Abstract
Objective:
To evaluate whether breastfeeding and its duration are associated with a reduced risk of low intelligence quotient (IQ) scores or other neurodevelopmental problems.
Methods:
We conducted a secondary analysis of two parallel multicenter, double-blinded randomized controlled trials in which participants with a singleton pregnancy and either subclinical hypothyroidism or hypothyroxinemia were treated with thyroxine or placebo. Our primary outcome was low IQ score (<85 at age 5 by Wechsler Preschool and Primary Scale of Intelligence III). Secondary outcomes included performance measures on other validated neurodevelopmental tests. Univariable and multivariable analyses were performed to evaluate the association between breastfeeding and neurodevelopmental outcomes. Step-wise backward proceeding linear and logistic regression models were used to develop the final adjusted models.
Results:
Of the 772 participants studied, 614 (80%) reported breastfeeding. Of these, 31% reported breastfeeding for <4 months, 19% for 4–6 months, 11% for 7–9 months, 15% for 10–12 months and 23% for >12 months. IQ scores were available for 756 children and mean age 5 scores were higher with any breastfeeding (96.7±15.1) than without (91.2±15.0, mean difference 5.5, 95% CI 2.8–8.2) and low IQ scores were less frequent with any breastfeeding (21.5%) than with no breastfeeding (36.2%, OR 0.48, 95% CI 0.33–0.71). In adjusted analyses, breastfeeding remained associated with reduced odds of low IQ (aOR 0.62, 95% CI 0.41–0.93) and each additional month of breastfeeding was associated with lower odds of a low IQ score (aOR 0.97, 95% CI 0.939–0.996). No significant associations between breastfeeding and other neurodevelopmental outcomes were identified in adjusted analyses.
Conclusion:
Breastfeeding and its duration are associated with lower odds of low IQ score at age 5.
Precis:
Breastfeeding and its duration are associated with a lower risk of a low intelligence quotient score (<85) at age 5.
Introduction:
Several studies have evaluated breastfeeding and its association with childhood neurodevelopmental outcomes. Some of these studies, including a recent meta-analysis, have demonstrated a relationship between breastfeeding, particularly exclusive breastfeeding, and better child neurodevelopmental outcomes (1–7).. A few studies have demonstrated associations with breastfeeding and continued intellectual and achievement benefit through adolescence and adulthood (8–11).. In addition, in a population-based study of an urban cohort in Brazil, short duration of breastfeeding (<1 month) was reported as an independent predictor of low intelligence quotient (IQ) scores at age 6 after adjusting for multiple demographic and family conditions (12). Similarly, lack of breast feeding was associated with both low-IQ and attention deficit hyperactivity disorder (ADHD) in children age 8–11 from schools in five Korean cities after adjustment for social and demographic factors including maternal IQ (13). A recent meta-analysis of 11 studies also found that lack of breast feeding and short breast feeding duration were associated with the development of ADHD (14).
The composition of breast milk, particularly early in infancy, is rich in long-chain polyunsaturated fatty acids compared with infant formulas (15–16). Infant brain development depends, in part, upon myelination and the corresponding expansion of neural networks throughout infancy and early childhood (17–169). Myelination contributes to the development of neural pathways that then provide the foundation for emerging cognitive and behavioral developments (20). The myelination process requires the delivery of long-chain polyunsaturated fatty acids, among other nutrients (21). Theoretically, through enhanced myelination, breastfeeding could be associated with early child neurodevelopment and potentially long-lasting benefit (15).
We hypothesized that breastfeeding and its duration are associated with a reduced risk of low intelligence quotient (IQ) scores at age 5 and potentially other neurodevelopmental problems. The primary objective of this analysis was to evaluate whether breastfeeding and its duration are associated with a lower risk of low IQ scores at age 5 as compared with no breastfeeding. The secondary objective was to evaluate whether breastfeeding is associated with a lower risk of other neurodevelopmental problems.
