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RESEARCH AND PRACTICE |
Sibylle Kranz is with the Department of Nutritional Sciences and the Population Research Institute, Pennsylvania State University, State College, Pa. Anna Maria Siega-Riz is with the Department of Nutrition, School of Public Health, and the Department of Maternal and Child Health, and Amy H. Herring is with the Department of Biostatistics, University of North Carolina at Chapel Hill.
Correspondence: Requests for reprints should be sent to Sibylle Kranz, PhD, RD, Population Research Institute, 5-G Henderson Bldg, Pennsylvania State University, University Park, PA 16802 (e-mail: sxk72{at}psu.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Objectives. We determined diet quality trends among nationally representative samples of preschoolers between 1977 and 1998.
Methods. Adjusted diet quality index scores, overall intake, and tertiles of total score were compared for combined samples and 2 age groups using t tests with Bonferroni correction; surveys used were the US Department of Agriculture’s National Food Consumption Survey 1977–1979 (n = 2342), Continuing Survey of Food Intake by Individuals (CSFII) 1989–1991 (n = 858), and CSFII 1994–1996 and 1998 (n = 5355).
Results. Total scores increased slightly. Consumption of grains, fruits, and vegetables improved while added sugar and juice intake worsened.
Conclusions. Diet quality improved marginally since 1977. Consumption of fruits and vegetables needs to be increased and that of total and saturated fat, juice, and added sugar decreased.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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It has been recognized that a safe and effective approach to decreasing the prevalence of overweight among children could be the improvement of overall diet quality and thus the establishment of healthier eating patterns.9–12 A high-quality diet is one that provides the nutrients and foods needed to maintain optimal health and promote growth and development. Assessment of diet quality aims to capture dietary intake patterns rather than intakes of individual nutrients or foods and is based on established dietary intake recommendations.13
Since dietary behavior tracks well from early childhood,14–17 the establishment of healthy eating patterns at a very young age might support better diet during childhood and thus in adults. As previous studies showed, preschoolers’ diets typically do not provide sufficient servings of fruit and vegetables but exceed the recommended intake in fat, saturated fat, and juice.18 In this population, the 2 main food sources for fat, saturated fat, added sugar, and grains are high-fat desserts and high-fat grain-based mixed dishes (data available from the authors upon request). Thus, targeting diet quality to improve childhood obesity might entail messages to limit intake of certain foods and food groups rather than focusing solely on increasing consumption of certain nutrients.
This study aimed to assess trends in overall diet quality in a study using nationally representative samples of the American preschool population from the US Department of Agriculture (USDA) National Food Consumption Survey (NFCS) for 1977 to 1979 (referred to here as NFCS77), the USDA Continuing Survey of Food Intake by Individuals (CSFII) for 1989 to 1991 (CSFII89), and the 1994–1996 CSFII combined with the supplemental survey of children for 1998 (CSFII94). We developed an overall Diet Quality Index for Children (C-DQI) and examined component scores in each survey to establish whether there are trends over the 3 survey time periods (scoring criteria of the index are available from the authors upon request). To observe differences by age group, we conducted an analysis using the full sample in each survey year, as well as 2 mutually exclusive age groups (children aged 2 years and 3 years, compared with children aged 4 years and 5 years).
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Samples
This analysis includes only children aged between 2 and 5 years who were not breastfed and for whom sociodemographic information was provided and data were available on at least 2 days of intake: 2342 children in the NFCS77, 849 in the CSFII89, and 5437 in the CSFII94. In all 3 surveys, interview respondents or another adult in the household reported diets of children aged younger than 6 years. The data sets provide sociodemographic information, dietary intakes, and a food servings database file with the number of Food Guide Pyramid19 serving sizes per 100g of a food code. Food codes were linked to intake data similarly in all 3 survey years to accommodate new food codes in the latest survey wave and to make data comparable across all survey waves.
Variables
Sociodemographic information, such as age, race, gender, total household income, years of education, and employment, was ascertained during the survey. In this study, education and employment data of the female head of household were used as a proxy for mothers. In an effort to capture cultural differences, the variables race (Black, White, and other) and Hispanic origin (Mexican, Puerto Rican, Cuban, other Spanish subgroup, or non-Hispanic) were recoded to define 4 distinct ethnic groups: non-Hispanic White, non-Hispanic Black, non-Hispanic other, and Hispanic. Similar coding has been employed by Odgen et al.20 Urbanicity was defined as living in a nonmetropolitan statistical area (non-MSA), MSA central city, or MSA non–central city.
The C-DQI was employed to determine overall diet quality. This composite assessment tool was specifically designed to assess over- and underconsumption of nutrients, foods, or food groups important for American children of preschool age. On the basis of the definition by Ibrahim,21 only areas of public health importance were included, resulting in 8 components: added sugar, total fat, saturated fat, grains, fruits and vegetables, dairy products, excessive juice, and iron. Added sugar, fat, and saturated fat were assessed as percentage of total energy. Grains, fruits, vegetables, and dairy products were assessed by number of servings, excess juice by number of 6-ounce servings of 100% fruit juices in excess of 1 serving per day, and iron by milligrams per day. To accommodate the consumption of smaller portions by younger children, serving sizes for children aged 2 and 3 years were two thirds of the serving size for older children.19 Component scores were allocated according to dietary intake, with increasing points reflecting improved diet quality. The measured component scores were compiled into a composite overall dietary intake score.
