How Babies Are Affected if Mother Gains Only 6 Pounds
Lancet. Writer manuscript; bachelor in PMC 2011 Sep xviii.
Published in concluding edited form every bit:
PMCID: PMC2974327
NIHMSID: NIHMS245932
The Relationship Between Pregnancy Weight Proceeds and Birth Weight: A Within Family Comparison
David South. Ludwig
i Department of Medicine, Children'south Hospital, Boston MA 02115
Janet Currie
2 Section of Economic science, Columbia Academy, New York, NY 10027
Abstract
Background
Excessive pregnancy weight gain appears to increase birth weight and the offspring's take a chance for obesity subsequently in life. Even so, this relationship may be confounded by genetic and other shared influences.
Methods
Nosotros used Vital Statistics Natality records to examine all known births in Michigan and New Bailiwick of jersey from 1989 to 2003. Our sample included 513,501 women who had more than one singleton pregnancy and their ane,164,750 offspring. We examined how differences in weight gain that occurred during two or more pregnancies for each adult female predicted the birth weight of her offspring, using a inside-subject blueprint to minimize confounding.
Findings
We establish a remarkably consistent relationship between pregnancy weight gain and birth weight (β 7.35 [95% CI seven.10–7.59], p < 0.0001). Infants of women who gain more than 24 kg during pregnancy were 148.9 thousand (CI 141.7–156.0) heavier at nascency, compared to infants of women who gained 8–x kg. The odds ratio of giving nativity to an babe greater than 4000 one thousand was 2.26 (2.09 – 2.44) for a woman who gained more than 24 kg during pregnancy, compared to a adult female who gained 8–10 kg.
Interpretation
Maternal weight proceeds during pregnancy increases nascency weight contained of genetic factors. In view of the apparent relationship between birth weight and developed weight, obesity prevention targeted to adult female during pregnancy may exist warranted.
INTRODUCTION
The fetal origin of adult affliction, or prenatal programming, has been the subject of much study in the last 2 decades. Today, compelling bear witness exists in back up of the hypothesis, proposed by Barker et al,1 – three that undernutrition during pregnancy and depression birth weight increase the hazard for diabetes and cardiovascular disease in adulthood. Indeed, the agin effect of perinatal undernutrition on long-term health may equal or exceed that of many conventional adventure factors measured in machismo.
In view of the ascent prevalence of obesity, a variant of the original Barker hypothesis has been formulated, wherein overnutrition during pregnancy and high birth weight may cause obesity and related conditions in adulthood.four – 9 According to this concept, excessive maternal trunk weight or weight gain in pregnancy perturbs the intrauterine surroundings during fetal development, producing permanent changes in the hypothalamus, pancreatic islet cells, adipose tissue or other biological systems that regulate torso weight. Animal inquiry provides an experimental basis for this possibilty.10 , 11 Levin and Govek10 studied diet sensitive female rats on standard or high-energy diets prior to and during gestation. Progeny of the mothers in the high energy diet group gained more than weight and had higher leptin levels than did progeny of mothers in the standard diet grouping, even though offspring from both groups were fed the same diet. In humans, high birth weight predicts trunk mass alphabetize (BMI) and agin health outcomes after in life.12 – 21
Observational studies take generally constitute direct associations between maternal body weight or weight gain during pregnancy and birth weight or baby adiposity.22 – 26 Moreover, maternal adiposity tends to exist more strongly related to nascency weight27 , 28 or childhood BMI29 than paternal adiposity. All the same, these studies involving comparisons between individuals have fundamental limitations, most notably confounding due to genetic and environmental factors. For case, excessive maternal weight gain may be related to high birth weight only because a mother and her infant share obesity-related genes. Therefore, the aim of our written report is to examine the associations betwixt maternal weight gain, every bit a measure of overnutrition during pregnancy, and birth weight using land-based birth registry data that provide an opportunity to compare outcomes from several pregnancies in the same mother. This within-subject blueprint serves to reduce or eliminate potential confounding past genetic, sociodemographic and other individual characteristics.
