Growth patterns in early childhood and the onset of menarche before age twelve
Padrões de crescimento na infância precoce e ocorrência de menarca antes de doze anos de idade
Patrones de crecimiento en la infancia precoz y ocurrencia de menarca antes de doce años de edad
Jeovany MartínezI; Cora AraújoII; Bernardo Lessa HortaI; Denise Petrucci GiganteII
IPrograma de Pós-Graduação em Epidemiologia. Faculdade de Medicina. Universidade Federal de Pelotas (UFPel). Pelotas, RS, Brasil
IIPrograma de Pós-Graduação em Epidemiologia. Faculdade de Nutrição. UFPel. Pelotas, RS, Brasil
OBJECTIVE: To examine the relationship between growth patterns in early childhood and the onset of menarche before age 12.
METHODS: The study included 2,083 women from a birth cohort study conducted in the city of Pelotas, Southern Brazil, starting in 1982. Anthropometric, behavioral, and pregnancy-related variables were collected through home interviews. Statistical analyses were performed using Pearson's chi-square and chi-square test for linear trends. A multivariable analysis was carried out using Poisson regression based on a hierarchical model.
RESULTS: Mean age of menarche was 12.4 years old and the prevalence of menarche before age 12 was 24.3%. Higher weight-for-age, height-for-age, and weight-for-height z-scores at 19.4 and 43.1 months of age were associated with linear tendencies of increased prevalence and relative risks of the onset of menarche before age 12. Girls who experienced rapid growth in weight-for-age z-score from birth to 19.4 months of age and in weight-for-age or height-for-age z-scores from 19.4 to 43.1 months of age also showed higher risk of menarche before age 12. Higher risk was seen when rapid growth in weight-for-age z-score was seen during these age intervals and the highest risk was found among those in the first tertile of Williams' curve at birth. Rapid growth in weight-for-height z-score was not associated with menarche before age 12.
CONCLUSIONS: Menarche is affected by nutritional status and growth patterns during early childhood. Preventing overweight and obesity during early childhood and keeping a "normal" growth pattern seem crucial for the prevention of health conditions during adulthood.
Descriptors: Menarche. Puberty. Child Development. Adolescent Development. Sexual Maturation. Body Weights and Measures. Risk Factors. Cohort Studies. Weight by age. Height by Weight. Height by Age.
OBJETIVO: Avaliar a relação entre padrões de crescimento na infância precoce e ocorrência de menarca antes de 12 anos de idade.
MÉTODOS: O estudo incluiu 2.083 mulheres do estudo de coorte de nascidos em Pelotas, RS, de 1982. Variáveis antropométricas, comportamentais e relacionadas à gestação foram coletadas por meio de entrevistas domiciliares. As análises estatísticas empregadas foram o qui-quadrado de Pearson e qui-quadrado para tendência linear. Além disso, análise multivariável foi realizada usando a regressão de Poisson, seguindo um modelo hierárquico.
RESULTADOS: A média de idade da menarca foi de 12,4 anos e a prevalência de menarca antes dos 12 anos foi de 24,3%. Maiores valores de escores Z nos índices peso/idade, altura/idade e peso/altura aos 19,4 e 43,1 meses corresponderam a maiores riscos de apresentar menarca antes dos 12 anos. Esse risco foi sistematicamente maior na idade de 43,1 meses. Meninas que experimentaram rápido crescimento em escore Z de peso/idade entre o nascimento e 19,4 meses ou em escore Z de peso/idade ou altura/idade entre 19,4 e 43,1 meses, mostraram os maiores riscos. O risco de menarca antes dos 12 anos foi mais elevado quando o crescimento rápido em escore Z de peso/idade ocorreu em ambos os períodos; e ainda maior entre as meninas do primeiro tercil da curva de Williams. Crescimento rápido em escore Z de peso/altura não esteve associado com menarca antes dos 12 anos.
CONCLUSÕES: A idade da menarca mostrou-se influenciada pelo estado nutricional e padrões de crescimento durante a infância precoce. Assim, evitar sobrepeso e obesidade na infância precoce mantendo um padrão "normal" de crescimento parece ser importante para prevenir problemas de saúde em futuras etapas da vida.
Descritores: Menarca. Puberdade. Desenvolvimento Infantil. Desenvolvimento do Adolescente. Maturidade Sexual. Pesos e Medidas Corporais. Fatores de Risco. Estudos de Coortes. Peso para Idade. Peso para Altura. Altura para Idade.
