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Abstract
Background—The duration and exclusivity of breastfeeding in infancy have been inversely associated with future cardiometabolic risk. We investigated the effects of an experimental intervention to promote increased duration of exclusive breastfeeding on cardiometabolic risk factors in childhood.
Methods and Results—We followed-up children in the Promotion of Breastfeeding Intervention Trial, a cluster-randomized trial of a breastfeeding promotion intervention based on the World Health Organization/United Nations Children’s Fund Baby-Friendly Hospital Initiative. In 1996 to 1997, 17 046 breastfeeding mother-infant pairs were enrolled from 31 Belarusian maternity hospitals and affiliated polyclinics (16 intervention versus 15 control sites); 13 879 (81.4%) children were followed up at 11.5 years, with 13 616 (79.9%) who had fasted and did not have diabetes mellitus. The outcomes were blood pressure; fasting insulin, adiponectin, glucose, and apolipoprotein A1; and the presence of metabolic syndrome. Analysis was by intention to treat, accounting for clustering within hospitals/clinics. The intervention substantially increased breastfeeding duration and exclusivity in comparison with the control arm (43% versus 6% and 7.9% versus 0.6% exclusively breastfed at 3 and 6 months, respectively). Cluster-adjusted mean differences at 11.5 years between experimental versus control groups were as follows: 1.0 mm Hg (95% confidence interval, −1.1 to 3.1) for systolic and 0.8 mm Hg (−0.6 to 2.3) for diastolic blood pressure; −0.1 mmol/L (−0.2 to 0.1) for glucose; 8% (−3% to 34%) for insulin; −0.3 μg/mL (−1.5 to 0.9) for adiponectin; and 0.0 g/L (−0.1 to 0.1) for apolipoprotein A1. The cluster-adjusted odds ratio for metabolic syndrome, comparing experimental versus control groups, was 1.21 (0.85 to 1.72).
Conclusions—An intervention to improve breastfeeding duration and exclusivity among healthy term infants did not influence cardiometabolic risk factors in childhood.
Clinical Trial Registration—Current Controlled Trials: ISRCTN37687716 (http://www.controlled-trials.com/ISRCTN37687716). URL: http://clinicaltrials.gov. Unique identifier: NCT01561612.
- adiponectin
- blood pressure
- breast feeding
- fasting
- glucose
- lactation
- lipids
- insulins
- randomized controlled trial
Introduction
Observational studies suggest that greater duration and exclusivity of having been breastfed is associated with lower levels of cardiometabolic risk factors in later life, including blood pressure,1 insulin resistance,2 blood glucose,2 lipids,3 carotid intima media thickness4 and type 2 diabetes mellitus,2 although associations with cardiovascular disease end points have been inconsistent.5
Editorial see p 281
Clinical Perspective on p 329
Breastfeeding6 and metabolic factors,7 however, are both highly socially patterned in high-income countries, where most of the studies cited above were set. Even if observational associations of breastfeeding with cardiometabolic risk are adjusted for maternal or socioeconomic confounders, residual confounding by unmeasured or poorly measured factors may explain the observed associations.6 Inference from observational studies is also hampered by other problems: (1) reverse causality, because the relationship of breastfeeding with infant growth is bidirectional, such that the direction of cause and effect may be the reverse—poor growth (itself associated with later adiposity8 and metabolic risk)9 may be the cause of formula supplementation or weaning10; (2) selective publication1; and (3) limited information on the exclusivity of breastfeeding, of particular relevance for high-income countries where truly exclusive breastfeeding is rare and robust information on any benefits could help promote it. The causal effects of breastfeeding, therefore, can best be investigated in a large randomized, controlled trial.11
To overcome the limitations inherent in observational studies of the long-term effects of breastfeeding,12 we designed a follow-up of 17 046 children participating in the Promotion of Breastfeeding Intervention Trial (PROBIT), a cluster-randomized, controlled trial in the Republic of Belarus.13 The intervention resulted in 2 groups with substantially different exposure to breastfeeding, providing a unique opportunity to test, in an intention-to-treat analysis, the extent to which greater duration and exclusivity of breastfeeding causally influences cardiometabolic risk factors. We previously reported that the breastfeeding promotion intervention had no measurable effect on adiposity or blood pressure at age 6.5 years (PROBIT II)14 or on adiposity, height, and insulin-like growth factor at age 11.5 years (PROBIT III).15 The current study (also part of PROBIT III) provides experimental evidence on whether increased duration and exclusivity of breastfeeding has beneficial effects on cardiometabolic risk factors at 11.5 years.
