Hum. Reprod. Advance Access originally published online on October 12, 2007
Human Reproduction 2008 23(1):168-177; doi:10.1093/humrep/dem316
Parental characteristics as predictors of birthweight
1 Obstetrics and Gynecology Epidemiology Center, Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Avenue, Boston, MA 02115, USA 2 Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA 3 Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115, USA 4 Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA 5 Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA 6 M. D. Anderson Cancer Center, The University of Texas, Houston, TX 77030, USA
8 Correspondence address. Obstetrics and Gynecology Epidemiology Center, Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Avenue, Boston, MA 02115, USA. Tel: +1-(617)-953-6459; Fax: +1-(617)-732-4899; E-mail: n2fei{at}channing.harvard.edu
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Abstract |
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BACKGROUND: Previous studies provided conflicting results on the relevance of parental characteristics for offspring's size at birth. The objective of this study was to investigate parental predictors of birthweight.
METHODS: In this cross-sectional study, 34 063 women in the Nurses' Mother's Cohort were queried about parental characteristics during the pregnancy with and birthweight of their nurse daughter.
RESULTS: The predictive linear regression model of birthweight included 13 factors and the majority of the predictive power came from parental anthropometric factors. In the adjusted analysis, daily consumption of each additional glass of milk was associated with an increase of 
6 g in birthweight (P for trend = 0.01) and daily consumption of each additional cup of coffee was associated with a decrease of 10 g in birthweight (P for trend < 0.0001). Drinking 1–2, 3–4 and 5+ cups of coffee daily was associated with a 28% [95% confidence interval (CI) 0.12, 0.47], 30% (95% CI 0.10, 0.55) and 63% (95% CI 0.25, 1.12) increase, respectively, in the odds of intrauterine growth restriction when compared with non-drinkers.
CONCLUSIONS: The present study confirmed several previously reported determinants of birthweight. Maternal dietary intake of milk and coffee during pregnancy may influence fetal growth.
Key words: epidemiology/pregnancy/embryo development/birthweight/parental characteristics
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Introduction |
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Low birthweight (LBW) is a major determinant of fetal mortality and morbidity (U.S. Department of Health and Human Services, 2003
). In the past 20 years, birthweight, as a proxy of in utero growth and relevant prenatal exposures, has been related to several chronic diseases, including breast cancer (Michels and Xue, 2006), cardiovascular diseases (Rich-Edwards et al., 1997; Barker, 2004), diabetes (Rich-Edwards et al., 1999) and hypertension (Curhan et al., 1996), although the pathology underlying this relation is unclear. Therefore, efforts to identify the determinants of birthweight could contribute not only to neonatal survival and health but also to an understanding of the effect of prenatal exposures on health conditions later in life.
Health conditions and behaviors of parents before and during pregnancy may directly influence the fetus through genetic inheritance, hormonal alteration, supply of nutrients and oxygen and other factors. Previous studies have found parental factors such as gestational age (Morrison et al., 1991; Parker et al., 1994), parity (Amin et al., 1993; Arif et al., 1998), maternal age (Amin et al., 1993; Aldous and Edmonson, 1993; Abel et al., 2002), maternal smoking (Ash et al., 1989; Abell et al., 1991), maternal pre-pregnancy weight (Hibbert et al., 1999; Grandi, 2003) and weight gain during pregnancy (Ash et al., 1989; Amine and al-Awadi, 1991) to be consistently related to birthweight. However, the results for other important parental characteristics, such as maternal diet and life style, paternal health conditions and parental occupation and socioeconomic status, remain conflicting. Maternal diet during pregnancy has been widely studied in relation to fetal growth; however, birthweight has been related to only a few food items, including milk (Elwood et al., 1981; Godfrey et al., 1996; Rao et al., 2001; Ludvigsson and Ludvigsson, 2004; Mitchell et al., 2004; Moore et al., 2004), coffee (Jadsri and Jadsri, 1995; Santos et al., 1998; Eskenazi et al., 1999; Bracken et al., 2003) and seafood (Olsen et al., 1993, 2000; Olsen and Secher, 2002), with inconsistent results.
