In this study, a higher variance was found in weight and height between self-reported and actual measured values in men and women.
The differences between self-reported values and measured values were statistically significant and the mean value variance was higher than that in previous Japanese studies [ 18 , 19 ]. Simple correlation analysis in Fig. Both men and women with higher M-weight individuals were more likely to underestimate their weight.
Multiple-stepwise regression analyses were performed to identify which independent variables were good predictors of the differences between SR-weight and M-weight. The present data confirmed a significant positive age effect for this difference in women only. Although many previous studies have investigated the association between age and bias in self-reported values, their results were not always concordant [ 16 , 18 , 21 , 23 , 24 , 36 — 40 ]. In addition, sex differences were found in certain independent variables; weight measurement frequency and M-weight had a significant positive effect only in men.
The results suggest that those who measure their body weight frequently understand their proper body weight well. Average M-weight of participants not maintaining proper weight was significantly higher than that of participants who maintained proper weight for both men and women. This study had several limitations. First, body weight is affected by many factors, the most important of which is metabolic rate related to muscular exercise.
Determining metabolic rate during daily life activities is difficult because several factors affect metabolic rate i. Although height and weight were measured while participants were dressed in light indoor clothing, without footwear, and after not eating or drinking for 2 h, many other factors could not be controlled. Second, in this study sample, 66 young women were missing reported weight data. This might reflect a societal custom or tendency for young women to withhold their body weight.
Despite these limitations, the present findings suggest cautious use of SR-weight in epidemiologic study and health care services. With the growing prevalence of obesity, it is becoming increasingly important to understand estimations of actual body weight relevant to health care service relationships in order to minimize health consequences. In addition, a sex effect was observed in the difference between SR-weight and M-weight, which is consistent with recent research but warrants further exploration.
Unfortunately, the sample did not include enough severely obese respondents for meaningful statistical comparison across sexes or for examination of important characteristics of body image missing data in women. In many studies, self-reported data were obtained days or months before the measurement, and the measured value was obtained from health check-up. In this study, self-reported weight was obtained just before the measurement that was not at the health check-up.
Even though students and company employee have health check-up every year, it is usually only once a year and the time of health check-up is not same. Therefore, it is necessary to ask the time of last weight measurement in the future study. In examining the prevalence of obesity or the association of obesity with various diseases among a general population, SR-BMI should be used with caution given its tendency to be lower than the measured value.
Thus, it is recommended not only to consider these biases carefully in data interpretation, but also to adjust for them when using SR-weight in epidemiological studies and community health care planning. Body mass index and mortality in a middle-aged Japanese cohort.
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What is the feminine form for son-in-law? Study Guides. Trending Questions. Still have questions? Find more answers. Previously Viewed. The Kolmogorov-Smirnov test was used to confirm the normality of the continuous variables weight, height and BMI. To assess the relationship between the self-reported and measured values for weight, height and BMI, the Intraclass Correlation Coefficients ICCs , which evaluated the relationship between the groups, were calculated considering interpersonal variability, i.
This measure is used when we wish to obtain an agreement between two measures for the same individual [ 34 34 Szklo M, Nieto FJ, Miller D.
Epidemiology: Beyond the basics. Am J Epidemiol. It quantifies the agreement between these two measures of the same variable [ 35 35 Lin LI-K. A concordance correlation coefficient to evaluate reproducibility. Measuring agreement in method comparison studies. Stat Methods Med Res. Rev Bras Med Esporte. The predictive equations for weight and height were generated from the self-reported values using the linear regression method, using as a response variable the referred measures, and as an explanatory variable the measures measure [ 38 38 Hayes AJ, Kortt MA, Clarke PM, Brandrup JD.
Estimating equations to correct self-reported height and weight: Implications for prevalence of overweight and obesity in Australia.
Sensitivity, specificity and positive and negative predictive values were calculated for validation by comparing the values measured against the following datasets: a self-reported measures; b measures corrected with their own predictive equation and, c measures corrected with the predictive equation by Duran et al. The degree of agreement between measures was evaluated using the Kappa coefficient. The mean time since diagnosis for these individuals was 6.
There were no statistically significant differences Chi-square test between the total sample and the subsample, which had their values measured, for the variables sex, age, income per capit a, affective status, time since diagnosis and duration of receiving antiretroviral therapy.
The continuous variables, weight, height and BMI, measured and self-reported, showed normal distribution according Kolmogorov-Smirnov test. Upon calculating the linear regression, the following predictive equations for weight and height were generated for the sample according to sex 57 men and 42 women , with their respective coefficients of determination:. In general, the differences between the measures were small; the largest differences were 0.
The confidence intervals were generally small. According to the ICCs, these measures present good correlations between themselves Table 2. Women tend to underestimate weight and overestimate height, which results in an underestimated BMI. Exactly the opposite occurs with men, with overestimation of weight and underestimation of height, which results in an overestimated BMI.
The ICC values for the self-reported measures, the measures corrected with the predictive equations obtained with the sample itself and the measures corrected using the equations proposed by Duran et al. People showing the highest weights have a greater tendency to underestimate weight than other individuals, which partly has effects on the BMI.
Nutritional status was diagnosed using the self-reported measures, the measures corrected based on the predictive equations generated with the sample partitioned by sex and the correction equations proposed by Duran et al. Based on the self-reported measures, the prevalence of low weight in the sample was small, approximately 4. This value precluded the calculations of sensitivity, specificity and predictive values for those individuals.
The prevalence rates of overweight and obesity were For individuals diagnosed as normal and overweight, the diagnostic test evaluation measures were calculated Table 3. The four underweight patients, based on the self-reported measures, were excluded from the calculation. The sensitivity, which represents the proportion of individuals effectively with normal weight or overweight who were diagnosed using the self-reported and the corrected measures as such, was high-namely, higher than Specificity represents the proportions of individuals classified as not having normal weight or being overweight using the self-reported measures and who in fact do not have the classified condition.
All of the values were higher than The positive and negative predictive values were all higher than Accuracy presented equal values
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