Dietary patterns of early childhood and maternal socioeconomic status in a unique prospective sample from a randomized controlled trial of Prenatal DHA Supplementation

Childhood has been widely studied as a critical period for establishing dietary habits that carry short and long term health consequences. However, the complexity of dietary intake data can cloud the connection between intake and health outcomes. Many European colleagues have begun to use multivariate statistical methods to consolidate large amounts of information about food and drink intake into dietary patterns that have been linked to pediatric health outcomes [1‐6]. Heretofore, there are no examples of the use of these data-driven approaches to characterize dietary patterns among US children.

Socioeconomic status (SES) confounds efforts to isolate how childhood dietary habits relate to health outcomes. SES is a multidimensional construct that conveys relative wealth, power, and prestige, and it is influenced by race, ethnicity, parental education, occupation, and income. It is also a strong determinant of health [7] and has been repeatedly linked to diet quality [8‐14]. Importantly, the association between SES and a health outcome can differ depending on how SES is measured [15]. Furthermore, the overall effect of SES cannot be accurately estimated when the highly collinear variables that determine SES are all added as covariates in a statistical model.

There is steadily accumulating evidence that the intrauterine environment has long-lasting effects on child growth and development (see [16] for just one recent review). We are extensively phenotyping a cohort of children from a randomized controlled trial of high dose prenatal docosahexaenoic acid (DHA) supplementation [17]. Given that the relationship between long-chain n-3 polyunsaturated fatty acids (n-3 LCPUFA) and a health outcome can hinge on environmental and genetic circumstance [18‐20], it is possible that the effect of prenatal supplementation differs depending on diet and/or maternal SES. For example, children exposed to high levels of DHA in utero may be strongly buffered against the negative effects of a stressful, low-income environment; whereas, children born into a more privileged environment and fed nutrient-rich foods may not benefit as much from prenatal DHA exposure. We therefore sought to succinctly characterize the diets and maternal SES of this cohort of US toddlers and preschool children using an unbiased, empiric approach so that we may later test for interactions with prenatal DHA supplementation. Our goals were to 1) efficiently summarize dietary intake into dietary patterns, 2) generate an SES score for each subject, and 3) describe how they are related in this unique cohort.

Table 1 describes the 190 mother-child dyads. Only three participants reported “Other” race/ethnicity and they described themselves as “Pacific Islander or Native Hawaiian,” “Asian,” and “American Indian or Native Alaskan.” There was higher variance in maternal RBC DHA at delivery than at baseline (p < 0.0001).

The SES factor explained 58% of the variance in its four composite variables: maternal race, years of formal education, age, and income by zip code. Individual SES scores ranged from 0.12 to 4.02 with a mean ± SD of 2.00 ± 1.00.

The associations among SES and sample characteristics are exhibited in Table 2. The average non-Hispanic White mother’s SES score was 1.52 (95% confidence interval (CI): 1.29 to 1.74) higher than the average Black mother’s and 1.35 (95% CI: 0.93 to 1.78) higher than Hispanic White mother’s scores. Women who had never smoked tobacco had higher SES compared to those who had smoked (mean difference 0.36, 95% CI: 0.08 to 0.65). Women who breastfed had a higher SES score compared to those who fed their infant only formula (mean difference 0.73, 95% CI: 0.43 to 1.02). Maternal SES was positively associated with maternal height, gestational weight gain, birthweight, duration of breastfeeding, maternal RBC DHA at enrollment and delivery, change in DHA, and adherence and negatively associated with maternal weight, maternal BMI, and duration of formula feeding (all p < 0.05). Overweight and obese mothers (BMI ≥25) had a lower SES score (mean difference 0.48, 95% CI: 0.19 to 0.78).

In decreasing order, the six most consumed food and beverage categories were 1) refined grains, 2) discretionary fat and condiments, 3) sweet beverages, 4) yogurt and non-whole milk, 5) artificially sweetened and unsweetened beverages (not sweet beverages), and 6) fruit. In servings, the mean ± SD daily consumption of total grains was 3.6 ± 1.1, total meat 2.0 ± 1.3, total dairy 1.7 ± 1.1, total fruit 0.8 ± 0.7, and total vegetables plus legumes 0.8 ± 0.7. Intake of only 6 of the 24 food and beverage categories changed significantly over the 2.5 years period as depicted in Fig. 1 (all p < 0.05). From 2 to 4.5 years of age, the average daily intake of refined grains increased by 44%, discretionary fat and condiments by 53%, not sweetened beverages by 43%, desserts and sweets by 75%, and nuts and seeds by 145% while mean daily whole milk intake decreased by 78%.