Methods
A detailed description of the cluster-based randomization, experimental intervention, sample size calculations, and participant eligibility in PROBIT has been published.13 In brief, the units of randomization (clusters) were maternity hospitals and their associated polyclinics (outpatient health clinics following up both well and ill children). These units were randomly assigned to a control group, consisting of continuation of the breastfeeding practices and policies in effect at the time of randomization, or an experimental intervention, based on the Baby Friendly Hospital Initiative developed by the World Health Organization and United Nations Children’s Fund to promote and support breastfeeding, particularly among mothers choosing to initiate breastfeeding.16 The trial results are based on 17 046 healthy breastfed infants from 31 maternity hospitals/polyclinics, born at term (≥37 weeks gestation) in 1996 to 1997 and enrolled during their postpartum stay. Trial inclusion criteria required the infants to be healthy, singleton, with birth weight ≥2500 g, and Apgar score ≥5 at 5 minutes, and their mothers to have initiated breastfeeding and have no condition that would interfere with breastfeeding.13 The mother-infant pairs were followed up regularly within the first 12 months of life for the occurrence of ≥1 episodes of gastrointestinal tract infection (the primary outcome and basis for the original sample size calculation), ≥2 episodes of respiratory tract infection, and atopic eczema during infancy, compared between the intervention and control groups. The results reporting on these outcomes have been published.13
A long-term follow-up of the trial (PROBIT II) was conducted between 2002 and 2005 when the children were a mean age of 6.5 years, for the following a priori defined secondary outcomes that have been reported: anthropometry, blood pressure, cognition, behavior, asthma/allergies, and dental caries.17 The focus of the current article is a further follow-up when the children were 11.5 years (PROBIT III) for the following a priori defined secondary outcomes: adiposity and insulin-like growth factor-I (reported previously)15; blood pressure; fasting insulin, adiponectin (a marker of insulin resistance),18 glucose, and apolipoprotein A1 (the main protein constituent of high-density lipoprotein cholesterol, strongly correlated with high-density lipoprotein cholesterol (r≈0.80) and inversely associated with coronary events at a similar magnitude to high-density lipoprotein cholesterol)19; and metabolic syndrome, defined by the European Group for the Study of Insulin Resistance.20
PROBIT III follow-up was approved by the Belarusian Ministry of Health and received ethical approval from the McGill University Health Centre Research Ethics Board; the Human Subjects Committee at Harvard Pilgrim Health Care; and the Avon Longitudinal Study of Parents and Children Law and Ethics Committee. A parent or legal guardian provided written informed consent in Russian at enrollment and at the follow-up visits, and all children provided written assent at the 11.5-year visit.
Follow-Up at 11.5 Years
Between January 2008 and December 2010, the children were followed up at dedicated research visits by 39 specially trained pediatricians at 31 polyclinics.17 Training and quality assurance procedures have been fully described previously and included a 3-day initial training workshop and practical sessions, retraining workshops every 6 months, and ongoing data monitoring.21 We asked children to fast for at least 8 hours before the visit, which included the following measurements21: whole blood fasting glucose (Roche ACCU-CHEK Advantage meter system, Basel, Switzerland); systolic and diastolic blood pressure in triplicate with the use of OMRON 705IT and an appropriately sized cuff; Tanner pubertal stage by direct physician examination; and waist circumference in duplicate. Pediatricians also obtained single measurements of maternal systolic and diastolic blood pressure, height and body mass index, and asked mothers whether they had a diagnosis of hypertension, type 2 diabetes mellitus, or gestational diabetes mellitus.
Dried Blood Spot Sampling
At the visit, finger-prick whole-blood spot samples were collected by the 39 pediatricians, who had received special training, onto Whatman 903 filter paper cards as described previously.22 To maintain sample stability, the dried blood spot cards were air-dried, placed in sealed low gas-permeable plastic bags containing dry silica gel, and stored in a −20°C freezer at each of the 31 polyclinic sites until transport to the laboratory at the National Mother and Child Centre in Minsk, where they were stored at −80°C. Pediatricians collected a median of 8 blood spots from 13 487 (97%) children22; the samples used in the current analysis were stored at −20°C for a median of 1.7 months (interquartile range, 1.0–5.1 months) and at −80°C for a median of 18.6 (interquartile range, 13.8–22.2) months.