METHODS
Study overview
Data for this study come up from individual Vital Statistics Natality records covering all births in Michigan and New Bailiwick of jersey from 1989 to 2003. These records provide data on nascency outcomes and maternal characteristics, including weight gain during pregnancy. A summary of the data files, including covariates, is bachelor from the National Center for Health Statistics: http://world wide web.cdc.gov/nchs/births.htm.
The state of Michigan provided a file which identified children born to the same mother. For New Jersey, nosotros performed this lucifer on location in the state's Department of Health offices based on mother'due south proper noun, race, birth engagement and, in some cases, address. The file was then de-identified. The report was conducted with approval from the Institutional Review Board at Columbia University.
Report population
From an initial sample size of 2,359,843 singleton births, we made the following exclusions: gestational age <37 or ≥ 41 weeks to focus on term pregnancies (n = 358,833 births); maternal diabetes (75,665 births); nascence weight < 500 grams or > 7,000 grams, extreme values that could result from data entry fault (2,225 births); missing information on pregnancy weight gain (192,819 births); and births to mothers with simply 1 child in the database, per report design (1,204,249 births). All observed pregnancies for included mothers were retained in the sample. Every bit a result of these exclusions, the concluding study sample consists of 1,164,750 singleton births to 513,501 mothers.
Data drove
All information used in this study are mandated by state law to exist routinely collected and recorded in birth records. The variables include: pregnancy weight gain, birth weight, an indicator for diabetes during pregnancy, week of gestation, maternal age, maternal education, maternal marital status, maternal race and ethnicity, maternal smoking, adequacy of prenatal care, method of delivery, child gender, child parity, and year of nativity.
Physicians were responsible for completing or verifying the nascence records. Prior evaluation suggests that birth weight collected in this fashion is highly reliable.xxx Doctor report of pregnancy weight gain may accept somewhat lower reliability. Especially for women with delayed prenatal intendance, physicians would likely base determination of pregnancy weight gain in part upon mothers' cocky written report. Consistent with this possibility, the weight gain variable shows testify of "heaping" in the raw data with rounding to 10-pound increments, accounting for the irregular weight gain frequency distribution in Figure 1 noted peculiarly around the 18 to 20 kg (twoscore pound) category. However, one validation study that compared birth certificate data to medical records for a random sample of births in North Carolina reported an exact cyclopedia on pregnancy weight gain 82.8% of the time.31 Moreover, pregnancy weight gain obtained from nascence records, similar to those we utilize in our study, has been associated with numerous infant and maternal wellness outcomes,32 providing bear witness of validity. Pre-pregnancy weight and height were non routinely collected on birth certificates. Therefore, pre-pregnancy BMI could non exist considered in this study, though absence of this information would not derange study findings for reasons considered below (see Discussion). Because the data files link births to the same female parent, it is non possible to determine whether or not siblings had the same father.
Distribution of A) Pregnancy Weight Gain and B) Birth Weight.
Statistical analysis
Our primary hypothesis is that maternal weight gain during pregnancy is positively associated with birth weight, contained of confounding factors. The sample option criteria serve to reduce or eliminate some sources of potential misreckoning (due east.grand., maternal diabetes or prematurity), but others remain. Of these remaining potential confounders, some are measured by variables in our data (smoking) whereas others are not (genetic determinants of birth weight). Our analytic strategy was to command for appreciable confounders through inclusion in the statistical models, and to command for unvarying unobservable confounders past comparing several pregnancies in the same mother. Using this arroyo, the influence of inter-individual differences in genes and other potentially relevant factors can be minimized.