Analysis
Descriptive statistics (means and standard errors) were employed to describe the study sample populations by age groups. Standard errors were employed to allow estimation of the stability of the mean after weighted analysis was conducted. To account for differences in the distribution of sociodemographic characteristics in the American population over time, estimates were adjusted for ethnicity, urbanicity, maternal employment, and education status. To ascertain whether there was a significant trend in diet quality status between surveys, Student t tests were performed on the adjusted mean total C-DQI scores, as well as component scores, between individuals in the NFCS77 and CSFII89, CSFII89 and CSFII94, and NFCS77 and CSFII94. A P value of .05 that was corrected for multiple comparisons by Bonferroni correction was assumed to detect significance between mean scores (P 
.0019).
To further examine the changes of dietary intake over time, we subsequently compared average intakes of the nutrient, foods, and food groups that comprise the C-DQI of each of the 3 survey waves in the full sample as well as by age group (P .0006). Additionally, we assessed whether there was a significant difference in intakes between individuals in the 2 age groups (P .0019). To assess where areas of improvement were, we compared the average intakes of the C-DQI components in the lowest and highest tertile of total C-DQI points from the sample in the NFCS77 and CSFII94.
Changes occurring in dietary intake or dietary intake patterns can be assessed by several methods.22,23 If one assumes that the population investigated is the same (such as in a longitudinal study) or comparable and that the methods are similar, one can determine differences over time to establish trends. There is no longitudinal nationally representative data set available at this time. Thus, the nationally representative character of the 3 surveys was used as bases for comparability of the data sets to estimate trends over time. Although the dietary data collection slightly varied between the 2 older surveys (NFCS77 and CSFII89) and the most recent one (CSFII94), the methods were comparable and satisfactory for assessing dietary intake in large populations. Similar assumptions have been used by others to establish dietary trends over time in the US population.22,24–29 The statistical package used for all analysis was Stata (version 7.0; Stata Corp, College Station, Tex), which allowed adjustment for sample design effect and weighting to maintain the nationally representative character of the data.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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. While the number of subjects aged 2 to 5 years varied greatly among the surveys, the distribution of sociodemographic characteristics within each group remained constant for most of the characteristics, indicating comparability of the data sets. However, more female heads of households had a higher educational level in CSFII89 and CSFII94 and almost twice as many were employed as in NFCS77. Approximately half of the children were male, two thirds or more were non-Hispanic White, and nearly half lived in households with a total income of less than 185% of the poverty level. Average energy intakes of the children significantly increased, from 1389 kcal per day in NFCS77 to 1558 kcal per day in CSFII94.
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. Average total scores were 43.7 in the NFCS77, 45.0 in the CSFII89, and 45.7 in the CSFII94, indicating a small increase between the first and second, second and third, and first and third USDA survey wave. Higher component or total points indicated improved diet quality. However, the significance of changes in the full sample were similar to those in the 2 age groups, with the exception of the decrease in scores for excess juice between the NFCS77 and the CSFII89 and between the CSFII89 and the CSFII94 (P = .0493 and .0085). Scores for added sugar, dairy, and iron decreased, while total and saturated fat, grains, and fruits and vegetables as well as total scores increased over time.
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shows the comparison of average dietary intakes of the nutrients, foods, and food groups that comprise the components of the C-DQI between the 2 age groups and the total sample for each USDA survey. Over the last 21 years, the main changes in intake were that percentage of total energy from fat and saturated fat decreased, whereas consumption of added sugar as percentage of total energy and servings of grains, fruits, vegetables, dairy products, juice, and iron increased.
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Examination of diets between age groups within each survey year showed that the diets of children aged 2 and 3 years were significantly different from those of children 4 and 5 years old in most of the components in the NFCS77 and CSFII94 but not in the CSFII89.
