Effect of Continuing or Stopping Smoking during Pregnancy on Infant Birth Weight, Crown-Heel Length, Head Circumference, Ponderal Index, and Brain:Body Weight Ratio

Anna A. Lindley1, Stan Becker2, Ronald H. Gray2 and Allen A. Herman3

1 Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH.
2 Department of Population and Family Health Sciences, School of Hygiene and Public Health, The Johns Hopkins University, Baltimore, MD.
3 National School of Public Health at Medunsa, Medunsa, South Africa.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The objective of this study was to determine whether stopping smoking between the first prenatal care visit and the 32nd week of pregnancy affects the smoking-associated changes in five infant anthropometric indices. The study population consisted of 15,185 births in the Swedish Medical Birth Register from 1991 and 1992. The associations between birth weight, crown-heel length, head circumference, ponderal index, brain:body weight ratio, maternal smoking status at the first prenatal care visit and at 32 weeks' gestation, and other maternal and infant characteristics were assessed using multivariate linear regression. The infants of 946 women who stopped smoking before week 32 of pregnancy were statistically indistinguishable from the 9,802 infants of nondaily smokers in terms of birth weight, head circumference, and brain:body weight ratio, but they retained a significant deficit in crown-heel length of 0.23 cm (standard error, 0.08) and a significant elevation in ponderal index of 0.027 (standard error, 0.009). In this study, stopping smoking between the first prenatal care visit and week 32 of pregnancy prevented smoking-associated deficits in infant birth weight, head circumference, and brain:body weight ratio, but did not completely prevent deficits in crown-heel length in comparison with nonsmokers' infants of the same age, and did not prevent elevation of ponderal index in comparison with nonsmokers' infants of the same weight and age. Am J Epidemiol 2000;152:219–25.

anthropometry; birth weight; body constitution; body weights and measures; pregnancy outcome; smoking

Abbreviations: BBR, brain:body weight ratio; CI, confidence interval.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Smoking during pregnancy is known to have a marked effect on fetal growth, increasing the risk of having a small-for-gestational-age infant (1GoGoGoGo–5Go), reducing infant birth weight (1Go, 6GoGoGoGo–10Go), crown-heel length (6Go, 8GoGoGoGo–12Go), and head circumference (6Go, 8GoGoGo–11Go), and affecting indicators of infant body proportionality such as ponderal index (13Go) (defined as 100 x [birth weight (g)/crown-heel length (cm)3]) and brain:body weight ratio (BBR) (14Go) (defined as 100 x the ratio of estimated brain weight to birth weight). Cessation of smoking during pregnancy has been found to mitigate the smoking-associated deficits in birth weight (15GoGoGoGoGo–20Go) and crown-heel length (19Go, 20Go) in hospital-based cohorts. However, the different physical dimensions of the infant have their peak periods of growth during different periods of pregnancy (21Go). Thus, smoking during the early part of gestation may still affect infant dimensions and body proportions even if the mother quits smoking midway through her pregnancy. This study examined whether stopping smoking in early to midpregnancy is sufficient to eliminate the smoking-associated deficits in five anthropometric indices: birth weight, crown-heel length, head circumference, ponderal index, and BBR.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
For this study, we used a subpopulation of Swedish births from 1991 and 1992 for which data on smoking status were available for both the first prenatal care visit and the 32nd week visit. We compared the anthropometric measurements of infants born to nonsmokers with those of infants born to women who reported smoking at both the first prenatal care visit and the 32nd week visit and infants born to women who reported smoking at the first prenatal care visit but having ceased smoking at the 32nd week visit. The data used in this study were obtained from the Swedish Medical Birth Register for 1991 and 1992. The Swedish Medical Birth Register is maintained by Sweden's National Board of Health and Welfare, and it contains data on more than 99 percent of all births in Sweden (22Go). Prenatal care in Sweden is standardized, and more than 95 percent of pregnant women receive antenatal care before the 15th week of gestation (23Go). Ninety percent of pregnant women have at least nine visits for antenatal care (24Go).