Our models backslide a measure out of birth weight (continuous or dichotomous) on indicators for the following categories of maternal weight gain: 0–ii, >2–four, >iv–6, … >22–24, >24kg. Hence, the effects of weight gain are non constrained to exist linear: unless otherwise noted, all of our specifications allow this flexible human relationship betwixt the measure of nascency weight and the mensurate of maternal weight gain. The other covariates in all our models include: child gender, maternal didactics (less than high school, loftier school, some college, college or more), maternal marital condition, an indicator for maternal smoking during pregnancy, child parity (indicators for parity of one, 2, 3, 4, v or more; Northward.B., the first nativity observed in the data is non necessarily the mother's showtime born child), indicators for each twelvemonth of maternal age, and indicators for each year of birth. We included year of nativity as a covariate to control for possible secular trends in nascency weight unrelated to maternal weight gain during pregnancy. Where chiselled data on controls are missing, we too include controls for missing variables.
For models using birth weight every bit a continuous variable, we conducted two analyses. Beginning, we estimated models that include maternal stock-still effects using the XTREG control in STATA (Release eleven, STATA Corp., College Station TX). Any maternal covariate that does not change over fourth dimension will be controlled by this process.33 Thus, the effect of the mother's weight prior to first observed pregnancy is controlled, as is the event of maternal meridian (even though neither are observed in our information). Although fixed effects estimates may be less precise than ordinary least squares models, this issue is of petty business organization in a large sample size.34 We accounted for the presence of multiple values for each mother by using the CLUSTER command in STATA to correlate and adapt the errors. This procedure did not materially change our mean estimates or confidence intervals, and therefore data are presented without clustering.
Every bit an culling, conceptually simpler analytic method to control for covariates that modify between but non within individuals, we calculated the differences in weight gain and in nativity weight between adjacent pregnancies for each mother. Nosotros then regressed changes in birth weight on categories of changes in maternal weight gain (<−12, >=−12 to −10, … >ten to <=12, >12 kg), including those of the other covariates described above which can vary between births for the same mother. The sample in these models was restricted to sibling pairs in which the difference in gestational historic period is less than three weeks. In these "kickoff difference" models, changes in the year of birth and in maternal age are the aforementioned. Also, most changes in parity are equal to i. Therefore, nosotros included indicators for each year of maternal historic period at the time of the first observed nascency, and indicators for parity of the first nativity observed in the information set. The distribution of changes in weight proceeds suggests that on average women gain slightly less weight for college order pregnancies: the 10th, 50th and ninetythursday percentiles of the distribution of the difference in pregnancy weight gain between an older sibling and the adjacent younger sibling are 6.24, −.45, and −8.62 kg respectively. In other words, the majority of women gain rather similar amounts of weight over subsequent pregnancies.
We also estimated models using a dichotomous "high nascence weight" (>4000 1000) measure as the dependent variable. The independent variables were categories of maternal weight proceeds (0–2, >ii–4, >four–6, … >24 kg). We estimated a fixed effect logit (or conditional logit) using the CLOGIT procedure in STATA.35 These models command for the same variables every bit the fixed effects models discussed above. Finally, nosotros conducted subgroup analyses to examine for event modification. Based on our primary results, nosotros constrained the main issue of pregnancy weight proceeds to be linear; that is, the weight gain categories included in the previous models were excluded, and simply a single continuous weight proceeds variable (and its interaction) were included.
We chose viii to 10 kg equally the reference pregnancy weight gain category for Figures 2a and 3 considering this category is within the seven.0 – 11.5 kg range recommended for overweight women past the Institute of Medicine36 and because the hateful BMI among adult women in the US is inside the overweight range. All data are presented as ways and standard deviations (SD, for maternal cohort characteristics) or 95% confidence intervals (CI, for result information).
Associations Between Pregnancy Weight Gain and Birth Weight. Data from a) fully adapted fixed effect model, using a reference group of 8–10kg; and b) first difference model, subtracting values of variables from the first observed pregnancy from those of the second observed pregnancy for each woman. Grey bands indicated 95% confidence intervals.
Odds Ratio for High Birth Weight (> 4000 chiliad). Grey bands indicate 95% conviction intervals.
