1 Department of Medical Epidemiology, Karolinska Institutet, Stockholm, Sweden.
2 Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
3 Department of Medical Laboratory Sciences and Technology, Huddinge University Hospital, Karolinska Institutet, Stockholm, Sweden.
4 International Epidemiology Institute, Rockville, MD; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; and Vanderbilt-Ingram Comprehensive Cancer Center, Nashville, TN.
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ABSTRACT |
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birth weight; caffeine; coffee; fetal growth retardation; pregnancy
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INTRODUCTION |
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Several epidemiologic studies have found associations between caffeine intake during pregnancy and increased risks of low birth weight and/or small for gestational age births (7, 8
, 11
15
). These studies, however, relied on retrospectively collected information from questionnaires or interviews, which may result in imprecise and inadequate assessment of exposure. Among prospective studies, results are inconsistent, with some (16
20
), but not all (9
, 10
, 21
), authors reporting an association. It has also been suggested that a possible association between caffeine and fetal growth may be confounded by smoking (24
); smoking is causally related to fetal growth (25
), and smoking is also more common among caffeine consumers (17
, 18
, 22
).
In Sweden, the consumption of caffeine (coffee) intake is high (26). We conducted a population-based, prospective study of the effect of caffeine on birth weight, gestational age, and birth weight standarized for gestational age (birth weight ratio), in which caffeine consumption was self-reported during in-person interviews twice during pregnancy. We also collected detailed information on potentially confounding factors, including smoking (as measured by plasma cotinine levels) and pregnancy symptoms.
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MATERIALS AND METHODS |
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In-person interviews were conducted at 612 and 3234 completed gestational weeks. Of the 953 women who completed the first interview, six pregnancies were later terminated via induced abortions and 22 via miscarriage. Twelve women opted to withdraw from the study, six moved outside Uppsala County, and six were lost to follow-up. We also excluded mothers with multiple pregnancies (n = 14), stillbirths (n = 4), and livebirths with chromosomal abnormalities (n = 2). Eight women delivered liveborn singleton infants before the second interview. Thus, the study included 873 singleton pregnancies with liveborn infants with questionnaire data from both the first and third trimesters.
All cohort members agreed to participate in the study, which was approved by the Ethics Committee of the Medical Faculty at Uppsala University.
Data collection
In-person interviews using a structured questionnaire were conducted by three midwives. The first interview occurred between the sixth and the 12th completed weeks of gestation. Participants reported caffeine intake and pregnancy symptoms (nausea, vomiting, and fatigue) on a week-by-week basis from 4 weeks before the last menstrual period up to the most recently completed week of gestation. Blood samples for the analysis of cotinine levels were also drawn at the time of the baseline interview. In addition, data on maternal characteristics were ascertained, including age, height, prepregnancy body mass index, parity, a previous low birth weight infant (less than 2,500 g), years of education, mother's country of birth, work hours per week, changes in eating habits during pregnancy, and alcohol intake. The body mass index was defined as weight (kg)/height (m)2 and stratified into four categories (<20, 2024.9, 2529.9, and 30) (27
). At 1518 completed gestational weeks, study participants had a second routine ultrasound examination. The results of this examination, in which the biparietal diameter and femur length were measured, were used for assessing the gestational length of the pregnancy (28
). The second interview took place at 3234 gestational weeks. Assessment of caffeine intake and pregnancy symptoms was performed as in the first interview, but on a biweekly basis from the seventh gestational week up to the most recently completed week of gestation. At this interview, blood samples were again collected for the analysis of cotinine levels. After delivery and hospital discharge, data on outcomes such as birth weight, gestational age at delivery, sex, and maternal and fetal diagnoses were retrieved from the prenatal and delivery records.
In addition, information about chronic diseases, such as pregestational diabetes and essential hypertension, was collected during the first interview. Information about pregnancy complications was collected after delivery through scrutinization of prenatal and delivery records. Anemia was defined as a hemoglobin concentration under 110 g/liter at any time during pregnancy (29). For the diagnosis of gestational diabetes, all prenatal and delivery records with the diagnostic codes E1014 and O24 (International Classification of Diseases, 10th Revision) and all prenatal records with one or more instances of glucose in the urine were reviewed by an obstetrician (B. C.). Gestational diabetes was defined as a glucose tolerance test with a blood sugar level higher than 8 mmol/liter after 2 hours (30
). For the diagnosis of pregnancy-induced hypertensive diseases (gestational hypertension and preeclampsia), a similar procedure was used. An obstetrician (B. C.) scrutinized all prenatal records with a recording of blood pressure at or above 140/90 mmHg, or an elevation of blood pressure of more than 15 units of diastolic pressure, and also checked all prenatal and delivery records with International Classification of Diseases, 10th Revision, diagnoses O10 and O1315. Gestational hypertension was defined as blood pressure at or above 140/90 mmHg (in at least two readings 6 or more hours apart) and no recording of proteinuria. Preeclampsia was defined as the existence of this blood pressure level accompanied with proteinuria (two urinary protein dip sticks of at least 1+ or 300 mg of protein in a 24-hour urine collection) (31
).