Assays
All samples were analyzed after a single thaw. Discs were punched from the center of the blood spot cards directly into 96-well microtiter plates by using an automated hole puncher (Wallac DBS [Dried Blood Spot] Puncher: 1296-071, Perkin Elmer). We quantified circulating insulin from two 3-mm diameter discs (≈6 µL of blood) per child, with the use of methods described previously22 that are based on an adaptation of an existing commercial kit (Mercodia Human Insulin ELISA 10-1113-01, Mercodia AB, Sweden). Circulating levels of adiponectin and apolipoprotein A1 were each quantified from one 3-mm diameter disc (≈3 µL of blood) per child by using existing assay kit reagents (adiponectin human ELISA, EIA4177, DRG International Inc, New Jersey, and Turbox APO A1 catalogue number 67561, Orion Diagnostica, Finland, respectively) and validated methods for blood spots.23,24 We did not assay high-density lipoprotein cholesterol directly, because the direct measurement of cholesterol from dried blood spots is not straightforward or reliable.25 The assay performance characteristics are given in Table I in the online-only Data Supplement. All blood spot analytes were stable for at least 30 months at −80°C.22 Insulin was assayed from 2 reagent lots (production batches), adiponectin from 4 lots, and apolipoprotein A1 from 3 lots between December 2009 and May 2012. To remove the potential effect of storage time and between-lot or between-run variation, we adjusted regression models containing these analytes for the time between sampling and assay date.
We calculated the homeostasis model assessment (HOMA) of β-cell function and HOMA of insulin resistance by using the calculator available at http://www.dtu.ox.ac.uk. We defined a binary outcome for the presence or absence of metabolic syndrome according to recommendations of the European Group for the Study of Insulin Resistance:20 raised insulin levels (fasting values ≥75th sample percentiles for sex and pubertal stage, as in other studies)26 and at least 2 of the following metabolic abnormalities based on population reference values: hyperglycemia (whole blood fasting values ≥5.6 mmol/L, hypertension (systolic blood pressure ≥90th percentile for age, sex, and height),27 dyslipidemia (apolipoprotein A values ≤10th percentile for age, sex),28 and abdominal obesity (waist circumference ≥90th percentile for age, sex).29
Analysis
All analyses used SAS version 9.3 (SAS Institute, Cary, NC), unless stated. We excluded children who had fasted for <8 hours before sampling (n=130) or with known diabetes mellitus (n=39). Continuous measures of insulin, HOMA of β-cell function, and HOMA of insulin resistance were natural log-transformed. Comparisons between experimental and control groups were based on intention-to-treat analysis. We accounted for possible nonindependence of measurements within individual hospital/polyclinic sites (clustering) by using random effects models, which permit inference at the level of the individual child rather than the cluster. The MIXED procedure was used for continuous outcomes (to estimate mean differences and 95% confidence intervals [CIs]) and the GLIMMIX procedure for binary outcomes (to estimate odds ratios and 95% CIs) in SAS. The results are presented for the simple cluster-adjusted model, and after additional adjustment, as well, for stratum-level variables (urban versus rural and East versus West Belarus residence) and for child age at follow-up, sex, birth weight, and maternal and paternal education (further controlling for maternal age and smoking made little difference to the results). Differences in mean insulin, HOMA of insulin resistance, and HOMA of β-cell function were based on the natural log of their values. Hence, we report exponentiated estimates from the model by using these logged variables, which are interpreted as the ratio of geometric means in intervention versus control group; the confidence intervals were back transformed from the log scale. To determine whether results differed in boys versus girls, we analyzed mixed models that included terms for the sex of each child and a multiplicative sex×treatment interaction term.
In a sensitivity analysis, we investigated whether loss to follow-up influenced the results by undertaking multiple imputation to generate plausible values of missing 11.5-year outcomes and thereby including all 17 046 randomly assigned participants (assuming data missing at random).30 We used SAS imputations (Proc MI) to impute 5 values for each missing observation and combined multivariable modeling estimates by using Proc MI ANALYZE in SAS (using 10 and 25 imputations gave almost identical results).
