Abstract
Background
The American Academy of Pediatrics recommends juice introduction after 12 months of age. Juice consumption has been linked to childhood obesity and cardiometabolic risk.
Objectives
To examine the prospective relationship between the age of juice introduction and primary and secondary cardiometabolic outcomes in middle childhood.
Methods
Parents reported the age of juice introduction on Upstate KIDS questionnaires completed between 4 and 18 months. The quantity and type of juice introduced were not measured. Anthropometry, blood pressure (BP), and arterial stiffness by pulse wave velocity (PWV) were measured for 524 children (age, 8–10 y) at study visits (2017–2019). Age- and gender-adjusted z-scores were calculated using the Centers for Disease Control and Prevention reference for anthropometrics. Plasma lipids, hemoglobin A1c (HbA1c), and C-reactive protein (CRP) in a subset of children were also measured (n = 248). Associations between age at juice introduction (categorized as <6, 6 to <12, ≥12 months), and outcomes were estimated using mean differences and odds ratios, applying generalized estimating equations to account for correlations between twins.
Results
Approximately 18% of children were introduced to juice at <6 months, 52% between 6 and <12 months, and 30% ≥ 12 months of age. Children who were introduced to juice before 6 months had higher systolic BP (3.13 mmHg; 95% confidence interval [CI]: 0.52, 5.74), heart rate (4.46 bpm; 95% CI: 1.05, 7.87), and mean arterial pressure (2.08 mmHg; 95% CI: 0.15, 4.00) compared with those introduced ≥12 months after covariate adjustment including sociodemographic factors and maternal prepregnancy body mass index. No adjusted differences in anthropometry, lipids, HbA1c, and CRP levels were found.
Conclusions
Early juice introduction during infancy was associated with higher systolic BP, heart rate, and mean arterial pressure in middle childhood.
This trial was registered at clinicaltrials.gov as NCT03106493 (https://clinicaltrials.gov/study/NCT03106493?term=upstate%20KIDS&rank=1).
Keywords: juice, pediatric nutrition, cardiometabolic outcomes, early infant feeding practices, childhood
Introduction
Cardiovascular disease (CVD) remains the leading cause of death in the United States [1]. Efforts to prevent CVD have focused on the role of diet starting in childhood [1,2] as markers of cardiometabolic risk are evident even in childhood [3,4]. During the first years of life, beverages serve as the primary source of calories and nutrients [5,6]; however, recent studies found an effect of sugar-containing beverages (SCBs) such as 100% fruit juice and sugar-sweetened beverages (SSBs) on cardiometabolic risk factors in children [1,2,7,8]. Although whole fruit consumption provides basic nutritional needs and prevents various chronic diseases, the evidence of fruit juice consumption remains controversial [[9], [10], [11]]. Similar to whole fruit, 100% fruit juice should provide micronutrients such as vitamins, minerals, and polyphenols thus recognized as a healthier alternative to SSBs. However, evidence has highlighted that 100% fruit juice and SSBs’ energy densities and overall sugar profiles are similar, and there are longstanding concerns that both have low fiber content, high caloric density, heightened risk for dental caries, among others [[11], [12], [13], [14]]. Based on the risks associated with juice consumption, the American Academy of Pediatrics (AAP) now recommends parents introduce juice after 12 months of age [[15], [16], [17]]. Despite these recommendations, recent evidence has found most children are introduced to juice prior [5,[18], [19], [20]].
We previously found that ∼25% of infants were introduced to juice before 6 months of age and that earlier introduction was tied to higher SCB consumption in middle childhood [19]. Although several studies have examined juice intake before 1 y of age with cardiometabolic risk in later childhood [2,8,21], to our knowledge, no studies have examined the age of juice introduction and cardiometabolic markers in children beyond anthropometry. SCBs as a cause for weight gain has been well established in children and adults, including clinical trial evidence involving reduction interventions [22]. Although interventions could prove helpful as secondary prevention of cardiometabolic risk, evaluating the ties between early introduction during infancy could provide more insight for primary prevention.
Despite evidence of an association between SCB intake and CVD risk in adults [23,24], a few pediatric studies have examined SCB intake during childhood on cardiometabolic health. One systematic review [25] included 4 studies examining the intake of SCBs during childhood and cardiometabolic outcomes [21,[26], [27], [28]]. Two studies found an association between any SCB intake in middle childhood and an increased CVD risk [26,27]; however, the others found no associations [21,28].
The American Heart Association (AHA) highlights the need to examine the introduction of added sugars during infancy and future cardiometabolic risk as available data are limited [29]. Early exposure to juice may contribute to the premature development of CVD as early life nutritional experiences may influence the metabolic programming that contributes to the onset of metabolic diseases later in adulthood [30]. However, given the difficulties of quantifying pediatric juice consumption, particularly during infancy, age at introduction could serve as a surrogate marker for higher consumption. Moreover, evidence suggests that earlier introduction can lead to preferential consumption later due to developmental programming [31,32]. Examining the age of juice introduction may reveal associations with cardiometabolic outcomes in middle childhood. Therefore, we examined the relationship between the age of juice introduction and primary and secondary cardiometabolic outcomes in 8- to 10-y-old children within the Upstate KIDS study, a prospective birth cohort with the methodological advantages of assessing children’s health.