Assessment of caffeine
Caffeine sources included coffee (brewed, boiled, instant, and decaffeinated), tea (loose, tea bags, and herbal), cocoa, chocolate, soft drinks, and caffeine-containing medications. Respondents were offered four cup sizes (1 dl, 1.5 dl, 2 dl, 3 dl) from which to choose. Weekly soft drink intake in centiliters was estimated by the participants. Caffeine intake was estimated using the following conversion factors: 150 ml of coffee: brewed = 115 mg, boiled = 90 mg, and instant coffee = 60 mg; 150 ml of loose tea or tea bags = 39 mg (herbal tea = 0 mg); 150 ml of soft cola drinks = 15 mg; 150 ml of cocoa = 4 mg; 1 g of a chocolate bar = 0.3 mg; and a few drugs contained 50100 mg of caffeine per tablet (32). Eighty-eight percent of the coffee drinkers used predominantly brewed coffee, 6 percent used boiled coffee, 6 percent used instant coffee, and none used predominantly decaffeinated coffee during pregnancy. To determine the total caffeine intake during pregnancy, intake was summed for each subject from the time of estimated conception (i.e., 2 weeks after the last menstrual period) until the second in-person interview. The mean daily caffeine intake during this period was then computed as the total intake divided by the (number of completed gestational weeks x 7). We used information from the first interview to reflect exposure through the first 6 completed gestational weeks and information from the second interview to reflect exposure thereafter. Of all the caffeine ingested, coffee accounted for 70 percent, tea for 26 percent, and other sources for 4 percent.
Assessment of smoking and pregnancy symptoms
Plasma samples for cotinine measurements were analyzed by gas chromatography using N-ethylnorcotinine as an internal standard (33). Smokers in the first and the third trimesters were defined as subjects who had a cotinine level above 15 ng/ml at the time of the first or second interview, respectively. Passive smokers in the first and the third trimesters were defined as subjects who had a cotinine level between 1 and 15 ng/ml at the time of the first or second interview, respectively (34
). Pregnancy symptom scores were determined for each week of pregnancy by assigning a score for nausea (0 = never; 1 = sometimes; 2 = daily but not all day; 3 = daily, all day), vomiting (0 = never; 1 = sometimes but not daily; 2 = daily), and fatigue (0 = no; 1 = yes but unchanged sleeping habits; 2 = yes and slightly changed sleeping habits; 3 = yes and pronounced change in sleeping habits). The weekly score for each symptom was summed from the estimated time of conception to the most recently completed week of gestation and then divided by the number of weeks to arrive at an average score for each symptom.
Outcome variables
Outcomes were birth weight (in grams), gestational age (in completed days of gestation according to the second trimester ultrasound scan), and birth weight ratio (defined as a deviation from the expected gestation and sex-standardized birth weight, according to Swedish fetal growth standards) (35). The birth weight ratio was calculated by standardizing the birth weight by subtracting the gestational age- and sex-specific expected weight and dividing by the standard deviation and, thereafter, applying a logarithmic transformation. Because the birth weight ratio is close to zero, it can be interpreted as the number of standard deviations above or below the expected gestational age- and sex-specific birth weight.
Statistical analysis
Univariate associations between birth weight, gestational age, and the birth weight ratio and the potential risk factors were studied by one-way analysis of variance and are presented as the means and standard errors (tables 1 and 2). In multivariate analyses, the models included the average caffeine intake during pregnancy, the cotinine levels in the third trimester, and all the variables presented in table 2. Because the data are unbalanced with respect to the covariates and the applied models are additive, the absolute level after adjustment is arbitrary. The adjusted means for the caffeine intake categories were therefore normalized to have the same mean in the lowest intake category in both the univariate and the multivariate analyses, facilitating the assessment of potential confounding. Furthermore, the lower two-sided 95 percent confidence limits of the pairwise differences between the lowest intake category (099 mg of caffeine per day) and the remaining categories (100299 mg, 300499 mg, and 500 mg of caffeine per day) are presented, indicating the largest detrimental effect of mean caffeine intake that cannot be excluded in our data set. Interaction terms between caffeine intake and both smoking and pregnancy symptoms were introduced into the multivariate models to assess the potential effect modification. In these interaction analyses, caffeine intake was used as both a categorical and a continuous variable, the latter in order to improve the statistical power. The p value for testing the homogeneity of the means for all categorized variables is provided for both crude and multivariate models and was assessed by F tests in the analysis of variance models. Statistical analyses were performed using PROC GLM SAS software (SAS Institute, Inc., Cary, North Carolina). A post hoc power analysis showed that the study had 80 percent statistical power (at a 5 percent two-sided significance level) to detect the following differences between intake groups 099 mg per day and >300 mg per day: 169 g in birth weight, 3.6 days in gestational age, and 3.6 percent difference in birth weight ratio.