Methods:
We conducted a secondary analysis of two Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network trials, entitled, “Treatment of subclinical hypothyroidism or hypothyroxinemia in pregnancy” (22). These trials were parallel-design, randomized controlled trials of thyroxine for either subclinical hypothyroidism or hypothyroxinemia and took place across 33 hospitals in the United States. People with singleton pregnancies were screened prior to 20 weeks gestation for subclinical hypothyroidism (thyrotropin 3.0 milliunits/L or greater and free thyroxine 0.86–1.9 ng/dL) or hypothyroxinemia (thyrotropin 0.08–3.99 milliunits/L and free thyroxine less than 0.86 ng/dL) and randomized to receive levothyroxine or placebo. Patients with overt hypothyroidism or hyperthyroidism were excluded. For participants, thyroid function was assessed monthly and (depending on trial) adjusted to achieve normal free thyroxine levels. Sham adjustments were performed for placebo subjects. Children underwent annual neurodevelopmental testing for 5 years. The primary outcome of the parent trial was intelligence quotient score at age 5, or at age 3 if the 5-year data were missing or death occurred after age 3. The study’s conclusions were that neither treatment for subclinical hypothyroidism nor hypothyroxinemia beginning between 8 and 20 weeks of gestation resulted in significantly better cognitive outcomes in children through age 5 as compared to no treatment for these conditions. Institutional review board approval was obtained at each clinical site for the primary trial.
In this secondary analysis we included subjects for whom breastfeeding data, collected by self-report two years after delivery, were available and 3 or 5-year child neurodevelopmental data were available. We excluded infants with chromosomal or structural anomalies and those who required neonatal intensive care admission. The primary outcome for this secondary analysis was low IQ score at age 5 defined as <85 by Wechsler Preschool and Primary Scale of Intelligence III (WPPSI-III). Secondary outcomes included the following: IQ score at age 5, low Differential Ability Scales-II (DAS-II) General Conceptual Score at age 3 defined as <85, DAS-II General Conceptual Score at age 3, DAS-II specific scores on sub-tests at age 4 (recall digits forward and picture recognition with a low score defined as <25th percentile), Bayley III Cognitive, Motor and Language scores (age 1 and 2) evaluated by total score and score <85 for each domain, Child Behavioral Checklist (CBCL) T-score > 60 (age 3 and 5), and Conners’ Rating Scales-Revised for assessment of attention deficit hyperactivity disorder (ADHD) T-score >60 (age 4). A T-score >60 for both the CBCL and Conner’s Rating Scales-Revised were considered to be of possible clinical concern (22). Breastfeeding occurrence was self-reported 2 years after delivery and categorized as any versus none. Duration was categorized as 0 for no breastfeeding, and the median of the following categories <4 months, 4 to 6 months, 7 to 9 months, 10 to12 months, and >12 months. Demographic and clinical data were obtained by interview and chart abstraction by trained research personnel. Race was determined by subject self-identification as either White, Black, Asian, Native Hawaiian or Pacific Islander, Other, Not Reported. Ethnicity was self-reported as Hispanic or Non-Hispanic. Due to small numbers, Asian, Native Hawaiian or Pacific Islander, Other and Not Reported were collapsed into Other. Small for gestational age (SGA) was defined as a birth weight less than tenth percentile for gestational age based upon a neonatal sex and race and ethnicity specific nomogram (23). Trained and certified examiners assessed all neurodevelopmental outcomes. Research staff, examiners and patients were unaware of trial or treatment group.
Univariable analyses were performed using chi-square or Fisher’s exact tests for categorical variables and Wilcoxon rank sum test for continuous variables to compare maternal characteristics and child outcomes based on breastfeeding occurrence (any vs. none). Linear regression analysis examining the association between breastfeeding and child outcomes reported on a continuous scale and logistic regression analysis examining the association between breastfeeding and binomial outcomes were also performed. To develop the final adjusted models, step-wise backward proceeding multivariable regression models were used. Variables eligible for multivariable analysis included maternal age, race and ethnicity, pre-pregnancy body mass index (BMI), parity, education level, insurance type, smoking, alcohol use, thyroid status, treatment group, gestational age at delivery, birth weight <10th percentile, infant sex, and age at neurodevelopmental exam. Variables with a P-value <0.1 in the step-wise models were included in final regression models and those that did not achieve a P-value of <0.1 were excluded from the final regression models. For outcomes in which there was a significant association with breastfeeding in the multivariate analysis, we also examined the duration of breastfeeding. To evaluate the association between duration of breastfeeding and neurodevelopmental outcomes, we ran logistic regression models using 0 for no breastfeeding and the midpoint of each of the pre-specified breastfeeding duration categories (2, 6, 8, 12, and 18) in the models to provide the adjusted odds per month of breastfeeding and a 95% confidence interval. We further explored whether there was a curvilinear relationship with duration of breastfeeding by generating models that included a quadratic term for duration of breastfeeding. For the primary outcome and all secondary outcomes, we performed sensitivity analyses to evaluate if inclusion of treatment (thyroxine versus placebo) or group assignment (subclinical hypothyroidism versus hypothyroxinemia) altered the conclusions. Similarly, we performed a propensity score matching analysis as an alternative analytic strategy to corroborate our findings.