The controversial results regarding the relation of parental factors to birthweight may be due in part to the tight inter-relationship among parental characteristics, which previous studies usually did not adjust for in a statistically valid and efficient way. Our objective was to use data from the Nurses' Mother's Cohort to build a predictive model of birthweight using a wide variety of parental characteristics, emphasizing factors that are still controversial. On the basis of the established predictive model, we further analyzed the association of maternal dietary factors with birthweight and intrauterine growth restriction (IUGR).
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Study population
The study population comprises participants of the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII), whose mothers were enrolled in the Nurses' Mothers' Cohort. In March 2001, nurses who were alive and free of cancer and whose mothers were alive were sent letters inviting their mothers to participate in the Nurses' Mothers' Cohort. If the nurse agreed and her mother was able to participate, the mother was sent a questionnaire and a prepaid return envelope. A total of 52 155 Mothers' Questionnaires were sent in 2001 and 2002. Overall, 39 904 (76.5%) completed questionnaires were returned to us. To improve the homogeneity of the study population, we only included the 34 063 white women whose mother reported daughter's birthweight, had lived with her spouse, had received prenatal care, had a singleton pregnancy and had not been diagnosed with pre-eclampsia or eclampsia during her pregnancy with her nurse daughter. Among them, 3239 were participants of NHS and 30 824 were participants of NHSII.
Assessment of birthweight
On the mailed questionnaire to mothers, we asked for information on birthweight of the nurse daughter in pounds and ounces and the source of birthweight information (memory, birth certificate, baby book or family records, or nurse daughter). Birthweight information was available from 95% (n = 37 802) of the Nurses' Mothers' Cohort. We converted birthweight to grams in the analysis. The mean value of reported birthweight in the study population (n = 34 063) and in the entire cohort (n = 37 802) were, respectively, 3307 and 3291 g, which are both slightly lower than the mean birthweight of 3450–3500 g among white women in the US reported in recent studies (Paine et al., 1999; Lagiou et al., 2003). Data on birthweight reported by mothers were validated in a sample of NHSII participants by comparing this information with that from birth certificates and were found to be accurate (r = 0.85) (Troy et al., 1996). We also compared birthweight reported by mothers with that reported by nurse daughters in NHS and NHSII and found the data from the two sources were highly correlated (r = 0.80).
Assessment of parental characteristics
Participants were asked a wide variety of questions related to early life exposures of nurse daughters, including maternal and paternal demographic characteristics, maternal health condition and behavior (including consumption of common energy- and nutrient-dense foods) during pregnancy and early childhood, maternal reproductive history, parental history of specific diseases and family history of specific diseases. For the purpose of this study, we were interested primarily in parental factors potentially related to birthweight, including parental anthropometric characteristics, maternal or fetal pregnancy-related conditions, parental behavior and maternal diet during pregnancy with the nurse daughter, parental demographic and socioeconomic characteristics and maternal reproductive factors.
Statistical analysis
The predictive model was selected using multivariate linear regression. Birthweight was analyzed as a continuous variable in grams. Nominal covariates such as parental occupation were analyzed as indicator variable. Continuous covariates such as parental age and body mass index (BMI) were analyzed as continuous variables unless a non-linear trend was suggested in the univariate analysis, in which case a square or cubic term was considered. Missing data were coded as missing indicators for all covariates used in the model selection procedures. This permitted us to maintain the same number of individuals in all analyses, which is essential for comparability of models. The linearity of ordinal covariates was checked using a likelihood ratio test by comparing the model with indicator variables versus a model with an ordinal variable.
Model selection started from a full model with all candidate covariates, including covariates with a P-value <0.10 in univariate linear regression and birthweight predictors suggested by previous studies (e.g. parental age, parental height, BMI before pregnancy, maternal weight gain during pregnancy, maternal birthweight, gestational age, birth order, maternal smoking, parental home ownership, pregnancy-related diseases and maternal reproductive factors). Each of the insignificant covariates with P-value >0.05 was tested by being removed from the model one at a time from the highest to the lowest P-value, and potential collinearity and confounding were checked on the basis of change in the magnitude of the effect estimate of other covariates. If the change in any of the other covariates was >10%, the tested variable was considered as a confounder and retained in the model; otherwise, the covariate was removed to avoid potential collinearity. The predictive power of different categories of parental characteristics was separately calculated as percentage of the change in R2 with each category of covariates added to the model until the final predictive model was reached.