OBJETIVO: Evaluar la relación entre patrones de crecimiento en la infancia precoz y ocurrencia de menarca antes de 12 años de edad.
MÉTODOS: El estudio incluyó 2.083 mujeres del estudio de cohorte de nacidos en Pelotas, 1982, Sur de Brasil. Variables antropométricas, comportamentales y relacionadas a la gestación fueron colectadas por medio de entrevistas domiciliares. Los análisis estadísticos empleados fueron el chi-cuadrado de Pearson y ji-cuadrado para tendencia linear. Así mismo, análisis multivariable fue realizado usando la regresión de Poisson, siguiendo un modelo jerárquico.
RESULTADOS: El promedio de edad de menarca fue de 12,4 años y la prevalencia de menarca antes de los 12 años fue de 24,3%. Mayores valores de escores Z en los índices peso/edad, altura/edad y peso/altura a los 19,4 y 43,1 meses correspondieron a mayores riesgos de presentar menarca antes de los 12 años. Ese riesgo fue sistemáticamente mayor en la edad de 43,1 meses. Niñas que experimentaron rápido crecimiento en escore Z de peso/edad entre el nacimiento y 19,4 meses o en escore Z de peso/edad o altura/edad entre 19,4 y 43,1 meses, mostraron mayores riesgos. El riesgo de menarca antes de los 12 años fue más elevado cuando el crecimiento rápido en escore Z de peso/edad ocurrió en ambos períodos; y aún mayor entre las niñas del primer tercil de la curva de Williams. Crecimiento rápido en escore Z de peso/altura no estuvo asociado con menarca antes de los 12 años.
CONCLUSIONES: La edad de menarca se mostró influenciada por el estado nutricional y patrones de crecimiento durante la infancia precoz. Así, evitar sobrepeso y obesidad en la infancia precoz manteniendo un patrón "normal" de crecimiento parece ser importante para prevenir problemas de salud en futuras etapas de vida.
Menarche (first menstrual bleeding) is a milestone in female reproductive life and has been reported as an important predictor of health status during adolescence, adulthood, and post-menopause. Early menarche has been described as a risk factor for chronic diseases, especially breast cancer.5
The 1982 Pelotas Birth Cohort Study found high body mass index (BMI) and lower increment in weight gain after adolescent pregnancy among girls who experienced menarche before age 12,13 and lower stature at 19 when menarche was before 13.14
Studies suggest chronic diseases are programmed by restrictive environments during intrauterine life resulting in abnormally programmed metabolic pathways that act regulating metabolic, hormonal adaptive capacities in future life.2,12 Therefore, identifying early health determinants and adopting the so-called life course approach6,18 are new goals of epidemiology and public health.20 Early childhood has been also described as a "window" for programming of chronic disease and there is evidence that rapid growth can produce negative health effects in later life.7-9,11,17,19,21,22 If rapid growth occurs after a "restriction" period, known as catch-up growth, it could have short-term benefits with lower rates of infections during childhood.23 However, weight gain in the first two years of life has been associated with lean mass in 18-year-old males in Brazil, whereas later weight gain was more strongly associated with fat mass.26
There are scarce studies investigating the association between early events and early menarche. Some authors have identified an association between the timing of puberty and early weight gain,1,7 but no association was found with low birthweight.1 Other studies reported an association between low birthweight and early puberty.7,16
The objective of the present study was to examine the relationship between growth patterns during early childhood and the onset of menarche before age 12.
The 1982 Pelotas Birth Cohort Study included 5,914 live born births. The cohort subjects have been followed up in several studies and detailed information are available elsewhere.24,25 The present study included 2,084 women with information on menarche. One subject was excluded due to a uterine tumor; thus the final sample comprised 2,083 women.
The study was based on information from the perinatal study (1982) and follow-up studies in 1984, 1986 and 2004-2005. In summary, in 1982, all subjects were weighed and their mothers answered a questionnaire on socioeconomic, demographic and health-related conditions. Data on their length at birth was not collected. During the 1984 and 1986 follow-up studies, the mothers or caretakers answered a questionnaire and their children had weight and height measurements taken. Subjects were on average 19.4 and 43.1 months old and 12.8% and 15.9% from the original cohort were lost to follow-up, respectively. Likewise, in 2004-2005, subjects were 23-24 years old and 22.6% from the original cohort were lost to follow-up. Interviewers were thoroughly trained before fieldwork and quality control included repeating 5% of the interviews and double data entry.
