JoAnne W. Ray

Who Underreports Dietary Intake in a Dietary Recall? Evidence from the Second National Health and Nutrition Examination Survey.

The present study sought to identify the presence and degree of apparent underreporting of dietary intake in 11,663 participants in the Second National Health and Nutrition Examination Survey (NHANES II). Self-reported dietary intake was compared with estimated basal metabolic rate. Underreporting was based on cutoff limits that identified plausible levels of energy expenditure for adult individuals. Results indicated that up to 31% of adults in this sample may have underreported dietary intake. Those individuals at greatest risk of underreporting were less well educated and heavier. The Sex x Race interaction indicated that for both ethnic categories, women were more likely to underreport than men, but the difference between men and women was greater among Caucasian participants. It is concluded that such factors as reduced energy needs, deliberate falsification, and measurement error inherent in dietary assessment contribute to apparent underreporting, and this occurs in a large percentage of dietary data.

How much weight gain occurs following smoking cessation ? A comparison of weight gain using both continuous and point prevalence abstinence

Estimates of postcessation weight gain vary widely. This study determined the magnitude of weight gain in a cohort using both point prevalence and continuous abstinence criteria for cessation. Participants were 196 volunteers who participated in a smoking cessation program and who either continuously smoked (n = 118), were continuously abstinent (n = 51), or who were point prevalent abstinent (n = 27) (i.e., quit at the 1-year follow-up visit but not at others). Continuously abstinent participants gained over 13 lbs. (5.90 kg) at 1 year, significantly more than continuously smoking (M = 2.4 lb.) and point prevalent abstinent participants (M = 6.7 lbs., or 3.04 kg). Individual growth curve analysis confirmed that weight gain and the rate of weight gain (pounds per month) were greater among continuously smoking participants and that these effects were independent of gender, baseline weight, smoking and dieting history, age, and education. Results suggest that studies using point prevalence abstinence to estimate postcessation weight gain may be underestimating postcessation weight gain.

How interchangeable are different estimators of effect size

The computation of effect sizes is a key feature of meta-analysis. In treatment outcome meta-analyses, the standardized mean difference statistic on posttest scores (d) is usually the effect size statistic used. However, when primary studies do not report the statistics needed to compute d, many methods for estimating d from other data have been developed. Little is known about the accuracy of these estimates, yet meta-analysts frequently use them on the assumption that they are estimating the same population parameter as d. This study investigates that assumption empirically. On a sample of 140 psychosocial treatment or prevention studies from a variety of areas, the present study shows that these estimates yield results that are often not equivalent to d in either mean or variance. The frequent mixing of d and other estimates of d in past meta-analyses, therefore, may have led to biased effect size estimates and inaccurate significance tests.

The prospective relationships between smoking and weight in a young, biracial cohort: The Coronary Artery Risk Development in Young Adults study.

This study examined the relationship between smoking status and weight change from baseline to Year 7 in a large biracial cohort, the Coronary Artery Risk Development in Young Adults study. Unadjusted for covariates, only male smokers weighed less than nonsmokers, with no effect among women. Adjusted for covariates, male and female smokers weighed less than nonsmokers at baseline, adjusted for age, total energy intake, alcohol intake, and physical fitness. Over the 7-year follow-up, all smoking status groups gained weight, including continuous smokers and initiators. Weight gain was greatest among those who quit smoking. Weight gain attributable to smoking cessation was 4.2 kg for Whites and 6.6 kg for Blacks. Smoking had a small weight-attenuating effect on Blacks. No such effects, however, were observed among Whites. These results suggest, at least in younger smokers, that smoking has minimal impact on body weight.

ARE SELF-REPORTS OF SMOKING RATE BIASED? EVIDENCE FROM THE SECOND NATIONAL HEALTH AND NUTRITION EXAMINATION SURVEY

This study determined evidence for digit preference in self-reports of smoking in the Second National Health and Nutrition Examination Survey (NHANES II). Subjects were 4275 adult smokers. Self-reports of smoking showed a marked degree of digit preference, with the vast majority of smokers reporting in multiples of 10 cigarettes per day. When number per day was compared to an objective measure of smoking exposure (carboxyhemoglobin; n = 2070) the distribution was found to be significantly assymetrical. Analysis of the distribution of COHb and various levels of number per day indicates that the differences in distribution are not due to variability in COHb. Heavier smokers, Caucasians, and those with less education were more likely to report a digit preference than lighter smokers. African-Americans, and those with more education. Results suggest that self-reports of number of cigarettes per day may be biased towards round numbers (particularly 20 cigarettes per day). Implications for assessment of smoking behavior are discussed.