At the first prenatal care visit, each woman is interviewed, and information on smoking habits is recorded using check-boxes categorizing smoking into nondaily smoking (i.e., 0 or <1 cigarette per day), moderate smoking (1–9 cigarettes per day), and heavy smoking (>=10 cigarettes per day). In the 1991–1992 cohort used in this study, similar smoking data were collected at the 32-week visit for approximately 15 percent of the women. This was not a random sample but rather a convenience sample of women whom health care providers chose to question about smoking at the 32-week visit. Data on maternal age, height, parity, and prepregnancy weight are also collected at the first prenatal care visit. At birth, data from infant anthropometric measurements are collected by standardized methods. Beginning in 1990, the collection of head circumference data was standardized to the pediatric method of measurement, that is, across the forehead and around the largest part of the crown. Table 1 describes how the subjects included in our analysis differed from the rest of the population in terms of the variables used in this study. Unfortunately, information on socioeconomic status and maternal use of alcohol, drugs, and coffee was not available in this data set.


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TABLE 1. Distribution of the study population with regard to smoking during pregnancy and maternal and infant characteristics, Swedish Medical Birth Register, 1991–1992

 
The original data set comprising all 239,251 singleton births occurring in Sweden during 1991 and 1992 was edited to exclude births with congenital malformations, births to women with diabetes mellitus or hypertension, and births with missing data on key variables. (On the data collection form filled out by each woman's physician, there are specific boxes for checking off whether the woman has diabetes, hypertension, or one of six other relatively common conditions. Thus, disease status for diabetes and hypertension was coded as it was reported by the physician in the check-boxes, not by International Classification of Diseases, Ninth Revision, codes.) Births occurring before 32 completed weeks of gestation were excluded from this analysis because of small sample sizes. Gestational age was defined as the duration of gestation from the woman's last menstrual period to the date of delivery, expressed in days. (Among the 15,185 infants finally used in this study, 84.7 percent had gestational age calculated from an expected date of delivery based on ultrasound; 13.5 percent had gestational age calculated from an expected date of delivery based on the mother's last menstrual period; 1.0 percent had gestational age calculated directly from the date of the last menstrual period; and 0.8 percent had gestational age estimated as reported from the delivery hospital.)

Of the 206,258 births remaining at this point, data on maternal height and prepregnancy weight were available for approximately 40 percent and data on smoking in late pregnancy were available for approximately 18 percent, leaving a total of 15,185 births for study. We carried out {chi}2 tests to compare the distributions of important maternal and infant variables among these 15,185 births with the distributions among those births that were excluded because of missing data.

The outcome variables were birth weight (in grams), crown-heel length (in centimeters), head circumference (in centimeters), and two measures of infant body proportionality: ponderal index and BBR. Table 1 shows the percentage distributions of the population studied and of the subjects excluded for each outcome variable. Ponderal index is defined as 100 x [birth weight (g)/crown-heel length (cm)3]. A lower ponderal index indicates a longer, thinner infant, while a higher ponderal index indicates a shorter and/or fatter infant. Typical values of ponderal index in this data set were between 2.6 and 2.9, with the range extending from 2.0 through 3.5. BBR is an indicator of head-to-body proportionality, and is defined as 100 x the ratio of the infant's estimated brain weight to its birth weight (in other words, the percentage of the infant's birth weight that is estimated to reside in the brain). Brain weight was estimated from the formula brain weight (g) = 0.037 x head circumference (cm)2.57, which is derived from the National Institute of Neurological and Communicative Disorders and Stroke's Collaborative Perinatal Project (25Go). Thus, the value for each infant's BBR was calculated from the values of its birth weight and head circumference using the formula BBR = 100 x [0.037 x head circumference (cm)2.57]/birth weight (g). A higher BBR indicates a higher proportion of birth weight residing in the brain, while a lower BBR indicates a lower percentage of birth weight residing in the brain. Typical BBR values for healthy full term infants are 9–10 percent, and the range of values seen in this data set extended from 7 percent to 14 percent.

