Bias in Hazard Ratios Arising From Misclassification According to Self-Reported Weight and Height in Observational Studies of Body Mass Index and Mortality.
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ABSTRACT:
SUBMITTER: Flegal KM
PROVIDER: S-EPMC5859975 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To investigate temporal changes in the bias associated with self-reported (as opposed to measured) body mass index (BMI) and explore the relationship of such bias to changing social attitudes towards obesity.Using data from the National Health and Nutrition Examination Survey covering two time periods, 1988-1994 and 2005-2008, discrepancy scores between self-reported vs measured BMI were generated. Changes in the sensitivity of BMI categories based on self-reports were examined for six weight groups, both for the US adult population as a whole and major demographic groups. Linear regression models were used to examine temporal changes in average bias, as well as attitudes about weight within each weight category and by demographic group.Between 2005-2008 and 1988-1994, the bias towards underestimation of a person's BMI based on interview responses has declined among obese individuals, a trend evident in virtually all demographic subgroups explored. Conversely, most demographic groups showed little change in the extent of bias among underweight and normal-weight individuals. Although the 2005-2008 survey respondents underestimated their measured BMI more than the 1988-1994 respondents, this shift can be entirely explained by the increased prevalence of obesity in more recent years. In fact, obese individuals in 2005-2008 were less likely to overreport their height and underreport their weight than their counterparts in the 1988-1994. Evidence from responses to questions about ideal weight and desire to lose weight point in the direction of a shift in social attitudes, which may make it easier to 'admit' to greater weight in surveys.Over the past 20 years, the bias in self-reported height and weight has declined leading to more accurate BMI categorizations based on self-report. This change is likely to affect efforts to find correction factors to adjust BMI scores based on self-reported height and weight.
| S-EPMC3595465 | biostudies-other
Project description:Parental reporting of height and weight was evaluated for US children aged 2-13 years. The prevalence of obesity (defined as a body mass index value (calculated as weight (kg)/height (m)(2)) in the 95th percentile or higher) and its height and weight components were compared in child supplements of 2 nationally representative surveys: the 1996-2008 Children of the National Longitudinal Survey of Youth 1979 Cohort (NLSY79-Child) and the 1997 Child Development Supplement of the Panel Study of Income Dynamics (PSID-CDS). Sociodemographic differences in parent reporting error were analyzed. Error was largest for children aged 2-5 years. Underreporting of height, not overreporting of weight, generated a strong upward bias in obesity prevalence at those ages. Frequencies of parent-reported heights below the Centers for Disease Control and Prevention's (Atlanta, Georgia) first percentile were implausibly high at 16.5% (95% confidence interval (CI): 14.3, 19.0) in the NLSY79-Child and 20.6% (95% CI: 16.0, 26.3) in the PSID-CDS. They were highest among low-income children at 33.2% (95% CI: 22.4, 46.1) in the PSID-CDS and 26.2% (95% CI: 20.2, 33.2) in the NLSY79-Child. Bias in the reporting of obesity decreased with children's age and reversed direction at ages 12-13 years. Underreporting of weight increased with age, and underreporting of height decreased with age. We recommend caution to researchers who use parent-reported heights, especially for very young children, and offer practical solutions for survey data collection and research on child obesity.
| S-EPMC3732021 | biostudies-literature
Project description:ObjectiveTo compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.MethodsWe used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMIPM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMISR). The usefulness of including demographics and perceived weight category in those models was also examined.ResultsThe model that used BMISR, compared to BMIPM, as the only variable produced a larger R2 (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m2) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m2). The performance of the model containing BMISR alone was not substantially improved by the addition of demographics, perceived weight category or BMIPM.ConclusionsOur work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMIM when the time interval between measures is relatively long. Other time frames and alternatives to in-person collection of self-reported data need to be examined.