Methods
Study population
Upstate KIDS enrolled 5034 mothers and 6171 infants born between 2008 and 2010 in New York State (excluding New York City) [33]. The study was designed to determine the effects of infertility treatment on childhood development and growth. As previously described, singleton infants conceived by infertility treatment were identified based on birth certificate data and were frequency matched (3:1) to infants without treatment by perinatal region of birth [33]. The current analysis is part of a second phase of follow-up that began in 2015 when invitations were sent out to 4644 children living within 2 h of 1 of 4 study sites across the state (i.e., the University at Albany, the University at Buffalo, the University of Rochester, and New York University Langone Health). Families were invited to attend a clinic visit from 2017 to 2019, and 559 children completed a visit when they were 8–10 y olds, as previously described [34]. We previously found a few differences in cardiometabolic risk factors between children conceived with and without fertility treatment [34], thus the full sample was used to explore associations between timing of juice introduction and cardiometabolic risk (Figure 1).
FIGURE 1.
Study participant flow diagram, 2017–2019.
The study was conducted in accordance with the Declaration of Helsinki. The New York State Department of Health and the University at Albany (State University of New York) Institutional Review Boards approved the study and served as the Institutional Review Boards designated by the National Institutes of Health under a reliance agreement. Parents provided written informed consent and children assented to the clinic visits.
Age of juice introduction
Parents reported the age of juice introduction on questionnaires at 4, 8, 12, and 18 months of age. On each of these questionnaires, parents were asked whether they had introduced juice into their child’s diet and, if so, to indicate the age when they first gave juice to their child. If parents reported introduction of juice on >1 questionnaire, the first chronological questionnaire was prioritized to minimize recall bias. If parents specified that juice was introduced but failed to provide the age when juice was introduced, the midpoint between the child’s age at the time of the first questionnaire and last questionnaire on which they had indicated their child had not yet begun to drink juice was used as the time at which juice was introduced. Timing of juice introduction was then categorized as <6, 6 to <12, and ≥12 months to reflect current and former AAP recommendations [16,17]. Although the questionnaire reported information on juice consumption, no additional information was requested to distinguish the specific type introduced (e.g., 100% fruit juice compared with juice not from concentrate, juice containing artificial sweeteners, or added sugars).
Cardiometabolic measures
The primary outcomes of interest were systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure, heart rate, and pulse wave velocity (PWV). Clinical staff measured children’s systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure, and heart rate using the Welch Allyn Connex ProBP 3400 digital blood pressure (BP) device before their blood draw. Children were instructed to rest in a sitting position for 10 min before the measurement of BP was taken from the upper right arm. Three measurements of BP were taken at 5-min resting intervals with the first measurement of BP voided. If the difference between the 2 remaining measurements exceeded 5 mmHg, another measurement was taken, and all measurements were averaged. Pediatric clinical cut points at the 95th percentile for gender, age, and height were used to assess hypertension based on SBP and DBP [34,35].
Arterial stiffness was measured by PWV using the SphygmoCor XCEL System (AtCor Medical Inc). Two measurements were taken while the child was in the supine position following 10 min of rest. The system measured the child’s carotid-to-femoral wave using a tonometer at the carotid and a cuff wrapped around the upper thigh [36]. The femoral pulse is detected using volumetric displacement detected based on the thigh cuff. If 2 PWV measurements differed by >0.5 m/s and a third measurement was available, the median of the 3 values was taken; otherwise, if the third measurement was unavailable, the average of the 2 values was taken. Overall, 25 children (4%) required a third measurement (with 5 [1%] noncompliant to another attempt), and 45 (8%) only had a single measurement. Children with one single measurement were retained in the analyses. The average of interindividual coefficients of variations was 0.1%–5.3% for all examination measurements taken using the difference in measurements taken on the same day.
Anthropometrics
At clinic visits, the measurements for both the mothers and their children were recorded by clinic staff [34]. Primary anthropometric measures included weight, height, and waist and hip circumference. Weight and height were measured in duplicate using a standardized electronic scale and a portable stadiometer, respectively. Children were advised to wear light clothing without shoes. The waist circumference was measured twice to the nearest millimeter using a measuring tape over the iliac crest. The hip circumference was measured in duplicate by locating the widest circumference. A third measurement was taken and the 2 closest measurements of the 3 were averaged if differences exceeded 0.5 cm for height and circumferences and 0.454 kg for weight. BMI was calculated as kg/m2. From these measurements, age- and gender-standardized weight-, height-, and BMI-for-age z-scores were calculated using the Centers for Disease Control and Prevention reference [18,37]. Children were classified as obese if they had BMI-for-age z-scores ≥ 95th percentile. Children’s body fat was measured using bioimpedance analysis (BIA) with the Quantum V portable device (RJL Systems Inc.) while the child was in the supine position. BIA measures included both total and segmental body fat.