Imputation for missing data was not performed. Nominal P values of less than 0.05 were considered statistically significant. No adjustments were made for multiple comparisons. All analyses were performed using SAS 9.4 statistical software (SAS Institute Inc., Cary, NC,). Approval was obtained from the institutional review board at each participating institution.
Results:
Of the 1,203 participants in the trial, 772 were included in this analysis (Figure 1) of whom 614 (80%) reported breastfeeding: 188 (31%) for <4 months, 118 (19%) for 4–6 months, 65 (11%) for 7–9 months, 93 (15%) for 10–12 months and 141 (23%) for >12 months. Of the 141 who reported breastfeeding for >12 months, 34 (24.1%) reported that they were still breastfeeding at the time of the two-year exam. Nine participants breastfed for an unknown duration. Maternal demographic and clinical characteristics according to breastfeeding occurrence are displayed in Table 1. Participants who breastfed were older and had a lower BMI, on average, and were more likely to be Non-Hispanic White, privately insured, non-smokers, have a college degree, have subclinical hypothyroidism and were less likely to have subclinical hypothyroxinemia.
Figure 1:
Patient inclusion and exclusion.
Table 1.
Baseline demographic and clinical characteristics by breastfeeding status
| Breastfeeding N=614 | No Breastfeeding N=158 | P-value | |
|---|---|---|---|
| Age (years) | 28.4 ± 5.7 | 26.5 ± 5.7 | <0.001 |
| Race and ethnicity | <0.001 | ||
| Non-Hispanic White | 210 (34.2) | 36 (22.8) | |
| Non-Hispanic Black | 51 (8.3) | 58 (36.7) | |
| Hispanic | 335 (54.6) | 63 (39.9) | |
| Other/Unknown | 18 (2.9) | 1 (0.6) | |
| Pre-pregnancy body mass index (kg/m2)* | 27.2 ± 6.1 | 29.5 ± 7.8 | 0.002 |
| Nulliparity | 203 (33.1) | 43 (27.2) | 0.16 |
| Insurance | <0.001 | ||
| Public | 322 (52.4) | 128 (81.0) | |
| Private | 208 (33.9) | 20 (12.7) | |
| Self-pay | 84 (13.7) | 10 (6.3) | |
| Maternal education | <0.001 | ||
| Less than high school | 258 (42.0) | 75 (47.5) | |
| High school or some college | 192 (31.3) | 71 (44.9) | |
| College graduate or higher | 164 (26.7) | 12 (7.6) | |
| Smoked during pregnancy | 23 (3.7) | 34 (21.5) | <0.001 |
| Alcohol use during pregnancy | 37 (6.0) | 10 (6.3) | 0.89 |
| Illicit drug use during pregnancy | 3 (0.5) | 5 (3.2) | 0.01 |
| Gestational hypertension or preeclampsia | 56 (9.1) | 13 (8.2) | 0.73 |
| Thyroid status | <0.001 | ||
| Subclinical hypothyroidism | 372 (60.6) | 66 (41.8) | |
| Subclinical hypothyroxinemia | 242 (39.4) | 92 (58.2) | |
| Levothyroxine treatment group | 312 (50.8) | 77 (48.7) | 0.64 |
| Gestational diabetes | 41 (6.7) | 13 (8.2) | 0.50 |
| Gestational age at delivery (weeks) | 39.4 ± 1.3 | 39.4 ± 1.4 | 0.81 |
| Preterm birth <37 weeks | 24 (3.9) | 13 (8.2) | 0.02 |
| Route of delivery | 0.32 | ||
| Spontaneous vaginal | 429 (69.9) | 101 (63.9) | |
| Operative vaginal | 20 (3.3) | 5 (3.2) | |
| Cesarean | 165 (26.9) | 52 (32.9) | |
| Small for gestational age birth weight < 10th percentile | 45 (7.3) | 15 (9.5) | 0.36 |
| Male sex | 322 (52.4) | 94 (59.5) | 0.11 |
Data are displayed as mean ± standard deviation or n (%). N is provided in the column header unless otherwise indicated below. Race was determined by subject self-identification as either White, Black, Asian, Native Hawaiian or Pacific Islander, Other, Not Reported. Ethnicity was self-reported as Hispanic or Non-Hispanic. Due to small numbers, Asian, Native Hawaiian or Pacific Islander, Other and Not Reported were collapsed into Other.