Each of the five infant measurements was regressed on maternal smoking status and other potential confounders using multivariate linear regression. For the outcomes of birth weight, crown-heel length, and head circumference, the other predictor variables included infant gender, gestational age, parity, maternal age, maternal height, and maternal body mass index (weight (kg)/height (m)2). For the two infant proportionality outcomes, the predictors, in addition to smoking, included the variables listed above plus the infant's birth weight z score. Birth weight z score was included because the degree of growth retardation, measured by birth weight z score, was found to strongly confound the effect of smoking on body proportionality in earlier studies (13Go, 14Go). The more growth-retarded an infant is by weight, the lower the ponderal index tends to be (26Go) and the higher the BBR. This aspect of our study sought to examine the effect of a particular growth-retarding influence, namely smoking, on body proportionality. Thus, to compare the body proportions of infants who have had different intrauterine environments and therefore different reasons for growth retardation, it is necessary to control for the birth weight factor as well as for gestational age. If one were not to control for birth weight in these analyses, smokers' infants, who are known to be growth-retarded in comparison with nonsmokers' infants, would appear to be thinner and to have proportionately larger heads compared with the full-sized infants of nonsmokers. Instead of comparing growth-retarded infants to full-sized infants (which is what comparing smokers' infants to nonsmokers' infants amounts to if one doesn't control for the degree of growth retardation), our study sought to compare the proportions of infants with the same degree of growth retardation who differed in only one aspect of their exposure, i.e., whether or not their mothers smoked during pregnancy.

All of these predictor and outcome variables were coded continuously except for infant gender, which is a dichotomous variable. Each continuous variable except for parity was centered around the population mean so that the regression intercepts would refer to the mean value of the outcome variable at the population mean of each predictor variable. Parity was expressed as actual parity minus 1 (e.g., a parity of 1 was coded as 0, a parity of 2 was coded as 1, etc.) so that the regression intercepts would refer to the mean values of the outcome variables among first births. The value of each infant's birth weight z score was calculated relative to that of other infants of the same 1-week gestational-age group and sex, using the standard formula: birth weight z score = (birth weight – mean birth weight)/standard deviation of birth weight. Birth weight z score was included as a predictor in these regressions because it is known that both of the proportionality indicators are highly correlated with birth weight z score, and that it confounds the effect of smoking on these outcomes (13Go, 14Go).

The women were divided into four categories depending on their smoking status at the first prenatal care visit and the 32-week prenatal care visit: nondaily smokers (n = 9,802), women who smoked at the moderate level (1–9 cigarettes per day) at the first visit and continued to smoke at the 32-week visit (n = 2,340), women who were heavy smokers (>=10 cigarettes per day) at the first visit and who continued to smoke at the 32-week visit (n = 2,097), and women who smoked one or more cigarettes per day at the first visit and were nondaily smokers by the 32-week visit (n = 946). For the regression analyses, the three smoking categories were coded as three indicator variables compared with the control group of nondaily smokers.

Regression variables were selected and parameters were calculated using PROC STEPWISE and PROC REG in the Statistical Analysis System (SAS Institute, Cary, North Carolina). In each regression, the variables representing each of the three smoking categories were retained in the model. Other variables were selected using a backward selection procedure which employed the F test and eliminated at each step the variable with the lowest p value. When all of the variables were significant at least at the 0.05 level, the stepwise elimination procedure was ended. Once the main effects were thus selected, interactions between each of the smoking categories and each of the other main predictors were tested using the same procedure. In the final model for each outcome, the interaction terms for a confounder with all three smoking categories were included even if only one of them was significant.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Table 1 shows the distribution of women according to the predictor and outcome variables used in the regression analyses. Subjects included in the analyses were more likely to be smokers at the first prenatal care visit and to be younger and primiparous than subjects for whom late-pregnancy smoking data were missing. There appeared to be no significant differences in height or body mass index between included and excluded subjects, among those for whom data on these variables were available. Infants included in the analysis were more likely to have gestational ages between 39 and 42 weeks than infants who were excluded. The included group also tended to have fewer members with extreme values for the five outcome variables.

