Seven-day recall and other physical activity self-reports in children and adolescents

Sallis, James F.; Buono, Michael J.; Roby, Julia J.; Micale, Frank G.; Nelson, Julie A.

doi:10.1249/00005768-199301000-00014

Cited by 656 publications

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“…Participants maintained a log book so that duration of wear and number of steps could be recorded daily. Over the same period, a self-report PA record was kept to document the amount of time participants spent engaged in moderate-to-vigorous PA [MVPA (17)], which represents higher intensity activities and sports (e.g., running, basketball, soccer). As a proxy measure of sedentary activity, time spent viewing screens (e.g., television, video games, and computer games) during leisure time periods was also collected.…”

Section: Dietary and Physical Activity Assessmentsmentioning

confidence: 99%

Predictors of Metabolically Healthy Obesity in Children

et al. 2014

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OBJECTIVETo determine the prevalence of metabolically healthy obesity (MHO) in children and examine the demographic, adiposity, and lifestyle predictors of MHO status. RESEARCH DESIGN AND METHODSThis cross-sectional study included 8-17 year olds with a BMI ‡85th percentile who were enrolled in a multidisciplinary pediatric weight management clinic from 2005-2010. Demographic, anthropometric, lifestyle, and cardiometabolic data were retrieved by retrospective medical record review. Participants were dichotomized as either MHO or metabolically unhealthy obese (MUO) according to two separate classification systems based on: 1) insulin resistance (IR) and 2) cardiometabolic risk (CR) factors (blood pressure, serum lipids, and glucose). Multivariable logistic regression was used to determine predictors of MHO using odds ratios (ORs) with 95% CIs. RESULTSThe prevalence of MHO-IR was 31.5% (n = 57 of 181) and MHO-CR was 21.5% (n = 39 of 181). Waist circumference (OR 0.33 [95% CI 0.18-0.59]; P = 0.0002) and dietary fat intake (OR 0.56 [95% CI 0.31-0.95]; P = 0.04) were independent predictors of MHO-IR; moderate-to-vigorous physical activity (OR 1.80 [95% CI 1.24-2.62]; P = 0.002) was the strongest independent predictor of MHO-CR. CONCLUSIONSUp to one in three children with obesity can be classified as MHO. Depending on the definition, adiposity and lifestyle behaviors both play important roles in predicting MHO status. These findings can inform for whom health services for managing pediatric obesity should be prioritized, especially in circumstances when boys and girls present with CR factors.In Canada, numerous multidisciplinary clinics offer weight management care for children with obesity (1), most of which are affiliated with children's hospitals. The supply of these services is exceeded by the potential demand since there are .2 million young Canadians (2,3) who are either overweight or obese and eligible to receive health services in these clinics. Because of the demand for weight management care, in circumstances when services are limited or difficult to access, there is a need to prioritize service delivery in these specialized centers for those individuals who are at greatest cardiometabolic health risk. By distinguishing individuals with obesity based on their relative health risks, those at lower health risk can be guided to less intensive services (e.g., self-management resources or outpatient dietitian counseling), whereas their peers at higher health risk can be directed to more intensive services (e.g., multidisciplinary obesity management or bariatric surgery). The heterogeneous

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Section: Dietary and Physical Activity Assessmentsmentioning

confidence: 99%

Predictors of Metabolically Healthy Obesity in Children

et al. 2014

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“…Misreporting of EE could be due to misreporting of frequency, intensity or duration of activity; however, this has not been much studied. One study indicates that reports of vigorous physical activity were relatively accurate 17 , and in another study it was found that moderate intensity activities were underestimated 18 .…”

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confidence: 99%

Characteristics of misreporters of dietary intake and physical activity

Rasmussen¹,

Matthiessen²,

Biltoft-Jensen³

et al. 2007

Public Health Nutr.