Cardiometabolic biomarkers
Secondary outcomes of plasma lipids, hemoglobin A1c (HbA1c), and C-reactive protein (CRP) were collected in a subset of 248 children who agreed to a blood draw. The study was limited by the number of families living in proximity to the study sites and children agreeing to participate in the blood draw, reducing biomarker information availability [38,39]. To accommodate families traveling to attend the clinic visits and scheduling clinical visits after school hours, fasting samples were not taken. The samples were stored and frozen at −80°C until analysis after being processed for plasma and packed red blood cells. Plasma lipids (mg/dL) and high-sensitivity CRP (mg/L) were measured using the Roche COBAS 8000 chemistry analyzer (Roche Diagnostics). The limit of detection for CRP was 0.15 mg/L, with 90 (36% of 248) children measuring below this limit. Four values of CRP levels > 10 mg/L were excluded as outlying values potentially indicating an infection. HbA1c was measured using nonporous ion exchange high-performance liquid chromatography (Tosoh Automated Analyzer HLC-723G8; Tosoh Bioscience, Inc.). Additional information about biomarker measurement and processing is detailed in Yeung et al. [34].
Covariates
Maternal race or ethnicity, education, marital status, and fertility treatment use were reported by the mothers in the baseline questionnaire at ∼4 months after delivery. Maternal age, insurance status, participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), maternal prepregnancy height and weight, and children’s gender, plurality, and gestational age were obtained from vital records. Mothers answered questions regarding medical diagnoses and medications for diabetes and hypertension at the time of the visit. Maternal hypertension was defined by a BP ≥ 130/80 mmHg SBP or DBP or a self-reported diagnosis at the time of clinic visit [34,40]. Duration of breastfeeding was determined by the dates mothers reported stopping breastfeeding and the last questionnaire on which they had indicated their child was continuously breastfeeding. Duration of breastfeeding was then categorized as <6, 6 to <12, and ≥12 months in line with AAP and WHO guidelines [41].
Statistical analyses
Maternal and child characteristics based on the age of juice introduction were compared using 1-way analyses of variance (ANOVA) or chi-square (χ2) test. Associations between juice introduction (categorized as <6, 6 to <12, ≥12 mo) and outcomes were estimated using ANOVA for continuous dependent variables to estimate the mean differences (95% confidence intervals [CIs]), and logistic regression was used for dichotomized outcomes to estimate the odds ratios (ORs; 95% CIs) applying generalized estimating equations to account for correlations between twins. To assess normality of each of the variables, a series of histogram and quantile–quantile (Q–Q) plots were used. Models were adjusted for child gender and gestational age, maternal age at delivery, race or ethnicity, education, marital status, hypertension, prepregnancy BMI, fertility treatment, plurality, clinical site, private insurance, and WIC participation. The percentage of individuals excluded due to missing covariate data among the study sample was <10%, thus a complete-case analysis was conducted [42,43]. In sensitivity analyses, we additionally adjusted for child BMI and breastfeeding duration to further examine mean differences for cardiovascular measures based on timing of juice introduction. Analyses were conducted using SAS 9.4 (SAS Institute Inc).
Results
Based on the age of juice introduction, ∼18% of infants were introduced to juice at <6 months, 52% between 6 and <12 months, and 30% at ≥12 months. Mothers introducing juice at <6 months of age were younger, had lower educational attainment, had a lower household income, had a higher prepregnancy BMI, higher report of smoking during pregnancy, higher WIC participation, and a higher report of breastfeeding for <6 months (44.9%) (Table 1). Descriptive statistics for child cardiometabolic characteristics by age of juice introduction are presented in Table 2. Cardiovascular and anthropometrics measures
TABLE 1.