Table 2 presents the intercepts and smoking parameter estimates for the regression analyses of the five anthropometric outcome variables. (Covariates included in the model are given in the footnotes to table 2.) Each regression intercept refers to the main value of the outcome variable among nonsmokers' infants who also have the reference values for the other predictors in the model–namely, female gender, parity of 1, maternal age of 28.2 years, maternal height of 166.2 cm, and maternal body mass index of 23.4. The mean birth weight was 3,459 g (95 percent confidence interval (CI): 3,444, 3,474). Smoking at the lower level throughout pregnancy was associated with a decrease in birth weight of 136 g (95 percent CI: -109, -162). Smoking at the higher level throughout pregnancy was associated with a decrease in birth weight of 175 g (95 percent CI: -146, -203). For infants of women who stopped smoking some time between the first prenatal care visit and the 32nd week of pregnancy, the birth weight differences compared with infants of nonsmokers were not statistically significant.


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TABLE 2. Regression parameter estimates for five infant anthropometric birth outcomes according to maternal smoking during pregnancy{dagger}, Swedish Medical Birth Register, 1991–1992

 
The adjusted mean value for crown-heel length among nondaily smokers was 49.94 cm (95 percent CI: 49.88, 50.00). Continued smoking at the lower level was associated with a decrease in crown-heel length of 0.62 cm (95 percent CI: 0.50, 0.74), while continued smoking at the higher level was associated with a decrease of 0.89 cm (95 percent CI: 0.77, 1.01). There was a statistically significant deficit in crown-heel length among the infants of smokers who stopped smoking between the first prenatal care visit and the 32nd week of pregnancy. This deficit was 0.23 cm (95 percent CI: 0.07, 0.39).

The regression intercept value for head circumference was 34.43 cm (95 percent CI: 34.39, 34.47). Continued smoking at the lower level was associated with a statistically significant decrease in head circumference of 0.37 cm (95 percent CI: -0.31, -0.43), while continued smoking at the higher level was associated with a statistically significant decrease in head circumference of 0.41 cm (95 percent CI: -0.35, -0.47). No effect on head circumference was observed among the infants of mothers who stopped smoking.

The ponderal index regression controlled for the infant's birth weight z score as well as for the factors controlled for in the other regression analyses (table 2 footnotes). The mean ponderal index value for nondaily smokers' infants was 2.803 (95 percent CI: 2.795, 2.811). Continued smoking throughout pregnancy was associated with an increase in ponderal index of 0.029 for moderate smoking (95 percent CI: 0.017, 0.041) and 0.040 for heavy smoking (95 percent CI: 0.026, 0.054). Infants of smokers who stopped smoking had a statistically significant increase in ponderal index of 0.027 (95 percent CI: 0.009, 0.045) compared with the infants of nonsmokers of the same birth weight and gestational age. In other words, when smokers' infants were compared with nonsmokers' infants who nevertheless had a similar degree of growth (as measured by birth weight z score), the smokers' infants had a higher ponderal index, being presumably shorter for the same birth weight. Some of this smoking effect was evident even when the mothers had stopped smoking early in pregnancy.