Cluster analysis identified two major dietary patterns. Eighty-five children (45%) had a Prudent diet and 105 children (55%) had a Western diet. As illustrated in Fig. 2, which includes all 24 final food and beverage groupings, the Prudent diet (versus the Western diet) was principally characterized by greater consumption of whole grains, fruit, and yogurt and low-fat milk; and lower consumption of red meat, discretionary fat and condiments, sweet beverages, refined grains, and French fries and potato chips (all p < 0.0001). Smaller magnitude differences included children with a Prudent diet consuming more green and non-starchy vegetables and nuts and seeds, and less eggs, starchy vegetables, processed meats, fried and not fried chicken and seafood, and whole milk (all p < 0.05).

Table 3 presents the associations between the child dietary patterns and characteristics of mothers and children. Compared to the mothers of children with a Western dietary pattern, mothers of children with a Prudent diet had a mean SES score that was one standard deviation higher (difference 1.05, 95% CI: 0.80 to 1.30). Compared to children with a White mother, children with a Black mother were twice as likely to have a Western dietary pattern (relative risk 2.1, 95% CI: 1.6 to 2.7). Mothers of children with a Prudent diet had higher RBC DHA at baseline; relative difference 12 % (95% CI: 3.6 to 20%); however, this association lost strength with adjustment for SES. After controlling for maternal SES, the mothers of children with a Prudent diet, on average were 1.9% taller (p = 0.03), had a 9.8% lower BMI (p = 0.04), breastfed 110% longer (p = 0.002), were 24% more likely to have breastfed at all (p = 0.01), and were more adherent (p = 0.004), i.e., they took 8.8% (95% CI: 2.8 to 15%) more of their capsules. There was no evidence of an interaction between SES and dietary pattern for any maternal characteristic (all p > 0.05), except for adherence. The women with the lowest adherence were of low SES and reported a Prudent diet for their offspring (p_interaction = 0.0007).

Supplementation affected maternal RBC DHA composition (p < 0.0001); mothers randomized to the control group increased their DHA 0.35% (95% CI: -0.04 to 0.74%) while mothers who received active treatment increased their DHA 3.09% (95% CI: 2.72 to 3.46%). The effect of supplementation on maternal RBC DHA differed by SES (p_interaction = 0.002); high SES was associated with a larger increase in DHA among those who received DHA (r = 0.34, p = 0.0007), but not among those who received placebo (p = 0.76) (Fig. 3). Interestingly, the interaction between SES, supplementation, and change in DHA persisted even after controlling for adherence (p_interaction = 0.002). In fact, adherence was not significantly associated with change in maternal RBC DHA among women who received active treatment (r = 0.13, p = 0.20).

We have characterized the dietary habits of a diverse and unique cohort of young children in the US and reported how a child’s major dietary pattern relates to maternal SES and other maternal characteristics. We found that daily food and drink intake is relatively stable across the ages of 2 to 4.5 years, in general agreement with data from longitudinal studies conducted in Europe [10, 14]. However, it was concerning that the young children mostly added energy-dense foods of low nutritional value (refined grains, discretionary fat and condiments, and desserts and sweets) as they grew older.

We chose to average a child’s intake over time in order to maximize our sample size (i.e., include children with missing data) while attempting to minimize the effect of age via residualization. Using average intake over the 2.5 years period, we categorized the pattern of food and drink consumption in early childhood as either Prudent or Western. A Prudent diet represented relatively greater consumption of whole grains, fruit, yogurt and low-fat milk, green and non-starchy vegetables, and nuts and seeds. In contrast, children with a Western diet ate more red meat, discretionary fat and condiments, sweet beverages, refined grains, French fries and potato chips, eggs, baked or boiled starchy vegetables, processed meats, fried chicken and seafood, not-fried chicken & seafood, and whole milk.

