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Children’s Growth Parameters Vary by Type of Fruit Juice Consumed

Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York (B.A.D.)
Research Institute, Bassett Healthcare, Cooperstown (B.A.D., H.L.R., M.J.N., P.J.), New York

Address reprint requests to: Dr. Barbara A. Dennison, Research Institute, Bassett Healthcare, One Atwell Road, Cooperstown, NY 13326.

	ABSTRACT

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 
Background: Excessive fruit juice consumption in young children has been associated with nonorganic failure to thrive and short stature in some children and with obesity in others.

Objective: To evaluate, in a sample of healthy young children, whether the associations between fruit juice intakes and growth parameters differ by the type of fruit juice consumed.

Design: Cross-sectional study.

Setting: General primary care health center in upstate New York.

Participants: One hundred sixteen two-year-old children and one hundred seven five-year-old children, who were scheduled for a nonacute visit, and their primary care-takers or parents were recruited over a two-year period.

Methods: For 163 children (73% of total), 14 days of dietary records were available. The dietary records were entered and analyzed using the Nutrition Data System (NDS). Type of fruit juice was classified according to Nutrition Coordinating Center food codes. Height was measured using a Harpenden Stadiometer. Weight was measured using a standard balance beam scale.

Results: The children consumed, on average, 5.5 fluid oz/day of fruit juices, which were classified by the NDS software as 35% apple juice, 31% orange juice, 25% grape juice and 9% other types and/or mixtures of fruit juice. Children with higher fruit juice intakes had lower total fat, saturated fat and cholesterol intakes. Child height was inversely related to apple juice intake (p=0.007) and grape juice intake (p=0.02), after adjustment for child age, gender and energy intake (excluding fruit juice) and maternal height. Apple juice intake was correlated with child body mass index (p<0.05) and ponderal index (p<0.005), after adjustment for the above covariates. Total cholesterol, LDL-cholesterol, triglyceride and lipoprotein(a) levels were not related to intakes of any of the fruit juices examined. The children’s ratios of total cholesterol to HDL cholesterol were correlated with grape juice intakes, while HDL-cholesterol levels were inversely related to grape juice intakes. There were no significant relationships between fruit juice intake and measures of anemia (hematocrit or mean corpuscular volume).

Conclusions: The previously reported associations between short stature and high intakes of fruit juice were observed for intakes of both apple juice and grape juice. The associations between high fruit juice intakes and obesity were observed with apple juice intakes only. Because most of the fruit juice mixtures were classified as single fruit juices, the findings, especially those with grape juice, need to be cautiously interpreted. High intakes of fruit juice, however, appear to be associated with growth extremes in young children. Thus, it would seem prudent for parents and caretakers to moderate the fruit juice intakes of their young children.

Key words: child nutrition, obesity, body height, fruit juice, beverages, diet, nutrition policy, growth disorders

Abbreviations: AAP=American Academy of Pediatrics • BMI=body mass index • Lp(a)=Lipoprotein(a) • NCC=Nutrition Coordinating Center • NDS=Nutrition Data System • SAS=Statistical Analysis System

	INTRODUCTION

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 
Fruit juice consumption by infants and young children has increased over the past 30 to 40 years because of increased availability, convenience, marketing and children’s preferences. Sweetened beverages are preferred over unsweetened drinks even by neonates, as well as young children [1,2]. By one year of age almost all children drink fruit juice [3]. Concerns about children’s excessive consumption of fruit juice have been raised by a number of professional groups. The American Academy of Pediatrics (AAP) and the American Academy of Pedodontics have expressed concerns about tooth decay and fruit juice [4]. The AAP Committee on Nutrition has expressed concern about sorbitol, a naturally occurring, but nonabsorbable sugar alcohol present primarily in pear juice and apple juice; they cautioned that the "excessive use of fruit juice" may result in gastrointestinal symptoms, such as chronic diarrhea, abdominal pain or bloating [5]. The role of juice carbohydrate malabsorption (especially fructose) in chronic nonspecific diarrhea in children has been recognized for some time [6,7].