The intention-to-treat analysis underestimates the effect of the true exposure of interest (breastfeeding exclusivity and duration), owing to the overlap in breastfeeding between the randomized groups (many intervention mothers did not exclusively breastfeed for 3 or 6 months, whereas some control mothers did). In a secondary analysis, we used instrumental variable methods to estimate the causal effect of the duration of exclusive breastfeeding on our outcomes,31 comparing <3 months (reference), ≥3 to <6 months, and ≥6 months. We used randomization status as the instrument, because it is independent of any confounders of the exposure-outcome relationship and is related to the outcomes only via the exposure (breastfeeding duration and exclusivity). We performed instrumental variable estimation of continuous outcomes by using the generalized 2-stage least-squares estimator implemented in the xtivreg command in Stata version 12.1 (Stata Corp, College Station, TX), while accounting for clustering by study site. Instrumental variable estimation of the binary metabolic syndrome’ outcome used a random effects version of the ratio estimator of the causal odds ratio.32
To assess whether we could reproduce the inverse associations of increased duration and exclusivity of breastfeeding reported in previous observational studies, we conducted observational analyses (ie, disregarding randomization status), in which we estimated the effects of the duration of any and exclusive breastfeeding on the same outcomes, accounting for clustering and the same baseline characteristics as in the expanded mixed models described above, with the use of multiple linear regression for continuous outcomes and multiple logistic regression for binary outcomes. Duration of breastfeeding (any or exclusive) was classified as <3 months (reference), ≥3 to <6 months, and ≥6 months.
Results
As previously reported,13 the randomization produced 2 groups with similar distributions of baseline sociodemographic and potential confounding factors, including birth weight, maternal and paternal education, smoking, and alcohol intake. The intervention substantially increased breastfeeding duration and exclusivity, based on World Health Organization definitions,16 versus the control arm; eg, at 3 months, intervention infants were 7 times more likely to be exclusively (43.3% versus 6.4%) and twice as likely to be predominantly (51.9% versus 28.3%) breastfed, and were breastfed to any degree at higher rates throughout infancy.13
A total of 13 879 children were examined at a median age of 11.5 years (standard deviation, 0.50; interquartile range, 11.3–11.8 years), representing 81.4% of the 17 046 originally randomly assigned children (Figure). Of the 3167 children randomly assigned, but not followed up at 11.5 years, 2645 were lost to follow-up, 425 were unable or unwilling to come for their visit, and 97 had died since randomization. Follow-up rates were similar in the experimental (83.5%) and control (79.1%) polyclinics, although they varied between 48% and 98%. Of the 13 879 children who were followed up at age 11.5, 13 616 (98.1%) fasted at least 8 hours overnight and did not have diabetes mellitus. Included children in the experimental and control groups had similar baseline characteristics, with small differences paralleling those seen (and previously reported)13 at randomization (Table 1). The groups were also virtually identical in mean parental height and body mass index and maternal systolic and diastolic blood pressure, and reported maternal hypertension, type 2 diabetes mellitus, and gestational diabetes mellitus, as measured during follow-up.
Baseline and Follow-Up Characteristics of PROBIT Children at 11.5 Years Who Were Fasted at Least 8 Hours and Did Not Have Diabetes Mellitus (n=13 616)
Flow diagram of progress of clusters and individuals through PROBIT recruitment and follow-up phases I, II, and III. Of the 3167 children not seen at PROBIT III, 913 were seen at both 12 months and PROBIT II, 483 were not seen at either 12 months or PROBIT II, 1768 were seen at 12 months but not seen at PROBIT II, and 3 were seen at PROBIT II but not seen at 12 months. Data shown in this Figure vary minimally from previously published data owing to the updating of some variables during PROBIT III data collection and cleaning.
