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DHA supplementation during pregnancy does not reduce BMI or body fat mass in children: Follow-up of the DHA to Optimize Mother Infant Outcome randomized controlled trial

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Background: The omega-3 (n-3) long-chain polyunsaturated fatty acid (LCPUFA) docosahexaenoic acid (DHA) has proven effective at reducing fat storage in animal studies. However, a systematic review of human trials showed a lack of quality data to support or refute this hypothesis. Objective: We sought to determine whether maternal DHA supplementation during the second half of pregnancy results in a lower body mass index (BMI) and percentage of body fat in children. Design: We conducted a follow-up at 3 and 5 y of age of children who were born to mothers enrolled in the DOMInO (DHA to Optimize Mother Infant Outcome) double-blind, randomized controlled trial, in which women with a singleton pregnancy were provided with DHA-rich fish-oil capsules (800 mg DHA/d) or vegetable-oil capsules (control group) in the second half of pregnancy. Primary outcomes were the BMIzscore and percentage of body fat at 3 and 5 y of age. Potential interactions between prenatal DHA and the peroxisome proliferator-activated receptor-γ (PPARγ) genotype as a measure of the genetic predisposition to obesity were investigated. Results: A total of 1614 children were eligible for the follow-up. Parent or caregiver consent was obtained for 1531 children (95%), and these children were included in the analysis. BMIzscores and percentages of body fat of children in the DHA group did not differ from those of children in the control group at either 3 y of age [BMIzscore adjusted mean difference: 0.03 (95% CI: -0.07, 0.13;P= 0.61); percentage of body fat adjusted mean difference: -0.26 (95% CI: -0.99, 0.46;P= 0.47)] or 5 y of age [BMIzscore adjusted mean difference: 0.02 (95% CI: -0.08, 0.12;P= 0.66); percentage of body fat adjusted mean difference: 0.11 (95% CI: -0.60, 0.82;P= 0.75)]. No treatment effects were modified by thePPARγgenotype of the child. Conclusion: Independent of a genetic predisposition to obesity, maternal intake of DHA-rich fish oil during the second half of pregnancy does not affect the growth or body composition of children at 3 or 5 y of age. This trial was registered atwww.anzctr.org.auas ACTRN1260500056906 and ACTRN12611001127998.
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See corresponding editorials on pages 1385 and 1387.
DHA supplementation during pregnancy does not reduce BMI or body
fat mass in children: follow-up of the DHA to Optimize Mother Infant
Outcome randomized controlled trial
1,2
Beverly S Muhlhausler,
3,4
* Lisa N Yelland,
3,5
Robyn McDermott,
7,8
Linda Tapsell,
9
Andrew McPhee,
10
Robert A Gibson,
3,4
and Maria Makrides
3,6,11
3
Child Nutrition Research Centre, Women’s and Children’s Health Research Institute, Women’s and Children’s Hospital and Flinders Medical Centre,
Adelaide, Australia;
4
FOODplus Research Centre, Department of Wine and Food Science, School of Agriculture, Food and Wine and Schools of
5
Public
Health and
6
Pediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia;
7
School of Public Health, University of South Australia,
Adelaide, Australia;
8
College of Public Health, Medical & Vet Sciences, James Cook University, Cairns, Australia;
9
Illawarra Health and Medical Research
Institute, School of Medicine, University of Wollongong, Wollongong, Australia;
10
Women’s and Children’s Hospital, Adelaide, Australia; and
11
South
Australian Health and Medical Research Institute, Adelaide, Australia
ABSTRACT
Background: The omega-3 (n–3) long-chain polyunsaturated fatty
acid (LCPUFA) docosahexaenoic acid (DHA) has proven effective
at reducing fat storage in animal studies. However, a systematic
review of human trials showed a lack of quality data to support or
refute this hypothesis.
Objective: We sought to determine whether maternal DHA supple-
mentation during the second half of pregnancy results in a lower
body mass index (BMI) and percentage of body fat in children.
Design: We conducted a follow-up at 3 and5yofageofchildrenwho
were born to mothers enrolled in the DOMInO (DHA to Optimize
Mother Infant Outcome) double-blind, randomized controlled trial, in
which women with a singleton pregnancy were provided with DHA-
rich fish-oil capsules (800 mg DHA/d) or vegetable-oil capsules (con-
trol group) in the second half of pregnancy. Primary outcomes were the
BMI zscore and percentage of body fat at 3 and 5 y of age. Potential
interactions between prenatal DHA and the peroxisome proliferator–
activated receptor-g(PPARg) genotype as a measure of the genetic
predisposition to obesity were investigated.
Results: A total of 1614 children were eligible for the follow-up.
Parent or caregiver consent was obtained for 1531 children (95%),
and these children were included in the analysis. BMI zscores and
percentages of body fat of children in the DHA group did not differ
from those of children in the control group at either 3 y of age [BMI
zscore adjusted mean difference: 0.03 (95% CI: 20.07, 0.13; P=
0.61); percentage of body fat adjusted mean difference: 20.26 (95%
CI: 20.99, 0.46; P= 0.47)] or 5 y of age [BMI zscore adjusted
mean difference: 0.02 (95% CI: 20.08, 0.12; P= 0.66); percentage
of body fat adjusted mean difference: 0.11 (95% CI: 20.60, 0.82;
P= 0.75)]. No treatment effects were modified by the PPARggeno-
type of the child.
Conclusion: Independent of a genetic predisposition to obesity,
maternal intake of DHA-rich fish oil during the second half of
pregnancy does not affect the growth or body composition of chil-
dren at 3 or 5 y of age. This trial was registered at www.anzctr.org.
au as ACTRN1260500056906 and ACTRN12611001127998.
Am J Clin Nutr 2016;103:1489–96.
Keywords: body composition, growth, maternal nutrition, omega-
3, pregnancy
INTRODUCTION
The prevalence of overweight and obesity has reached epi-
demic proportions in many Western countries, and there is an
urgent need for effective intervention strategies. Compelling
epidemiologic and experimental animal data have indicated that
overweight and obesity have early life origins and that exposure
to an inappropriate balance of nutrients during fetal life or in early
infancy can permanently alter the properties of fat cells and
predispose an individual to fatness (1, 2). These data have led to
suggestions that nutritional interventions during the perinatal
period are likely to be more effective than are those later in life in
producing lifelong reductions in body fat mass and improvements
in metabolic health (3).