Maternal and infant characteristics; entire cohort (n = 524) and by age of juice introduction in the Upstate KIDS cohort1
| Age at juice introduction |
|||||
|---|---|---|---|---|---|
| Overall, n, % | Entire cohort |
<6 months |
6 to <12 months |
≥12 months |
|
| (n = 524) | (n = 94, 18%) | (n = 274, 52%) | (n = 156, 30%) | P value2 | |
| Maternal characteristics | |||||
| Age, y, mean ± SD | 31.6 ± 5.8 | 29.3 ± 6.6a | 31.5 ± 5.5b | 33.4 ± 5.1c | <0.0001 |
| Race/ethnicity, n (%) | 0.005 | ||||
| Non-Hispanic White | 461 (88.0) | 74 (78.7) | 243 (88.7) | 144 (92.3) | |
| Education | <0.0001 | ||||
| College or advanced degree | 342 (65.3) | 41 (43.6) | 167 (61.0) | 134 (85.9) | |
| Private insurance | 444 (84.7) | 64 (68.1) | 236 (86.1) | 114 (27.0) | <0.0001 |
| WIC recipient | 100 (19.3) | 42 (45.2) | 46 (16.9) | 12 (7.9) | <0.0001 |
| Household income, $ | <0.0001 | ||||
| 10,000–24,999 | 45 (10.2) | 20 (27.4) | 20 (8.4) | 5 (3.8) | |
| 25,000–49,999 | 88 (20.0) | 21 (28.8) | 52 (21.9) | 15 (11.5) | |
| 50,000–74,999 | 103 (23.4) | 14 (19.2) | 52 (21.9) | 37 (28.2) | |
| 75,000–99,999 | 78 (17.7) | 6 (8.2) | 44 (18.6) | 28 (21.4) | |
| ≥100,000 | 128 (28.8) | 12 (16.4) | 69 (29.1) | 46 (35.1) | |
| Married or living as married | 463 (89.7) | 71 (78.0) | 243 (89.7) | 149 (96.8) | <0.0001 |
| Smoking during pregnancy | 34 (6.5) | 10 (10.6) | 20 (7.3) | 4 (2.6) | 0.031 |
| Alcohol during pregnancy | 76 (14.6) | 14 (14.9) | 37 (13.5) | 25 (16.2) | 0.740 |
| Height, cm, mean ± SD | 165.0 ± 7.2 | 164.1 ± 7.1 | 165.6 ± 7.0 | 165.5 ± 7.2 | 0.191 |
| Weight, kg, mean ± SD | 76.0 ± 19.8 | 82.9 ± 22.0a | 76.4 ± 19.5b | 71.0 ± 17.4c | <0.0001 |
| Prepregnancy BMI, kg/m2, mean ± SD | 27.3 ± 7.1 | 30.1 ± 8.0a | 27.3 ± 7.1b | 25.3 ± 5.8c | <0.0001 |
| Gestational diabetes | 61 (11.6) | 10 (10.6) | 39 (14.2) | 12 (7.7) | 0.120 |
| Gestational hypertension | 73 (13.9) | 12 (12.8) | 28 (6.6) | 20 (12.8) | 0.775 |
| Fertility treatment use | 228 (43.5) | 28 (29.8) | 122 (44.5) | 78 (50.0) | 0.007 |
| Breastfeeding duration | <0.0001 | ||||
| None (formula feeding) | 91 (18.7) | 28 (31.5) | 49 (19.1) | 14 (9.9) | |
| <6 months | 186 (38.2) | 40 (44.9) | 105 (41.0) | 41 (28.9) | |
| 6 to <12 months | 118 (24.2) | 14 (15.7) | 62 (24.2) | 42 (29.6) | |
| ≥12 months | 92 (18.9) | 7 (7.9) | 40 (15.6) | 45 (31.7) | |
| Infant characteristics | |||||
| Age at visit, mean ± SD | 9.0 ± 0.6 | 9.0 ± 0.7 | 8.9 ± 0.6 | 9.1 ± 0.7 | 0.174 |
| Child gender, male | 254 (48.5) | 51 (54.3) | 146 (53.3) | 73 (46.8) | 0.365 |
| Birth weight, g, mean ± SD | 2915 ± 788 | 2996 ± 747 | 2903 ± 796 | 2888 ± 798 | 0.540 |
| Plurality, twin | 206 (39.3) | 32 (34.0) | 111 (40.5) | 63 (40.4) | 0.513 |
| Gestational age, mean ± SD | 38.0 ± 2.7 | 38.0 ± 2.0 | 37.7 ± 2.6 | 37.3 ± 3.4 | 0.159 |
Abbreviations: BMI, body mass index, SD, standard deviation.
Different superscript letters mean significantly different among groups at the α = 0.05 level in Tukey post hoc tests.
Different superscript letters mean significantly different among groups at the α = 0.05 level in Tukey post hoc tests.
Different superscript letters mean significantly different among groups at the α = 0.05 level in Tukey post hoc tests.
Values are n (%) unless otherwise noted. Total participants with missing covariate data: married (n = 8); WIC recipient (n = 7); breastfeeding duration (n = 37).
P values were calculated using the χ2 test for categorical variables and 1-way ANOVA test for continuous variables.
TABLE 2.