All significant maternal dietary factors (P-value 
0.05) in the final model were analyzed separately in relation to birthweight and risk of IUGR, defined as a birthweight lower than the 10th percentile or the fifth percentile conditional on gestational age according to the Baltimore 1966 growth reference (Gruenwald, 1966). The association between dietary factors and birthweight was analyzed by a multivariate linear regression model adjusting for all covariates in the final predictive model. Dietary factors in relation to risk of IUGR were assessed with the multivariate logistic regression model, adjusting for all covariates in the final predictive model except gestational age. Dietary factors were analyzed as categorical values using indicator variables, and a separate trend test was performed using the midpoint of each category. We evaluated whether the association of maternal dietary factors with birthweight and IUGR was modified by the predicted probability of LBW (<2500 g) and IUGR (10th percentile of birthweight for gestational age), which was derived from multivariate logistic regression models, adjusting for all covariates in the final predictive model except the dietary factor of interest (plus gestational age for IUGR). Potential effect modification by premature birth (<37 weeks), ever cigarette smoking during pregnancy and predicted probability of LBW and IUGR (>median versus median) was analyzed by stratified analysis and a Wald test on the cross-products between each potential effect modifier and the categorical variable of dietary factors.
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Results |
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Although the distribution of several selected parental characteristics did not vary substantially across categories of birthweight, women with a lower birthweight were more likely to be born to parents who had a lower BMI and smoked during pregnancy, to mothers who were shorter and nulliparous and to mothers who had a lower birthweight (Table I).
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The final predictive multivariate linear regression model indicated that daughters' birthweight was positively associated with birth order, gestational age, paternal BMI and maternal birthweight, height, BMI, weight gain, diabetes and milk consumption during pregnancy; and was negatively associated with maternal smoking and coffee consumption during pregnancy, maternal infertility and maternal occupation as white collar worker, craftworker or machine operator (Table II). The full model predicted
23.3% of the variance in birthweight, and the major contribution to the predictive power came from parental anthropometric factors (11.6%) and maternal or fetal pregnancy-related conditions (8.7%) (Table III).
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Maternal consumption of milk and coffee during pregnancy were the only two significant dietary factors in the final model. Consumption of 2–3 and 4+ glasses of milk per day by the mother during pregnancy was associated with a 16 (P = 0.007) and a 19 g (P = 0.13) increase, respectively, in birthweight when compared with consumption of
4 glasses per week (P for trend = 0.01) (Table IV). Consumption of 1–2, 3–4 and 5+ cups of coffee per day by the mother during pregnancy was associated with a 15 (P = 0.009), 34 (P < 0.0001) and 54 g (P < 0.001) decrease in birthweight when compared with no consumption of coffee (P for trend <0.0001) (Table V). The dose–response relation between birthweight and consumption of milk and coffee appeared to be more consistent among term deliveries than among preterm deliveries (Tables IV and V); the effect modification by premature birth was significant for coffee consumption (P for interaction = 0.03) but not for milk consumption (P for interaction = 0.12). The positive association between milk consumption and birthweight was stronger for non-smokers (P for trend = 0.002) than for smokers (P for trend = 0.78), although the interaction with smoking status was not significant (P for interaction = 0.08) (Table VI). Conversely, the dose–response association of birthweight with coffee was stronger among smokers (P for trend < 0.0001) than among non-smokers (P for trend = 0.01) and the interaction with smoking status was statistically significant (P for interaction = 0.001) (Table VII).
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IUGR defined as below the 10th percentile of birthweight for gestational age was significantly related to maternal consumption of coffee [odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.05, 1.13 for daily consumption of each cup of coffee] but not to that of milk (OR = 0.99, 95% CI 0.94, 1.04 for daily consumption of each glass of milk) (Tables VIII and IX). Drinking 1–2, 3–4 and 5+ cups of coffee daily during pregnancy was associated with a 28%, 30% and 63% increase, respectively, in the odds of IUGR when compared with drinking no coffee. The association between IUGR and maternal coffee consumption was slightly stronger for smokers (OR = 1.11, 95% CI 1.04, 1.19 for daily consumption of each cup of coffee) than non-smokers (OR = 1.07, 95% CI 0.99, 1.15 for daily consumption of each cup of coffee) but effect modification by smoking status was not statistically significant (P for interaction = 0.12). The association between IUGR and coffee consumption was not modified by premature birth (P for interaction = 0.79). The significant association remained after redefining IUGR as below fifth percentile of birthweight for gestational age (P for trend < 0.001).
