004 National Health and Nutrition Examination Survey aged >/=6 years who wore an activity monitor for up to 7 days. Among 6,329 participants with at least one 10-hour day of monitor wear, the average monitor-wearing time was 13.9 hours/day (standard deviation, 1.9). Overall, participants spent 54.9% of their monitored time, or 7.7 hours/day, in sedentary behaviors. The most sedentary groups in the United States were older adolescents and adults aged >/=60 years, and they spent about 60% of their waking time in sedentary pursuits. Females were more sedentary than males before age 30 years, but this pattern was reversed after age 60 years. Mexican-American adults were significantly less sedentary than other US adults, and White and Black females were similarly sedentary after age 12 years. These data provide the first objective measure of the amount of time spent in sedentary behavior in the US population and indicate that Americans spend the majority of their time in behaviors that expend very little energy.

Background: Several studies have reported positive associations between pet ownership and a variety of health outcomes. In this study, we explored associations between pet ownership and physical activity in a large, ethnically diverse population-based sample in California., Method: Data from the California Health Interview Survey (CHIS) were used to assess the associations between pet ownership (ie, dog, dog and cat, cat, and non-pet owners) and transportation and leisure walking in a sample of 41,514 adults. Logistic regression was used to assess associations between pet ownership and type of walking, and linear regression was used to assess associations between pet ownership and total minutes walking per week., Results: Dog owners were slightly less likely to walk for transportation than were non-pet owners (OR = 0.91; 95% CI: 0.85 to 0.99) but more likely to walk for leisure than non-pet owners (OR = 1.6; 95% CI: 1.5 to 1.8) in multivariate analyses. Overall, dog owners walked 18.9 (95% CI: 11.4 to 26.4) minutes more per week than non-pet owners. Walking behaviors of cat owners were similar to non-pet owners., Conclusion: Our findings support the moderate association between dog ownership and higher levels of physical activity.

Purpose: To describe physical activity levels of children (6-11 yr), adolescents (12-19 yr), and adults (20+ yr), using objective data obtained with accelerometers from a representative sample of the U.S. population., Methods: These results were obtained from the 2003-2004 National Health and Nutritional Examination Survey (NHANES), a cross-sectional study of a complex, multistage probability sample of the civilian, noninstitutionalized U.S. population in the United States. Data are described from 6329 participants who provided at least 1 d of accelerometer data and from 4867 participants who provided four or more days of accelerometer data., Results: Males are more physically active than females. Physical activity declines dramatically across age groups between childhood and adolescence and continues to decline with age. For example, 42% of children ages 6-11 yr obtain the recommended 60 min x d(-1) of physical activity, whereas only 8% of adolescents achieve this goal. Among adults, adherence to the recommendation to obtain 30 min x d(-1) of physical activity is less than 5%., Conclusions: Objective and subjective measures of physical activity give qualitatively similar results regarding gender and age patterns of activity. However, adherence to physical activity recommendations according to accelerometer-measured activity is substantially lower than according to self-report. Great care must be taken when interpreting self-reported physical activity in clinical practice, public health program design and evaluation, and epidemiological research.

Background: Few large doubly labeled water (DLW) studies have provided an objective measure of total energy expenditure (TEE) in free-living men and women. The committee that developed the 2002 Dietary Reference Intake (DRI) estimated energy requirements (EER) noted that DLW studies in adults aged 40 to 60 y were limited., Objective: We aimed to describe TEE and physical activity energy expenditure in middle-aged men and women by sex, age, menopausal status, and level of obesity, and to compare TEE to the DRI EER., Design: TEE was measured by the DLW method in 450 men and women aged 40-69 y from the Observing Protein and Energy Nutrition Study. Resting metabolic rate was estimated by use of the Mifflin equation., Results: Unadjusted TEE was lower in women than in men (591 kcal/d); however, when the analysis was adjusted for fat-free mass, women had significantly higher TEE than did men (182 kcal/d). This difference appeared to be due to higher physical activity levels in women (physical activity energy expenditure adjusted for FFM was 188 kcal/d greater in women than in men). Mean TEE was lowest in the seventh decade. TEE from DLW was highly correlated (r = 0.93) with EER from the DRI equations., Conclusion: In this population, TEE was higher in women than in men when adjusted for FFM, apparently because of higher physical activity levels in women. There were no significant differences in TEE, FFM, or physical activity levels in women by menopausal status. TEE was inversely associated with age and increased linearly with body mass index. This study corroborates the use of the DRI equations for EER.