Child cardiometabolic outcomes; entire cohort (n = 524) and by age of juice introduction in the Upstate KIDS cohort1
| Age at juice introduction |
||||
|---|---|---|---|---|
| Overall, n, % | Entire cohort |
<6 months |
6 to <12 months |
≥12 months |
| (n = 524) | (n = 94, 18%) | (n = 274, 52%) | (n = 156, 30%) | |
| Child cardiometabolic outcomes | ||||
| SBP, mmHg, mean ± SD | 105.2 ± 9.9 | 107.5 ± 10.1 | 105.0 ± 10.3 | 104.0 ± 9.2 |
| DBP, mmHg, mean ± SD | 62.6 ± 6.5 | 63.6 ± 6.6 | 62.5 ± 6.8 | 62.5 ± 6.2 |
| Heart rate, beats/min, mean ± SD | 84.5 ± 11.5 | 87.0 ± 12.3 | 84.9 ± 11.1 | 81.7 ± 11.1 |
| MAP, mmHg, mean ± SD | 76.8 ± 7.1 | 78.3 ± 7.0 | 76.6 ± 7.5 | 76.3 ± 6.7 |
| PWV, m/s, mean ± SD | 4.4 ± 0.9 | 4.5 ± 0.9 | 4.4 ± 1.0 | 4.3 ± 0.6 |
| Weight, kg, mean ± SD | 34.3 ± 9.1 | 36.3 ± 9.3 | 34.5 ± 9.7 | 33.4 ± 8.4 |
| Height, cm, mean ± SD | 137.2 ± 7.4 | 136.9 ± 6.9 | 137.4 ± 7.4 | 137.6 ± 8.1 |
| Waist, cm, mean ± SD | 65.0 ± 9.5 | 67.8 ± 10.7 | 64.7 ± 9.4 | 64.0 ± 9.3 |
| BMI, kg/m2, mean ± SD | 18.1 ± 3.7 | 19.3 ± 4.0 | 18.1 ± 3.8 | 17.5 ± 3.2 |
| Weight-for-age z-score | 0.36 ± 1.1 | 0.66 ± 1.1 | 0.39 ± 1.1 | 0.16 ± 1.1 |
| Height-for-age z-score | 0.25 ± 1.0 | 0.22 ± 0.9 | 0.31 ± 1.0 | 0.22 ± 1.1 |
| BMI-for-age z-score | 0.31 ± 1.1 | 0.67 ± 1.3 | 0.31 ± 1.1 | 0.08 ± 1.1 |
| Obesity, y/n | 119 (22.7) | 37 (39.4) | 58 (21.2) | 24 (15.4) |
| Fat, kg, mean ± SD | 8.9 ± 5.6 | 10.5 ± 5.7 | 8.9 ± 6.0 | 7.7 ± 5.0 |
| Lean dry mass, kg, mean ± SD | 5.3 ± 1.8 | 5.3 ± 1.7 | 5.4 ± 1.8 | 5.3 ± 2.0 |
| Bone mineral content, kg, mean ± SD | 1.6 ± 0.5 | 1.7 ± 0.5 | 1.6 ± 0.5 | 1.5 ± 0.5 |
| Lean soft tissue, kg, mean ± SD | 23.0 ± 5.3 | 23.4 ± 5.0 | 23.1 ± 5.4 | 23.0 ± 5.5 |
| Fat-free mass, kg, mean ± SD | 25.3 ± 4.9 | 25.4 ± 5.0 | 25.6 ± 4.9 | 25.2 ± 4.9 |
| Fat mass index, mean ± SD | 4.7 ± 3.1 | 5.8 ± 3.8 | 4.7 ± 3.1 | 4.2 ± 2.5 |
| Fat-free mass index, mean ± SD | 13.4 ± 1.5 | 13.7 ± 1.7 | 13.5 ± 1.6 | 13.2 ± 1.4 |
Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure; SD, standard deviation.
Values are n (%) unless otherwise noted.
Compared with children introduced to juice at ≥ 12 months, children introduced to juice at <6 months had a higher SBP (adjusted mean difference, 3.13; 95% CI: 0.52, 5.74) and odds of hypertension (adjusted OR, 2.11; 95% CI: 1.05, 4.22) when defined by elevated SBP but not DBP (adjusted mean difference, 1.22; 95% CI: −0.57, 3.02; adjusted OR, 4.14; 95% CI: 0.94, 18.21). When applying the false discovery rate correction, hypertension defined by SBP was borderline significant. Children introduced to juice before 6 months also had a higher heart rate (adjusted mean difference, 4.46; 95% CI: 1.05, 7.87) and MAP (adjusted mean difference, 2.08; 95% CI: 0.15, 4.00) relative to juice introduction ≥ 12 months. Children introduced to juice between 6 and <12 months had a higher heart rate (adjusted mean difference, 3.21; 95% CI: 0.79, 5.62), but did not differ in BP measures from children introduced at ≥12 months. No associations were observed for PWV (Table 3). Sensitivity analyses were conducted adjusting for child BMI (Supplemental Table 1) and breastfeeding duration (Supplemental Table 2) to further examine child factors associated with cardiovascular disease risk. The results remained consistent with our findings on select cardiovascular measures.
TABLE 3.
Childhood cardiometabolic measures based on timing of juice introduction, Upstate KIDS cohort1
| Age at juice introduction |
|||
|---|---|---|---|
| Characteristics | n | <6 vs. ≥12 months |
6 to <12 vs. ≥12 months |
| Mean difference (95% CI) | |||
| SBP (mm Hg) | |||
| Unadjusted | 511 | 3.30 (0.64, 5.96) | 1.02 (−1.00, 3.05) |
| Adjusted | 497 | 3.13 (0.52, 5.74) | 1.32 (−0.72, 3.37) |
| DBP (mm Hg) | |||
| Unadjusted | 511 | 1.23 (-0.50, 2.95) | 0.03 (−1.32, 1.37) |
| Adjusted | 497 | 1.22 (-0.57, 3.02) | 0.27 (−1.06, 1.59) |
| Heart rate (beats/min) | |||
| Unadjusted | 511 | 5.25 (2.08, 8.41) | 3.09 (0.78, 5.41) |
| Adjusted | 497 | 4.46 (1.05, 7.87) | 3.21 (0.79, 5.62) |
| MAP (mm Hg) | |||
| Unadjusted | 510 | 2.08 (0.20, 3.96) | 0.45 (−1.04, 1.93) |
| Adjusted | 496 | 2.08 (0.15, 4.00) | 0.76 (−0.72, 2.24) |
| PWV (m/s) | |||
| Unadjusted | 468 | 0.20 (−0.01, 0.42) | 0.14 (−0.03, 0.31) |
| Adjusted | 456 | 0.17 (−0.07, 0.41) | 0.15 (−0.02, 0.32) |
| Odds ratio (95% CI) | |||
| Hypertension by SBP (y/n) | |||
| Unadjusted | 511 | 2.29 (1.24, 4.22) | 1.03 (0.60, 1.78) |
| Adjusted | 497 | 2.11 (1.05, 4.22) | 1.10 (0.61, 2.00) |
| Hypertension by DBP (y/n) | |||
| Unadjusted | 511 | 2.50 (0.89, 7.03) | 0.88 (0.32, 2.46) |
| Adjusted | 497 | 4.14 (0.94, 18.21) | 1.41 (0.38, 5.23) |
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure; PWV, pulse wave velocity.