As we did in the ponderal index regression analysis, the regression of BBR controlled for infant birth weight z score and other covariates shown in the relevant footnote of table 2. The mean BBR in this group was 9.456 (95 percent CI: 9.427, 9.485). Continued smoking throughout pregnancy was associated with decreases in BBR of 0.074 for moderate smoking (95 percent CI: -0.031, -0.117) and 0.046 for heavy smoking (95 percent CI: -0.001, -0.091). The infants of women who stopped smoking between the first prenatal care visit and week 32 of pregnancy were statistically indistinguishable from the infants of nondaily smokers in terms of their BBRs. In other words, when we compared smokers' infants with nonsmokers' infants with the same gestational age and birth weight, the smokers' infants had disproportionately smaller heads (and presumably made up the weight in some other body dimension). However, the infants of women who stopped smoking before week 32 of pregnancy were no different in their BBRs from nonsmokers' infants of the same birth weight and gestational age.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
As was expected, continued smoking throughout pregnancy was associated with reductions in birth weight, crown-heel length, and head circumference, and the effects were more severe with heavier smoking. Stopping smoking sometime between the first prenatal care visit and the 32nd week of pregnancy resulted in complete elimination of the smoking-associated deficits in birth weight and head circumference but not the deficits in crown-heel length. Since we do not know the average time at which these women stopped smoking, only that they stopped sometime between the first visit and the 32-week visit, we do not know the latest point in pregnancy at which a woman can stop smoking and still prevent these deficits. However, an earlier study of smoking habits in 3,678 pregnant Swedish women reported that among 307 women who were smokers at conception and then stopped smoking permanently, 62.2 percent of them stopped even before the first prenatal care visit, 23.5 percent of them stopped between weeks 10 and 24 of pregnancy, and 14.3 percent stopped between weeks 25 and 36 (Go). Thus, it is likely that in our population, a substantial proportion of the women who stopped smoking between the first prenatal care visit and week 32 did so at a point early on in that period. It has been shown that the peak period of linear growth of the fetus is the first 15 weeks of pregnancy (28Go), while the peak period of lean and fat tissue growth is the last trimester of pregnancy (21Go). This is compatible with our finding that stopping smoking by midpregnancy prevented retardation in birth weight but not in crown-heel length.

Regarding the two indicators of body proportionality, BBR and ponderal index, continued smoking throughout pregnancy reduced BBR and increased ponderal index. The BBR represents the percentage of birth weight that is estimated to reside in the brain, based on the measure of head circumference (14Go). Choosing a reference birth weight of 3,500 g, we calculated that continued moderate smoking resulted in an average brain weight deficit of 2.59 g, corresponding to the regression coefficient of –0.074 for continued moderate smoking. We calculated that continued heavy smoking resulted in an average brain weight deficit of 1.61 g. However, quitting smoking at the point the women in our study did was sufficient to completely eliminate the smoking-associated deficits in BBR.

The BBR regression results appear to suggest that the effect of moderate smoking on BBR is greater than the effect of heavy smoking. However, in the regression analyses, the infants of moderate smokers and the infants of heavy smokers were not necessarily compared with nonsmokers' infants in the same way. Because birth weight z score was a predictor in the regression analyses, each group of smokers' infants was compared with nonsmokers' infants with the same degree of growth retardation. For example, infants of moderate smokers may be only moderately growth-retarded, and it appears from the regression results that they have a significant reduction in BBR compared with other such moderately growth-retarded infants. The infants of heavy smokers also showed a significant reduction in BBR compared with nonsmokers' infants with a degree of growth retardation equal to their own. The infants of heavy smokers tended to be more growth-retarded than the infants of moderate smokers, and thus they would have been compared with more severely growth-retarded infants of nonsmokers. Thus, the gap in BBR between moderate smokers' infants and similarly growth-retarded nonsmokers' infants and the gap in BBR between heavy smokers and other (possibly more severely growth-retarded) nonsmokers' infants need not follow a dose-response pattern. However, the point remains that, regardless of their birth weight z score, infants with smoking exposure had lower mean BBRs than similarly growth-retarded infants who did not have smoking among their prenatal exposures, and the effect was not seen when the mothers stopped smoking before week 32 of pregnancy.

