We provide an updated version of the Compendium of Physical Activities, a coding scheme that classifies specific physical activity (PA) by rate of energy expenditure. It was developed to enhance the comparability of results across studies using self-reports of PA. The Compendium coding scheme links a five-digit code that describes physical activities by major headings (e.g., occupation, transportation, etc.) and specific activities within each major heading with its intensity, defined as the ratio of work metabolic rate to a standard resting metabolic rate (MET). Energy expenditure in MET-minutes, MET-hours, kcal, or kcal per kilogram body weight can be estimated for specific activities by type or MET intensity. Additions to the Compendium were obtained from studies describing daily PA patterns of adults and studies measuring the energy cost of specific physical activities in field settings. The updated version includes two new major headings of volunteer and religious activities, extends the number of specific activities from 477 to 605, and provides updated MET intensity levels for selected activities.

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Compendium of physical activities: an update of activity codes and MET intensities.

OBJECTIVES: To consider methods and related evidence for evaluating bias in non-randomised intervention studies. DATA SOURCES: Systematic reviews and methodological papers were identified from a search of electronic databases; handsearches of key medical journals and contact with experts working in the field. New empirical studies were conducted using data from two large randomised clinical trials. METHODS: Three systematic reviews and new empirical investigations were conducted. The reviews considered, in regard to non-randomised studies, (1) the existing evidence of bias, (2) the content of quality assessment tools, (3) the ways that study quality has been assessed and addressed. (4) The empirical investigations were conducted generating non-randomised studies from two large, multicentre randomised controlled trials (RCTs) and selectively resampling trial participants according to allocated treatment, centre and period. RESULTS: In the systematic reviews, eight studies compared results of randomised and non-randomised studies across multiple interventions using meta-epidemiological techniques. A total of 194 tools were identified that could be or had been used to assess non-randomised studies. Sixty tools covered at least five of six pre-specified internal validity domains. Fourteen tools covered three of four core items of particular importance for non-randomised studies. Six tools were thought suitable for use in systematic reviews. Of 511 systematic reviews that included non-randomised studies, only 169 (33%) assessed study quality. Sixty-nine reviews investigated the impact of quality on study results in a quantitative manner. The new empirical studies estimated the bias associated with non-random allocation and found that the bias could lead to consistent over- or underestimations of treatment effects, also the bias increased variation in results for both historical and concurrent controls, owing to haphazard differences in case-mix between groups. The biases were large enough to lead studies falsely to conclude significant findings of benefit or harm. Four strategies for case-mix adjustment were evaluated: none adequately adjusted for bias in historically and concurrently controlled studies. Logistic regression on average increased bias. Propensity score methods performed better, but were not satisfactory in most situations. Detailed investigation revealed that adequate adjustment can only be achieved in the unrealistic situation when selection depends on a single factor. CONCLUSIONS: Results of non-randomised studies sometimes, but not always, differ from results of randomised studies of the same intervention. Non-randomised studies may still give seriously misleading results when treated and control groups appear similar in key prognostic factors. Standard methods of case-mix adjustment do not guarantee removal of bias. Residual confounding may be high even when good prognostic data are available, and in some situations adjusted results may appear more biased than unadjusted results. Although many quality assessment tools exist and have been used for appraising non-randomised studies, most omit key quality domains. Healthcare policies based upon non-randomised studies or systematic reviews of non-randomised studies may need re-evaluation if the uncertainty in the true evidence base was not fully appreciated when policies were made. The inability of case-mix adjustment methods to compensate for selection bias and our inability to identify non-randomised studies that are free of selection bias indicate that non-randomised studies should only be undertaken when RCTs are infeasible or unethical. Recommendations for further research include: applying the resampling methodology in other clinical areas to ascertain whether the biases described are typical; developing or refining existing quality assessment tools for non-randomised studies; investigating how quality assessments of non-randomised studies can be incorporated into reviews and the implications of individual quality features for interpretation of a review's results; examination of the reasons for the apparent failure of case-mix adjustment methods; and further evaluation of the role of the propensity score.

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Evaluating non-randomised intervention studies.

Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults. Eight electronic databases were searched to identify observational and experimental studies of adult populations. Searching identified 4,463 potential articles. Initial screening found that 293 examined the relationship between self-reported and directly measured physical activity and met the eligibility criteria. Data abstraction was completed for 187 articles, which described comparable data and/or comparisons, while 76 articles lacked comparable data or comparisons, and a further 30 did not meet the review's eligibility requirements. A risk of bias assessment was conducted for all articles from which data was abstracted. Correlations between self-report and direct measures were generally low-to-moderate and ranged from -0.71 to 0.96. No clear pattern emerged for the mean differences between self-report and direct measures of physical activity. Trends differed by measure of physical activity employed, level of physical activity measured, and the gender of participants. Results of the risk of bias assessment indicated that 38% of the studies had lower quality scores. The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity. Self-report measures of physical activity were both higher and lower than directly measured levels of physical activity, which poses a problem for both reliance on self-report measures and for attempts to correct for self-report – direct measure differences. This review reveals the need for valid, accurate and reliable measures of physical activity in evaluating current and changing physical activity levels, physical activity interventions, and the relationships between physical activity and health outcomes.