Adjusted analyses control for gender, gestational age, maternal race, maternal education, marital status, maternal hypertension, prepregnancy BMI, fertility treatment, plurality, laboratory site, private insurance, and WIC participation.
With respect to anthropometry, timing of juice introduction was not related to a majority of child cardiovascular measures at 8–10 y of age after adjustment of covariates, suggesting that these differences are accounted for by socioeconomic and familial factors. This was evident as the unadjusted model revealed that children introduced to juice before 6 months trended toward higher cardiometabolic risk. Children introduced to juice earlier weighed more (unadjusted mean difference, 2.65; 95% CI: 0.26, 5.03), had a higher waist circumference (unadjusted mean difference, 3.48; 95% CI: 0.78, 6.18), and showed higher BMI- (unadjusted mean difference, 0.55; 95% CI: 0.21, 0.88), and weight-for-age z-scores (unadjusted mean difference, 0.45; 95% CI: 0.16, 0.74) with a higher risk of obesity (OR, 3.49; 95% CI: 1.91, 6.37) compared with later juice introduction. After adjustment of covariates, only risk of obesity trended in the same direction (OR, 1.95; 95% CI: 0.96, 3.94) for those introduced to juice earlier. In addition, a similar pattern was observed in the unadjusted model for select measures performed by BIA (i.e., fat, bone mineral content, FMI, and FFMI) (Supplemental Table 3).
Cardiometabolic biomarkers
The distributions of biomarkers are provided in Supplemental Table 4 based on timing of juice introduction. No statistically significant unadjusted or adjusted mean differences in the levels of lipids, HbA1c, or CRP were observed based on timing of juice introduction (Table 4). As previously described [34], based on the national guidelines on pediatric dyslipidemia, there were 10 children with a non–high-density lipoprotein level >145 mg/dL, 17 with a high-density lipoprotein level of <40 mg/dL, and 24 children with either cutoff. The prevalence of dyslipidemia was similar across groups: [6 (6.4%)] for <6 months, 11 (4%) for 6 to <12 months, and 6 (4%) for ≥12 months. Results remained the same when adjusting for child BMI (Supplemental Table 1) and breastfeeding duration (Supplemental Table 2).
TABLE 4.
Childhood differences in cardiometabolic biomarkers based on timing of juice introduction, Upstate KIDS cohort1
| Age at juice introduction |
|||
|---|---|---|---|
| Characteristics | n | <6 vs. ≥12 months |
6 to <12 vs. ≥12 months |
| Mean difference (95% CI) | |||
| Total cholesterol (mg/dL) | |||
| Unadjusted | 248 | 2.88 (−6.64, 12.40) | −2.54 (−9.60, 4.53) |
| Adjusted | 245 | 6.81 (−3.69, 17.31) | 0.78 (−6.46, 8.02) |
| HDL cholesterol (mg/dL) | |||
| Unadjusted | 248 | −0.27 (−4.56, 4.01) | −1.15 (−4.78, 2.49) |
| Adjusted | 245 | 0.09 (−4.84, 5.03) | −1.10 (−4.79, 2.59) |
| LDL cholesterol (mg/dL) | |||
| Unadjusted | 248 | 3.09 (−5.36, 11.54) | −1.14 (−7.65, 5.37) |
| Adjusted | 245 | 4.95 (−4.58, 14.49) | 1.23 (−5.51, 7.97) |
| Non-HDL cholesterol (mg/dL) | |||
| Unadjusted | 248 | 3.18 (−6.27, 12.64) | −1.61 (−8.95, 5.73) |
| Adjusted | 245 | 5.90 (−4.35, 16.14) | 1.61 (−5.53, 8.75) |
| Tg (mg/dL) | |||
| Unadjusted | 248 | 1.54 (−22.42, 25.51) | −0.18 (−18.85, 18.50) |
| Adjusted | 245 | 13.55 (−12.49, 39.59) | 6.35 (−9.71, 22.41) |
| CRP (mg/L) | |||
| Unadjusted | 154 | 0.27 (−0.38, 0.93) | 0.27 (−0.33, 0.87) |
| Adjusted | 152 | −0.56 (−1.36, 0.23) | −0.03 (−0.69, 0.63) |
| HbA1c (%) | |||
| Unadjusted | 248 | 0.04 (−0.06, 0.13) | 0.01 (−0.07, 0.08) |
| Adjusted | 245 | −0.03 (−0.13, 0.07) | −0.01 (−0.09, 0.06) |
Abbreviations: HDL, high-density lipoprotein; LDL, low-density lipoprotein; Tg, triglycerides; CRP, C-reactive protein; HbA1c, hemoglobin A1c.