Objective: Obesity-related under-reporting of usual dietary intake is one of the most persistent sources of bias in nutrition research. The aim of this paper is to characterize obese and non-obese individuals with respect to reporting errors observed with two common dietary instruments, using energy and protein recovery biomarkers as reference measures., Population and Methods: This report employs data from the Observing Protein and Energy Nutrition (OPEN) study. Analyses are based on stratified samples of 211 (57 obese) men and 179 (50 obese) women who completed 24-h recalls (24HR), food frequency questionnaires (FFQ), doubly labelled water (DLW) and urinary nitrogen (UN) assessments., Results: In obese and non-obese subgroups, FFQ yielded lower energy and protein intake estimates than 24HR, although biomarker-based information indicated under-reporting with both dietary instruments. Gender differences in obesity-related bias were noted. Among women, the DLW-based energy requirement was 378 kcal greater in obese than in non-obese groups; the FFQ was able to detect a statistically significant portion of this extra energy, while the 24HR was not. Among men, the DLW-based energy requirement was 485 kcal greater in the obese group; however, neither FFQ nor 24HR detected this difference in energy requirement. Combining protein and energy estimates, obese men significantly over-reported the proportion of energy from protein using the 24HR, but not with the FFQ. In obese women, no significant reporting error for energy percent protein was observed by either method. At the individual level, correlations between energy expenditure and reported energy intake tended to be weaker in obese than non-obese groups, particularly with the 24HR. Correlations between true and reported protein density were consistently higher than for protein or energy alone, and did not vary significantly with obesity., Conclusion: This work adds to existing evidence that neither of these commonly used dietary reporting methods adequately measures energy or protein intake in obese groups. The 24HR, while capturing more realistic energy distributions for usual intake, may be particularly problematic in the obese.

Background: Levels of physical activity (PA) contribute to health status and outcomes directly and indirectly via the effects of PA on obesity and other risk factors. Much past surveillance has focused on leisure-time physical activity (LTPA), but this may bias estimates of prevalence. This study explores inclusion of non-leisure-time walking and bicycling (NLTWB) used for transportation on the prevalence of adherence to PA recommendations and the magnitude of apparent disparities in adherence for California adults., Methods: Results of the 2001 California Health Interview Survey, a large (n = 55,151) telephone survey were analyzed in 2005 using tabulation and logistic regression., Results: Higher levels of LTPA were associated with youth, males, education, income, Pacific Islanders, and non-Hispanic (NH) whites. Inclusion of NLTWB reduced these differences for all five variables. The largest decreases in disparities in adherence occurred for race/ethnicity, education, and income, with decreases in adherence differences from approximately 18% to 7% for NH white vs Latino, approximately 27% to 16% for more than high school versus less than high school, and approximately 25% to 11% for more than 300% versus less than 100% of poverty level. Logistic regression comparing adherence gives similar results. For example, in respondents with more than high school education versus less than high school education (referent), the odds ratio changed from 2.23 (95% confidence interval [CI] = 2.0-2.4) to 1.7 (1.6-1.9) after the inclusion of NLTWB., Conclusions: Assessment of PA in multiple domains is required to understand differences in total levels of PA for people with different incomes, education levels, and racial/ethnic backgrounds. Inclusion of NLTWB reduces but does not eliminate disparities in adherence to recommended levels of PA.

Background: Previous research suggests food diaries may be more efficient than food frequency questionnaires (FFQ) in detecting a dietary fat-breast cancer relationship. We assessed this further using 4 day food records (FRs) and FFQs in a large sample., Methods: Participants were from the non-intervention group of the dietary modification component of the Women's Health Initiative Clinical Trial: 603 breast cancer cases and 1206 controls matched on age, clinic, and length of follow-up. Relative risks (RRs) were estimated using unconditional logistic regression, adjusted for confounders and for the selection into the trial of women with an FFQ report exceeding 32% calories from fat. Direct comparison of the statistical power of the two instruments used the standardized log RR. An alternative analysis after removing subjects with missing covariate data was also conducted., Results: The RR estimate for breast cancer in the top quintile of total fat intake, adjusted for confounders and total energy, was 1.82 (P for trend 0.02) for the FR but 0.67 for the FFQ (P for trend 0.24). Following adjustment for selection, estimates were 2.09 (P for trend 0.008) for the FR (alternative: 2.54, P for trend 0.006) and 1.71 (P for trend 0.18) for the FFQ (alternative: 1.24, P for trend 0.41). Similar results were seen for fat subtypes, particularly unsaturated fats. Comparisons showed higher statistical power for the FR than the FFQ (e.g. total fat, P = 0.08: alternative P = 0.01)., Conclusions: Alternative instruments, such as FRs, may be preferable to FFQs for evaluating diet-disease relationships in cohort studies. The results support a positive association between dietary fat and breast cancer.