In this context, there has been growing interest in an in-
creased supply of omega-3 (n–3) long-chain PUFAs (LCPUFAs)
12
1
Supported by the National Health and Medical Research Council
(NHMRC) of Australia [original DOMInO (DHA to Optimize Mother Infant
Outcome) trial: grant 349301; 3- and 5-y follow-up study: grant 570109].
BSM was supported by a Career Development Fellowship from the NHMRC
(grant APP1004211). LNY was supported by an Early Career Fellowship
from the NHMRC (grant APP1052388). RAG (grant APP1046207) and MM
(grant APP1061074) were supported by Senior Researcher Fellowships from
the NHMRC. DOMInO-trial treatment (Incromega 500 TG) and control
capsules were donated by Croda Chemicals.
2
Supplemental Tables 1–4 are available from the “Online Supporting Ma-
terial” link in the online posting of the article and from the same link in the
online table of contents at http://ajcn.nutrition.org.
*Towhom correspondence should be addressed. E-mail: beverly.muhl-
hausler@adelaide.edu.au.
Received November 2, 2015. Accepted for publication March 1, 2016.
First published online March 30, 2016; doi: 10.3945/ajcn.115.126714.
12
Abbrevaitions used: DOMInO, DHA to Optimize Mother Infant Out-
come; LCPUFA, long-chain PUFA; PPARg, peroxisome proliferator–
activated receptor-g.
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Supplemental Material can be found at:
during the perinatal period as a potential means to limit fat
deposition and improve metabolic health outcomes in children
(4, 5). This possible effect has been based on results from studies
that were conducted in vitro and in adult humans and rodents
that have shown that the n–3 LCPUFAs, in particular DHA,
inhibit the hyperplastic and hypertrophic expansion of fat depots
and improve insulin sensitivity (6–11).
Despite these apparent benefits of n–3 LCPUFAs, clinical
studies that were designed to evaluate the effect of maternal DHA
supplementation on body fat mass in children have produced
mixed results (12). However, these studies have had a number of
methodologic limitations including high rates of attrition, a lack of
statistical power, and the absence of appropriately sensitive mea-
sures of body composition (12). In addition, the potential impact
of a genetic predisposition to obesity and type 2 diabetes on the
relation between metabolic outcomes and maternal DHA sup-
plementation has to our knowledge not yet been investigated.
In the current article, we report on the follow-up of children of
Adelaide mothers who participated in the DOMInO (DHA to Op-
timize Mother Infant Outcome) trial (13) at 3 and 5 y of age. The
primary objective of this study was to determine the effect of increased
prenatal DHA on BMI zscores and percentages body fat in children.
A secondary objective was to determine whether the effects of ma-
ternal DHA supplementation on these outcomes were dependent on
the child’s genotype for the Pro/Ala single nucleotide polymorphism
in the PPARggene, which has been strongly associated with the
genetic predisposition to obesity and type 2 diabetes (14).
METHODS
Study design
This study involved a follow-up of children who were born to
mothers enrolled in a registered, multicenter, double-blind, ran-
domized controlled trial called the DOMInO trial (www.anzctr.org.
au; original trial: ACTRN12605000569606; 3- and 5-y follow-ups:
ACTRN12611001127998). The DOMInO trial methods have been
published previously (13). Briefly, women with singleton
pregnancies at ,21 wk of gestation were randomly assigned to
the treatment or control group with the use of a computer-
driven service and were stratified by center and parity. Women
allocated to the treatment group received three 500-mg capsules
DHA-rich fish oil/d [w800 mg DHA/d and 100 mg EPA/d (In-
cromega 500 TG; Croda Chemicals)], and women in the control
group received three 500-mg vegetable-oil capsules (without
DHA)/d. Women were asked to take the capsules from study entry
until the birth of their child. All DOMInO children who were born
to women enrolled in an Adelaide center (Flinders Medical Centre
or Women’s and Children’s Hospital; n= 1660) and had not died
or withdrawn from the study were eligible for the 3- and 5-y
follow-ups (n= 1614; 97%). All procedures were conducted in
accordance with the study protocol and were approved by the local
institutional boards of each center. Written informed consent was
obtained from the guardian of each child.
Outcome assessments
Assessments of anthropometric variable, BMI zscores, and
percentages of body fat were conducted at the hospital study
centers between 25 March 2009 and 4 October 2013. Assess-
ments were administered by trained research staff who were
blinded to the treatment-group allocation.
Anthropometric assessments
Body weight was measured without shoes and in underwear to
the nearest 100 g with the use of electronic scales. Height without
shoes was measured with the use of a stadiometer. Waist, head,
and hip circumferences were measured with the use of a non-
stretch tape. All measures were recorded in duplicate [or triplicate
if the first 2 measures differed by .0.1kg(weight)or.0.5 cm
(height and girths)] and averaged for the analysis. Weight and
height measurements were used to calculate BMI (kg/m
2
)as
weight divided by the square of height. The measures for each
child were compared with standardized reference charts for the
child’s age and sex to calculate their zscores (15, 16). Corrected
ages were used for children born preterm (,37 wk of gestation).
The number of children classified as underweight (BMI ,10th
percentile), overweight (BMI .85th percentile), and obese
(BMI .90th percentile) was determined at each age.
Total fat mass and fat-free mass were assessed with the use of
bioelectrical impedance spectroscopy (17). Fat-free mass was
derived from the measure of total body water with the use of an
equation that was previously validated for use in pediatric pop-
ulations (18, 19). The percentage of body fat was determined as
½ðFat-free mass 2body weightÞObody weight3100 ð1Þ
Systolic, diastolic, and mean arterial blood pressures at 5 y of age
were assessed in duplicate with the use of a DINAMAP Procare
V100 monitor (GE Healthcare) with an appropriate sized cuff.