We used cluster analysis to create a single, categorical variable from the large amount of information describing the diets of children age 2 to 4.5 years. We chose to avoid dietary factor analysis, because (a) categorical variables are easier to comprehend compared to continuous variables, (b) it can be difficult to justify how many factors are retained (c) we wanted to minimize the number of newly constructed variables, and (d) factor scores are usually categorized into quantiles, a practice that has been critiqued [32]. Other groups of investigators have used reduced rank regression (RRR) as a multivariate technique to identify dietary patterns that explain maximum variance of outcomes [22, 28], however, defining dietary pattern by RRR could limit future evaluations. The children in this cohort are being extensively phenotyped (e.g., cognitive testing, blood pressure, body composition, brain structure/function and growth) as they age to 9 years. The empirically defined dietary patterns herein are not biased toward prediction of any outcome; however, they are not optimized for any outcome either.

We found that several important maternal features differed by offspring dietary pattern. Mothers of children with a Western dietary pattern had a lower SES, breastfed less, and had a higher BMI at enrollment; observations similar to what was found for the “Junk” dietary pattern from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort [33]. Our findings are also congruent with the direct association between parental education and more favorable nutrient intake among older female children in the US [34]. We found evidence that a child’s diet was related to his or her mother’s dietary behavior, because higher maternal DHA at baseline was associated with the offspring consuming a Prudent diet. Interestingly, maternal height was positively associated with a child adhering to a Prudent dietary pattern even after adjusting for SES. Children with a Prudent diet consumed more low-fat milk and yogurt; this observation is consistent with the hypothesis that milk protein intake is associated with greater height in children [35, 36].

Mothers who were non-Hispanic White, older, more educated, and lived in a higher income area had elevated SES scores, while mothers who were Black or Hispanic, younger, less educated, and lived in an economically disadvantaged neighborhood had lower SES scores. The collinearity among these variables is consistent with other US samples showing that education is positively correlated with age at first birth [37] and income [38]. Black and Hispanic families are about twice as likely to live in poverty compared to Asian and non-Hispanic White households [38]. Individuals with higher income tend to be taller [39], which is consistent with the positive correlation between SES and maternal height that we observed. We also found that SES was inversely correlated with maternal weight and BMI at enrollment, which is compatible with known associations between weight status, race, and education [40]. The more weight a mother gains during pregnancy, the greater the offspring’s weight at birth [41]. A positive correlation between SES and gestational weight gain and birthweight parallels the association between poverty and likelihood of intrauterine growth restriction [42]. We replicated the positive correlation between breastfeeding and SES [43]. The congruency between the SES associations in this report and previous research corroborates the validity of the SES index we constructed.

There was a large range in effect of supplementation on maternal RBC DHA concentration. DHA levels were stable for those randomized to control, regardless of maternal SES or adherence; however, for those mothers randomized to DHA supplementation, maternal SES was a stronger predictor of DHA increase than pill count. There was an interesting interaction between maternal SES and child dietary pattern for adherence. Low SES mothers that reported a Prudent diet for their child had the worst adherence by pill count; this may indicate a lack of candor with regard to dietary recall. The observation is limited to a small number of participants and could be spurious; nevertheless, it will be interesting to see if this subset of children exhibits a developmental trajectory more similar to those with a Western dietary pattern.

Our study has several limitations. First, the dietary pattern analysis is susceptible to (a) inaccurate recalls from caregivers reporting healthier dietary habits than reality, (b) a sample biased by loss to follow-up, (c) the constraints of the NDSR’s categories of food and beverages, and (d) our food/beverage group consolidation scheme. Second, for the sake of parsimony, cluster analysis admittedly discards a large amount of the variance. Third, SES is a multidimensional construct that includes measurements not included here, e.g., accumulated economic assets, parity, occupation, marital status, and paternal income [15]. Fourth, we did not directly measure family income, but instead used a residential proxy. Fifth, we incorporated age and race/ethnicity into the SES index, because they are likely mediators of SES effects on maternal-fetal health; however, this assumes that the associations among education level, income, and age are stable across racial/ethnic categories, an assumption that may not be true [15]. Lastly, the major tradeoff of extracting the maximum SES signal from available variables is that this obviates the potential to assess independent effects of the covariates that comprise SES in future analyses.

We observed a consistent number of servings per day consumed for most food and beverage categories across the period of 2 to 4.5 years of age, defined two major and mutually exclusive dietary patterns in a unique sample of US preschool children and a single, continuous axis of maternal SES, and identified significant relationships between dietary pattern and maternal variables that were present even after adjusting for maternal SES. We look forward to exploring how a young child’s diet, maternal SES, and prenatal supplementation of DHA interact to influence child growth and development.