Adjusted analyses control for gender, gestational age, maternal race, maternal education, marital status, maternal hypertension, prepregnancy BMI, fertility treatment, plurality, laboratory site, private insurance, and WIC participation.
Discussion
In our population-based, longitudinal cohort, we observed that timing of juice introduction was associated with select cardiovascular measures in middle childhood. Specifically, earlier age of juice introduction was associated with higher SBP and higher odds of hypertension relative to elevated SBP. Furthermore, earlier juice introduction before 6 months was associated with a higher heart rate as was juice introduction between 6 and <12 months. Additionally, earlier introduction was associated with a higher risk of obesity relative to those introduced to juice later. There were no observed differences between the timing of juice introduction and most anthropometric outcomes after adjustment for socioeconomic and familial factors, nor any cardiometabolic biomarkers. Data for this cohort were collected before the AAP changed their guidelines in 2017 and ∼52% of infants in this subsample were introduced to juice between 6 and <12 months, consistent with the guidelines at the time of data collection. Limited evidence then remains on whether delaying juice introduction past 12 months consistent with AAP guidelines is more advantageous in reducing cardiometabolic risk.
Currently, there are no studies that have evaluated the effects of juice introduction during infancy on cardiometabolic outcomes in middle childhood. Prior studies have focused on the adverse effects of the quantity of juice consumed during early childhood and combined individual risk factors into a continuous cardiometabolic risk factor score, which makes it difficult to compare our overall findings [8,21,44]. One study, however, found significant associations among juice intake at 13 months and higher cardiometabolic risk in boys in middle childhood [21]. Of the number of longitudinal and cross-sectional studies examining juice intake, most observed associations between juice intake with adiposity in childhood; evidence suggesting an increased risk of obesity and CVD [22,[45], [46], [47]].
To our knowledge, only 3 studies have examined the timing of SCB introduction with anthropometric outcomes (i.e., BMI, BMI-, and weight-for-age z-scores, developing overweight or obesity) in childhood [18,20,48]. Our unadjusted results align with Pan et al. [20], who observed a higher odds of obesity (OR: 1.92; 95% CI: 1.01, 3.66) in children introduced to SSBs before 6 months of age compared with those not introduced. Although we observed attenuated differences for most anthropometric outcomes after adjusting for sociodemographic factors in this subsample, we previously observed associations between the timing of juice introduction and anthropometric measures in middle childhood in our larger cohort, not limited to those who attended clinic visits at 4 sites [18]. We found juice introduced before 6 months was associated with higher BMI- (adjusted mean difference, 0.38; 95% CI: 0.12, 0.64) and weight-for-age z-scores (adjusted mean difference, 0.27; 95% CI: 0.06, 0.49) and higher odds of developing obesity (OR: 2.17; 95% CI: 1.11, 4.23) at 7–9 y of age compared with those introduced to juice later. Despite observing no differences in our smaller cohort, examining BMI-for-age z-scores is an ideal clinical measure to examine excess adiposity in children. Traditional anthropometric measures used to detect changes in body composition such as BMI or depending on parental report of their child’s weight alone may inaccurately assess significant changes in child’s adiposity over time [49,50]. However, how timing of juice introduction influences nonanthropometric cardiometabolic outcomes independent of children’s anthropometry remains unclear.
Although we found no significant associations between timing of juice introduction and cardiometabolic biomarkers, there are no studies directly comparable to our findings. Most studies have examined an association between juice and cardiometabolic markers with respect to intake of SCBs in early and middle childhood. For instance, Leermakers et al. [21] found in 2045 children that higher SCB intake during infancy trended toward higher cardiometabolic risk with higher triglycerides (adjusted mean difference, 0.12; 95% CI: −0.01, 0.25) and lower HDL-c (adjusted mean difference, 0.12 95% CI: −0.25, 0.01) at 6 y of age. A study conducted by Kosova et al. [2] found in 4880 children that high SSB intake was positively associated with CRP concentrations (P < 0.05), whereas there was an inverse association with HDL-c (P < 0.001) in 3- to 11-y-old children. Another study conducted by Van Rompay et al. [26] found in 613 children that high SSB intake was positively associated with higher plasma Tg concentrations (P = 0.03) in 8- to 15-y-old children.
