946 resultados para Self-reported Weight


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The aim of this study was to investigate the role of motivation, anxiety and self-efficacy in self-reported behaviour that may be important for weight loss and weight maintenance. One hundred and twenty-nine females aged 18–81 years were recruited from a variety of social, sporting venues and work places within a local community. Participants completed questionnaires assessing their levels of participation and perseverance in weight management activities, their motivation levels, their anxiety levels (State Anxiety Inventory) and their levels of self-efficacy for weight management behaviours. Motivation was found to play a major role in participation in weight management activities. Anxiety and self-efficacy played no significant role. The findings are discussed in relation to previous studies, and directions for future studies are indicated. It is argued that the level of motivation is a key factor that should be taken into account for each individual engaging in women's weight management programmes, and that further research should be undertaken to identify other relevant factors.

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BACKGROUND: Self-reported anthropometric data are commonly used to estimate prevalence of obesity in population and community-based studies. We aim to: 1) Determine whether survey participants are able and willing to self-report height and weight; 2) Assess the accuracy of self-reported compared to measured anthropometric data in a community-based sample of young people.

METHODS: Participants (16-29 years) of a behaviour survey, recruited at a Melbourne music festival (January 2011), were asked to self-report height and weight; researchers independently weighed and measured a sub-sample. Body Mass Index was calculated and overweight/obesity classified as ≥25 kg/m². Differences between measured and self-reported values were assessed using paired t-test/Wilcoxon signed ranks test. Accurate report of height and weight were defined as <2 cm and <2 kg difference between self-report and measured values, respectively. Agreement between classification of overweight/obesity by self-report and measured values was assessed using McNemar's test.

RESULTS: Of 1405 survey participants, 82% of males and 72% of females self-reported their height and weight. Among 67 participants who were also independently measured, self-reported height and weight were significantly less than measured height (p=0.01) and weight (p<0.01) among females, but no differences were detected among males. Overall, 52% accurately self-reported height, 30% under-reported, and 18% over-reported; 34% accurately self-reported weight, 52% under-reported and 13% over-reported. More females (70%) than males (35%) under-reported weight (p=0.01). Prevalence of overweight/obesity was 33% based on self-report data and 39% based on measured data (p=0.16).

CONCLUSIONS: Self-reported measurements may underestimate weight but accurately identified overweight/obesity in the majority of this sample of young people.

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Using a nationally representative sample of 142 783 middle school (13-15 years old) and high school (16-18 years old) students in South Korea, this study examined whether (1) overweight and obesity are more likely to be associated with lower self-reported school performance; (2) overweight and obese students are more likely to enrol in a vocational high school as opposed to a general high school; (3) the association between obesity and poorer self-reported school performance is mediated through body image stress and health status. We found that excess weight was negatively associated with self-reported school performance among middle and general high school students, and that obese students had a higher probability of being enrolled in a vocational over a general high school. We did not find strong evidence on the mediating role of body image stress and health status.

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A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.

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Background: Accurate assessment tools are required for the surveillance of physical activity (PA) levels and the assessment of the effect of interventions. In addition, increasing awareness of PA is often used as the first step in pragmatic behavioural interventions, as discrepancies between the amount of activity an individual perceives they do and the amount actually undertaken may act as a barrier to change. Previous research has demonstrated differences in the amount of activity individuals report doing, compared to their level of physical activity when measured with an accelerometer. Understanding the characteristics of those whose PA level is ranked differently when measured with either self-report or accelerometry is important as it may inform the choice of instrument for future research. The aim of this project was to determine which individual characteristics are associated with differences between self-reported and accelerometer measured physical activity.

Methods: Participant data from the 2009 wave of the Commuting and Health in Cambridge study were used. Quartiles of self-reported and accelerometer measured PA were derived by ranking each measure from lowest to highest. These quartiles were compared to determine whether individuals’ physical activity was ranked higher by either method. Multinomial logistic regression models were used to investigate the individual characteristics associated with different categories of mismatch.

Results: Data from 486 participants (70% female) were included in the analysis. In adjusted analyses, the physical activity of overweight or obese individuals was significantly more likely to be ranked higher by self-report than by accelerometer than that of normal-weight individuals (OR = 2.07, 95%CI = 1.28–3.34), particularly among women (OR = 3.97, 95%CI = 2.11–7.47).

Conclusions: There was a greater likelihood of mismatch between self-reported and accelerometer measured physical activity levels in overweight or obese adults. Future studies in overweight or obese adults should consider employing both methods of measurement.