19 missing pre-pregnancy body mass index
WPPSI-III IQ scores were available for 756 children whose average age at exam was 60.1±1.7 months. The Bayley one-year exam scores were available for 758 children whose average age at exam was 12.0±1.2 months. The Bayley two-year exam scores were available for 764 children whose average age at exam was 24.0±1.1 months. The DAS-II three-year exam scores were available for 757 children whose average age at exam was 36.0±1.3 months. The Conners’ Rating Scales-Revised ADHD was available for 747 children whose average age was 48.0±1.1 months. The CBCL 5-year evaluation score was available for 760 children whose average age at exam was 60.1±1.7 months.
In unadjusted analysis, low IQ scores at age 5 occurred less frequently after any breastfeeding (21.5%) than without breastfeeding (36.2%, OR 0.48, 95% CI 0.33–0.71) (Table 2). Similarly, mean IQ scores were higher at age 5 with any breastfeeding (96.7 ± 15.1) than without (91.2 ± 15.0, mean difference 5.5, 95% CI 2.8–8.2). The DAS II outcomes assessed at age 3 were similar to the age 5 IQ scores. Low DAS II scores occurred less frequently after any breastfeeding (32.2%) as compared with no breastfeeding (43.5%,OR 0,62, 95% CI 0.43–0.88) and the mean score was higher among breastfed infants (92.0 ± 15.8) as compared with no breastfeeding (88.2 ± 15.4, mean difference 3.8, 95% CI 0.99 to 6.6). Low scores for the DAS II subtest on picture recognition at age 4 occurred less frequently with breastfeeding (17.6%) as compared with no breastfeeding (30.0%,OR 0.50, 95% CI 0.33–0.75). Similarly, low CBCL scores at age 5 were less common among breastfed children (9.2%) as compared with those who were not breastfed (16.3%, OR 0.52, 95% CI 0.31–0.87). Mean Bayley III motor scores and Bayley III language scores at age 2 were also significantly higher with any breastfeeding compared with no breastfeeding. In unadjusted analyses, all other neurodevelopmental assessments were similar between those children who were breastfed and those who were not.
Table 2.
Neurodevelopmental outcomes by breastfeeding status
| Breastfeeding N=614 | No Breastfeeding N=158 | Mean Difference in Scores (95% CI) | Unadjusted OR (95% CI) | Mean Difference in Adjusted Scores (95% CI) | Adjusted OR (95% CI)* | |
|---|---|---|---|---|---|---|
| Primary outcome | ||||||
| WPPSI III IQ <85 age 5 | 130 (21.5) | 55 (36.2) | 0.48 (0.33 – 0.71) | 0.62 (0.41 – 0.93) | ||
| Secondary outcomes | ||||||
| WPPSI III IQ score age 5 | 96.7±15.1 | 91.2±15.0 | 5.49 (2.80 – 8.17) | 0.72 (−1.75 – 3.20) | ||
| CBCL T score >60 age 5 | 56 (9.2) | 25 (16.3) | 0.52 (0.31 – 0.87) | 0.59 (0.35 – 1.01) | ||
| Conners’ Rating Scale-Revised ADHD score T score >60 age 4 | 86 (14.5) | 29 (19.0) | 0.72 (0.46 – 1.15) | 0.76 (0.46 – 1.27) | ||
| DAS II subtests age 4 | ||||||