Among children referred for evaluation of failure to thrive, excessive fruit juice consumption was reported as a contributing factor in nonorganic failure to thrive in eight children, aged 14 to 27 months [8]. In some children, an association between excessive fruit juice consumption and short stature was reported, while in other children, a relationship between high intakes of fruit juice and obesity was found [9].

The purpose of this study was to evaluate, in a sample of healthy preschool-aged children, whether the associations between fruit juice intake and growth parameters differ by the type of fruit juice consumed.

	METHODS

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 
Study Population
A total of 223 children, two through five years of age, who were scheduled for a nonacute visit, and their parent or primary caretaker were recruited from a general primary care practice located in Schoharie County, a rural community in upstate New York. The study population is 97% white and low to middle class. Children with significant medical conditions that affect growth and/or dietary intake were excluded (one with diabetes mellitus and one with chronic renal failure). Data were collected during 1992 and 1993 as part of a larger study to evaluate different methods of assessing dietary fat intake in young children. Written informed consent was obtained from the child’s parent or legal guardian. This study was approved by the Institutional Review Board of The Mary Imogene Bassett Hospital.

Dietary Intake Assessment
A 24-hour dietary recall for the child was collected from the child’s parent or primary caretaker at the initial visit. The child’s parent or parents or primary caretaker was given detailed instructions by a research nutritionist in how to complete a written, consecutive, seven-day dietary record for their child. Dietary recalls and records included brand names of foods, preparation techniques and a detailed description of the foods consumed. To improve estimation of portion size, parents were given measuring cups and spoons, rulers and a "Kids Food Portion Booklet." They were also given a postage-paid, pre-addressed envelope to return the written seven-day dietary record. If necessary, the primary caretakers were called twice to remind them to mail in the written dietary record. Once the written dietary record was finished, six additional 24-hour dietary recalls were obtained. Telephone calls to collect the dietary recalls were scheduled randomly over a three-week period so that all days of the week would be included.

Dietary data were reviewed by a registered dietitian and entered by an experienced research nutritionist. Nutrient calculations were performed using the Nutrition Data System (NDS) software developed by the Nutrition Coordinating Center (NCC), University of Minnesota, Minneapolis, MN, Version 2.3; Nutrient Database, Version 20. For the 14 days of dietary records, entered and analyzed using the NDS program, the amounts of apple, grape and orange and other fruit juices consumed were determined based on the NCC food codes (Appendix I).

The amounts of all 100% fruit juices consumed (apple juice, orange juice, grape juice and other/mixed fruit juice) were also determined by manual review of the seven-day written food records.

Children’s Anthropometric Measurements
The child’s height, in stocking feet, was measured to the nearest 0.1 cm using a Harpenden Stadiometer (Cambridge, MD). The child, lightly clad and in stocking feet, was measured to the nearest 0.25 pounds using a standard balance beam scale.

Questionnaire Data
Demographic data and self-reported height and weight were collected from the parent or primary caretaker by an experienced interviewer. All questionnaire data were dual-entered and verified before being entered into a Statistical Analysis System (SAS Institute, Cary, NC, Version 6.12) data base.

Laboratory Data
After an eight- to twelve-hour fast, five cc of blood were collected by venipuncture from an antecubital vein.

Lipid and Lipid Profiles.
The blood was allowed to clot for ten minutes; the serum was separated by centrifugation and stored on ice for a maximum of four hours. Analysis of total cholesterol, HDL-cholesterol and triglycerides was conducted at the MIBH Clinical Laboratory according to standard protocols. LDL-cholesterol was computed using the Friedewald equation. The laboratory participates in the CDC-Standardization program. The coefficient of variation for total cholesterol was 3%.