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The association between coffee consumption and LBW was remarkably stronger among women with predicted probability of LBW by all the other covariates greater than the median (2.9%) (β = –15.4 g/cup and P for trend < 0.0001) than among women with a lower predicted probability (β = –2.9 g/cup and P for trend = 0.26). Similarly, among women for whom a probability of IUGR was predicted by all the other covariates higher than the median (4.4%), coffee consumption was more consistently associated with the risk of IUGR (P for trend < 0.0001) than among women with a lower probability (P for trend = 0.24). Among women for whom the predicted risk of IUGR was higher than the median, drinking 5+ cups of coffee was associated with 73% increase in the odds of IUGR when compared with drinking no coffee, as compared to a 26% increase among women with a lower probability predicted by other covariates.
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Discussion |
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The present study confirms several previously reported determinants of birthweight, including gestational age (Morrison et al., 1991
; Parker et al., 1994), maternal birthweight (Magnus et al., 1997, 2001; Conley and Bennett, 2000), maternal height (Amine and al-Awadi, 1991; Neel and Alvarez, 1991; Amin et al., 1993; Lawoyin, 1997; Blickstein et al., 2003; Martin et al., 2004), maternal pre-pregnancy BMI (Lawoyin, 1997; Voigt et al., 2004), maternal weight gain during pregnancy (Ash et al., 1989; Amine and al-Awadi, 1991; Pezzarossa et al., 1996; Grandi, 2003), maternal diabetes in pregnancy (Pezzarossa et al., 1996), maternal smoking during pregnancy (Ash et al., 1989; Abell et al., 1991; Parker et al., 1994; England et al., 2001), birth order (Morrison et al., 1991; Amin et al., 1993; Parker et al., 1994; Arif et al., 1998), paternal BMI (Klebanoff et al., 1998; To et al., 1998) and maternal occupation requiring heavy labor (Dindar, 1991; Ceron-Mireles et al., 1997; Lekea-Karanika et al., 1999). The decreased birthweight associated with maternal history of infertility is a novel finding. In consistence with our finding, a recent study has indicated an association of female-factor infertility with an increased risk of LBW but not with male-factor infertility, for singletons and twins born after assisted reproductive technology (Wang et al., 2005). Diseases associated with female infertility, such as tubal diseases, endometriosis and hormonal disorders, may be involved in defective uteroplacental interaction and retarded fetal growth (Wang et al., 1994). The observed association between maternal occupation as white-collar workers and a slightly lower birthweight is unexpected because overall higher maternal socioeconomic status has been related to a higher birthweight (Neel and Alvarez, 1991; Arif et al., 1998). Residual confounding by age at delivery and parity is possible, since women with white-collar jobs are more likely to delay their first birth, and birthweight has been positively associated with parity (Morrison et al., 1991; Amin et al., 1993; Parker et al., 1994; Arif et al., 1998) and negatively associated with maternal age (Aldous and Edmonson, 1993; Abel et al., 2002).
The final predictive model explained 23.3% of the variation in birthweight, and parental anthropometric characteristics were major contributors (11.6%). A recent study also indicated that the difference in birthweight of infants born to white American women and Chinese women can be fully explained by the difference in height, pre-pregnancy BMI and weight gain during pregnancy of the two populations (Lagiou et al., 2003). The association between parental anthropometry and birthweight suggests that part of the variability in birthweight might be due to inheritance, since height has been found to be highly heritable (Silventoinen et al., 2003). Consistent evidence has also indicated that infant's birthweight is positively associated with birthweight of both the mother and the father (Magnus et al., 1997; Conley and Bennett, 2000; Magnus et al., 2001). Although genetic inheritance likely plays a role in the variability of birthweight, previous studies suggest that genes might not explain a large part of the variability. A genetic analysis of parent–offspring covariance in birthweight suggested that, whereas fetal genes explained 60% of the variance in birthweight, the maternal genes had little detectable effect (Magnus, 1984).