Blood sample collection and processing
Children were instructed to fast $4 h before their 5-y clinic
appointment, and blood samples (w5 mL) were collected into
tubes treated with EDTA and kept on ice until transfer to the
laboratory and processed (centrifugation at 1500 3gfor 30 min
at 48C). The majority of samples were processed #4 h of col-
lection, and all samples were processed within 24 h. Plasma and
buffy coat fractions were separated into aliquots and frozen at
–808C, red blood cells were washed in sterile saline, and lipids
were extracted into chloroform and used to assess the fatty acid
composition of the phospholipids as previously described (20).
Determination of insulin sensitivity
Glucose and insulin concentrations in the 5-y plasma samples were
determined with the use of an enzymatic assay (Thermo Electron) and
a human ultrasensitive insulin ELISA kit (ALPCO Diagnostics),
respectively. The intra-assay and interassay CVs for both assays were
,10%. Fasting glucose and insulin measures were used to calculate
the HOMA-IR index for each child according to the equation
½Glucose ðmmol=LÞ3insulin ðmU=LÞ O22:5ð2Þ
PPARggenotyping
DNA was extracted from 200 mL 5-y buffy coat samples with
the use of the Qiagen DNA extraction kit (Qiagen Pty. Ltd.). The
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PPARggenotyping of each child was undertaken by the Aus-
tralian Genome Facility with the use of TaqMan technology
(Applied Biosystems).
Other measures
In the DOMInO trial, maternal weight, height, BMI, parity,
education, and smoking status were collected at enrollment. The
weight and height of the biological mother of the child were
remeasured by a clinic staff member at the time of the 5-y as-
sessments. Questions about the home environment, education,
and employment of the primary caregiver and whether the
participant had requested to be unblinded were also reasked at
the time of the 3- and 5-y assessments.
At both the 3- and 5-y follow-ups, detailed information on
the care received outside the home and general health of the
child was collected at the clinic appointment. Information on
feeding practices in the first 6–12 mo of life, the family food
environment, and the child’s habitual dietary intake, physical
activity, and screen time was collected with the use of
a structured questionnaire that was completed by the primary
caregiver.
FIGURE 1 Participant flow. DOMInO, DHA to Optimize Mother Infant Outcome.
PRENATAL DHA AND CHILDHOOD GROWTH 1491
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Sample size and statistical analysis
The follow-up of the 1660 children born to women enrolled in
Adelaide-based centers provided .90% power to detect a 3%
relative reduction in mean BMI (16 to 15.52; SD: 1.6), and a 2%
absolute reduction in the mean percentage of body fat (25–23%
at 3 y and 21–19% at 5 y; SD: 5%) in boys and girls separately,
which allowed for a 10% loss to follow-up (a= 0.05).
All analyses were performed on an intention-to-treat basis
according to the treatment group allocated at random assignment.
Multiple imputation was performed separately by treatment
group with the use of chained equations to create 100 complete
data sets for analysis, with the assumption that data were
missing at random. The effect estimates from the imputed data
sets were combined with the use of Rubin’s rules (21). The
primary analysis was based on imputed data and included all
participants who consented to the follow-up study because the
missing-at-random assumption was considered most plausible
in this subgroup. Sensitivity analyses were performed on the
available data and on imputed data for all 1660 children born to
women enrolled in Adelaide-based centers. All analyses pro-
duced similar results, and only the results of the primary anal-
ysis are presented.
Continuous outcomes were analyzed with the use of linear
regression models with treatment effects expressed as differences
in means. For continuous outcomes that were log transformed
before analysis, treatment effects are expressed as ratios of
geometric means on the original scale. Binary outcomes were
analyzed with the use of log binomial regression models with
treatment effects expressed as RRs. For outcomes that were
measured at both 3 and 5 y, the repeated measurements were
taken into account with the use of generalized estimating
equations with treatment effects estimated at each time point
separately. A priori secondary analyses were performed to test for
an effect-measure modification by sex and PPARggenotype.
Both unadjusted and adjusted analyses were performed with
adjustment for the stratification variables center and parity as
well as prespecified variables depending on the outcome that
included the child’s sex and PPARggenotype and the mother’s
secondary education, additional education, smoking status,
and BMI at enrollment. Statistical significance was assessed
at the 2-sided P,0.05 level. No adjustment was made for
multiple comparisons, and results of secondary analyses
should be interpreted with caution unless there were highly
significant.
Post–random-assignment child demographics and clinical
characteristics were compared between treatment groups on the
basis of the available data with the use of chi-square tests for
categorical variables, Mann-Whitney Utests for continuous
variables, and log Poisson regression for count variables. All
analyses followed a prespecified statistical analysis plan and
were performed with the use of SAS version 9.3 software (SAS
Institute).
RESULTS
Participant flow and baseline characteristics
Participant flow is shown in Figure 1. A total of 1531 families
consented to the 3- and 5-y follow-up (92.2% of the 1660
families who were originally enrolled in Adelaide centers and
94.9% of the 1614 families who were invited to participate).
BMI zscores and percentages of body fat were determined for
1468 of 1531 children (95.9%) and 1269 of 1531 children
(82.9%), respectively, at 3 y and 1352 of 1531 children (88.3%)
and 1120 of 1531 children (73.2%), respectively, at 5 y. The
amount of missing data that required imputation was similar
between the treatment groups.
The sociodemographic characteristics of the families in the
subset who consented to follow-up were comparable between
treatment groups at baseline (Table 1) and at 3 and 5 y (Sup-
plemental Table 1). The distribution of PPARggenotypes in the
children was similar between groups (Table 1).
BMI zscore and percentage of body fat
BMI zscores of children in the DHA group did not differ
from those in the control group at either 3 y (adjusted mean
difference: 0.03; 95% CI: 20.07, 0.13; P= 0.61) (Tab l e 2)or5y
(adjusted mean difference: 0.02; 95% CI: 20.08, 0.12; P= 0.66)
TABLE 1
Baseline characteristics by treatment group
Characteristic DHA supplement (n= 770) Control supplement (n= 761)
Maternal data collected at enrollment, n(%)
Primiparous 319 (41.4) 321 (42.2)
Mother completed secondary education 485 (63.0) 495 (65.0)
Mother completed additional education
1
515 (66.9) 533 (70.0)
Nonsmoker before and during early pregnancy 556 (72.2) 512 (67.3)
Maternal BMI,
2
kg/m
2
26.2 (23.5–30.1) 26.3 (23.2–30.5)
Infant pre–random-assignment characteristics, n(%)
Infant female sex 384 (49.9) 382 (50.2)
PPARgPro12Ala genotype
3
Pro/Pro 260 (77.6) 245 (77.3)
Pro/Ala 66 (19.7) 66 (20.8)
Ala/Ala 9 (2.7) 6 (1.9)
1
Included a degree, diploma, certificate, or trade.