Confounders in the perinatal study included skin color, family income (in quintiles of minimum monthly wages), smoking during pregnancy and pre-gestational maternal BMI. Weight-for-age z-scores using Williams' curve27 were used to generate other variables. In addition, from the 1984 and 1986 follow-up studies, breastfeeding duration was used for control of confounding. Height, weight and age were used to generate weight-for-age, height-for-age and weight-for-height z-scores based on the 2006 World Health Organization (WHO) curves,4 and were categorized as <0, 0.01 to 1, 1.01 to 2, and >2.
Growth patterns were analyzed at two age intervals (interval 1 and 2): from birth to 19.4 months of age; and from 19.4 to 43.1 months of age. For interval 1, the change in weight-for-age z-score was a result of "z-score at 19.4 months of age minus z-score using Williams' curve". For interval 2, it was a result of "z-score at 43.1 months of age minus z-score at 19.4 months of age".
The change in height-for-age and weight-for-height z-scores was analyzed separately in interval 2 as "z-score at 43.1 months of age minus z-score at 19.4 months of age," respectively. Rapid growth has been described as gain of more than 0.67 z-score,21 used as a cut-off in other studies.19,23 In addition, z-scores were defined as "catch-down growth" if they were <-0.67; "normal" if between -0.669 and 0.669; and "rapid growth" if >0.67. Otherwise, a variable analyzing change in both intervals in weight-for-age z-score was generated as "never rapid growth" (if catch-down or normal growth in intervals 1 and 2); "rapid growth/no rapid growth"; "no rapid growth/rapid growth" (if normal or catch-down growth in interval 1 and rapid growth in interval 2); and "always rapid growth" (rapid growth in both intervals 1 and 2). These analyses were performed in the entire sample and stratified by tertiles of z-scores at the beginning of each age interval (at birth and 19.4 months of age).
The age of menarche was obtained from the 2004-2005 follow-up and was analyzed as a dichotomous outcome: <12 and >12 years old.
Pearson's chi-square and chi-square test for linear trends were used. A multivariable analysis was performed using Poisson regression with a robust variance estimative to obtain prevalence ratios.3 The regression was based on a hierarchical model (Figure).
All potential confounders (Figure) were cross-tabulated against the outcome and explanatory variables and only those showing an association (p<0.20) were included in the multivariable analysis. Confounding was defined as the difference between crude and adjusted estimates higher than 10%.
In levels 2 and 3 (Figure), two independent models - one "static" and the other "dynamic" - were analyzed and designated by letters (a through g). The variables in the level 3 were adjusted for the related "static" model in the level 2 (letters a-c) and for variables in the level 1, but not between them. The variables in the level 2 included in the "dynamic" model (letters d-g) were adjusted only for the level 1, but not between them.
Using the actual sample size, prevalence ratio was estimated with a power of 80% and at 5% significance level. Some independent variables showed missing data: change in weight-for-age z-score in interval 1 (26.1%) and change in weight-for-age z-score in both intervals (30.7%). Moreover, the characteristics of subjects with missing data had a similar distribution for family income quintiles, indicating that they were not different from the study subjects. The number of observations for each regression model is included in the respective tables.
The analyses were performed using Stata 9.
All followed-up subjects signed an informed consent. The study was approved by the Research Ethics Committee of Universidade Federal de Pelotas.
Mean age of menarche was 12.44 years old (95% CI: 12.38; 12.51); median age was 12 years old and the standard error was 1.51. The prevalence of menarche before 12 was 24.3% (95% CI: 22.5; 26.2) and 66.8% and 8.9% between age 12 and 14 and older than 14, respectively. In addition, the asymmetry coefficient was equal to 0.15 with Kurtosis of 3.53, indicating near-normal frequency distribution.
Table 1 shows a summary description of the sample including skin color, family income, smoking during pregnancy, anthropometric and growth pattern variables, among others. There were a higher proportion of girls who experienced rapid growth with change in weight-for-age z-score from birth to 19.4 months of age (41.0%) than from 19.4 to 43.2 months of age (8.0%).