Maternal consumption of milk and coffee are the only two food items found to be related to birthweight in our study. To our knowledge, in six studies, including three prospective observational studies (Godfrey et al., 1996; Rao et al., 2001; Moore et al., 2004), two retrospective observational studies (Ludvigsson and Ludvigsson, 2004; Mitchell et al., 2004) and one randomized intervention study (Elwood et al., 1981), maternal dairy consumption has been evaluated in relation to birthweight. In four of these studies, birthweight was found to be positively associated with maternal consumption of milk (Elwood et al., 1981; Rao et al., 2001; Ludvigsson and Ludvigsson, 2004) or dairy food (Moore et al., 2004) during pregnancy, and the association was statistically significant in three studies (Rao et al., 2001; Ludvgisson and Ludvigsson, 2004; Moore et al., 2004). Ludvigsson and Ludvigsson (2004) also found a significant association of low milk intake during pregnancy with an increased risk of IUGR. The mechanism of the relation of milk consumption to birthweight is largely unknown, but hormones and micronutrients, rather than the macronutrients and energy in milk seem to be more likely involved. In previous studies, above a minimal nutritional requirement for fetal growth, calorie and protein intake did not contribute much to the variability in birthweight (Godfrey et al., 1996; Mathews et al., 1999). In addition, the association of milk consumption with birthweight remained significant in some studies after additional adjustment for intake of energy and relevant macronutrients (Rao et al., 2001) or consumption of vegetables, eggs, fish, iron supplement and vitamin supplement (Ludvgisson and Ludvigsson, 2004).
Emerging evidence suggests that insulin-like growth factor-1 (IGF-I) content of milk or the effect of milk consumption on endogenous IGF-I levels may be a promising candidate. Although total protein and caloric intake have both been positively related to circulating IGF-I levels in animals (Thissen et al., 1994; Ketelslegers et al., 1995), epidemiologic studies have suggested a direct effect of milk consumption on circulating IGF-I level independent of protein and energy content (Holmes et al., 2002; Gunnell et al., 2003). The null association of birthweight with dairy food other than milk in our study suggests that the biological activity of milk protein including some peptide hormones, such as IGF-I, may be affected by the fermentation process involved in the production of other dairy foods, such as cheese and yogurt (Heller, 2001).
A reduced birthweight or an increased risk of LBW among offspring of women with a high consumption of coffee or caffeine has been reported by some studies (Cook et al., 1996; Rondo et al., 1996; Eskenazi et al., 1999; Bracken et al., 2003) but not others (Fortier et al., 1993; Jadsri and Jadsri, 1995; Santos et al., 1998; Bech et al., 2007). A positive association between high caffeine intake and increased risk of IUGR has also been reported by a number of studies (Fortier et al., 1993; Rondo et al., 1996, 1997; Vik et al., 2003) but not others (Santos et al., 1998; Eskenazi et al. 1999). It is generally accepted that a daily caffeine intake of 
300 mg, equivalent to approximately three cups of coffee, during pregnancy is associated with a small reduction in birthweight (Christian and Brent, 2001; Higdon and Frei, 2006), as opposed to our results that daily coffee consumption of even 1–2 cups of coffee is associated with a lower birthweight and increased risk of IUGR. Caffeine has been found to pass though placental barriers and may influence fetal growth by reducing uteroplacental, fetoplacental or villous blood flow (Bracken et al., 2003).