2
Values are medians; IQRs in parentheses.
3
PPARg, peroxisome proliferator–activated receptor-g. Numbers do not add up to the total in each group because of
missing data. Percentages were calculated on the basis of participants with available data.
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(Table 2). The percentage of body fat was also not different be-
tween children in the DHA and control groups at either 3 or 5 y [3-y
adjusted mean difference: 20.26 (95%: CI 20.99, 0.46; P=
0.47); 5-y adjusted mean difference: 0.11 (95% CI: 20.60, 0.82;
P= 0.75)] (Table 2). There were no significant interactions between
the treatment group and either sex or PPARggenotype in relation
TABLE 2
Primary and secondary anthropometric outcomes at 3 and 5 y of age
DHA supplement
(n= 770)
Control supplement
(n= 761)
Unadjusted Adjusted
1
Effect (95% CI) PEffect (95% CI) P
3yofage
BMI zscore 0.72 60.97
2
0.70 61.06 0.02 (20.08, 0.12) 0.73 0.03 (20.07, 0.13) 0.61
Body fat,
3
% 24.54 67.07 24.87 66.69 20.32 (21.08, 0.43) 0.40 20.26 (20.99, 0.46) 0.47
Body weight, kg 15.40 62.02 15.34 62.01 0.07 (20.14, 0.27) 0.53 0.08 (20.12, 0.27) 0.43
Body weight zscore 0.51 60.97 0.48 60.95 0.04 (20.06, 0.13) 0.43 0.04 (20.05, 0.14) 0.38
BMI, kg/m
2
16.52 61.41 16.51 61.54 0.01 (20.14, 0.16) 0.92 0.02 (20.13, 0.16) 0.81
BMI percentile,
4
n(%)
.85th 256 (33.2) 287 (37.7) 0.88 (0.77, 1.01) 0.07 0.89 (0.78, 1.02) 0.10
.90th 195 (25.4) 216 (28.4) 0.89 (0.76, 1.06) 0.19 0.91 (0.77, 1.07) 0.26
,10th 11 (1.4) 21 (2.8) 0.51 (0.24, 1.07) 0.07 0.51 (0.24, 1.07) 0.07
Total fat mass, kg 3.79 61.26 3.84 61.25 20.05 (20.18, 0.09) 0.48 20.03 (20.17, 0.10) 0.62
Total fat-free mass, kg 11.61 61.76 11.50 61.68 0.11 (20.07, 0.20) 0.24 0.11 (20.06, 0.27) 0.20
Fat-free mass,
3
% 75.43 67.03 75.13 66.64 0.30 (20.44, 1.05) 0.43 0.24 (20.47, 0.95) 0.51
Total body water, kg 8.68 61.25 8.59 61.19 0.09 (20.04, 0.22) 0.20 0.09 (20.04, 0.21) 0.17
Impedance index 13.00 62.02 12.88 61.91 0.12 (20.08, 0.33) 0.23 0.12 (20.07, 0.32) 0.22
Height, cm 96.43 64.21 96.27 64.04 0.16 (20.26, 0.57) 0.45 0.16 (20.23, 0.55) 0.41
Height zscore
3
0.03 61.04 20.01 60.97 0.05 (20.05, 0.15) 0.36 0.05 (20.06, 0.15) 0.38
Head circumference,
3
cm 50.04 61.57 50.06 61.55 20.02 (20.17, 0.14) 0.84 20.02 (20.16, 0.13) 0.81
Head circumference zscore 0.69 61.02 0.69 61.00 0.00 (20.11, 0.10) 0.96 0.00 (20.11, 0.10) 0.96
Waist circumference,
3
cm 50.73 63.53 50.50 63.48 0.23 (20.12, 0.59) 0.20 0.25 (20.10, 0.60) 0.17
Waist circumference zscore 0.47 60.88 0.40 60.91 0.07 (20.02, 0.16) 0.11 0.08 (20.01, 0.17) 0.09
Hip circumference,
3
cm 53.65 63.54 53.66 63.67 20.01 (20.38, 0.35) 0.95 0.03 (20.33, 0.39) 0.87
Waist:hip ratio
3
0.95 60.05 0.94 60.04 0.00 (0.00, 0.01) 0.04 0.00 (0.00, 0.01) 0.04
5yofage
BMI zscore 0.56 60.97 0.54 61.03 0.01 (20.09, 0.12) 0.78 0.02 (20.08, 0.12) 0.66
Body fat,
3
% 23.46 66.82 23.42 66.59 0.05 (20.72, 0.81) 0.91 0.11 (20.60, 0.82) 0.75
Body weight, kg 19.95 63.00 19.87 63.07 0.09 (20.22, 0.39) 0.58 0.06 (20.23, 0.36) 0.68
Body weight zscore 0.45 60.98 0.42 60.97 0.03 (20.06, 0.13) 0.49 0.04 (20.06, 0.14) 0.43
Body weight increase from 3 to 5 y of age, kg 4.51 61.60 4.47 61.71 0.04 (20.13, 0.22) 0.65 0.02 (20.15, 0.18) 0.85
BMI, kg/m
2
16.19 61.61 16.20 61.73 20.01 (20.18, 0.16) 0.90 0.00 (20.17, 0.17) 0.99
BMI percentile,
4
n(%)
.85th 221 (28.7) 223 (29.4) 0.98 (0.83, 1.15) 0.78 0.99 (0.84, 1.16) 0.90
.90th 165 (21.5) 168 (22.1) 0.97 (0.80, 1.19) 0.78 0.99 (0.81, 1.20) 0.91
,10th 13 (1.7) 19 (2.5) 0.66 (0.31, 1.40) 0.28 0.66 (0.31, 1.40) 0.28
Total fat mass, kg 4.75 61.78 4.74 61.85 0.01 (20.18, 0.20) 0.92 0.02 (20.17, 0.20) 0.86
Total fat-free mass,
3
kg 15.25 62.36 15.15 62.22 0.11 (20.14, 0.35) 0.40 0.08 (20.15, 0.32) 0.48
Percentage fat-free mass
3
76.52 66.80 76.61 66.52 20.09 (20.84, 0.67) 0.82 20.15 (20.85, 0.55) 0.67
Total body water, kg 11.32 61.67 11.24 61.58 0.08 (20.10, 0.26) 0.39 0.06 (20.11, 0.24) 0.48
Impedance index 16.98 62.67 16.88 62.50 0.10 (20.17, 0.38) 0.45 0.08 (20.19, 0.34) 0.56
Height, cm 110.82 65.06 110.58 64.93 0.24 (20.27, 0.75) 0.35 0.16 (20.32, 0.65) 0.51
Height zscore 0.12 61.03 0.08 60.98 0.04 (20.06, 0.14) 0.46 0.04 (20.07, 0.14) 0.48
Height increase between 3 and 5 y, cm 14.36 62.66 14.28 62.75 0.07 (20.22, 0.37) 0.61 20.02 (20.26, 0.22) 0.86
Head circumference,
3
cm 51.35 61.53 51.33 61.56 0.02 (20.14, 0.18) 0.80 0.01 (20.14, 0.16) 0.86
Head circumference zscore 0.66 60.98 0.64 60.98 0.02 (20.09, 0.13) 0.71 0.02 (20.09, 0.13) 0.71