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Objective: To characterise misreporters of energy intake (EI) and energy expenditure (EE). Design: Cross-sectional study, using a validated position and motion instrument, ActiReg w , as the reference method to study misreporters of EI and of EE. EI was measured using a dietary record and EE using a physical activity questionnaire (PAQ). Misreporters were defined as subjects outside the 95% confidence limits of agreement between EI or EE reported/EE measured. Setting: Free-living Danish volunteers. Subjects: One hundred and thirty-eight volunteers aged between 20 and 59 years. Results: Body mass index, smoking, 'try to eat healthily' and worries about weight were related to degree of under-reported EI. The percentage energy from added sugar was lowest (P , 0.001) and the percentage energy from protein (P , 0.001) highest in under-reporters compared with acceptable reporters. Subjects who reported being very physically active at work or in leisure time reported a higher EE than measured EE compared with less physically active subjects (P , 0.05). Likewise, subjects who regard themselves as fit or very fit reported a higher EE than subjects who regard themselves as moderately fit (P , 0.05). Possible over-reporters reported less time as very light activity (P ¼ 0.007), more time as moderate activity (P ¼ 0.01) and more time as vigorous activity (P ¼ 0.02) than acceptable reporters. Conclusions: Under-reporting of EI should always be taken into consideration; however, only a few characteristics of under-reporters are consistent among studies. Misreporting of EI was more prevalent than misreporting of EE. The level of physical activity more than the time spent involved in various activities was misreported. Keywords Dietary records Energy intake Energy expenditure Physical activity MisreportingUnder-reporting of energy intake (EI) is a common problem in dietary studies. Characteristics of underreporters have been investigated in a number of studies using various methods, but the results have not been consistent. The most common finding is a relationship between increased under-reporting and increased body mass index (BMI). This relationship is found in most 1 -4 but not all 5,6 studies. However, a relationship with body fat is not always found; in a study in women, a relationship between percentage body fat and under-reporting was not found, although a relationship with BMI was found 2 , whereas in another study the opposite relationships were found 6 . Under-reporting has been found to increase with increasing age 1,3,7 and to be more frequent in women than in men 5 -7 . However, in Denmark, this trend has not been identified recently 8 . Other characteristics of underreporters are less frequently identified. Smokers have been found to under-report EI less frequently than non-smokers 1,7,9 , although this finding has not been consistent 10 . Furthermore, educational level has been associated with under-reporting, but both a high and a low educational level has been related to under-reporting, and many stud...

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“…20,27 It might be thought that the cutoff point of 2,000 counts/ min for classifying moderate and vigorous physical activity was high for this age group. This would partly explain the fact that the LAF overestimates physical activity compared with the accelerometer, resulting in poor magnitude of correlation.…”

Section: Discussionmentioning

confidence: 92%

“…29 The LAF may assist in remembering the types of activities carried out, an important aspect in measuring the construct. 3 Sallis et al 20 (1993) compared four questionnaires aimed at nine-year-old children, with different formats. The questionnaire which did not contain a list of physical activities had the worst results for validity.…”

Section: Discussionmentioning

confidence: 99%

Estudo de validade do questionário "Lista de Atividades Físicas" em crianças

et al. 2013

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OBJECTIVE:To assess the validity and operational equivalence of the "Physical Activity Checklist" in children. METHODS:This study complements the cross-cultural adaptation of the Physical Activity Checklist Interview, conducted with 118 school children aged between seven and ten years old, enrolled from the second to the fi fth grades of primary education in the city of São Paulo, SP, Southeastern Brazil, in 2009. The questionnaire enables the quantifi cation of time spent in moderate and vigorous physical activities and sedentary activities and the total and weighted metabolic costs. The accelerometer was adopted as a criterion measure of physical activity. The variables total physical activity (counts/min) and time spent in moderate to vigorous physical activity were quantifi ed. The concurrent validity was assessed by Pearson's correlation coeffi cient while the operational equivalence was assessed by data concerning the duration and evaluation of the interview. RESULTS:The values for the correlation coeffi cient between the results from the questionnaire and the accelerometer ranged from 0.34 to 0.40. It was found that LAF overestimates time spent doing moderate and vigorous physical activity when compared to the accelerometer. The average duration of the interviews was 24 minutes (minimum = 13 min, maximum = 41 min, sd = 5 min). The interview item showing the poorest result was the children's ability to estimate time (poor or fair in 24.8% of interviews). CONCLUSIONS:In relation to the original version, the questionnaire "Physical Activity Checklist" presents similar indices of concurrent validity and operational equivalence, confi rming the appropriateness of the cross-cultural adaptation.

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Seven-day recall and other physical activity self-reports in children and adolescents

Cited by 656 publications

References 0 publications

Predictors of Metabolically Healthy Obesity in Children

Predictors of Metabolically Healthy Obesity in Children

Characteristics of misreporters of dietary intake and physical activity

Estudo de validade do questionário "Lista de Atividades Físicas" em crianças

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