Lipoprotein (a).
Lipoprotein (a) (Lp(a)) was measured by a commercially available ELISA (Enzyme Linked Immunosorbent Assay) using the Macra Lp(a) kit manufactured by Strategic Diagnostics (Newark, NJ). Monoclonal antibody to Lp(a), immobilized on microtiter wells, served as the capture antibody. Bound Lp(a) was detected using a polyclonal anti-Lp(a) antibody conjugated with horseradish peroxidase. The complex was detected and quantified by chromogen formation upon incubation of peroxide and o-phenylenediamine substrate. A 100-microliter aliquot of serum, stored at -80°C, was used for this assay. The antisera, calibrators and controls were provided by the manufacturer in their Macra Lp(a) kit. ELISA plates were read on an automated ELISA plate reader, Dynatech Model MR5000 set to monitor at 492 nm. A calibration curve, consisting of six standards ranging from 0–80 mg/dL Lp(a) were run in duplicate within each batch. Each sample was analyzed in duplicate. The precision of Lp(a) at 15 mg/dL has a long-term (day-to-day) precision of 3.9% and within run of 1.4%. Lp(a) of 36 mg/dL has a long-term precision (day-to-day) of 3.8% and within run of 1.8%. Samples with Lp(a) concentrations above the highest calibrator or absorbing at over 3.0 absorbing units are diluted 1-to-1 with saline and repeated on another run.

Red Blood Cell Counts and Indices.
Complete blood counts and indices were measured in the Bassett Hospital Clinical Laboratory using standard methods. Spun hematocrits (in duplicate) were measured in the office laboratory using standard methods.

Statistical Analysis
After the dietary data were entered and analyzed using the NDS computer software program, the total daily intake of each nutrient was calculated and transferred to an ASCII file, which was used to create a SAS database. The 14-day mean intake of each nutrient and each beverage consumed were determined and used in all analyses.

Obesity is a relative index and may be defined by a number of measures. Although the body mass index (BMI) is generally accepted as the standard measure of adiposity in adults, the ponderal index, which shows a lower direct correlation with height than BMI, may be a better measure of excess weight in growing children [10]. Therefore, both BMI and the ponderal index were used as measures of adiposity. BMI was calculated as BMI=weight (kg)/[(height (m)]². The ponderal index was calculated as Ponderal Index=weight (kg)/[height (m)]³. Age and gender-specific height, weight and weight for height percentiles were determined using Epi Info (Version 6.04b; URL:http://www.cdc.gov/epo/epi/downepi6.htm).

Chi-square tests or Fisher’s exact tests were used to compare dichotomous variables. Nonparametric tests (Wilcoxon) were used to compare ordered data. Student’s t tests were used to compare continuous variables. Multiple Linear Regression Models (SAS: PROC GLM) were used for multivariate analysis of child height, weight, BMI and ponderal index, which included child age, child gender, maternal height and total energy intake (excluding fruit juice intake), as covariates. Unless otherwise indicated, all statistical tests were two-sided. All statistical analyses were conducted using the SAS software package (Version 6.12) on a VAX computing system.

	RESULTS

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 
Study Participant Characteristics
The study population has been described previously [9]. For 163 children, 14 days of dietary records were available (seven days of written dietary records and seven days of 24-hour dietary recalls). Of note, the children’s mean height was at the 50th age-and-gender-specific percentile, while their mean weight was at the 57th age-and-gender-specific percentile (Table 1). Ninety-six percent of the children participating in the study were accompanied by their mothers. Thus, for multivariate models, the 4% of children not accompanied by their mothers were excluded, which should not change the findings.

Based on a manual review of the children’s seven-day written dietary records, 39% of the fruit juice consumed was mixed fruit juice, 30% was apple juice, 23% was orange juice, 7% was grape juice and 1% was pear or pear-apple juice [9]. The NDS computer program was used to enter and analyze both the written records and the dietary recalls (a total of 14 days of dietary records). The NDS program tends to classify these fruit juice blends or mixtures "according to the most prominent fruit juice" believed to be present in the blend and based on nutrient information available from the manufacturer. The average daily total fruit juice intake was the same based on the written dietary records and the 24-hour dietary records. If one assumes that the types of fruit juices consumed reported on the written dietary records were the same as those reported on the 24-hour dietary recalls, then the NDS program classified 79% of the mixed fruit juices as single fruit juices, predominantly as either apple, orange or grape juice. This resulted in apparent increases in the children’s consumption of apple juice from 30% to 35%, orange juice from 23% to 31% and grape juice from 7% to 25% of total fruit juice consumed and a decrease in consumption of other mixed fruit juice from 39% to 9% of the total (Fig. 1).