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BACKGROUND: The escalating prevalence of obesity might prompt obese subjects to consider themselves as normal, as this condition is gradually becoming as frequent as normal weight. In this study, we aimed to assess the trends in the associations between obesity and self-rated health in two countries. METHODS: Data from the Portuguese (years 1995-6, 1998-6 and 2005-6) and Swiss (1992-3, 1997, 2002 and 2007) National Health Surveys were used, corresponding to more than 130,000 adults (64,793 for Portugal and 65,829 for Switzerland). Body mass index and self-rated health were derived from self-reported data. RESULTS: Obesity levels were higher in Portugal (17.5% in 2005-6 vs. 8.9% in 2007 in Switzerland, p < 0.001) and increased in both countries. The prevalence of participants rating their health as "bad" or "very bad" was higher in Portugal than in Switzerland (21.8% in 2005-6 vs 3.9% in 2007, p < 0.001). In both countries, obese participants rated more frequently their health as "bad" or "very bad" than participants with regular weight. In Switzerland, the prevalence of "bad" or "very bad" rates among obese participants, increased from 6.5% in 1992-3 to 9.8% in 2007, while in Portugal it decreased from 41.3% to 32.3%. After multivariate adjustment, the odds ratio (OR) of stating one self's health as "bad" or "very bad" among obese relative to normal weight participants, almost doubled in Switzerland: from 1.38 (95% confidence interval, CI: 1.01-1.87) in 1992-3 to 2.64 (95% CI: 2.14-3.26) in 2007, and similar findings were obtained after sample weighting. Conversely, no such trend was found in Portugal: 1.35 (95% CI: 1.23-1.48) in 1995-6 and 1.52 (95% CI: 1.37-1.70) in 2005-6. CONCLUSION: Obesity is increasing in Switzerland and Portugal. Obesity is increasingly associated with poorer self-health ratings in Switzerland but not in Portugal.

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The purpose of this cross sectional survey design was to examine self-reported health status and lifestyle behaviours of the residents of the Town of Fort Erie, Ontario, as related to the Canadian Community Health Survey. Using a mail-out survey, entitled the Fort Erie Survey of Health (FESH), a probability cluster sampling technique was used to measure self-reported health status (present health, health conditions, health challenges, functional health limitations) and lifestyle behaviour (smoking, alcohol use, drug use, physical activity, fruit and vegetable consumption, body weight, and gaming). Each variable was described and analyzed in relation to socio-economic variables, age and gender. The findings from this study were compared to the Canadian Community Health Survey 2000/2001. Overall, 640 surveys were completed. The majority of Fort Erie residents rated their present health as good and were satisfied with their overall health and quality of life. The main chronic conditions reported were arthritis, back pain and heart disease. Other main health problems reported were vision, sleeping and chronic pain. Overall, 14.6% smoke; 58.8% engaged in physical activity either occasionally or never as opposed to regularly engaging in physical activity; 52.1% did not eat the required daily fruits and vegetables; and 40.0% were in the overweight category. Persons who practiced one healthy lifestyle behaviour were more likely to practice other healthy promoting behaviours. Therefore, health promotion programs are best designed to address multiple risk factors simultaneously. The ffiSH was generally consistent with the Canadian Community Health Survey in the overall findings. A small number of inconsistencies were identified that require further exploration to determine if they are unique to this community.

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In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual’s identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ −0.70 kg [−3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ −0.29 kg m−2 [−1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study.

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The study aimed at verifying the associated factors of self-perceived body changes in adults living with HIV in highly-active antiretroviral therapy (HAART) in the city of Sao Paulo, Brazil. This cross-sectional study was conducted among people living with HIV on HAART for at least three months. A standardized questionnaire was used for assessing self-perceived body changes. Associated factors relating to self-reported body changes in people living with HIV (PLHIV) were assessed with Student`s t-test and chi-square test. In total, 507 patients were evaluated. The mean time since diagnosis was 6.6 years [standard deviation (SD)+/-4.1], and the mean duration of HAART was 5.1 years (SD+/-3.3). Self-perceived body changes were reported by 79.5% of the participants and were associated with viral load and duration of HAART. Fibre intake was lower among males who gained in abdominal fat (p=0.035). HAART-related body changes were reported by the large majority of the population and were associated with demographic and clinical variables.

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Purpose: To evaluate the influence of high-intensity progressive resistance training (PRT) on self-reported physical and mental health in older persons with type 2 diabetes.

Methods: We performed a 12-month RCT with 36 overweight men and women with type 2 diabetes (aged 60-80 years) who were randomly assigned to a moderate weight-loss diet plus PRT (PRT&WL) or a moderate weight-loss diet plus a control (stretching) program (WL). Gymnasium-based training for 6 months was followed by an additional 6 months of home-based training. The SF-36 (v1) questionnaire was used to obtain physical (PCS) and mental (MCS) health component summary scores at baseline, 6 and 12 months.