Head circumference increase between 3 and 5 y, cm 1.30 60.86 1.25 60.91 0.04 (20.06, 0.14) 0.40 0.03 (20.07, 0.13) 0.53
Waist circumference,
3
cm 53.69 63.88 53.57 64.24 0.11 (20.31, 0.54) 0.60 0.10 (20.31, 0.51) 0.62
Waist circumference zscore 0.24 60.74 0.20 60.79 0.04 (20.04, 0.12) 0.34 0.04 (20.04, 0.12) 0.29
Hip circumference,
3
cm 59.34 64.16 59.31 64.55 0.03 (20.41, 0.47) 0.90 0.04 (20.40, 0.48) 0.87
Waist:hip ratio
3
0.91 60.04 0.90 60.04 0.00 (0.00, 0.01) 0.47 0.00 (0.00, 0.01) 0.43
BMI zscore 0.72 60.97 0.70 61.06 0.02 (20.08, 0.12) 0.73 0.03 (20.07, 0.13) 0.61
1
Adjusted for center, parity, maternal BMI at study entry, mother’s secondary education, mother’s additional education, mother’s smoking status, and
peroxisome proliferator–activated receptor-ggenotype.
2
Mean 6SD (all such values). Data were analyzed with the use of linear regression models with treatment effects expressed as difference in means unless
otherwise indicated. All analyses were based on 100 imputed data sets.
3
Also adjusted for infant sex and the actual age of child at the assessment.
4
Data were analyzed with the use of log binomial regression models with treatment effects expressed as RRs.
PRENATAL DHA AND CHILDHOOD GROWTH 1493
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to the BMI zscore or percentage of body fat at 3 or 5 y of age
(data not shown).There was no difference in the proportion of
children classified as overweight or obese between the treatment
groups at either 3 or 5 y of age (Table 2).
Other anthropometric outcomes
Body weight and height zscores were similar between groups
as was the mean weight gain between 3 and 5 y of age (Table 2).
Hip and waist circumferences and waist-circumference zscores
were also not different between the treatment groups at either 3
or 5 y (Table 2). The waist:hip ratio was slightly higher in the
DHA group than in the control group at 3 y (adjusted mean
difference: 0.00; 95% CI: 0.00, 0.01; P= 0.04) but was not
different between groups at 5 y (P= 0.43). Total fat-free mass
and the percentage fat-free mass, total body water, and the im-
pedance index were not different between groups at either 3 or 5
y (Table 2). Head circumference, the head circumference z
score, and the change in head circumference between 3 and 5 y
were also similar between groups (Table 2).
Insulin sensitivity at 5 y of age
In both adjusted and unadjusted analyses, insulin resistance at
5 y of age, as assessed with the use of HOMA-IR, was higher in
children in the DHA group than in controls (adjusted ratio of
geometric means: 1.20; 95% CI: 1.04, 1.39; P= 0.01) (Table 3).
Fasting insulin concentrations were also higher in the DHA
group (adjusted ratio of geometric means: 1.17; 95% CI:
1.03,1.33; P= 0.02). There was an interaction between the
treatment group and sex for fasting glucose concentrations (P=
0.03),such that boys in the DHA group had higher fasting glu-
cose concentrations than did boys in the control group (adjusted
mean difference: 0.21; 95% CI: 0.01, 0.42; P= 0.04); however,
there were no differences between groups in girls. Similar
effects were observed for both fasting insulin concentrations
and HOMA-IR. Boys in the DHA group had significantly higher
mean HOMA-IR (adjusted ratio of geometric means: 1.35; 95%
CI: 1.11, 1.65; P= 0.003) and fasting insulin concentrations
(adjusted ratio of geometric means: 1.26; 95% CI: 1.05, 1.51;
P= 0.01) than those in the control group, whereas no differences
were seen for girls; however, the interactions between treatment
and sex were NS for HOMA-IR (P= 0.13) or fasting insulin
(P= 0.28). All results were independent of the PPARggenotype
of the child.
Other postrandomization variables
More families in the control group had requested to be un-
blinded than occurred in the DHA group at both the 3- and 5-y
time points, but the total number of unblinded families repre-
sented ,10% of the cohort. Maternal and paternal BMI at
baseline and at the time of the 3 and 5 y follow-up were also
similar between groups (Supplemental Table 1).
There were no significant differences between groups in the
frequency of hospitalizations or diagnosis of any medical con-
ditions between birth and 5 y of age (Supplemental Table 2)or
habitual dietary intake, the family food environment, or reported
levels of physical activity or screen time at either 3 or 5 y of age
(Supplemental Table 3). Systolic, diastolic, and mean arterial
blood pressures and fatty acid compositions of red blood cell
phospholipids at 5 y of age were also similar between groups
(Supplemental Table 4).