The main results are shown in Table 2. Within-polyclinic clustering (the tendency for measurements on children attending the same polyclinic to be more similar to each other than to children attending other polyclinics)21 was moderate for fasting glucose and apolipoprotein A1 (intraclass correlation coefficients: 0.11 and 0.15, respectively), but low (intraclass correlation coefficients of ≤0.10) for the other measures. Mean values of all the continuous outcomes, and the prevalence of metabolic syndrome, were similar in the experimental versus control groups. Cluster-adjusted mean differences at 11.5 years between experimental versus control groups were: 1.0 mm Hg (95% CI, −1.1 to 3.1) for systolic and 0.8 mm Hg (95% CI, −0.6 to 2.3) for diastolic blood pressure; 8% (−3% to 34%) for insulin; 8% (−3% to 33%) for HOMA of insulin resistance; 7% (−9% to 27%) for HOMA of β-cell function; −0.3 μg/mL (−1.5 to 0.9) for adiponectin; and 0.0 g/L (−0.1 to 0.1) for apolipoprotein A1. The cluster-adjusted odds ratio for metabolic syndrome, comparing experimental versus control groups, was 1.21 (0.85 to 1.72). These findings were little altered after adjusting for baseline potential confounders (Table 2) or using multiply imputed outcomes (Table II in the online-only Data Supplement), apart from the emergence of a positive association of the intervention with systolic blood pressure by using multiple imputation. We observed little evidence of interaction by sex (all interaction P values > 0.06), except for metabolic syndrome (odds ratio, 1.49; 95% CI, 1.01–2.22 in males and 0.94; 95% CI, 0.63–1.42 in females; P for interaction=0.01).
Differences in Cardiometabolic Measurements at 11.5 Years in Experimental Versus Control Group: Intention-to-Treat Analysis Without Imputation From the PROBIT Trial (n=13 616)
The results of the instrumental variable analyses (Table 3), which provide estimates of the causal effects of exclusive breastfeeding for ≥ 3 to < 6 months and ≥6 months versus <3 months (and therefore directly comparable with estimates from observational studies), are in line with the intention-to-treat inference that increased duration and exclusivity of breastfeeding provides no important beneficial effects on the study outcomes.
Instrumental Variable Estimates of the Causal Effect of Duration of Exclusive Breastfeeding on Cardiometabolic Factors at 11.5 Years by Using Randomized Treatment as the Instrumental Variable (n=13 616)
In observational analyses (Table 4), increased duration of exclusive breastfeeding was associated with higher diastolic blood pressure, but there was little evidence of any associations with the other cardiometabolic outcomes. The results were similarly null for all outcomes when the exposure was duration of any breastfeeding (Table III in the online-only Data Supplement).
Observational Associations of Duration of Exclusive Breastfeeding With Cardiometabolic Factors at 11.5 Years (n=13 616)
Discussion
The results from this large cluster-randomized trial indicate that the experimental intervention, despite large improvements in the duration and exclusivity of breastfeeding, reduced neither measures of insulin resistance nor cardiometabolic risk at 11.5 years. The point estimates were generally in the opposite direction to the hypothesized protective effects, and the confidence intervals were consistent with chance or small intervention effects, thus ruling out an important beneficial impact of the intervention on cardiometabolic risk factors. The absence of a favorable effect on blood pressure is similar to the results we obtained at age 6.5 years14 and consistent with the recently reported lack of impact on stature or measures of general and peripheral adiposity at age 11.5 years.15 The data reported herein extend our observations to older children and include additional measures of cardiometabolic risk biomarkers.
Strengths and Weaknesses
The substantial differences in duration and exclusivity of breastfeeding between the 2 trial arms were created by randomization at the time of birth, rather than by the mother’s choice. Coupled with our high rates of follow-up over 11.5 years, the intention-to-treat analysis therefore minimizes the problems of confounding and reverse causality that plague observational studies.6 We minimized measurement bias by assessing infant feeding regularly during the first 12 months of life, strictly adhering to World Health Organization definitions of breastfeeding duration and exclusivity16; at 11.5 years we incorporated biomarker measures of insulin resistance, cardiometabolic risk, and metabolic syndrome. Several definitions exist for the metabolic syndrome in childhood.33 Our approach was 2-fold: (1) we evaluated individual components of the metabolic syndrome separately,7 and (2) we used the European Group for the Study of Insulin Resistance definition of metabolic syndrome20 because this definition has high sensitivity and specificity in predicting type 2 diabetes mellitus33 and cardiovascular disease34 in prospective studies. In contrast, the clinically focused definition of the metabolic syndrome proposed by the National Cholesterol Education Program Expert Group is relatively insensitive in predicting diabetes mellitus33 and cardiovascular disease mortality.34