Results: Subject retention was 81% and 72% after 6 and 12 months respectively. Exercise adherence during gymnasium- and home-based training was 88% and 73% for the PRT&WL group, and 85% and 78.1% for the WL group respectively. In a regression model adjusted for age and sex, PCS improved in the PRT&WL group compared to the WL group after 6 months of gymnasium-based training (2.3 versus -2.0, p = 0.05), which persisted after 12 months training (0.7 versus -4.1, p = 0.03). There were no between-group differences at 6 or 12 months for the MCS.

Conclusion: High-intensity PRT was effective in improving self-reported physical health, but not mental health. PRT provides an effective exercise alternative in lifestyle management for older adults with type 2 diabetes.

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Background
Error in self-reported measures of obesity has been frequently described, but the effect of self-reported error on recruitment into diabetes prevention programs is not well established. The aim of this study was to examine the effect of using self-reported obesity data from the Finnish diabetes risk score (FINDRISC) on recruitment into the Greater Green Triangle Diabetes Prevention Project (GGT DPP).

Methods
The GGT DPP was a structured group-based lifestyle modification program delivered in primary health care settings in South-Eastern Australia. Between 2004–05, 850 FINDRISC forms were collected during recruitment for the GGT DPP. Eligible individuals, at moderate to high risk of developing diabetes, were invited to undertake baseline tests, including anthropometric measurements performed by specially trained nurses. In addition to errors in calculating total risk scores, accuracy of self-reported data (height, weight, waist circumference (WC) and Body Mass Index (BMI)) from FINDRISCs was compared with baseline data, with impact on participation eligibility presented.

Results
Overall, calculation errors impacted on eligibility in 18 cases (2.1%). Of n = 279 GGT DPP participants with measured data, errors (total score calculation, BMI or WC) in self-report were found in n = 90 (32.3%). These errors were equally likely to result in under- or over-reported risk. Under-reporting was more common in those reporting lower risk scores (Spearman-rho = −0.226, p-value < 0.001). However, underestimation resulted in only 6% of individuals at high risk of diabetes being incorrectly categorised as moderate or low risk of diabetes.

Conclusions
Overall FINDRISC was found to be an effective tool to screen and recruit participants at moderate to high risk of diabetes, accurately categorising levels of overweight and obesity using self-report data. The results could be generalisable to other diabetes prevention programs using screening tools which include self-reported levels of obesity.

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Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.

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In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual's identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ -0.70 kg [-3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ -0.29 kg m(-2) [-1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study. TRIAL REGISTRATION: NCT01530139 ( http://clinicaltrials.gov/show/NCT01530139 ).

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PURPOSE: Understanding factors that influence accurate assessment of physical activity (PA) and sedentary behavior (SB) is important to measurement development, epidemiologic studies, and interventions. This study examined agreement between self-reported (International Physical Activity Questionnaire-Long Form [IPAQ-LF]) and accelerometry-based estimates of PA and SB across six countries and identified correlates of between-method agreement. METHODS: Self-report and objective (accelerometry-based) PA and SB data were collected in 2002-2011 from 3865 adult participants in eight cities from six countries (Belgium, Czech Republic, Denmark, Spain, United Kingdom, and United States). Between-method relative agreement (correlation) and absolute disagreement (mean difference between conceptually and intensity-matched IPAQ-LF and accelerometry-based PA and SB variables) were estimated. Also, sociodemographic characteristics and PA patterns were examined as correlates of between-method agreement. RESULTS: Observed relative agreement (relationships of IPAQ-LF with accelerometry-based PA and SB variables) was small to moderate (r = 0.05-0.37) and was moderated by sociodemographic (age, sex, weight status, and education) and behavioral (PA-type) factors. The absolute disagreement was large, with participants self-reporting higher PA intensity and total time in moderate-to-vigorous-intensity PA than accelerometry. Also, self-reported sitting time was lower than accelerometry-based sedentary behavior. After adjusting for sociodemographic and behavioral factors, the absolute disagreement between pairs of IPAQ-LF and accelerometry-based PA variables remained significantly different across cities/countries. CONCLUSIONS: Present findings suggest systematic cultural and/or linguistic and sociodemographic differences in absolute agreement between the IPAQ-LF and the accelerometry-based PA and SB variables. These results have implications for the interpretation of international PA and SB data and correlate/determinant studies. They call for further efforts to improve such measures.