The differences in proportions of menarche before age 12 and Poisson regression results by z-score groups are showed in Table 2. Increasing weight-for-age, height-for-age and weight-for-height z-scores at 19.4 and 43.1 months of age were associated to linear tendencies of increasing prevalence of the outcome. The prevalence and relative risks of menarche before age 12 were systematically higher in those with z-scores >2 or more at 43.1 months than at 19.4 months of age. On the other hand, weight-for-age z-score >2 at 19.4 and 43.1 months of age showed higher risk of the outcome compared to <0 z-score group. Negative confounding was detected at 43.1 months of age (crude PR=2.13; p<0.001; adjusted PR=2.66; p<0.001).
Height-for-age z-score (Table 2) at 19.4 months and 43.1 months old showed that taller girls were more likely to have menarche before 12 than shorter ones (p<0.001). The association at 43.1 months of age had a negative confounding effect (crude PR=2.26; p<0.001; adjusted PR=2.97; p<0.001). The analysis of weight-for-height z-score revealed that the >2 group at 43.1 months of age had the highest risk of the outcome and had a positive confounding effect (crude PR=1.95; p<0.001; adjusted PR=1.73; p=0.002).
Table 3 shows the results for growth variables. In interval 1, girls who experienced rapid growth in weight-for-age z-score showed the highest prevalence of the outcome (29.2%; p<0.001). The same was seen in interval 2, but with greater prevalence of menarche before age 12 (34.3%; p<0.001) than in interval 1. In fact, those who experienced rapid growth in both intervals had the highest prevalence of the outcome (37.8%; p<0.001) while those who experienced rapid growth in height-for-age z-score during interval 2 had the highest prevalence of the outcome (34.2%; p<0.001). Moreover, a change in weight-for-height z-score was not associated with the outcome (p=0.22).
In contrast, in interval 1 (Table 3), those girls who experienced rapid growth in weight-for-age z-score had higher risk than those who experienced catch-down growth in both crude (PR=1.65; p<0.001) and adjusted analyses (PR=1.75; p<0.001). The same was found in interval 2 with a relative risk very similar to that seen in interval 1 (crude PR=1.68; p=0.003; adjusted PR=1.82; p=0.002). Girls who experienced rapid growth in both intervals had the highest risk for the outcome (crude PR=1.79; p<0.001; adjusted PR=2.01; p<0.001) and those who experienced rapid growth in height-for-age z-score during interval 2 showed the highest relative risk for the outcome (crude PR1.79; p<0.001; adjust PR 1.96; p<0.001). Change in weight-for-height z-score was not associated with the outcome in crude analyses (p=0.2) but was marginally associated after controlling for confounders (PR=1.28; p=0.07).
Table 4 shows the relative risks of menarche before age 12 by growth patterns, taking into account the subjects' initial z-score tertiles adjusted by family income. This analysis was not adjusted for all confounders due to missing data that resulted in a lower number of subjects in each stratum: the program analyzes only those observations that include information for all variables of the model, which reduces the number of observations studied. To avoid the loss of many observations, the model was only adjusted for family income. In addition, family income was the only variable with no missing data. Girls in the first tertile of Williams' curve who experienced rapid growth in interval 1 showed the highest risk of the outcome (crude PR=2.10; p=0.01; adjusted PR=2.09; p=0.01). Those in the second or third tertiles had lower risk. When rapid growth occurred in interval 2, the girls in the first and second tertiles had no risk (p=0.2). Those girls in the third tertile showed higher relative risks than those who experienced catch-down growth (crude PR=1.92; p=0.02; adjusted PR=1.98; p=0.02). Otherwise, when there was rapid growth in both intervals, girls in the first tertile showed the highest risk (crude PR=2.87; p=0.01; adjusted PR=2.85; p=0.01).
Changes in weight-for-age z-score in interval 2 (Table 4) were analyzed taking account weight-for-age z-score tertiles at 19.4 months of age. The risk increased among girls in the highest tertiles (crude PR=2.14; p=0.001; adjusted PR=2.14; p<0.001). Changes in height-for-age z-score in interval 2 showed that the relative risk for the outcome was similar in height-for-age z-score tertiles at 19.4 months of age and higher among those who experienced rapid growth. Finally, changes in weight-for-height z-score in interval 2 showed increased risk only in the third tertile (PR=1.83, p=0.001).