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RESULTS |
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In univariate analyses, maternal height, prepregnancy body mass index, mother's country of birth, parity, and a previous low birth weight infant all significantly affected birth weight and the birth weight ratio and generally also gestational age (table 2). Neither the maternal age nor the educational level influenced birth weight, gestational age, or the birth weight ratio. Compared with women who worked 35 hours or more per week, women who worked less than 35 hours per week had infants with a lower mean gestational age but a higher mean birth weight ratio. Both nausea and fatigue during pregnancy were associated with birth weight and the birth weight ratio. Pregestational and gestational diabetes both appeared to be positively associated with the birth weight ratio and negatively associated with gestational age. Women with essential hypertension and preeclampsia had shorter gestations than did women without these disorders. No significant effects on birth weight or gestational age were seen for changes in dietary preferences or for the presence of anemia in pregnancy (data not shown).
Table 3 shows the relations between caffeine intake and the birth outcomes in multivariate analyses. Because we observed no differences in birth outcomes in relation to the mean daily caffeine consumption in separate trimesters, we used the mean daily caffeine consumption during pregnancy (i.e., from conception to 3234 weeks of gestation) as the exposure variable in the multivariate models. Caffeine exposure was not associated with any of the outcome variables (table 3). Compared with the results from the univariate analyses, there were no substantial changes of the caffeine-related estimates, suggesting that none of the adjustment variables acted as strong confounderms. To illustrate potential detrimental effects due to caffeine intake that cannot be excluded because of lack of statistical power, lower 95 percent confidence limits for the differences in the means of the outcome variables between the lowest intake category and the higher categories are presented. For instance, we cannot exclude the possibility that consuming 100299 mg of caffeine per day will, compared with maternal intake of 099 mg of caffeine per day, reduce birth weight up to 70 g. The estimated mean values of birth weight, gestational age, and the birth weight ratio for the categories of the other variables included in the analyses were essentially the same in the multivariate as in the univariate analyses and are therefore not presented.
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DISCUSSION |
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Even in prospective studies that have shown an effect of caffeine on birth weight, the evidence is inconsistent with respect to dose and whether the association is modified or confounded by smoking. Martin and Bracken (16) found daily caffeine consumption over 150 mg to be associated with low birth weight at term. Peacock et al. (17
) found a reduced birth weight for consumers of 2,800 mg of caffeine per week among smokers, and Olsen et al. (18
) found an increased odds ratio for low birth weight among nonsmoking nulliparas who consumed more than 8 cups (1.89 liters) of coffee per day. Cook et al. (19
) found that, although blood caffeine concentrations during pregnancy were not related to fetal growth, self-reported caffeine intake was, in smoking mothers, inversely associated with birth weight. The latter finding is consistent with the hypothesis that the observed associations between caffeine and birth weight may be due to residual confounding by smoking. Morrison (24
) suggested that, although smoking is perceived to be socially undesirable, caffeine consumption is not, and the true quantity smoked may be better reflected by the admitted level of caffeine consumption. Previously reported associations between caffeine intake and fetal growth may also have been confounded by unmeasured factors, such as pregnancy-related symptoms (37
).
In the present investigation, measurements of plasma cotinine were used to indicate maternal smoking exposure, and the influence of a number of other possible confounders has been taken into account. Although we tried to optimize data collection on caffeine exposure by obtaining two interviews, the quality of measuring caffeine exposure may be a concern. First, inexact measurements may have resulted from obtaining the data retrospectively. However, measurement of exposure was collected before delivery, and the misclassification should thus be nondifferential with regard to birth weight and gestational age. Second, we lack information about caffeine exposure after 3234 weeks of gestation. Growth of the normal fetus increases with gestational age (35), and the influence of growth-constraining factors may be more easily detected in late pregnancy. As caffeine exposure was essentially unchanged in the second trimester compared with the first part of the third trimester, we find it unlikely that caffeine exposure was substantially changed during the last weeks of pregnancy.
Birth weights of infants in this study were higher than birth weights in general in Sweden. The study cohort was restricted to a county dominated by a university city, and for practical purposes we recruited only women fluent in Swedish. Smoking during pregnancy is also less common in Uppsala County compared with Sweden in general (38). Thus, the women included in this study represent a relatively homogeneous population, with a somewhat better health status than that of the general population. In this population, the possibility of detecting effects of environmental factors on birth weight is optimal, as a large proportion of births can be assumed to attain their full birth weight potential.
Although our study is limited in size, it has sufficient statistical power to detect relatively small differences in birth weight between infants of moderate versus none or low caffeine consumers, i.e., the vast majority of women. Furthermore, the validity of our data is supported by the significant associations with other well-established risk factors for low birth weight and small for gestational age births. We therefore conclude that caffeine intake during pregnancy does not impose a major public health issue with regard to fetal growth.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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