To estimate the unbiased effects of the experimental breastfeeding promotion intervention, we used an intention-to-treat analysis. The estimates provided by the intention-to-treat analysis are the most robustly estimated expected average effects on the metabolic outcomes of the experimental (breastfeeding promotion) intervention. However, because of the substantial overlap in breastfeeding duration and exclusivity in the 2 randomized groups, these average effects may underestimate the differences in outcome caused by increased duration and exclusivity of breastfeeding. We used instrumental variables analysis to estimate the magnitude of the causal effects on our outcomes attributable to breastfeeding duration and exclusivity, which supported our inference that increased duration and exclusivity of breastfeeding was not inversely associated with the outcomes of interest. The confidence intervals of the instrumental variables analyses were wider than those provided by the intention-to-treat analysis, and thus do not exclude protective estimates reported in observational studies.1–4
PROBIT was performed in Belarus, because, at the time of randomization, maternity hospital practices in Belarus and other former Soviet republics were similar to those in North America and Western Europe 30 to 40 years ago and thus provided a greater potential contrast between intervention and control study sites. Although different in many socioeconomic, cultural, and economic respects from North America and Western Europe, Belarus is a relatively developed country with strict hygienic standards, high immunization rates, low incidence of infection, low rates of infant and child mortality, similar types of formula feeds, and accessible healthcare services. Our null results may not generalize to settings with childhood cardiometabolic levels that differ from those in Belarus (characterized, for example, by heavy paternal smoking35 but relatively low rates of child obesity).15
We excluded mothers who were unable to breastfeed and preterm or low-birth-weight infants, characteristics that may predict later-life metabolic syndrome. Thus, this healthy population at birth may have been at lower overall risk in comparison with a general population sample.
Over such long-term follow-up, imbalances in determinants of cardiometabolic risk in childhood could have arisen between trial arms. Because any such imbalances would have occurred after randomization and thus could be effects (mediators) of the randomized intervention, they should not be considered as confounding variables and should not be controlled for. Although imbalances can lead to selection bias when follow-up rates are low, >80% of randomly assigned children in PROBIT were followed up at 11.5 years, and no important differences in measured baseline characteristics were observed between the 2 randomized groups. The intervention may have altered the diet after weaning, given observational evidence that later-life food choices are influenced by whether a child was breast- or formula-fed, providing a potential mechanism by which promoting exclusive breastfeeding could exert later effects.36 We observed no effect of the intervention on cardiometabolic risk, however, so if there had been an intervention effect on later diet, this could only explain a false-negative result if the breastfeeding promotion led to an unhealthy diet that obscured (countered) a beneficial effect on cardiometabolic risk factors, which seems unlikely.36
The observed sex interaction of the intervention on presence/absence of metabolic syndrome, with boys in the intervention group having a higher risk, was observed in the context of multiple hypothesis tests and may have arisen by chance (Bonferroni corrected P value for 9 tests: 0.01×9=0.09). Our assays were measured from dried blood spots; in addition to our validation data, the metabolites presented here have previously been reported to be stable and validly and reliably measured from dried blood spots.22–24
Comparison With Other Studies
Our findings are in line with a cross-cohort observational study6 comparing results from the Avon Longitudinal Study of Parents and Children cohort in Bristol, UK (a setting with strong socioeconomic patterning of breastfeeding), with those from Pelotas, Brazil, and a meta-analysis of 5 cohorts in low- and middle-income countries (settings with weak socioeconomic patterning of breastfeeding). In the Avon Longitudinal Study of Parents and Children, breastfeeding was strongly associated with lower blood pressure and lower body mass index in the directions expected if attributable to socioeconomic patterning (even after adjustment for measured confounders), but in Pelotas and the low- and middle-income countries, breastfeeding was not strongly associated with these outcomes. Taken together with our experimental evidence, these findings suggest that previously reported inverse associations of breastfeeding duration and exclusivity with cardiometabolic risk factors (most of which were set in high-income countries with strong socioeconomic patterning of breastfeeding), are likely to reflect residual confounding.