Regarding ponderal index, the infants of women who continued to smoke throughout pregnancy had elevated ponderal indices compared with the infants of nonsmokers of the same age and weight, which suggests an excess reduction in crown-heel length compared with birth weight. Stopping smoking at the point the women in our study did was not sufficient to eliminate the smoking-associated increase in ponderal index. Thus, it appears that the length stunting, which had already occurred due to smoking during the early period of pregnancy, was not overcome even when the mother was a nondaily smoker by week 32.

Regarding the generalizability of this study, one should first note that the data were drawn from a very homogeneous population. While there are likely to have been some socioeconomic differences between smokers and nonsmokers in this population for which our analysis could not account, these may not be as large as one would find in a more ethnically and socially diverse population. This is a strength in that the smoking-associated effects seen here are more likely to be truly due to smoking than results one might find in a more diverse population. In a more diverse population, one would be more likely to see confounding in both directions, possibly either hiding or else seeming to exacerbate the effect of smoking. A second point to note is that it is clear from table 1 that the subpopulation for which both 32-week smoking status and maternal body mass index data were available was similar to but not entirely representative of the whole population, despite the fact that births occurring before 32 weeks' gestation were not considered. The infants studied were less likely to have extreme values in either infant dimensions or maternal predictors than were infants in the population as a whole. In a regression analysis, this is a strength in that it reduces the likelihood that points with extreme values have unduly influenced the results. However, it also means that the results should not be extrapolated beyond the values present in the data set.

In summary, our findings suggest that early to midpregnancy smoking cessation prevents deficits in infant birth weight, head circumference, and BBR. However, this study suggests that even smoking cessation in early to midpregnancy may not be sufficient to eliminate the effects of smoking in early pregnancy on the infant's crown-heel length and ponderal index at birth.


    ACKNOWLEDGMENTS
 
The authors thank Dr. Bengt Haglund of the Center for Epidemiology at the National Board of Health and Welfare (Stockholm, Sweden) for providing access to the Swedish Medical Birth Register and for advice on the manuscript. The authors also thank Dr. Robert Hartford, formerly of the US National Center for Health Statistics, and Howard J. Hoffman of the National Institute on Deafness and Other Communication Disorders, both of whom made important suggestions during the initial stages of the work which led to the use of the Swedish Medical Birth Register in this study. In addition, the authors thank Dr. Ann Trumble of the National Institute of Child Health and Human Development for invaluable technical support in the computer analyses.