Understanding the prevalence and demographic correlates of physical activity is important for public health and epidemiological research. This analysis examines the association between acculturation and physical activity in a large (approximately 5,000) sample of Hispanic adults from the 2000 National Health Interview Survey. Scores for eight questions concerning language use were summed to produce an acculturation index. Factor analysis indicated that these questions assessed a single underlying construct. Self-reported adherence to recommendations concerning leisure time physical activity increased from 22. 6% in the least acculturated tertile to 47% in the most acculturated tertile. In contrast, prevalence of walking or bicycling for errands decreased from 25.2 to 18.2%, and prevalence of standing or walking during most of the day decreased from 82.8 to 65.6% as acculturation increased. Thus, patterns of physical activity associated with leisure versus nonleisure time differed among Hispanics with varying acculturation levels. Alternatively, cultural factors may have differential effects on responses to questions concerning leisure and nonleisure time physical activity. In either case, assessing both types of activity is important for monitoring and understanding Hispanic health behaviors and interpreting epidemiological studies that involve physical activity in Hispanics.

We reexamined the current practice in estimating the distribution of usual dietary nutrient intakes from population surveys when using self-report dietary instruments, particularly the 24-h recall (24HR), in light of the new data from the Observing Protein and Energy Nutrition Study. In this study, reference biomarkers for energy (doubly labeled water) and protein [urinary nitrogen (UN)], together with multiple FFQs and 24HRs, were administered to 484 healthy volunteers. By using the reference biomarkers to estimate the distributions for energy and protein, the data confirmed previous reports that FFQs generally do not give an accurate impression of the distribution of usual dietary intake. The traditional method applied to 24HRs performed poorly because of underestimating the mean and overestimating the SD of the usual energy and protein intake distributions, and, although the National Research Council and the Iowa State University methods generally give better estimates of the shape of the distribution, they did not improve the estimates of the mean (10-15% underestimation for energy and 6-7% underestimation for protein). Results for urinary potassium, a putative biomarker for potassium intake, and reported potassium intake did not display this underestimation and may reflect either differential underreporting of foods or inadequacy of the potassium biomarker. A large controlled feeding study is required to validate conclusively the potassium biomarker. For energy intake, adjusting its 24HR-based distribution by using the UN biomarker appeared to capture the usual intake distribution quite accurately. Incorporating UN assessments into nutritional surveys, therefore, deserves serious consideration.

Despite recent interest in water intake, few data are available on water metabolism in adults. To determine the average and range of usual water intake, urine output, and total body water, we administered 2H oxide to 458 noninstitutionalized 40- to 79-yr-old adults living in temperate climates. Urine was collected in a subset of individuals (n = 280) to measure 24-h urine production using p-aminobenzoic acid to ensure complete collection. Preformed water intake was calculated from isotopic turnover and corrected for metabolic water and insensible water absorption from humidity. Preformed water intake, which is water from beverages and food moisture, averaged 3.0 l/day in men (range: 1.4-7.7 l/day) and 2.5 l/day in women (range: 1.2-4.6 l/day). Preformed water intake was lower in 70- to 79 (2.8 l/day)- than in 40- to 49-yr-old men and was lower in 70- to 79 (2.3 l/day)- than in 40- to 49- and 50- to 59-yr-old women. Urine production averaged 2.2 l/day in men (range: 0.6-4.9 l/day) and 2.2 l/day in women (0.9-6.0 l/day). There were no age-related differences in results in women, but 60- to 69-yr-old men had significantly higher urine output than 40- to 49- and 50- to 59-yr-old men. Only the 70- to 79-yr-old group included sufficient blacks for a racial analysis. Blacks in this age group showed significantly lower preformed water intake than did whites. Whites had significantly higher water turnover rates than blacks as well. Multivariate regression indicated that age, weight, height, and body mass index explained <12% of the gender-specific variance in water input or urine output, yet repeat measures indicated that within-individual coefficient of variation was 8% for preformed water intake (n = 22) and 9% for 24-h urine production (n = 222). These results demonstrate that water turnover is highly variable among individuals and that little of the variance is explained by anthropometric parameters.