DISCUSSION
The results of this study do not support, either positively or
negatively, the hypothesis that increasing maternal DHA intake
by 800 mg/d during the second half of pregnancy can influence
body weight, the BMI zscore, or body fat mass of children. We
have many reasons to have a high degree of confidence in our
findings. The DOMInO trial is the largest randomized controlled
TABLE 3
Secondary outcomes related to insulin sensitivity at 5 y of age
DHA supplement
(n= 770)
Control supplement
(n= 761)
Unadjusted Adjusted
1
Sex-by-treatment
effectEffect (95% CI) PEffect (95% CI) P
HOMA-IR 0.80 (0.43–1.71)
2
0.68 (0.38–1.31) 1.20 (1.04, 1.39) 0.01 1.20 (1.04, 1.39) 0.01 0.13
Fasting glucose 4.07 61.08
3
4.02 61.02 0.05 (20.11, 0.20) 0.56 0.05 (20.11, 0.20) 0.56 0.03
Fasting insulin 4.63 (2.68–9.20) 4.01 (2.38–7.25) 1.17 (1.03, 1.32) 0.02 1.17 (1.03, 1.33) 0.02 0.28
Boys
n386 379 ————
HOMA-IR 0.86 (0.44–1.88) 0.62 (0.35–1.21) 1.35 (1.11, 1.65) 0.003 1.35 (1.11, 1.65) 0.003
Fasting glucose 4.26 61.07 4.03 61.00 0.22 (0.02, 0.43) 0.03 0.21 (0.01, 0.42) 0.04
Fasting insulin 4.75 (2.70–9.63) 3.63 (2.22–6.81) 1.25 (1.04, 1.50) 0.02 1.26 (1.05, 1.51) 0.01
Girls
n384 382 ————
HOMA-IR 0.75 (0.43–1.58) 0.74 (0.41–1.41) 1.07 (0.86, 1.33) 0.55 1.07 (0.86, 1.33) 0.52
Fasting glucose 3.87 61.04 4.01 61.04 20.14 (20.36, 0.09) 0.24 20.12 (20.35, 0.11) 0.29
Fasting insulin 4.55 (2.66–8.90) 4.40 (2.56–7.72) 1.09 (0.90, 1.31) 0.37 1.09 (0.90, 1.31) 0.37
1
Adjusted for center, parity, maternal BMI at study entry, infant sex, mother’s secondary education, mother’s additional education, mother’s smoking
status, peroxisome proliferator–activated receptor-ggenotype.
2
Median; IQR in parentheses (all such values). Data were analyzed with the use of linear regression models with treatment effects expressed as the ratio
of geometric means.
3
Mean 6SD (all such values). Data were analyzed with the use of linear regression models with treatment effects expressed as difference in means unless
otherwise indicated. All analyses are based on 100 imputed data sets.
1494 MUHLHAUSLER ET AL.
by guest on December 25, 2017ajcn.nutrition.orgDownloaded from
trial of DHA supplementation during pregnancy and has high
retention and long-term follow-up rates of the children. The trial
is also the first study, to our knowledge, to include 2 measures of
obesity and body fat mass (i.e., bioelectrical impedance spec-
troscopy and BMI zscore) at 2 ages and to investigate the po-
tential impact of child genotype on their responses to the
prenatal DHA intervention.
The percentage of DOMInO children classified as overweight
or obese (i.e., .30% of children at 3 y of age and .25% of
children at 5 y of age) was similar to figures reported in previous
studies of preschool children in South Australia, by our group
(22) and by others (23), which indicate that this study population
is representative of the general Australian pediatric population.
Our new data confirmed that the percentage of overweight and
obese children in Australia remains high at 5 y of age despite the
fact that this age is considered to be a period of increased
physical activity and lower BMI and fat mass, which precedes
the adiposity rebound (24).
Our study suggests a possible negative effect of prenatal
DHA supplementation on the waist:hip ratio and insulin sensi-
tivity. An increased waist circumference has previously been
reported in children at 2.5 y of age whose mothers were sup-
plemented with DHA during lactation (5). Although, to our
knowledge, our study is the first study to determine the effect of
prenatal DHA supplementation on insulin sensitivity, our findings
were unexpected because of existing data from in vitro and
experimental animal studies that suggested that DHA increases
insulin sensitivity (25, 26). Although it is possible that the ob-
served differences in insulin sensitivity and the waist:hip ratio
may indicate a true underlying adverse effect of DHA supple-
mentation, these differences were secondary outcomes and, as
such, require confirmation. Note also that the differences between
groups were small, and the measures in both groups fell within
the normal range.
The PPARgPro12Ala single nucleotide polymorphism is
present in w20% of Caucasian populations and has been con-
sistently associated with reduced risks of obesity and type 2
diabetes in epidemiologic studies (14, 27). Although there were
no significant interactions between the PPARggenotype and
treatment in our study, we were likely underpowered to detect
such interaction effects, and additional studies will be needed to
explore the possible interactions.
Because w70% of pregnant women in Adelaide, independent
of any specific clinical advice, now consume nutritional sup-
plements that provide at least some DHA, it is encouraging that
this long-term follow-up of the DOMInO trial showed no det-
rimental effects of maternal DHA supplementation on childhood
growth or body composition. These data, together with the ab-
sence of significant effects on development in this same study
population at 4 y of age (28), support the safety of high-dose
DHA supplements in pregnancy for the long-term health of the
child, at least at the concentration of DHA supplementation used
in this study.
In conclusion, the results of this follow-up study provide no
evidence to support the hypothesis that increasing maternal DHA
intake during the second half of pregnancy influences body
weight, BMI, or body fat mass of children at least up to 5 y of age.
We cannot extend our conclusion to suggest that maternal DHA
intake does not influence later fat deposition in the child;
however, it seems that any effects on growth are likely small and
are far outweighed by the influence of other factors, such as
genetics and environment, that are experienced by the child after
birth. Similarly, our findings do not preclude their being benefits
of increased maternal fish consumption or DHA supplementation
earlier in pregnancy on these outcomes. Nevertheless, to our
knowledge, this trial provides the most robust data to date that
maternal DHA supplementation during the second half of
pregnancy is not an effective strategy by which to reduce the
population burden of childhood obesity.