Role of the funding sources
Funding sources had no role in study design; in the collection, assay, and interpretation of data; in the writing of the report; or in the conclusion to submit the paper for publication. David Ludwig had full access to all data analyses and Janet Currie had full access to all main data in the study; both had concluding responsibility to submit for publication.
RESULTS
Table one presents descriptive feature of the 513,501 women and i,164,750 offspring included in the study. These characteristics were like to the 77,125 women and 192,819 offspring excluded from the study because of missing data on pregnancy weight gain. Hateful maternal weight gain was 13.7 kg and the mean nascency weight was 3453 g. Approximately 12% (due north = 138,304) of the offspring had birth weight greater than 4000 one thousand. On average, each female parent had 2.41 offspring in the data set, and the mean nativity social club was 2.17. African Americans comprised xix.0% (n = 220,904) of the offspring and Hispanics comprised 10.0% (n = 116,490). The boilerplate mother had thirteen.2 years of teaching and thirteen.2% (n = 154,221) of the offspring had mothers who smoked during pregnancy.
Table 1
Descriptive characteristics of the mothers and offspring included in the study. (Mean ± Standard Deviation)
| Mother Characteristics | Hateful for analysis sample* | Mean including those with missing weight gain** |
|---|---|---|
| Maternal weight proceeds (lb) | 13.7 ± v.7 | |
| Maternal age (years) | 27.7 ± 5.8 | 27.7 ± v.8 |
| Race/ethnicity (%) | ||
| African American | 19.0 | xx.ane |
| Hispanic | ten.0 | nine.9 |
| White/Other | 71.0 | 70.0 |
| Female parent'southward education (years) | 13.2 ± 2.5 | thirteen.i ± ii.5 |
| Mother smoker (%) | 13.2 | 12.8 |
| Adequacy of prenatal care (%) | 55.4 ± 49.7 | 55.8 ± 49.7 |
| Babe Characteristics | ||
| Parity | 2.17 ± 1.24 | 2.17 ± one.25 |
| Nascence weight (k) | 3453 ± 473 | 3446 ± 477 |
| Birth Weight > 4000 grams (%) | xi.nine | xi.seven |
| Offspring gender (% male) | 51.0 | 51.0 |
| Number of offspring observed | 2.41 ± 0.73 | 2.46 ± 0.79 |
| Gestation length (weeks) | 39.three ± ane.1 | 39.iii ± 1.1 |
Figure 1a shows that many women exceeded recommended limits for weight gain during a singleton pregnancy, currently established as eleven.5–16 kg for those with normal prepregnancy weight, vii–11.5 kg for those with overweight, and five–9 kg for those with obesity.36 Weight gain of over 20 kg occurred in 11.9% (n = 139,040) of pregnancies. Equally expected, pregnancy weight gain was positively associated with length of pregnancy (p < 0.0001) and inversely associated with smoking (p < 0.0001). Figure 1b shows that the birth weight distribution was approximately normal, with very few greater than 5000 g.
Figure 2a, using a stock-still effects model, demonstrates a remarkably consistent human relationship between maternal weight gain and birth weight (β 7.35 [CI seven.x–7.59], p < 0.0001). Relative to the reference category of 8–ten kg, infants of mothers who gained 20–22 kg weighed 103.8 g (CI 97.0–110.6) more on average, while infants of mothers who gained over 24 kg weighed 148.9 thou (CI 141.7–156.0) more than.
Effigy 2b plots coefficient estimates from the "starting time difference" model (see Methods). Every bit expected, women who gained the same amount of weight in both pregnancies had infants of similar hateful birth weight. Women who gained over 12 kg more in the second pregnancy had second infants who weighed 107.6 g (CI 98.2–117.0) more than than offset infants, and those who gained over 12 kg less in the 2nd pregnancy had 2nd infants who weighed 85.8 one thousand (CI 93.5–78.ane) less.