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A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review

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Bioelectrical impedance analysis--part I: review of principles and methods.

Bioelectrical impedance analysis-part II: utilization in clinical practice.

Why bioelectrical impedance analysis should be used for estimating adiposity.

Plasma lipid and lipoprotein responses to dietary fat and cholesterol: a meta-analysis.

Body composition assessment has been used to evaluate clinical interventions in research trials, and has the potential to improve patient care in the clinical setting. Body cell mass (BCM) is an important indicator of nutrition status; however, its measurement in the clinic has been limited. BCM can be estimated by the measurement of intracellular water (ICW). The assessment of extracellular water (ECW) is also important because many clinical populations undergo alterations in fluid distribution, particularly individuals with wasting, those receiving dialysis, and obese individuals. Bioimpedance spectroscopy (BIS) is a unique bioimpedance approach that differs in underlying basis from the more readily recognized single-frequency bioelectrical impedance analysis (SF-BIA) in that it does not require the use of statistically derived, population-specific prediction equations. It has the potential advantage of not only measuring total body water (TBW), as does SF-BIA, but also offering the unique capacity to differentiate between ECW and ICW and, thus, to provide an estimate of BCM. This literature review was conducted to compare available BIS devices to multiple dilution for measuring fluid compartments or BCM in a number of populations. Variable results regarding the ability of BIS to measure absolute volumes, as well as the observation of wide limits of variation, make BIS problematic for individual assessment in the clinic, particularly in populations with abnormal fluid distribution or body geometry. BIS has been found to be more accurate for measuring changes in fluid volumes or BCM, particularly in post-surgical and human immunodeficiency virus (HIV)-infected individuals. It is certainly possible that population-specific adjustments may improve the accuracy of BIS for assessing individuals in the clinical setting; however, additional research and development is needed before the method can be accepted for routine clinical use.

Bioimpedance Spectroscopy for Clinical Assessment of Fluid Distribution and Body Cell Mass

Objective: Assess the association between reporting bias of dietary energy intake and the behavioral and psychological profiles in women. Design: At baseline a series of questionnaires were administered to 37 women, (the Marlowe-Crowne Social Desirability Scale, Weinberger Adjustment Inventory (WAI), the Eating Disorder Inventory (EDI), the Restraint Scale and Sorensen-Stunkard’s silhouettes). Subjects received training on how to record dietary records. Subjects recorded three days of dietary records to measure energy intake (EI) during a study to determine total energy expenditure (TEE) using doubly labeled water. Reporting accuracy (RA=EI/TEE×100) was determined for each subject. Statistical analysis of the data used a mixed effects model accounting for within subject variability to determine if the psychological scores were associated with reporting accuracy. Setting and subject: Women were recruited with local advertisements in Tucson, Arizona. The women had a mean (±1 s.d.) age of 43.6±9.3 yrs, body mass index (BMI) of 28.7±8.5 kg/m2 and total body fat (%TBF) of 31.9±7.3%. Results: Age and %TBF were significantly and inversely associated with RA. Furthermore, Social Desirability was negatively associated with RA. Body dissatisfaction and associating a smaller body size than one’s own as being more healthy were also associated with a lower RA. Conclusions: These results suggest that Social Desirability and self image of body shape are associated with RA. Modifications in subject training may reduce the effect of these factors on RA. Sponsorship: This project was supported by a grant from the National Institute of Diabetes, Digestive and Kidney Diseases.

The association of energy intake bias with psychological scores of women.

The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) is a professional society of physicians, nurses, dietitians, pharmacists, allied health professionals, and researchers. A.S.P.E.N. envisions an environment in which every patient receives safe, efficacious, and high quality patient care. A.S.P.E.N.’s mission is to improve patient care by advancing the science and practice of nutrition support therapy.

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Wanda H. Howell

Papers

Why bioelectrical impedance analysis should be used for estimating adiposity.

Plasma lipid and lipoprotein responses to dietary fat and cholesterol: a meta-analysis.

Bioimpedance Spectroscopy for Clinical Assessment of Fluid Distribution and Body Cell Mass

The association of energy intake bias with psychological scores of women.

Definition of Terms, Style, and Conventions Used in A.S.P.E.N. Guidelines and Standards