| S-EPMC5127553 | biostudies-literature
Project description:PURPOSE:Self-reported weight, height, and body mass index (BMI) are commonly used in cancer epidemiology studies, but information on the validity of self-reports among cancer survivors is lacking. This study aimed to evaluate the validity of these self-reported measures among African American (AA) breast cancer survivors, known to have high obesity prevalence. METHODS:We compared the self-reported and measured values among 243 participants from the Women's Circle of Health Follow-Up Study (WCHFS), a population-based longitudinal study of AA breast cancer survivors. Multivariable-adjusted linear regressions were used to identify factors associated with reporting errors. We also examined the associations of self-reported and measured BMI with obesity-related health outcomes using multivariable logistic regressions, with hypertension as an example, to evaluate the impact of misreporting. RESULTS:We found that self-reported and measured values were highly correlated among all and when stratified by participants' characteristics (intraclass correlation coefficients ??0.99, 0.84, and 0.96 for weight, height, and BMI, respectively). The agreement between BMI categories (normal, overweight and obese) based on self-reported and measured data was excellent (kappa?=?0.81). Women who were older, never smoked, had higher grade tumors, or had greater BMI tended to have overestimated BMI calculated from self-reported weight and height. The BMI-hypertension association was similar using self-reported (OR per 5 kg/m2 increase 1.63; 95% CI 1.27-2.10) and measured BMI (1.58; 95% CI 1.23-2.03). CONCLUSIONS:Self-reported weight, height, and BMI were reasonably accurate in the WCHFS. IMPLICATIONS FOR CANCER SURVIVORS:Our study supports the use of these self-reported values among cancer survivors when direct measurements are not possible.
| S-EPMC6054548 | biostudies-literature
Project description:BackgroundThere is widespread concern about the use of body mass index (BMI) to define obesity status in postmenopausal women because it may not accurately represent an individual's true obesity status. The objective of the present study is to examine and adjust for exposure misclassification bias from using an indirect measure of obesity (BMI) compared with a direct measure of obesity (percent body fat).MethodsWe used data from postmenopausal non-Hispanic black and non-Hispanic white women in the Women's Health Initiative (n=126,459). Within the Women's Health Initiative, a sample of 11,018 women were invited to participate in a sub-study involving dual-energy x-ray absorptiometry scans. We examined indices of validity comparing BMI-defined obesity (≥30 kg/m), with obesity defined by percent body fat. We then used probabilistic bias analysis models stratified by age and race to explore the effect of exposure misclassification on the obesity-mortality relationship.ResultsValidation analyses highlight that using a BMI cutpoint of 30 kg/m to define obesity in postmenopausal women is associated with poor validity. There were notable differences in sensitivity by age and race. Results from the stratified bias analysis demonstrated that failing to adjust for exposure misclassification bias results in attenuated estimates of the obesity-mortality relationship. For example, in non-Hispanic white women 50-59 years of age, the conventional risk difference was 0.017 (95% confidence interval = 0.01, 0.023) and the bias-adjusted risk difference was 0.035 (95% simulation interval = 0.028, 0.043).ConclusionsThese results demonstrate the importance of using quantitative bias analysis techniques to account for nondifferential exposure misclassification of BMI-defined obesity. See video abstract at, http://links.lww.com/EDE/B385.