Figure 3 shows the odds ratio for birth weight above 4000 grand according to pregnancy weight proceeds from the conditional logit models. Relative to the reference category of 8–10 kg, the odds ratio of having a baby with high nativity weight was 1.72 (CI ane.59–1.86) for those who gained betwixt 20 and 22 kg, and ii.26 (CI 2.09–two.44) for adult female who gained more than than 24 kg.
To test for residuum confounding, nosotros excluded women who had always smoked, those who delivered by caesarean department, and those who had any pregnancy with gestational length < 39 wk or > 40 weeks. The results of these analyses were not materially dissimilar from those of our other models (data not shown). To examine the reliability of the independent variable, we performed an analysis limited to the 208,067 women and their 469,472 infants with acceptable prenatal care indicated on the birth certificate. (The excluded women would have relatively less data in the medical record upon which an authentic cess of pregnancy weight gain could exist based, causing the physician to rely more on maternal cocky study.) These results were very like to those of the full grouping (data not shown).
We also looked for evidence of effect modification in additional subgroup analyses that included a "main event" of weight proceeds (β), and an interaction describing the differential weight gain between the main group and the subgroup (γ). Based on our main results, nosotros constrained the main effect of pregnancy weight gain to be linear. The slope for the relationship between pregnancy weight proceeds and nascency weight was modestly smaller for African Americans (β = vii.63, 7.34–7.91; γ = −1.05, −1.threescore – −.50), and larger for male infants (β = 7.01, half dozen.69 – seven.33; γ = 0.66, 0.26 – 1.05). There was no effect of older maternal age (age >= 28, β = vii.39, 7.23 – seven.71; γ = −0.11, −0.54 – 0.34) or state (Michigan: β = 7.62, 7.23 – 8.00; γ = −.46, −0.95 – 0.04).
DISCUSSION
Weight gain during pregnancy has been associated with nascency weight and measures of adiposity early in life. This study, using a state-based registry with more than 1 1000000 singleton births, provides testify for a causal relationship independent of shared genes. We observed that every additional kg of pregnancy weight proceeds increases nascence weight by about 7.35 grand and that variation in pregnancy weight proceeds through the observed range can touch on birth weight by approximately 200 g. Because high nascence weight predicts BMI later on in life,12 , 14 , 17 – 19 , 21 these findings advise that excessive pregnancy weight gain may increase the long-term take a chance for obesity-related disease in the offspring. High nascency weight may also increment take a chance for other diseases subsequently in life, including asthma, atopy and cancer.13 , xv , 16 , twenty
With regard to potential mechanisms, the physiologic pathways that may link fetal overnutrition to higher nativity weight take been described. During pregnancy, insulin resistance develops in the female parent in order to shunt vital nutrients to the growing fetus.37 Excessive weight or weight gain during pregnancy exaggerates this normal process by farther increasing insulin resistance and possibly also past altering other maternal hormones that regulate placental food transporters.38 The resulting excessive rate of nutrient transfer stimulates fetal insulin secretion, overgrowth and increased adiposity. Indeed, maternal postprandial glycemia, even inside the normal range, is strongly associated with birth weight in the tertiary trimester.39 The mechanisms whereby in utero overnutrition and related physiological derangements affect torso weight afterward in life remain speculative,nine , eleven , 38 though the critical part of maternal hyperglycemia is highlighted by contempo enquiry.40
The principal limitations of this study involve the possibility of measurement mistake and confounding. The pregnancy weight gain variable, more so than birth weight, is subject field to recall and reporting bias that may vary by BMI, education and level of prenatal intendance, among other factors. However, the inside bailiwick design would tend to minimize systematic bias arising from such factors. Thus, some individuals may tend to underestimate, and others overestimate weight proceeds, though each would probable practise so in a similar style beyond multiple pregnancies. Any random measurement error would tend to diminish apparent consequence size,41 causing our estimates to be conservative. In improver, results of a secondary analysis excluding individuals with inadequate prenatal care – a grouping especially subject to mistake in the measurement of pregnancy weight proceeds – were very similar to the chief assay. Other evidence of reliability derives from associations in the expected direction here (with length of pregnancy and smoking) and elsewhere (with preeclampsia, cephalopelvic disproportion, failed consecration and cesarean delivery)32 involving the pregnancy weight gain variable obtained from nativity certificates. Furthermore, a validation study showed an verbal cyclopedia between pregnancy weight gain obtained from birth certificates and from medical records 82.8% of the time.31