View larger version (60K): [in this window] [in a new window]   Fig. 1. The percent distribution of children’s 14-day total fruit juice intake (N=163). "Mixed" fruit juices and "other" fruit juice includes mixtures or blended 100% fruit juices. The "mixed apple," "mixed orange," and "mixed grape" juices were classified as single fruit juices (apple, orange and grape juice, respectively) by the NDS software program. Thus, the NDS-classified "apple juice group" includes "apple" plus "mixed apple" juices. The NDS-classified "grape juice group" includes "grape" plus "mixed grape" juices, and the NDS-classified "orange juice group" includes "orange" plus "mixed orange" juices.

In multivariate analysis, after adjustment for child age, child gender, child age-gender interaction, energy intake (excluding fruit juice) and maternal height, apple juice intake was significantly correlated with child BMI (both p<0.05; Table 5). In this analysis, there was also significant relationship between child BMI and child gender, child age-gender interaction and maternal height. In this multivariate model, intakes of orange juice, grape juice and other fruit juice were not significantly related to child BMI.

Multivariate models were also developed using fruit juice intakes expressed in calories rather than in grams; the findings were the same (data not shown).

Lipid and Lipoprotein Levels and FruitJuice Consumption
In multivariate analysis, after adjustments for child age, child gender and energy intake (excluding fruit juice), children’s total cholesterol levels were not significantly related to intakes of orange juice, apple juice, grape juice or other fruit juice. In multivariate analysis, LDL-cholesterol levels were not related to intakes of orange juice, apple juice, grape juice or other fruit juice. In multivariate models, triglyceride levels were also not related to intakes of orange juice, apple juice, grape juice or other fruit juice.

Child HDL-cholesterol levels increased with child age (B=1.73; p=0.01). After statistical adjustment for child age, child gender and energy intake (excluding fruit juice), children’s HDL-cholesterol levels were inversely related to grape juice intake (B=0.03; p=0.01; data not shown).

The total-cholesterol to HDL-cholesterol ratios differed by child gender (B=-0.31; p=0.03; data not shown). After statistical adjustment for child age, child gender and energy intake (excluding fruit juice), the children’s total cholesterol/HDL cholesterol ratios were significantly correlated with grape juice intakes (B=0.003; p=0.0006).

In multivariate analysis after adjustment for child age, child gender and energy intake (excluding fruit juice), child Lp(a) levels were not significantly related to intakes of orange juice, grape juice, apple juice or other fruit juice.

Measures of Anemia and Fruit Juice Consumption
In multivariate models, children’s hematocrit was not related to intakes of orange juice, apple juice, grape juice or other fruit juice. In similar multivariate analyses, Mean Corpuscular Volume (MCV) was also not related to intakes of orange juice, apple juice, grape juice or other fruit juice.

	DISCUSSION

 
The children’s mean fruit juice intake (5.5 oz/day) based on 14 days of dietary records was very similar to that reported previously based on seven days of dietary records [9]. The study children’s mean dietary intakes were comparable to those reported in the National Health and Nutrition Examination Survey III, despite differences in the years the data were collected [11].

Decreased child height or length has been reported previously with high intakes of fruit juice. Consumption of excessive fruit juice (more than 12 oz/day of "primarily apple juice") was a contributing factor in eight children with non-organic failure to thrive [8]. Five of the children (63%) had a length <5th percentile for age and gender, and two (25%) had a length equal to the 5th percentile. In a previous study by Dennison, et al., children who consumed 12 oz/day of fruit juice, were significantly shorter after adjustment for maternal height, child age, child gender and child age-gender interaction [9].