The study findings are consistent with Dunger et al8 reports that place great importance on rapid growth during childhood associated with the onset of puberty. In our study (dynamic model), girls who experienced rapid growth and weight gain during an early age interval showed less apparent risk for menarche before age 12 than those who experienced rapid growth in a later period. After stratifying by tertiles of Williams' curve, the risk of the outcome was clearly higher among "small" girls at birth who experienced rapid growth in both age intervals. Moreover, the first interval studied seems to have a more remarkable negative effect on these girls. This early accelerated weight gain was associated with younger age of menarche, corroborating other studies.1,8
There is biological plausibility in our findings regarding the association of early rapid growth and menarche before age 12. A study analyzing a sub-sample of subjects from the 1982 Pelotas Birth Cohort from same age intervals showed an association between rapid growth and overweight/obesity in adolescence.19 This finding could in part explain the mechanism that associates catch-up or rapid growth with age of menarche. These girls tend to have more body fat and it is well-recognized that greater body fat increases the risk for early menarche,8 possibly due to high levels of leptin.1,8
There could be other explanations for the effect of rapid growth on the onset of menarche before age 12 rather than obesity. High leptin levels following rapid weight gain during childhood may trigger early pubertal development.8
The present study found that higher weight-for-age and/or height-for-age z-scores during early childhood (static model) was associated with menarche before age 12, which is consistent to that described in other studies.1,7, 8,16
The analysis of nutritional status (static model) separately from growth patterns (dynamic model) could be a useful yet challenging approach in life course epidemiology.6,18 We believe that both models analyze the same issue but from different perspectives. The dynamic model had the advantage of describing the relative risk, especially in girls who were "small" at birth (first tertile of Williams' curve). For example, a risk was seen among girls who grew >0.67 z-score but did not reach the classic >2 z-score (static model) at 19.4 or at 43.1 months of age. However, further studies are required to estimate specificity and sensibility of each approach. Both models allow the assessment of relative risks of developing health conditions in future life at the individual level.
Our findings provide input supporting the importance of preventing overweight or obesity during early childhood and maintaining a "normal" growth pattern. Rapid growth during childhood is associated with short-term benefits such as lower risk of hospital admission and lower mortality,23 but it appear to be a risk for health outcome in the long run.11,17,19,21 Moreover, accelerated growth should be taken into account when following up "healthy" children in preventive medicine.
The present findings suggest that early experiences may partially determine later health outcomes and are consistent with a life course approach.2,18
The mean age of menarche found in the study (12.4 years old) was slightly lower than that reported in other studies in the same city (mean age of 12.7 years in 1991).15 Unpublished data from a representative study of women in Pelotas in the early 1990s showed that the average age of menarche was 12.8 years among 1,770 women in 2002.
In the early 1990s, the mean age of menarche in Brazil was 13.2 years. It could be argued that these studies did not take into account the year of birth, also known as the cohort effect.18
The 1982 Pelotas Birth Cohort Study24,25 provided good quality of data to the present study. However, there are some limitations: no data on length measurement at birth and no follow-up near menarche age for all girls. Age at menarche was collected retrospectively and in complete years at age 24. Two active birth cohort studies in the city of Pelotas including those born in 1993 and 2004 will allow a more detailed investigation.
1. Adair LS. Size at birth predicts age at menarche. Pediatrics. 2001;107(4):E59. DOI:10.1542/peds.107.4.e59
2. Barker DJ. The developmental origins of well-being. Philos Trans R Soc Lond B Biol Sci. 2004;359(1449):1359-66. DOI:10.1098/rstb.2004.15183.
3. Barros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol. 2003;20(3):21.
4. Borghi E, Onis M, Garza C, Van den Broeck J, Frongillo EA, Grummer-Strawn L, et al. Construction of the World Health Organization child growth standards: selection of methods for attained growth curves. Stat Med. 2006;25(2):247-65.
5. De Stavola BL, Silva IS, McCormack V, Hardy RJ, Kuh DJ, Wadsworth ME. Childhood growth and breast cancer. Am J Epidemiol. 2004;159(7):671-82. DOI:10.1093/aje/kwh097
6. De Stavola BL, Nitsch D, Silva IS, McCormack V, Hardy R, Mann V, et al. Statistical issues in life course epidemiology. Am J Epidemiol. 2006;163(1):84-96. DOI:10.1093/aje/kwj003
7. dos Santos Silva I, De Stavola BL, Mann V, Kuh D, Hardy R, Wadsworth ME. Prenatal factors, childhood growth trajectories and age at menarche. Int J Epidemiol. 2002;31(2):405-12. DOI:10.1093/ije/31.2.405
8. Dunger DB, Ahmed ML, Ong KK. Early and late weight gain and the timing of puberty. Mol Cell Endocrinol. 2006;254-255:140-5. DOI:10.1016/j.mce.2006.04.003
9. Eriksson JG, Forsen T, Tuomilehto J, Winter PD, Osmond C, Barker DJ. Catch-up growth in childhood and death from coronary heart disease: longitudinal study. BMJ. 1999;318(7181):427-31.