Implications
Among healthy term infants in Belarus, an intervention to improve the duration and exclusivity of breastfeeding did not alter levels of cardiometabolic risk factors among these children when aged 11.5 years. Nevertheless, the PROBIT trial, the largest randomized trial ever conducted in the field of human lactation, has provided robust evidence that promoting increased duration and exclusivity of breastfeeding prevents gastrointestinal infections and eczema in infancy13 and improves cognitive development.37 The intervention was designed to increase the duration and exclusivity of breastfeeding among women initiating breastfeeding. Our findings do not, therefore, apply to comparisons of breast versus formula feeding, the comparisons most frequently described in the literature. Nonetheless, our findings do not support a number of previous studies suggesting inverse associations of the exclusivity and duration of breastfeeding with cardiometabolic risk factors.1–4
Acknowledgments
We are grateful to the cohort members, their parents, and the study pediatricians and auditors who participated so willingly in the study. We thank Sheryl Rifas-Shiman and Ken Kleinman for statistical advice. Dr Martin had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Martin, Kramer, Davey Smith, and Gillman developed the hypotheses and secured funding; R. Patel, Dr Bogdanovich, and Dr Sergeichick ran the fieldwork under the direction of Drs Martin, Kramer, Oken, and Vilchuck. R. Patel and Dr Bogdanovich were responsible for the database and data cleaning. Drs Gusina and Foo developed the methods for the dried blood spot assays, and Dr Gusina directed the laboratory analyses. R. Patel, Dr Palmer, and J. Thompson undertook statistical analyses. Dr Martin wrote the first draft of the article. All authors critically commented on and approved the final submitted version of the paper. Dr Martin is the guarantor.
Sources of Funding
This study was supported by the European Union, Early Nutrition Programming Long-term Efficacy and Safety Trials grant FOOD-DT-2005-007036; Canadian Institutes of Health Research (MOP - 53155); and the National Institutes of Health (R01 HD050758). Dr Oken was supported by the US National Institute of Child Health and Development (K24 HD069408). The NIHR Bristol Nutrition Biomedical Research Unit is funded by the National Institute for Health Research (NIHR) and is a partnership between the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. No funding bodies played any role in the design, writing, or decision to publish this manuscript.
Disclosures
Dr Oken has given an invited talk for Nestle Nutrition Institute in 2011 on secular trends in birth weight. Dr Martin gave an invited talk for the Nestle Nutrition Institute in 2010 on the role of the insulin-like growth factor system in growth and chronic disease risk. Dr Kramer has received unrelated meeting expenses from the Nestle Nutrition Institute. The other authors report no conflicts.
Footnotes
The online-only Data Supplement is available with this article at http://circ.ahajournals.org/lookup/suppl/doi:10.1161/CIRCULATIONAHA.113.005160/-/DC1.
- Received July 22, 2013.
- Accepted October 15, 2013.
- © 2013 American Heart Association, Inc.
References
CLINICAL PERSPECTIVE
Several observational studies, and meta-analyses of these, have been published, showing protective effects of increased breastfeeding duration and exclusivity on cardiometabolic risk factors in later life. However, observational associations may be confounded by common causes of infant feeding choices and cardiometabolic outcomes. The unbiased effects of breastfeeding can probably only be convincingly demonstrated in a randomized, controlled trial. Although it is not feasible to randomly assign healthy term infants to be breast or bottle fed, it is possible to randomly assign mother-infant pairs to a breastfeeding promotion intervention. Our article is based on the 11.5-year follow-up of 17 046 children enrolled when newly born into the Promotion of Breastfeeding Intervention Trial (PROBIT, ISRCTN37687716), a cluster-randomized trial of a breastfeeding promotion intervention based on the World Health Organization/United Nations Children’s Fund Baby-Friendly Hospital Initiative. The intervention resulted in 2 groups with substantially different exposures to exclusive and prolonged breastfeeding, providing a unique opportunity to test, in an intention-to-treat analysis, the extent to which breastfeeding causally influences cardiometabolic risk factors in childhood. Our results, based on the largest randomized trial of breastfeeding ever conducted, provide no evidence that an intervention to promote longer duration of exclusive breastfeeding lowered levels of several cardiometabolic risk factors in childhood (blood pressure; fasting insulin, adiponectin, glucose, and apolipoprotein A1; and the presence of metabolic syndrome), in comparison with a shorter duration. Although we saw no evidence of an effect on cardiometabolic risk factors in our trial, there are several other important beneficial effects of breastfeeding that amply justify clinical and public health efforts to promote, protect, and support it.
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- Effects of Promoting Longer-Term and Exclusive Breastfeeding on Cardiometabolic Risk Factors at Age 11.5 YearsCLINICAL PERSPECTIVE
