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The objective of this study was to identify a measure of dietary variety that was associated with improved dietary quality and easily understood by consumers. Dietary quality was measured by nutrient adequacy and intakes of added sugars, saturated fat, cholesterol, and sodium. We developed four definitions of dietary variety: (a) a count of basic commodities consumed; (b) a count of food codes reported; (c) a count of five Food Guide Pyramid (FGP) food groups consumed; and (d) a count of 22 FGP subgroups consumed. The analysis sample included 4,964 men and 4,797 women aged 19 years and older who participated in the Continuing Survey of Food Intakes by Individuals 1994-96. For each day of dietary data, we examined associations of each type of dietary variety with several measures of dietary quality using Spearman's correlations and multivariate linear regression models. After adjusting for energy intake and the number of FGP food group servings, all types of dietary variety were positively associated with mean nutrient adequacy across 15 nutrients, but associations were strongest for commodity-based variety and for 22 FGP subgroup consumption variety. Likewise, all variety measures were inversely associated with intakes of added sugars and saturated fat, with commodity-based variety and 22 FGP subgroup variety the strongest. We conclude that variety measured using 22 FGP subgroups is preferable because it is a good predictor of dietary quality, is relatively simple to calculate, and is easy to explain to consumers.

Despite guidance to consume a variety of foods, the role of dietary variety in ensuring nutrient adequacy is unclear. The aim of this study was to determine whether a commodity-based measure of dietary variety was associated with the probability of nutrient adequacy after adjusting for energy and food group intakes. Subjects were 4969 men and 4800 women >/= 19 y old who participated in the Continuing Survey of Food Intakes for Individuals 1994-1996. Using 24-h recall data, the mean probability of adequacy across 15 nutrients was calculated using the Dietary Reference Intakes. Dietary variety was defined using a commodity-based method similar to that used for the Healthy Eating Index (HEI). Associations were examined in gender-specific multivariate regression models. Energy intake was a strong predictor of the mean probability of adequacy in models controlled for age, BMI, education level, and ethnicity (model R(2) = 0.60 and 0.54 for men and women, respectively). Adding the number of servings from each of the 5 Food Guide Pyramid (FGP) groups to the models significantly improved the model fit (R(2) = 0.69 and 0.66 for men and women). Adding dietary variety again significantly improved the model fit for both men and women (R(2) = 0.73 and 0.70, respectively). Variety counts within the dairy and grain groups were most strongly associated with improved nutrient adequacy. Dietary variety as defined by the HEI contributes an additional component of dietary quality that is not captured by FGP servings or energy intake.

The 1-day food intakes of 1,338 women, aged 19 to 50, who were respondents in the 1985 Continuing Survey of Food Intake by Individuals, were studied. The energy, nutrient, and food intake patterns of smokers, those how had quit smoking, and those who had never smoked cigarettes were compared. Mean energy intakes of smokers (1,627 kcal), those who had never smoked (1,620 kcal), and those who had quit at least 1 year before the interview (1,719 kcal) were not significantly different. Self-reported body weight was significantly different between never-smokers and smokers (p less than .01) and quitters (p less than .05) only for the oldest category of women (ages 41 to 50 years). The consumption of fruits (p less than .001) and vegetables (p less than .01) was significantly lower and the intake of eggs (p less than .01), sugars (p less than .001), regular carbonated soft drinks (p less than .01), coffee (p less than .001), and alcoholic beverages (p less than .001) was significantly higher for women smokers than for non-smokers. After controlling through regression analysis for physical activity, health status, and demographic characteristics, we found that smokers, compared with never-smokers, had significantly lower protein (p less than .04), dietary fiber (p less than .001), vitamin C (p less than .001), and thiamin (p less than .01) intakes and higher cholesterol (p less than .02) intakes per 1,000 kcal.

Data from a year-long study conducted by the US Department of Agriculture's Beltsville Human Nutrition Research Center were used to identify sources of variation in daily energy intakes. A specific hypothesis was that an inverse relationship exists between past body weight and future energy intake whereas a direct relationship exists between past energy intake and future weight. Daily energy intakes of 29 male (n = 13) and female (n = 16) adult subjects were related through linear-regression analysis to sex (+ for males), age (-), height (+), weight (- for past and present measurements, + for future measurement), data collection method (- for duplicate plate), day of week (+ for Friday and Saturday), and month (+ for May, July, August, December, and January). These relationships were statistically significant (p less than 0.05). The results confirmed the hypothesis and were in general agreement with previously published studies that used larger samples but fewer days of data.

The number of days of food intake data needed to estimate the intake of 29 male (n = 13) and female (n = 16) adult subjects, individually and as a group, was determined for food energy and 18 nutrients. The food intake records were collected in a year-long study conducted by the U.S. Department of Agriculture's Beltsville Human Nutrition Research Center. Each individual's average intake of nutrients and standard deviation over the year were assumed to reflect his or her "usual" intake and day-to-day variability. Confidence intervals (P less than 0.05) for each individual's usual intake were constructed, and from these the number of days of dietary records needed for estimated individual and group intake to be within 10% of usual intake was calculated. The results indicated that the number of days of food intake records needed to predict the usual nutrient intake of an individual varied substantially among individuals for the same nutrient and within individuals for different nutrients; e.g., food energy required the fewest days (averaging 31) and vitamin A the most (averaging 433). This was considerably higher than the number of days needed to estimate mean nutrient intake for this group, which ranged from 3 for food energy to 41 for vitamin A. Fewer days would be needed for larger groups.