| S-EPMC6481627 | biostudies-literature
Project description:BackgroundCultural pressures to be thin and tall are postulated to cause people to misreport their body weight and height towards more socially normative (i.e., desirable) values, but a paucity of direct evidence supports this idea. We developed a novel non-linear approach to examining weight, height, and BMI misreporting biases and used this approach to examine the association between socially non-normative weight and misreporting biases in adults.MethodsThe Survey of Lifestyles, Attitudes, and Nutrition 2007 (SLÁN 2007), a nationally representative survey of the Republic of Ireland (N = 1942 analyzed) was used. Self-reported weight (height) was classified as under-reported by ≥ 2.0 kg (2.0 cm), over-reported by ≥ 2.0 kg (2.0 cm), or accurately reported within 2.0 kg (2.0 cm) to account for technical errors of measurement and short-term fluctuations in measured weight (height). A simulation strategy was used to define self-report-based BMI as under-estimated by more than 1.40 kg/m2, over-estimated by more than 1.40 kg/m2, or accurately estimated within 1.40 kg/m2. Patterns of biases in self-reported weight, height, and BMI were explored. Logistic regression was used to identify factors associated with mis-estimated BMI and to calculate adjusted odds ratios (AOR) and 99% confidence intervals (99%CI).ResultsThe patterns of bias contributing the most to BMI mis-estimation were consistently, in decreasing order of influence, (1) under-reported weight combined with over-reported height, (2) under-reported weight with accurately reported height, and (3) accurately reported weight with over-reported height. Average bias in self-report-based BMI was -1.34 kg/m2 overall and -0.49, -1.33, and -2.66 kg/m2 in normal, overweight, and obese categories, respectively. Despite the increasing degree of bias with progressively higher BMI categories, persons describing themselves as too heavy were, within any given BMI category, less likely to have under-estimated BMI (AOR 0.5, 99%CI: 0.3-0.8, P < 0.001), to be misclassified in a lower BMI category (AOR 0.3, 99%CI: 0.2-0.5, P < 0.001), to under-report weight (AOR 0.5, 99%CI: 0.3-0.7, P < 0.001), and to over-report height (OR 0.7, 99%CI: 0.6-1.0, P = 0.007).ConclusionsA novel non-linear approach to examining weight, height, and BMI misreporting biases was developed. Perceiving oneself as too heavy appears to reduce rather than exacerbate weight, height, and BMI misreporting biases.
| S-EPMC3121629 | biostudies-literature
Project description:BackgroundAlthough excess body weight has been associated with cancers of the gastric cardia, relationships with gastric cancer at other anatomic subsites are not well defined. Furthermore, subsite-specific associations with attained height have not been fully assessed.MethodsIn 1995-1996, 483,700 Whites enrolling in the multi-state NIH-AARP Diet and Health Study self-reported height and weight. Gastric cancers occurring through 31 December 2006 were ascertained from regional population-based registries. We used Cox regression models to estimate cancer hazard ratios (HRs) for sex-specific tertiles of height and weight and for body mass index (BMI) categories of the World Health Organization.ResultsOne thousand incident cancers (48 % localized to the cardia, 4 % fundus, 6 % corpus, 3 % greater curvature, 6 % lesser curvature, 10 % antrum, 2 % pylorus, 5 % overlapping lesion, and 16 % unspecified) occurred an average of 5.4 years after enrollment. After controlling for effects of age, sex, education, and smoking, we found an inverse association between height and total noncardia cancers (i.e., fundus, corpus, greater and lesser curvatures, antrum, and pylorus), with HRs vs. tertile 1 of 0.65 and 0.71 for tertiles 2 and 3, respectively (p trend = 0.016). Trends were consistent for individual noncardia subsites. In contrast, although weight and BMI were each associated with risk of cardia cancer, neither was associated with total noncardia cancer nor individual subsites.ConclusionNoncardia gastric cancer is associated with short stature but not with high body weight or obesity. The excess risk for shorter adults would be consistent with the known association of chronic H. pylori infection with growth retardation during childhood.