Comparison of intakes in the lowest and highest tertile of C-DQI total points in the sample from the NFCS77 and CSFII94 (Table 4) indicated that intake of servings of grains and fruit increased over time across tertiles, whereas intake of fat and saturated fat decreased; thus, in the CSFII94, children in the lowest tertile consumed less fat or saturated fat as percentage of total energy than children in the highest tertile in 1977. Added sugar increased in both survey years in the lowest as well as highest tertiles, while dairy intake remained fairly stable. Excess juice consumption was equal in both tertiles in the NFCS77 and was much lower than in either tertile in the CSFII94 (0.2 serving, compared with 1.0 serving in the lowest tertile and 0.7 serving in the highest tertile in the CSFII94). Iron consumption also increased over time; consumption in the lowest tertile in the CSFII94 was not much lower than in the highest tertile in the NFCS77 (10.4 mg/day vs 11.3 mg/day). Likewise, total energy consumption increased over time; children in the lowest tertile of the C-DQI score in 1998 only consumed 21.5 kcal/day less than children in the highest tertile in 1977.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Total energy consumption increased significantly between 1977 and 1998, which might have contributed to the increase in the prevalence of childhood obesity. However, one has to consider that the methods of dietary intake assessment have changed over time and that some of the increased energy might have owed to improved measurement methods. Our results illustrate that although overall diet quality has improved over time, overall energy intake has risen significantly, and there has been a shift from consumption of fats as a high proportion of total energy intake to one of nonfat macronutrients (for instance, added sugars). As comparison of the lowest and highest tertiles of the total C-DQI scores indicates, over a 21-year period, consumption of certain items, such as grains and fruit, increased, while others (fat and saturated fat) decreased to levels below those of 1977. Hence, the change in dietary intake has affected the total pre–school-age population, not just the proportion of children who had higher or lower diet quality in 1977.
It is noteworthy that the C-DQI scores of children aged 2 and 3 years were higher for most components of the C-DQI, indicating that younger children have a healthier diet than older children. This might be because of the higher level of control in young children’s environment by parents or other caretakers. Older children are able to make more food choices independent of an adult and appear to select less healthy items.
The scoring scheme of the C-DQI uses different cutoff points for children aged 2 and 3 years compared with those aged 4 and 5 years in the total fat and saturated fat component, to better accommodate the most recent dietary intake recommendations of the American Academy of Pediatrics.34 In addition, the recommended dietary intakes for younger children are lower than for children aged older than 4 years, and thus younger children scored differently in the iron component than older children. However, this did not distort the relationship between actual dietary intake and C-DQI scores. As shown in Table 3
, the intakes of older children were significantly different from the diets of the younger ones, and as previous analysis has shown, diet quality deteriorated within each age group with increasing age (data available from the authors upon request).
The apparent contradiction between higher total diet quality scores and the increasing prevalence of childhood obesity can be explained by the shift in the C-DQI component scores over time. As Table 4 indicates, while consumption of grains, fruit, vegetables, and dairy products increased even in individuals in the lowest tertile of C-DQI total points to levels that are closer to the recommended intakes, percentage of total energy from added sugar strongly increased; it is even higher for the children in the highest C-DQI tertile in the CSFII94 than in the same tertile in the NFCS77. While consumption of fat in terms of percentage of total energy has decreased, data indicated that consumption in absolute amounts increased and contributed to higher energy intakes. Thus, although our index indicates more healthy food choices, overall energy consumption has increased, which might be a contributor to the increasing prevalence of childhood obesity.
One of the limitations of this study was that dietary intakes for children were collected by proxy in all survey waves. Children’s diets were reported by an adult who may have lacked complete knowledge of everything the child ate. Dietary assessment using 24-hour recalls is prone to incomplete data owing to memory lapses and may not be typical of usual intake. However, in large population studies, such as those conducted for nutrition monitoring purposes, more complicated dietary assessment methods are not feasible, and 2 days of data provide reasonable estimates at the group level. Additionally, bias might have been introduced owing to increased public awareness of the importance of limiting fat and saturated fat, especially in the later surveys; items high in fat and saturated fat might therefore have been underreported.
Another potential limitation to this study is the possibility of a bias in unknown direction owing to the change in dietary intake assessment methods between surveys. In the most recent survey, dietary intake data were collected in the form of 2 24-hour recalls, whereas in 1989 and 1977 there was only 1 such recall, but 2 consecutive days of food records were collected. Also, increases and changes in the food supply have occurred during the time span investigated. Although we used a system to link the food codes between survey years, additional alterations in consumption might have owed to the change in food supply. The direction and magnitude of this bias has not yet been specified.
It may be necessary to revise our C-DQI owing to the most recent release of new dietary reference intakes for macronutrients by the National Academy of Sciences.35 Once the appropriateness of the new recommendations for dietary intake for preschool age children has been established by authorities in pediatric nutrition, such as the American Academy of Pediatrics, a revised C-DQI might be developed.
Our research found that overall diet quality among preschool children has marginally improved over the past 21 years; however, total energy intake and consumption of fruit juices and added sugar have significantly increased. Nutritional concerns for American children have shifted from problems of deficient intakes to overconsumption of energy-contributing food groups, which this diet quality tool assesses. Overall diet in children needs to be improved to aid prevention of chronic diseases in adulthood.36,37 Studies using the Healthy Eating Index drew similar conclusions to the ones reported here.38,39 However, results of those studies were limited to the assessment of items provided by the Food Guide Pyramid. Despite their limited diet variety compared with children aged 4 and 5 years, younger children had better diets39; efforts to support high-quality diets from an early age might therefore improve health outcomes in the future.15,16,33,40
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Acknowledgments |
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Human Participant Protection
This secondary data analysis was approved by the institutional review board at the University of North Carolina at Chapel Hill.
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Footnotes |
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Accepted for publication May 31, 2003.
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References |
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