Our within-subject field design should effectively eliminate confounding by genetic and other unvarying factors. An important study limitation is the lack of information on maternal prepregnancy BMI. We address this limitation to some degree through the use of stock-still effects models and adjustment for age and parity, controlling in function for BMI prior to the first pregnancy and weight change betwixt pregnancies. In any consequence, we argue that absence of prepregnancy BMI could not account for the primary findings for a fundamental statistical reason. In gild for a confounder to explain a positive clan between an independent variable and a dependent variable, information technology must be associated with both in the same fashion, either positive or inverse. But prepregnancy BMI is inversely associated with pregnancy weight gain,42 – 44 and positively associated with nascency weight.22 – 26 In addition, nosotros used a secondary analytic approach to examine for remainder confounding, comparing differences in subsequent pregnancies for each woman (Figure 2b). We found that weight gain had a similar outcome on birth weight regardless of which pregnancy had greater weight gain. This would not take occurred if prepregnancy BMI differed between pregnancies in a systematic style that confounded findings. Nosotros recognize that pregnancy weight proceeds might impact birth weight differently among women with high compared to low prepregnancy BMI (i.east, event modification). Withal, the similarity in findings from analyses involving subgroups expected to differ in prepregnancy BMI, such as older and younger women or blacks and white, provides evidence against this possibility (and against misreckoning). Moreover, unrecognized effect modification by prepregnancy BMI, diet quality, physical activeness level or other factors wouldn't threaten the validity of the study's chief findings.
Several other methodological issues merit consideration. Concern for reverse causation can exist largely dismissed, because increased fetal weight would make a small-scale contribution (< ten%) to the associated increment in maternal weight. All the same, we cannot dominion out the possibility that hormonal or metabolic signals from the fetus might have an additional influence on maternal weight. Some women with unrecognized diabetes may exist in our sample and contribute to the observed effect size, particularly if they developed the disease in some only not all of their pregnancies. Furthermore, diagnostic criteria and screening practices may accept change during the study catamenia. We aimed to minimize these influences past excluding individuals who reported diabetes during any pregnancy, a group that would be at highest adventure during every pregnancy. In addition, at that place was no meaning departure in a subgroup analysis involving older women, who are at substantially increased adventure for this complication.45 Finally, we recognize the lack of information near paternity as a written report limitation. However, the similar effect of maternal weight proceeds on nascence weight in first and second pregnancies, regardless of which had greater weight gain (Figure 2b), argues confronting any systematic bias.
In conclusion, our findings propose that excessive maternal weight proceeds during pregnancy increases birth weight. In view of the apparent clan between high nascency weight and adult adiposity, an advantageous time to initiate obesity prevention efforts may be during pregnancy.
Acknowledgments
The collection of data used in this project was supported under NIH R21 HD055613-01. DSL was supported in office past a career grant from the NIDDK (K24 DK082730) and a grant from the New Balance Foundation. Cecilia Machado provided assistance with inquiry. We thank Drs. Cara Ebbeling, Matthew Gillman, Steven Gortmaker, Joseph Majzoub and Eric Rimm for critical review of the manuscript.
Footnotes
Contributors: Both authors contributed to the design of the study and drafting of the manuscript. DSL formulated the study hypotheses and JC supervised data collection and analysis.
Conflict of interest statement: The authors have no conflicts of involvement with respect to this work. The authors had full access to all the data in the report and had last responsibility for the decision to submit for publication.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2974327/
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