| Recall of digits forward <25th% | 141 (24.0) | 32 (21.5) | 1.15 (0.75 – 1.78) | 0.92 (0.55 – 1.53) | ||
| Picture recognitions <25th% | 104 (17.6) | 45 (30.0) | 0.50 (0.33 – 0.75) | 0.71 (0.45 – 1.13) | ||
| DAS II General Conceptual Ability Score age 3 | 92.0 ± 15.8 | 88.2 ± 15.4 | 3.77 (0.99 – 6.56) | 0.59 (−1.98 – 3.15) | ||
| DAS II General Conceptual Ability Score < 85 age 3 | 194 (32.2) | 67 (43.5) | 0.62 (0.43 – 0.88) | 0.77 (0.50 – 1.18) | ||
| CBCL T score >60 age 3 | 54 (8.9) | 19 (12.3) | 0.70 (0.40 – 1.22) | 1.01 (0.55 – 1.85) | ||
| Bayley III Scores age 2 | ||||||
| Cognitive | 91.1 ± 12.4 | 89.1 ± 13.1 | 1.93 (−0.31 – 4.16) | −1.07 (−3.22 – 1.08) | ||
| Cognitive <85 | 135 (22.1) | 39 (25.7) | 0.82 (0.54 – 1.24) | 1.00 (0.63 – 1.60) | ||
| Motor | 98.4 ± 12.5 | 95.8 ± 13.0 | 2.61 (0.33 – 4.89) | 1.48 (−0.77 – 3.73) | ||
| Motor < 85 | 54 (8.9) | 16 (10.9) | 0.80 (0.44 – 1.44) | 0.79 (0.41 – 1.51) | ||
| Language | 92.5 ± 15.7 | 88.7 ± 15.0 | 3.74 (0.92 – 6.57) | 0.26 (−2.15 – 2.67) | ||
| Language < 85 | 189 (31.4) | 47 (32.6) | 0.94 (0.64 – 1.39) | 1.14 (0.73 – 1.77) | ||
| Bayley III Scores age 1 | ||||||
| Cognitive | 99.5 ± 13.2 | 99.1 ± 14.3 | 0.39 (−1.99 – 2.77) | −1.46 (−3.83 – 0.90) | ||
| Cognitive <85 | 53 (8.8) | 17 (11.1) | 0.77 (0.43 – 1.37) | 0.94 (0.52 – 1.71) | ||
| Motor | 96.6 ± 11.0 | 97.7 ± 12.5 | −1.10 (−3.12 – 0.91) | 0.12 (−2.13 – 2.37) | ||
| Motor < 85 | 56 (9.3) | 15 (9.9) | 0.93 (0.51 – 1.70) | 1.02 (0.54 −1.91) | ||
| Language | 94.9 ± 11.9 | 94.9 ± 14.7 | 0.03 (−2.21 – 2.27) | −0.79 (−3.09 – 1.52) | ||
| Language < 85 | 101 (16.7) | 34 (22.5) | 0.69 (0.45 – 1.07) | 0.86 (0.55 – 1.36) | ||
Data are displayed as mean ± standard deviation or n (%). N is provided in the column header unless otherwise indicated below. WPPS III, Wechsler Preschool and Primary Scale of Intelligence-III, IQ Intelligence quotient, DAS II Differential Ability Scales-II, CBCL Child Behavioral Checklist, Conners’ Rating Scales-Revised
Number of participants in each outcome: WPPSI-III age 5: 756; Bayley cognitive age 1: 758; Bayley motor age 1: 756; Bayley language age 1: 754; Bayley cognitive age 2: 764; Bayley motor age 2: 754; Bayley language age 2: 746; DAS II age 3: 757; CBCL age 3: 761; DAS II subtest age 4 – Recall of digits: 737: DAS II subtest age 4 – Picture Recognition: 742; Conners’ Rating Scale-Revised age 4: 747; CBCL age 5: 760.
See Table 3 for variables included in the final regression models
In multivariable logistic regression analysis, breastfeeding was associated with reduced odds of low IQ at age 5 (aOR 0.62, 95% CI 0.41–0.93, P= 0.02) (Table 2; see Table 3 for variables included in the final regression models). When breastfeeding duration was examined, we observed a 3.3% reduced odds of an IQ <85 at age 5 with each month of breastfeeding (aOR 0.97, 95% CI 0.939–0.996, P=0.03).
Table 3.