    NOTES
 
Reprint requests to Dr. Anna A. Lindley, 23514 Beachwood Boulevard, Beachwood, OH 44122 (e-mail: aal5{at}po.cwru.edu).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Kramer MS. Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 1987;65:663–737.[ISI][Medline]
  2. Miller HC, Jekel JF. Epidemiology of white full-term infants with short crown-heel lengths for gestational ages at birth. Yale J Biol Med 1989;62:1–12.[ISI][Medline]
  3. Cnattingius S, Axelsson O, Elklund G, et al. Factors influencing birth weight for gestational age with special respect to risk factors for intrauterine growth retardation. Early Hum Dev 1984;10:45–55.[ISI][Medline]
  4. O'Callaghan MJ, Harvey JM, Tudehope DI, et al. Aetiology and classification of small for gestational age infants. J Pediatr Child Health 1997;33:213–18.
  5. Meis PJ, Michielutte R, Peters TJ, et al. Factors associated with term low birth weight in Cardiff, Wales. Paediatr Perinat Epidemiol 1997;11:287–97.[ISI][Medline]
  6. Cliver SP, Goldenberg RL, Cutter GR, et al. The effect of cigarette smoking on neonatal anthropometric measurements. Obstet Gynecol 1995;85:625–30.[Abstract/Free Full Text]
  7. Horta BL, Victora CG, Menezes AM, et al. Low birth weight, preterm births and intrauterine growth retardation in relation to maternal smoking. Paediatr Perinat Epidemiol 1997;11:140–51.[ISI][Medline]
  8. Roquer JM, Figueras J, Botet F, et al. Influence on fetal growth of exposure to tobacco smoke during pregnancy. Acta Paediatr 1995;84:118–21.[ISI][Medline]
  9. Zaren B, Lindmark G, Gebre-Medhin M. Maternal smoking and body composition of the newborn. Acta Paediatr 1996;85:213–19.[ISI][Medline]
  10. Vik T, Jacobsen G, Vatten L, et al. Pre- and post-natal growth in children of women who smoked in pregnancy. Early Hum Dev 1996;45:245–55.[ISI][Medline]
  11. Miller HC, Hassanein K. Maternal smoking and fetal growth of full term infants. Pediatr Res 1974;8:960–3.[ISI][Medline]
  12. Haste FM, Anderson HR, Brooke OG, et al. The effects of smoking and drinking on the anthropometric measurements of neonates. Paediatr Perinat Epidemiol 1991;5:83–92.[Medline]
  13. Lindley AA, Gray RH, Herman AA, et al. Maternal cigarette smoking during pregnancy and infant ponderal index at birth in the Swedish Medical Birth Register, 1991–1992. Am J Public Health 2000;90:420–3.[Abstract/Free Full Text]
  14. Lindley AA, Herman AA, Becker S, et al. Maternal cigarette smoking during pregnancy and reductions in estimated brain-body weight ratio. (Unpublished manuscript).
  15. Li CQ, Windsor RA, Perkins L, et al. The impact on infant birth weight and gestational age of cotinine-validated smoking reduction during pregnancy. JAMA 1993;269:1519–24.[Abstract]
  16. Haddow JE, Knight GJ, Kloza EM, et al. Cotinine-assisted intervention in pregnancy to reduce smoking and low birthweight delivery. Br J Obstet Gynaecol 1991;98:859–65.[ISI][Medline]
  17. MacArthur C, Knox EG. Smoking in pregnancy: effects of stopping at different stages. Br J Obstet Gynaecol 1988;95:551–5.[ISI][Medline]
  18. Hebel JR, Fox NL, Sexton M. Dose-response of birth weight to various measures of maternal smoking during pregnancy. J Clin Epidemiol 1988;41:483–9.[ISI][Medline]
  19. MacArthur C, Newton JR, Knox EG. Effect of anti-smoking health education on infant size at birth: a randomized controlled trial. Br J Obstet Gynaecol 1987;94:295–300.[ISI][Medline]
  20. Sexton M, Hebel JR. A clinical trial of change in maternal smoking and its effect on birth weight. JAMA 1984;251:911–15.[Abstract]
  21. Bernstein IM, Goran MI, Amini SB, et al. Differential growth of fetal tissues during the second half of pregnancy. Am J Obstet Gynecol 1997;176:28–32.[ISI][Medline]
  22. Cnattingius S, Ericson A, Gunnarskog J, et al. A quality study of a medical birth registry. Scand J Soc Med 1990;18:143–8.[ISI][Medline]
  23. Lindmark G, Cnattingius S. The scientific basis of antenatal care routines. Obstet Gynecol Scand 1991;70:105–9.
  24. Aberg A, Lindmark G. Competence and compliance in antenatal care: experience from Sweden. Int J Technol Assess Health Care 1992;8(suppl 1):20–4.
  25. McLennan JE, Gilles FH, Neff RK. A model of growth of the human fetal brain. In: Gilles FH, Leviton A, Dooling EC, eds. The developing human brain: growth and epidemiologic neuropathy. Boston, MA: Wright P G, 1983:43–58.
  26. Kramer MS, Oliver M, McLean FH, et al. Determinants of fetal growth and body proportionality. Pediatrics 1990;86:18–26.[Abstract]
  27. Cnattingius S, Lindmark G, Meirik O. Who continues to smoke while pregnant? J Epidemiol Community Health 1992;46:218–21.[Abstract]
  28. Falkner F. Ultrasonography and fetal growth: key perinatal factors. J Perinatol 1995;15:114–18.[Medline]
Received for publication August 10, 1999. Accepted for publication August 27, 1999.