We thank the following staff of the Women’s and Children’s Health Re-
search Institute (Adelaide, Australia) who assisted in the 3- and 5-y follow-
ups of the DOMInO trial: Helen Loudis, Daniela Calderisi, Jacki Aldis,
Elizabeth Strahan, Jo Collins, Karen Best, Heather Garreffa, Pamela Sim,
and Jing Zhou. We also thank the staff at the Data Management & Analysis
Centre, School of Population Health, The University of Adelaide (Adelaide,
Australia), in particular Jennie Louise, who assisted LNY with the statistical
analysis.
The authors’ responsibilities were as follows—BSM: had primary respon-
sibility for the final content of the manuscript; BSM, RM, LT, AM, RAG,
and MM: designed the research; BSM, RAG, and MM: wrote the manuscript;
BSM and MM: conducted the research; LNY: performed the statistical anal-
ysis; LNY and MM: had full access to all of the data in the study and took
responsibility for the integrity of the data and accuracy of the data analysis;
and all authors: read and approved the final manuscript. Croda Chemicals
had no input into any aspect of the trial or the follow-up study. BSM has
given lectures on maternal nutrition for Aspen Nutrition and Danone Nutri-
cia. RAG serves on scientific advisory boards for Fonterra and Ferrero. MM
serves on scientific advisory boards for Nestle
´and Fonterra. Associated
honoraria for BSM, RAG, and MM were paid by their institutions to
support conference travel and continuing education for postgraduate stu-
dents and early career researchers. LT serves on the Science Advisory
Committees of the California Walnut Commission and the McCormicks
Science Institute. LNY, RM, and AM reported no conflicts of interest re-
lated to the study.
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... Although observational evidence suggests that higher levels of maternal n-3 PUFAs are associated with a lower risk of childhood obesity, 49 evidence from human interventional trials [69][70][71][72][73][74][75] and systematic reviews [76][77][78] do not indicate n-3 PUFA supplementation during pregnancy reduces weight, BMI, or adiposity of the children. Insights from systematic reviews [76][77][78] are limited by the heterogeneity of the published randomized trials, because there is major variation in key factors, including study population, dosage, timing and duration of supplementation, different long-chain PUFA preparations (ie, fish body oil, [70][71][72][73][74][75]79 cod liver oil, 69 and algal oil 80 ), and different control treatments (ie, corn oil 69 ; vegetable oil made of rapeseed, sunflower, and palm 71 ; mixed vitamins; and prebiotics 70,79 ) ( Table 1). ...
... Although observational evidence suggests that higher levels of maternal n-3 PUFAs are associated with a lower risk of childhood obesity, 49 evidence from human interventional trials [69][70][71][72][73][74][75] and systematic reviews [76][77][78] do not indicate n-3 PUFA supplementation during pregnancy reduces weight, BMI, or adiposity of the children. Insights from systematic reviews [76][77][78] are limited by the heterogeneity of the published randomized trials, because there is major variation in key factors, including study population, dosage, timing and duration of supplementation, different long-chain PUFA preparations (ie, fish body oil, [70][71][72][73][74][75]79 cod liver oil, 69 and algal oil 80 ), and different control treatments (ie, corn oil 69 ; vegetable oil made of rapeseed, sunflower, and palm 71 ; mixed vitamins; and prebiotics 70,79 ) ( Table 1). In a recent clinical trial, researchers identified a potential growthpromoting effect of maternal n-3 PUFAs, as there was greater lean tissue mass and BMI at age 6 years. ...
... With one exception, 79 previous trials have recruited populations predominantly of normal-weight women. [69][70][71]73,74,80 This is important because normalweight mothers have children with lower risk of obesity. There are four key reasons why studies are required that focus on women who are overweight or obese for the analysis of the effects of maternal n-3 PUFA supplementation on body composition and metabolism of the offspring: (1) greater risk of obesity in their children means they are the group that would benefit most from an effective treatment; (2) demonstrating an effect is easier in a high-risk group; (3) maternal obesity is associated with exaggeration of the insulin resistance of pregnancy and subsequent fetal overnutrition, so if the key mechanism of action of n-3 PUFAs is as an insulinsensitizing treatment, 38,39 this would only be expected to be beneficial in overweight and obese women; and (4) maternal obesity is associated with increased suppression of IGF-2, a growth factor that has a role in fetal overgrowth 84 and later risk of metabolic disease development. ...
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Eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and trans fatty acids (TFAs) may have an impact on offspring weight development. We conducted a systematic review and meta-analysis according to PRISMA guidelines to evaluate whether levels of these fatty acids during pregnancy influenced offspring weight development. Randomized controlled trials (RCTs) with DHA and/or EPA supplementation or cohort studies, which examined levels of DHA, EPA, or TFAs in maternal or neonatal blood samples and recorded offspring weight, were included. Overall, 27 RCTs and 14 observational studies were identified. The results showed that DHA and/or EPA supplementation doses >650 mg/day resulted in slightly higher birth weight (MD 87.5 g, 95% CI 52.3–122.6, n = 3,831) and combined BMI and BMI z score at 5–10 years (SMD 0.11, 95% CI 0.04–0.18, n = 3,220). These results were rated as moderate quality. Results from the observational studies were generally inconsistent. High TFA levels during pregnancy seemed to be associated with lower birth weight. Finally, this review and meta-analysis supports a relationship between high maternal or neonatal DHA and/or EPA levels and higher offspring birth weight and weight in childhood. More high-quality long-term studies are still needed.
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With the worldwide increase in overnutrition rates, maternal obesity during pregnancy has also increased. This condition is related to increasing incidence of pregnancy and delivery complications, and it is associated to long-term vulnerability of the offspring to suffer metabolic impairments. In addition, nutrition of the newborn through maternal breast milk could be influenced by the nutritional status of the mother, thus adding another factor to be analyzed. In this chapter, we analyze how maternal obesity during pregnancy and composition of maternal milk can affect the newborn metabolic features. Then we discuss, using approaches in animal models and humans, how these alterations could be projected to the adult descendants. Finally, we discuss some of the possible treatments of maternal obesity with the aim to prevent the alterations in offspring.