Variables included in final regression models for the association of breastfeeding with neurodevelopmental outcome
| Age | Race and Ethnicity | BMI | Nulli-parous | Insurance type | Education | Smoking | Alcohol | Thyroid status | Treatment group | Gestational age | Infant male sex | SGA | Child age at exam | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| WPPSI III Score <85 | ● | ● | ● | |||||||||||
| WPPSI III Score | ● | ● | ● | ● | ● | ● | ||||||||
| CBCL 5 years | ● | |||||||||||||
| Conners-R ADHD 4 years | ● | ● | ||||||||||||
| DAS II Digits forward – 4 years | ● | ● | ● | ● | ||||||||||
| DAS II Picture recognition – 4 years | ● | ● | ● | ● | ● | |||||||||
| DAS II Score 3 years | ● | ● | ● | ● | ● | |||||||||
| DAS II Score <85 3 years | ● | ● | ● | ● | ● | |||||||||
| CBCL 3 years | ● | ● | ● | ● | ||||||||||
| Bayley III 2 years | ||||||||||||||
| Cognitive score | ● | ● | ● | ● | ● | ● | ||||||||
| Cognitive < 85 | ● | ● | ● | ● | ● | |||||||||
| Motor score | ● | ● | ● | ● | ||||||||||
| Motor < 85 | ● | ● | ● | ● | ||||||||||
| Language | ● | ● | ● | ● | ● | ● | ||||||||
| Language< 85 | ● | ● | ● | ● | ||||||||||
| Bayley III 1 year | ||||||||||||||
| Cognitive score | ● | ● | ● | ● | ||||||||||
| Cognitive <85 | ● | ● | ||||||||||||
| Motor score | ● | ● | ● | ● | ● | ● | ||||||||
| Motor <85 | ● | ● | ● | |||||||||||
| Language score | ● | ● | ● | ● | ● | ● | ● | |||||||
| Language <85 | ● | ● | ● |
Models that examined a curvilinear relationship between breastfeeding duration and low IQ at age 5 were not significant for duration of breastfeeding. No other neurodevelopmental outcome, including mean IQ scores at age 5, was found to be significantly associated with breastfeeding in multivariate analyses (Table 2; see Table 3 for variables included in the final regression models).
Sensitivity analyses were performed in which treatment and group assignment were included in each of the models. The results and conclusions were not altered in any of the analyses. The results for multivariable analyses for the association between breastfeeding and its duration are provided in Tables 4 and 5, respectively. The results for the other sensitivity analyses are not shown. In the propensity score analysis, 158 no breastfeeding and 614 breastfeeding participants resulted in 122 matched pairs with a total sample size of 244. Although not significant with this reduced sample size, breastfeeding still suggested a protective effect with respect to the primary outcome (OR 0.72, 95% CI: 0.413 – 1.270).
Table 4.
Multivariable analysis to evaluate the association of any breastfeeding with WPPSI III IQ <85 age 5
| Adjusted OR | 95% Confidence Interval | P-value | ||
|---|---|---|---|---|
| Any breastfeeding | 0.619 | 0.409 | 0.935 | 0.02 |
| College graduate or higher versus < high school degree | 0.283 | 0.132 | 0.608 | 0.001 |
| High school degree or some college vs < high school degree | 0.626 | 0.419 | 0.936 | 0.02 |
| Government insurance vs private Insurance | 3.464 | 1.762 | 6.810 | <0.001 |
| Self-pay vs private insurance | 4.024 | 1.835 | 8.821 | <0.001 |
| Infant male sex | 1.505 | 1.052 | 2.152 | 0.03 |
| Treatment group (levothyroxine vs placebo) | 0.920 | 0.647 | 1.310 | 0.64 |
| Baseline thyroid status (subclinical hypothyroidism vs hypothyroxinemia) | 0.965 | 0.673 | 1.384 | 0.85 |
| Duration of breastfeeding (months) | 0.967 | 0.939 | 0.997 | 0.03 |
| College grad or higher vs < high school degree | 0.298 | 0.136 | 0.656 | 0.003 |
| High school degree or some college vs < high school degree | 0.616 | 0.411 | 0.923 | 0.02 |
| Government insurance vs private insurance | 4.389 | 2.102 | 9.165 | <0.001 |
| Self-pay vs private Insurance | 5.104 | 2.214 | 11.769 | <0.001 |
| Infant male sex | 1.490 | 1.038 | 2.138 | 0.03 |
| Treatment group (levothyroxine vs placebo) | 0.933 | 0.653 | 1.332 | 0.70 |
| Baseline thyroid status (subclinical hypothyroidism vs hypothyroxinemia) | 0.950 | 0.662 | 1.363 | 0.78 |
WPPS III, Wechsler Preschool and Primary Scale of Intelligence-III, IQ Intelligence quotient.
