摘要：Objectives. We evaluated bias in estimated obesity prevalence owing to error in parental reporting. We also evaluated bias mitigation through application of Centers for Disease Control and Prevention’s biologically implausible value (BIV) cutoffs. Methods. We simulated obesity prevalence of children aged 2 to 5 years in 2 panel surveys after counterfactually substituting parameters estimated from 1999–2008 National Health and Nutrition Examination Survey data for prevalence of extreme height and weight and for proportions obese in extreme height or weight categories. Results. Heights reported below the first and fifth height-for-age percentiles explained between one half and two thirds, respectively, of total bias in obesity prevalence. Bias was reduced by one tenth when excluding cases with height-for-age and weight-for-age BIVs and by one fifth when excluding cases with body mass–index-for-age BIVs. Applying BIVs, however, resulted in incorrect exclusion of nonnegligible proportions of obese children. Conclusions. Correcting the reporting of children’s heights in the first percentile alone may reduce overestimation of early childhood obesity prevalence in surveys with parental reporting by one half to two thirds. Excluding BIVs has limited effectiveness in mitigating this bias. The US Institute of Medicine now highlights early childhood as a critical period for obesity-related public health prevention. 1 Few studies of kindergarten age or preschool age obesity, however, offer national generalizability. 2–11 Among those that do, more costly measurement protocols may be sacrificed for longer follow-ups and greater breadth of determinants. 3,8–11 These trade-offs are frequently necessary in data sources used in multilevel and dynamic policy models, including those systems scientists have developed. 12 In the only 2 nationally representative US panel surveys with continuous measurement of individual, family, household, and environmental data from birth through early adulthood—the Panel Study of Income Dynamics (PSID) and the National Longitudinal Survey of Youth (NLSY79)—height and weight in early childhood are assessed predominantly via parent report rather than direct measurement. Their accurate assessment is crucial because the body mass index (BMI), from which obesity prevalence is typically derived in population studies, 13 is calculated from weight in kilograms divided by height in meters squared. Unfortunately, the accuracy of obesity prevalence estimated from parent-reported data on height and weight is known to be low, especially among young children. 14–20 In the 1999–2004 National Health Interview Survey and the 2003–2004 National Survey of Child Health, both of which rely exclusively on the parental reporting of height and weight, obesity prevalence has been found to be overestimated by a factor of 5 for children aged 2 to 3 years and by a factor of 3 for children aged 3 to 7 years. 16 Such extremely high biases led the National Survey of Child Health to cease releasing parent-reported height and weight and calculated BMI for children younger than 10 years. 21 A useful first step toward understanding and correcting these very large biases is separating the contributions to bias of the misreporting of weight from the misreporting of height. This is our primary goal. It has been remarked that parents’ perceptions of their young children’s heights do not keep up with their rapid growth in this period of childhood and that the potential for height misreporting to generate bias in obesity prevalence is increased by the squaring of height in the BMI denominator. 20 Errors in the reporting of very high values of weight, on the other hand, directly affect whether BMI crosses the obesity threshold. In a previous study, 15 we used a graphical method of diagnosis and found implausibly high prevalence of very low height for age for children aged 2 to 5 years in the PSID and NLSY79. We have extended that study by developing and applying a simulation method to quantify the resulting bias in obesity prevalence and then comparing it with the bias resulting from parental misreporting of weight. We do so alternately in conjunction with, and ignoring, the US Centers for Disease Control and Prevention (CDC) height-for-age, weight-for-age, and BMI-for-age biologically implausible values (BIVs). 22,23