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Although several epidemiological studies have reported that higher intake of n-3 long-chain polyunsaturated fatty acids during pregnancy is associated with both a reduced risk of postpartum depression and improved neurodevelopmental outcomes in offspring, the results of other intervention trials have been inconsistent. Despite the uncertainty of benefit, there are now international recommendations for pregnant women to increase their intake of docosahexaenoic acid (DHA), the n-3 long-chain polyunsaturated fatty acids believed to be responsible for the improved outcomes. The DHA to Optimize Mother Infant Outcome (DOMINO) study was a double-blind, multicenter, randomized controlled trial designed primarily to determine whether DHA supplementation during the last half of pregnancy would reduce the risk of maternal postpartum depression and improve early neurodevelopmental outcome of offspring. The study subjects were 2399 women with singleton pregnancies <21 weeks' gestation who were enrolled in 5 Australian maternity hospitals between 2005 and 2008, and 726 offspring who were followed up until 18 months of age. The women were randomly assigned to receive fish oil capsules providing 800 mg/d of DHA (n = 1197) or identical capsules without DHA (n = 1202). The level of postpartum depression was evaluated using a self-reported Edinburgh Postnatal Depression Scale (EPDS). A score >12 on the EPDS at 6 weeks or 6 months postpartum indicated a high level of depression. In the offspring, neurodevelopmental outcomes were compared at 18 months of age in the DHA group (n = 351) and the control group (n = 375) using the Cognitive and Language Composite Scales of the Bayley Scales of Infant and Toddler Development, Third Edition. More than 96% of the 2399 enrolled women completed the trial. There was no significant difference between the DHA and control groups in the percentage of women reporting high levels of depressive symptoms (EPDS score >12) at 6 weeks (DHA group: 9.6% vs. control group: 10.9%) or 6 months postpartum (9.7% vs. 11.5%); the adjusted relative risks were 0.87 (95% confidence interval [CI], 0.68–1.10; P = 0.24) and 0.83 (95% CI, 0.66–1.05; P = 0.11). Similarly, there was no significant difference between children in the DHA group and those in the control group with respect to mean cognitive scores (adjusted mean difference, 0.01; 95% CI, −1.36 to 1.37; P = 0.99) and mean language composite scores (adjusted mean difference, −1.42; 95% CI, −3.07 to 0.22; P = 0.09). These findings provide no support for routine supplementation with DHA in pregnant women, either to reduce symptoms of postpartum depression or to improve neurodevelopmental cognitive or language outcomes in early childhood.
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The link between poor maternal nutrition and an increased burden of disease in subsequent generations has been widely demonstrated in both human and animal studies. Historically, the nutritional challenges experienced by pregnant and lactating women were largely those of insufficient calories and severe micronutrient deficiencies. More recently, however, Western societies have been confronted with a new nutritional challenge; that of maternal obesity and excessive maternal intake of calories, fat, and sugar. Exposure of the developing fetus and infant to this obesogenic environment results in an increased risk of obesity and metabolic disease later in life. Furthermore, increased caloric, fat, and sugar intake can occur in conjunction with micronutrient deficiency, which may further exacerbate these programming effects. In light of the current epidemic of obesity and metabolic disease, attention has now turned to identifying nutritional interventions for breaking this intergenerational obesity cycle. In this review, we discuss the approaches that have been explored to date and highlight the need for further research.
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Objective: The peroxisome proliferator-activated receptor gamma 2 (PPARG2) gene has been intensively studied with relation to obesity and metabolic disorders. Indeed, a large number of studies assessing the association between the PPARG2 polymorphism Pro12Ala (rs1801282) and body mass index (BMI) have been published with some controversial results. In this meta-analysis, the effects of Pro12Ala polymorphism of the PPARG2 gene on BMI were investigated. Design and methods: Externally published data were collected and we included our own novel data from a study in the elderly participants (>55 years) of a Mediterranean cohort, the SUN ("Seguimiento Universidad de Navarra") Project (n = 972). A total of 75 independent studies with 49,092 subjects (39,806 with the genotype Pro12Pro and 9,286 carrier subjects of the Ala allele) were included. Results: The meta-analysis revealed a higher BMI with an overall estimation of +0.065 kg/m(2) (95%CI = 0.026-0.103, P = 0.001) for homo-/heterozygous carriers of the Ala allele of the PPARG2 gene in comparison to non-carriers. The analysis also showed that there was heterogeneity (P for heterogeneity <0.001), but funnel plots did not suggest apparent publication bias. Furthermore, the association between the Pro12Ala polymorphism of the PPARG2 gene and increased BMI was stronger in Caucasian. Thus, carriers of the Ala allele had significantly higher BMI than non-carriers in a subsample of 6,528 Caucasian male subjects (standardized mean difference = 0.090, 95%CI=0.032-0.148, P = 0.002, P for heterogeneity = 0.121). Conclusion: This updated meta-analysis showed that carriers of the Ala12 allele of the PPARG2 gene had a higher average BMI.
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To determine the nutrient intakes and status of preschool children from a representative population sample in Adelaide. Cross-sectional survey of children aged 1-5 years, using a stratified random sampling method and a doorknocking strategy, between September 2005 and July 2007. Dietary intake, assessed using a 3-day weighed-food diary; anthropometrics, biomarkers of iron, zinc and vitamin B(12), and fatty acid profiles assessed using standard methods. Median energy intakes were within dietary recommendations for the age group. Overall energy contributions from carbohydrate, protein, fat and saturated fat intakes were 50%, 17%, 33% and 16%, respectively. The rates of inadequate intake of iron, zinc, calcium and vitamin C were low, as was the prevalence of iron deficiency (5%). Only a minority of children achieved the adequate intake for n-3 long-chain polyunsaturated fatty acids (32%) and dietary fibre (18%). There was no association between socioeconomic status and intakes of macronutrients and key micronutrients. Fourteen per cent of children were obese (BMI, > 95th percentile); no association between BMI and energy intake was shown. The dietary intake of children in the study was adequate for macronutrients and the majority of micronutrients. However, low intakes of fibre and n-3 long-chain polyunsaturated fatty acids and high saturated fat intakes have raised concerns that this dietary pattern may be associated with adverse long-term health effects.