Based on fourteen days of dietary data and analysis by type of fruit juice consumed, the relationships between fruit juice intake and adiposity (BMI and ponderal index) persisted for apple juice only. Apple juice was also the most commonly consumed fruit juice by this study population. It should be noted, however, that the children who consumed the largest amounts of fruit juices consumed more than just one type of fruit juice. In fact, few children consumed only one type of fruit juice, making interpretation of study findings difficult.

In this study, child height was inversely correlated with both apple juice intake and with grape juice intake. One might hypothesize that the finding of short stature with high intakes of apple juice, with its high fructose to glucose content, might be related, in part, to fructose malabsorption. Fructose malabsorption is relatively common [12] and increases at higher concentrations and at higher doses of fructose [13]. In the presence of sorbitol, fructose malabsorption is further increased [14]. When combined with glucose, fructose malabsorption decreases, and, at equal concentrations of fructose and glucose, fructose is rarely malabsorbed [13]. This, however, does not explain the findings observed with grape juice.

While signs of malabsorption commonly appear after ingestion of apple juice, they are less frequently present after ingestion of white grape juice (54% vs. 19%) [6]. Almost none of the grape juice consumed in this study was white grape juice, and only a quarter of the NDS-classified grape juice was actually plain grape juice. Almost half (46%) of the mixed fruit juices (39% of total fruit juices) were classified by the NDS system as grape juice. As a result, 72% of the NDS-classified "grape juice" was really a grape juice mixture. Thus, one needs to be very cautious in interpreting the findings associated with grape juice intake.

This classification problem occurs the least with apple juice, where only 14% of the NDS-classified apple juice was really an apple juice mixture. With orange juice, there are two potential NDS-classification problems. First, juices entered into the NDS program as "100% fruit juice, type unknown," default to "orange juice." Thus, the apparent increase in orange juice, from 23% to 31% of total fruit juice, is due to the classification of orange juice blends as well as 100% fruit juices with unknown or unspecified types as "orange juice." Overall, 26% of the NDS-classified orange juice was either orange juice blends or juices of unknown type.

One can only speculate as to why intakes of different types of fruit juice were or were not associated with short stature and/or obesity. This study was cross-sectional; therefore, causality cannot be established. The selection and consumption of different types of fruit juices were not random. Parents and caregivers serve children different types of fruit juice, and the children choose to drink different amounts and types of fruit juice for a variety of reasons.

	CONCLUSION

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 
The relationship of children’s fruit juice intakes with short stature and obesity observed with seven days of dietary data persisted after analyzing 14 days of dietary data [9]. These relationships, however, varied with the type of fruit juice consumed. Intakes of orange juice or "other" fruit juice were not related to either child height or obesity. Apple juice intakes were significantly correlated with both child adiposity indices (BMI and ponderal index) and were negatively correlated with child height. Grape juice intakes were also negatively correlated with child height.

Because of the classification of mixed or blended fruit juices as single types of fruit juice, one needs to be cautious in interpreting these findings. Because the percent of mixed fruit juices included with each of the three major fruit juice types examined varies, with apple juice being the least affected and grape juice the most affected, the findings are also similarly affected. Because the majority (72%) of the NDS-classified grape juice was from grape juice mixtures, one must be extremely cautious when evaluating the significance of these findings. Only a very small portion of the NDS-classified grape juice was actually pure grape juice.

Additional studies, including randomized trials, are needed to further explore the relationships between children’s fruit juice consumption (amount and type) and their growth parameters. In the meantime, we conclude as previously, that parents and child caretakers would be prudent to moderate young children’s consumption of fruit juice.

	FOOTNOTES

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

Received June 1, 1998. Accepted March 1, 1999.

	REFERENCES

TOP FOOTNOTES ABSTRACT INTRODUCTION METHODS RESULTS CONCLUSION REFERENCES

 

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This Article Abstract Figures Only Full Text (PDF) Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Dennison, B. A. Articles by Jenkins, P. Search for Related Content PubMed PubMed Citation Articles by Dennison, B. A. Articles by Jenkins, P.