Discussion:
We found breastfeeding to be associated with a lower odds of low IQ in children at age 5 and that each month of breastfeeding is associated with a modest but significant reduction in the odds of a low IQ score at age 5. We did not find significant associations between breastfeeding and other neurodevelopmental outcomes including mean IQ scores at age 5. These conclusions remained unchanged when group assignment (subclinical hypothyroidism versus hypothyroxinemia) and treatment (thyroxine versus placebo) were included in our models.
Our analysis focused on low IQ score (<85) as the primary outcome. No breastfeeding has been reported as an independent marker of low cognitive function among premature infants. In a French population-based cohort study of 1503 infants born in 1997 before 33 weeks, parental socioeconomic status and lack of breastfeeding, in addition to medical factors, were independently associated with an increased risk of mild cognitive impairment (24).This same cohort was subsequently analyzed along with a second cohort of premature infants born in France at <33 weeks between 2003 and 2008. When these additional 1733 children were added to the analysis, breastfeeding was similarly independently associated with a reduced risk of suboptimal neurodevelopment assessment at age 2 and 5 (25).Short breastfeeding duration (<1 month), as compared with breastfeeding for one month or more, has also been associated with more frequent low IQ score in a 2004 birth cohort from Pelotas, Southern Brazil, a middle-income country (12). It is possible that breastfeeding has a differential association for children who may be at higher risk for poor neurodevelopmental outcomes as compared with those who are not at high risk. Further study of the association between neurodevelopmental outcomes and breastfeeding by risk stratification may be warranted.
Short breastfeeding duration has also been reported to be significantly associated with the subsequent development of attention deficit hyperactivity disorders in children (13–14). A recently published meta-analyses analyzed 11 previous studies and found a significant association between no breastfeeding or short duration of breastfeeding and the subsequent diagnosis of attention deficit disorders (14). However, our analysis did not find an association between breastfeeding occurrence and abnormal results on the Conners’ Rating Scales-Revised for assessment of attention in adjusted analyses. Our discordant results may be due to small sample size with inadequate power in our study cohort.
In addition to the limitations in detecting small differences in outcome measures due to the fixed sample size, our analysis is limited, in that other factors that could influence child neurodevelopmental outcomes such as parental IQ and the home and educational environment that were not available to include in these analyses. Similarly, it must be noted that infants who were admitted to the ICU were excluded from our analyses and thus our conclusions cannot be applied to this population. Although unlikely to be a major contributor, the use of donor breast milk was not specifically captured in the data set. Our study was also limited, as are all observational studies, in that it cannot address causality. Although the association between breastfeeding (and breastfeeding duration) and lower odds of low IQ score in children persisted despite adjusting for multiple covariates, we acknowledge the possibility of unmeasured residual confounding. Finally, no statistical adjustments were made for multiple comparisons. As a result, the conclusions should be interpreted accordingly.
The strengths of our study are numerous. The patient population is racially and ethnically diverse and drawn from 33 geographically varied hospitals across the United States, making the findings broadly generalizable. In addition, annual child assessments were performed from age 1 to 5 to provide a comprehensive assessment of neurocognitive outcomes. We were able to adjust for a number of key sociodemographic covariates such as maternal education level and insurance type which are associated with the outcome of interest, IQ scores in the offspring. Furthermore, trained and certified personnel, blinded to maternal data, performed each of these assessments to ensure valid measurement.
Supplementary Material
ACKNOWLEDGMENTS:
The authors thank Lisa Moseley, R.N., B.S.N., and Gail Mallett, R.N., B.S.N., C.C.R.C., for protocol development and coordination between clinical research centers; Barbara Jones-Binns, J.D., M.P.H., for protocol and data management, overall coordination, and quality control; and Elizabeth A. Thom, Ph.D., Alan M. Peaceman, M.D., and Catherine Y. Spong, M.D. for protocol development and oversight.
FUNDING: Supported by grants (HD34116, HD40512, HD27917, HD34208, HD40485, HD40560, HD53097, HD27869, HD40500, HD40545, HD27915, HD40544, HD53118, HD21410, and HD36801) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute of Neurological Disorders and Stroke. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Financial Disclosure
The authors did not report any potential conflicts of interest.
Each author has confirmed compliance with the journal’s requirements for authorship.
Other members of the NICHD MFMU Network are listed in Appendix 1, available online at http://links.lww.com/xxx.
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