Inadequate adjustment for cigarette smoking, a strong predictor of birthweight, may leave the association between coffee consumption and birthweight confounded. Cook et al. (1996), however, found that the relation of caffeine intake to birthweight remained significant after adjusting for blood cotinine concentration, a presumably finer measurement of smoking. As in the current study, several other studies also reported a stronger association among smokers (Olsen et al., 1991; Fortier et al., 1993; Cook et al., 1996). Cook et al. (1996) found that, at each intake level of caffeine, blood levels of caffeine were lower in smokers than non-smokers and that, with increasing cotinine levels in blood, when caffeine intake level increased, blood levels of caffeine decreased, suggesting that smoking may increase the metabolism of caffeine (Parsons and Neims, 1978; Cook et al., 1996) and enhance the level of some metabolite that may impair uteroplacental or fetoplacental function. Smoking has been found to induce CYP1A2 (Woolridge et al., 2004), which is the main enzyme involved in the metabolism of caffeine (Infante-Rivard, 2007). Higher risk of reduced fetal growth has been associated with maternal serum levels of paraxanthin, the primary metabolite of caffeine, particularly among women who smoked (Klebanoff et al., 2002). Grosso et al. (2006) also observed that maternal serum caffeine levels were associated with a decreased risk of IUGR whereas paraxanthin levels were associated with an increased risk of IUGR in the multivariate model including both caffeine and paraxathin levels. These findings suggest that either metabolites of caffeine, such as paraxanthin or the activity of CYP1A2, rather than caffeine itself may be related to impaired fetal growth.
We used model selection depending on changes in the effect estimate of other insignificant covariates in the model, which has been conventionally accepted as a better approach to detect confounding and collinearity (Kleinbaum et al., 1982; Greenland, 1989) than backward or forward selection. We later explored milk and coffee consumption in relation to birthweight, adjusting for all other covariates in the predictive model. Compared with multivariate analysis including all a priori confounders and risk factors, our approach has more statistical power to control for confounding.
One limitation of our study is that the data on all parental characteristics and birthweight were reported by mothers, who were 60–80 years old at enrollment and whose recall extends 40–60 years into the past. Our results are consistent with those in previously published studies regarding most of the established maternal and paternal predictors of birthweight, suggesting data collected from personal recall over decades may be adequate for many perinatal factors. The potential link between maternal consumption of milk and coffee during pregnancy and birthweight is not well known in public, and therefore any misclassification on milk and coffee consumption is likely to be non-differential and thus effects might be underestimated. Compared with studies that used concurrent data, in our study, the magnitude of effect estimate on birthweight may be lower for both milk (Ludvigsson and Ludvigsson, 2004) and coffee (Bracken et al., 2003) consumption. Non-differential misclassification of dietary factors during pregnancy recalled years later may also have contributed to the lack of association between birthweight and some of the dietary factors other than milk and coffee, including other dairy foods.
The study population comprises participants of NHS and NHSII, whose mothers were alive and willing to participate in the Nurses' Mothers Cohort in 2001. Compared with other study populations, such as a birth cohort, women from our study population may be in better overall health condition because they are health professionals or due to the fact that their mothers were healthy enough to participate in our study at advanced age. Nonetheless, our study population should not differ systematically in the distribution of parental characteristics from the general population.
In our study, we found that higher maternal milk consumption and lower coffee consumption were association with increased birthweight, but the magnitude of the increase was modest. Nonetheless, if IGF-I indeed mediates the association between high maternal milk consumption and increased birthweight, the implication of our study results based on women who gave birth 40–50 years earlier would be greater for women who gave birth after 1993, when the commercial sale of milk from cows injected with recombinant bovine growth hormone (rBGH) was approved in the USA (Epstein, 1996), since IGF-I levels in cow milk could be further elevated by two to three times in cows treated with rBGH (Juskevich and Guyer, 1990; Daxenberger et al., 1998). Reducing coffee consumption to less than three cups per day has been deemed as safe in previous publications. The present study found a modest yet significant association of drinking 1–2 cups of coffee per day during pregnancy with decreased birthweight and increased risk of IUGR. Furthermore, this association was suggested to be stronger for infants for whom the probability of LBW and IUGR was higher as predicted by other parental factors. To give more comprehensive recommendations to pregnant women regarding coffee consumption, further studies are warranted to complete the current understanding of the influence of caffeine intake on fetal growth and the underlying mechanisms.
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The Nurses' Health Study is supported by grant CA87969 from the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services. The Nurses' Health Study II is supported by Public Health Service grant CA50385 from the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services. The Nurses' Mothers' Cohort Study was funded by Research Contract N02-RC-17027 from the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services.
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7 Present address: 651 Huntington Avenue, Building II, Room 311, Boston, MA 02115, USA
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Submitted on May 20, 2007; resubmitted on August 6, 2007; accepted on August 28, 2007.
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