Between 2011 and 2014, ∼7.6% of United States children’s total caloric intake comes from SSBs [51]. This proportion was higher as children age and could purchase foods/beverages themselves, with younger children (2–5 y old) having ∼4% of daily calories accounted for by SSBs to over 9% of calories by 12–19 y. We previously observed that earlier juice introduction was associated with more juice and soda intake in early and middle childhood (P < 0.0001). Specifically, introduced before 6 months (adjusted relative risk, 1.6; 95% CI: 1.4, 1.8) and between 6 and 12 months (adjusted relative risk, 1.7; 95% CI: 1.5, 1.8) were associated with higher subsequent juice intake relative to later juice introduction, thus potentially leading to SCBS contributing more to children’s daily calories [19]. During the first half year of life, children are exposed to a variety of foods that differ in smell, taste, flavor, texture, and energy densities. Preferences for sweet tastes can be explained by the dietary sugars and their derivates, fructose and lactose, but other substances such as amino acids found in SCBs can activate the sensory cells that respond to sweetness [52]. Therefore, the age at which juice is introduced may influence the innate preferences for sweet tastes and most likely establish a pattern of beverage intake [53].
Emerging but inconclusive evidence of the biological mechanisms between SCBs and CVD suggests the influence of dietary sugars on CVD risk through multiple pathways [38,39]. As dietary sugars are ingested, this can induce a rapid spike in both blood glucose and insulin levels, which in combination with an excessive consumption of dietary sugars, can result in high dietary glycemic load and elevated plasma triglycerides. This elevation may promote hyperinsulinemia and insulin resistance and exacerbate inflammatory markers such as C-reactive protein [CRP] [54]. In addition, excessive dietary sugars can lead to increased hepatic de novo lipogenesis in the liver, leading to increased production and secretion of low-density lipoprotein cholesterol (LDL) and elevated plasma triglycerides; thus elevating the risk of CVD [55]. Despite evidence of a dose–response relationship between dietary sugars and CVD, there are no studies directly examining the effect of added sugars on CVD risk during infancy. In a cross-sectional study conducted by Kell et al. [56] in 124 children, added sugars in the diet were positively associated with diastolic BP and serum triglycerides at 7–12 y of age. Another study by Morrison et al. [57] found in 949 children that those with lower added sugars in the diet had lower triglycerides and higher HDL-c at 6–19 y of age compared with those with higher added sugars. Taken together these reported findings provide support for an association between dietary sugars and select cardiometabolic outcomes and possible ties to a higher risk of CVD in childhood.
The strengths of this study include the longitudinal design and comprehensive assessment of cardiometabolic risk by trained examiners, although our study has several limitations. We were unable to distinguish between the introduction of 100% fruit juice and juice with added sugars. This lack of specification in our questionnaire may introduce measurement error. Although this limitation has been noted in previous studies [20,48,58], the study was strengthened by prospectively asking mothers the age of juice introduction from 4 to 18 months, which may minimize recall bias. Furthermore, we were able to control for many potential confounders but could not account for maternal diet [59] or additional indicators of socioeconomic status that may impact the age of juice introduction and may result in residual confounding. Although differences were observed across the age of juice introduction for mothers smoking during pregnancy, we were unable to adjust for smoking as a potential confounder due to lack of convergence as few mothers who introduced juice to their children ≥ 12 months reported smoking (2.6%). Lastly, the cohort was predominantly non-Hispanic White and of higher socioeconomic status, which may limit the generalizability of the study findings.
In conclusion, in our population-based, longitudinal cohort study, we observed associations that earlier juice introduction was positively associated with select primary cardiometabolic outcomes in middle childhood with evidence that these differences are influenced by socioeconomic and familial factors. Future studies should examine the effects of different types of SCBs (e.g., 100% fruit juice compared with juice with added sugars) to understand the differing effects of introducing these beverages on cardiometabolic risk in childhood. Lastly, identifying how children’s dietary preferences may mediate these associations in middle childhood should be explored.
Author Contributions
The authors’ responsibilities were as follows – PKC, EHY, DLP: contributed substantially to the article via conceptualization, data curation, writing—original draft, and methodology; PKC: made formal analysis; EHY: contributed to resources, project administration, and funding acquisition; PKC, DLP, IRT, SLR, TGO, JNT, EHY were involved in writing—reviewing and editing; DLP, EHY: were involved in supervision; and all authors: read and approved the final version of the manuscript.
Conflict of interest
The authors declared no conflict of interest.
Funding
Supported by the Intramural Research Program of Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; contracts #HHSN267200700019C #HHSN275201200005C #HHSN275201300026I/27500004, and #HHSN275201400013C).
Data availability
Data described in the manuscript, code book, and analytic code will be made available upon request pending internal review. Requests for data and other information can be sent to the corresponding author, Dr. Edwina Yeung, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.tjnut.2024.06.014.
Contributor Information
Diane L Putnick, Email: putnickd@mail.nih.gov.
Ian R Trees, Email: ian.trees@nih.gov.
Sonia L Robinson, Email: sonialr@umich.edu.
Thomas G O’Connor, Email: tom_oconnor@urmc.rochester.edu.
Jordan N Tyris, Email: jbarger@childrensnational.org.
Edwina H Yeung, Email: edwina.yeung@nih.gov.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data described in the manuscript, code book, and analytic code will be made available upon request pending internal review. Requests for data and other information can be sent to the corresponding author, Dr. Edwina Yeung, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.