| S-EPMC4007380 | biostudies-literature
Project description:BackgroundChildren with familial dysautonomia (FD) are smaller and grow more slowly than the general population. It is unknown whether this abnormal growth is due to comorbidities that patients with FD live with, or if it is a direct effect of the disease-causing homozygous ELP-1 mutations. Here, we created growth curves for weight, height, and body mass index (BMI) in male and female children with FD to monitor the nutritional status of patients with FD.MethodsWe used the New York University (NYU) FD Registry which includes data from 680 individuals with FD who were followed longitudinally since birth. We generated sex-specific FD growth charts for three age ranges (birth to 36 months, 2 to 20 years, and 2 to 40 years) and compared them to the general population. We generated Kaplan-Meier curves to test the hypothesis that FD patients with low BMI had shorter survival than the rest of the cohort.ResultsGrowth charts generated from 591 individuals with FD show that these patients grow more slowly, reach less height, and gain less weight than the general population. The impact of FD on height was more pronounced in girls than in boys. However, both groups showed markedly low weights, which resulted in low BMI. Low weight, but not height, is already evident at birth. In a subpopulation of FD patients, we found that treatment with growth hormone or spinal fusion surgery helped patients achieve the expected growth characteristic of FD patients, but these treatments did not lead FD patients to achieve the growth pattern of the general population. Contrary to our hypothesis, low BMI had no impact on patient survival.ConclusionsPediatric patients with FD have lower height, weight, and BMI compared to the general pediatric population, but this does not appear to affect survival. Growth curves specific to the FD population are an important tool to monitor growth and nutritional status in pediatric patients with FD when the general population growth curves are of limited use.
| S-EPMC10635437 | biostudies-literature
Project description:ObjectivesThis study aimed to determine an effective survey method for the accurate calculation of obesity prevalence by comparing the self-reported and measured height, weight, and body mass index (BMI) using the 2018 Korea Community Healthy Survey (CHS) data.MethodsRaw data from the 2018 CHS were used to analyze the differences, correlation, and agreement between self-reported and measured height, weight, and BMI.ResultsThe self-reported height was over-reported than the measured height (0.59 cm greater for men and 0.71 cm greater for women), while the self-reported weight was under-reported than the measured weight (0.55 kg less for men and 0.67 kg less for women). Subsequently, the self-reported BMI was under-estimated (0.35 kg/m2 lower for men and 0.49 kg/m2 lower for women) compared with the measured BMI. The kappa statistic and agreement between measured and self-reported values per BMI category (underweight, normal, overweight, and obesity) were 0.82 and 79.6%, respectively.ConclusionsThe prevalence of obesity should be calculated using the measured values provided in the CHS in order to promote local health projects based on accurate evidence.
| S-EPMC9117107 | biostudies-literature
Project description:IntroductionSelf-reported height and weight may lead to inaccurate estimates of associations between BMI and health indicators. The purpose of this study is to assess anthropometric misreporting in emerging adults, compare weight classification by self-reported and direct measures, and examine associations of self-reported and direct measures with cardiometabolic biomarkers.MethodsSelf-reported and directly measured height and weight were obtained in five waves of a nationally representative cohort study of U.S. tenth graders (n=2,785) conducted in 2010-2016; data were analyzed in 2018. Cardiometabolic biomarkers were assessed in three waves in a systematically recruited subsample (n=567). Pearson correlations (r) and Lin's concordance correlations (ρc) evaluated misreporting. Gwet agreement coefficient-1 evaluated weight classification agreement by self-reported and direct measures. Generalized estimating equations examined associations of cardiometabolic biomarkers with self-reported and direct measures.ResultsParticipants overreported height by 1.0-1.7 cm and underestimated weight by 0.6-1.7 kg. Self-reported BMI was 0.6-1.0 lower than measured. Self-reported and measured height, weight, and BMI were strongly correlated (r=0.88-0.97, 0.86-0.98, and 0.65-0.96, respectively) and concordant (ρc=0.82-0.96, 0.94-0.97, and 0.65-0.95, respectively). Agreement of weight classification by self-reported and direct measures ranged from Gwet agreement coefficient-1=0.79-0.94. Associations of ten cardiometabolic biomarkers with self-reported BMI, measured BMI, and waist circumference were similar in magnitude, direction, and precision.ConclusionsSelf-reported and measured BMI were strongly correlated and concordant, providing substantial to near-perfect agreement in weight classification. Findings suggest self-reported BMI in U.S. emerging adults provides nearly identical estimates of associations with cardiometabolic biomarkers.
| S-EPMC6661894 | biostudies-literature