Background: Most large cohort studies have used a food frequency questionnaire (FFQ) for assessing dietary intake. Several biomarker studies, however, have cast doubt on whether the FFQ has sufficient precision to allow detection of moderate but important diet-disease associations. We use data from the Observing Protein and Energy Nutrition (OPEN) study to compare the performance of a FFQ with that of a 24-hour recall (24HR)., Methods: The OPEN study included 484 healthy volunteer participants (261 men, 223 women) from Montgomery County, Maryland, aged 40-69. Each participant was asked to complete a FFQ and 24HR on two occasions 3 months apart, and a doubly labelled water (DLW) assessment and two 24-hour urine collections during the 2 weeks after the first FFQ and 24HR assessment. For both the FFQ and 24HR and for both men and women, we calculated attenuation factors for absolute energy, absolute protein, and protein density., Results: For absolute energy and protein, a single FFQ's attenuation factor is 0.04-0.16. Repeat administrations lead to little improvement (0.08-0.19). Attenuation factors for a single 24HR are 0.10-0.20, but four repeats would yield attenuations of 0.20-0.37. For protein density a single FFQ has an attenuation of 0.3-0.4; for a single 24HR the attenuation factor is 0.15-0.25 but would increase to 0.35-0.50 with four repeats., Conclusions: Because of severe attenuation, the FFQ cannot be recommended as an instrument for evaluating relations between absolute intake of energy or protein and disease. Although this attenuation is lessened in analyses of energy-adjusted protein, it remains substantial for both FFQ and multiple 24HR. The utility of either of these instruments for detecting important but moderate relative risks (between 1.5 and 2.0), even for energy-adjusted dietary factors, is questionable.

Objective: To evaluate whether the doubly labeled water (DLW) method is precise under conditions required for a large-scale evaluation of dietary intake instruments., Design: Energy expenditure was measured in 484 subjects (main study). Subjects received one of five different weight DLW dose bottles prepared in advance of the study. A repeat energy expenditure measure was obtained in a subset of 24 subjects (substudy). DLW measures of energy expenditure were performed over a 2-week interval with urine collection at the beginning and end., Setting: Free-living environment with three clinic visits in the Maryland suburban area of Washington, DC., Subjects: A total of 484 subjects (261 men and 223 women) aged 40-69 y, 24 of whom (13 men and 11 women) participated in a substudy in which DLW was administered a second time., Results: The coefficient of variation of the DLW energy expenditure measurement was 5.1%. This included a 2.9% analytical and a 4.2% physiologic variation. Based on observed initial isotopic enrichment, the preweighed dosages were optimal in 70% of the main study subjects, and 9% received a dose that was less than optimal. Only six subjects (1%) were excluded because the final isotopic enrichment was too low to conduct precise measurement., Conclusions: Use of preweighed DLW dosages did not compromise the precision of the DLW method. The DLW method is a reliable measure of energy expenditure for large-scale evaluations of dietary intake instruments.

Multiple-day food records or 24-hour dietary recalls (24HRs) are commonly used as "reference" instruments to calibrate food frequency questionnaires (FFQs) and to adjust findings from nutritional epidemiologic studies for measurement error. Correct adjustment requires that the errors in the adopted reference instrument be independent of those in the FFQ and of true intake. The authors report data from the Observing Protein and Energy Nutrition (OPEN) Study, conducted from September 1999 to March 2000, in which valid reference biomarkers for energy (doubly labeled water) and protein (urinary nitrogen), together with a FFQ and 24HR, were observed in 484 healthy volunteers from Montgomery County, Maryland. Accounting for the reference biomarkers, the data suggest that the FFQ leads to severe attenuation in estimated disease relative risks for absolute protein or energy intake (a true relative risk of 2 would appear as 1.1 or smaller). For protein adjusted for energy intake by using either nutrient density or nutrient residuals, the attenuation is less severe (a relative risk of 2 would appear as approximately 1.3), lending weight to the use of energy adjustment. Using the 24HR as a reference instrument can seriously underestimate true attenuation (up to 60% for energy-adjusted protein). Results suggest that the interpretation of findings from FFQ-based epidemiologic studies of diet-disease associations needs to be reevaluated.