10. Eriksson J, Forsen T, Tuomilehto J, Osmond C, Barker D. Fetal and childhood growth and hypertension in adult life. Hypertension. 2000;36(5):790-4.
11. Eriksson JG, Forsen T, Tuomilehto J, Osmond C, Barker DJ. Early growth and coronary heart disease in later life: longitudinal study. BMJ. 2001;322(7292):949-53. DOI:10.1136/bmj.322.7292.949
12. Fowden AL, Forhead AJ. Endocrine mechanisms of intrauterine programming. Reproduction. 2004;127(5):515-26. DOI:10.1530/rep.1.00033
13. Gigante DP, Rasmussen KM, Victora CG. Pregnancy increases BMI in adolescents of a population-based birth cohort. J Nutr. 2005;135(1):74-80.
14. Gigante DP, Horta BL, Lima RC, Barros FC, Victora CG. Early life factors are determinants of female height at age 19 years in a population-based birth cohort (Pelotas, Brazil). J Nutr. 2006;136(2):473-8.
15. Horta RL, Santos I. Idade da menarca em Pelotas: estudo piloto. Rev AMRIGS. 1991;35(2):83-7.
16. Ibañez L, Zegher F. Puberty and prenatal growth. Mol Cell Endocrinol. 2006;254-255:22-5. DOI:10.1016/j.mce.2006.04.010
17. Ibañez L, Ong K, Dunger DB, Zegher F. Early development of adiposity and insulin resistance after catch-up weight gain in small-for-gestational-age children. J Clin Endocrinol Metab. 2006;91(6):2153-8. DOI:10.1210/jc.2005-2778
18. Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C. Life course epidemiology. J Epidemiol Community Health. 2003;57(10):778-83. DOI:10.1136/jech.57.10.778
19. Monteiro PO, Victora CG, Barros FC, Monteiro LM. Birth size, early childhood growth, and adolescent obesity in a Brazilian birth cohort. Int J Obes Relat Metab Disord. 2003;27(10):1274-82. DOI:10.1038/sj.ijo.0802409
20. Oken E, Gillman MW. Fetal origins of obesity. Obes Res. 2003;11(4):496-506. DOI:10.1038/oby.2003.69
21. Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study. BMJ. 2000;320(7240):967-71. DOI:10.1136/bmj.320.7240.967
22. Ong KK, Dunger DB. Birth weight, infant growth and insulin resistance. Eur J Endocrinol. 2004;151(Suppl 3):U131-9.
23. Victora CG, Barros FC, Horta BL, Martorell R. Short-term benefits of catch-up growth for small-for-gestational-age infants. Int J Epidemiol. 2001;30(6):1325-30. DOI:10.1093/ije/30.6.1325
24. Victora CG, Barros FC, Lima RC, Behague DP, Gon alves H, Horta BL, et al. The Pelotas birth cohort study, Rio Grande do Sul, Brazil, 1982-2001. Cad Saude Publica. 2003;19(5):1241-56. DOI:10.1590/S0102-311X2003000500003
25. Victora CG, Barros FC. Cohort profile: the 1982 Pelotas (Brazil) birth cohort study. Int J Epidemiol. 2006;35(2):237-42. DOI:10.1093/ije/dyi290
26. Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternal and child undernutrition: consequences for adult health and human capital. Lancet. 2008;371(9609):340-57. DOI:10.1016/S0140-6736(07)61692-4
27. Williams RL, Creasy RK, Cunningham GC, Hawes WE, Norris FD, Tashiro M. Fetal growth and perinatal viability in California. Obstet Gynecol. 1982;59(5):624-32.
Universidade Federal de Pelotas
R. Mal. Deodoro, 1160
3º andar - Centro
96020-220 Pelotas, RS, Brasil
Article based on the master's dissertation by Martínez JM, presented at Universidade Federal de Pelotas in 2006.
The authors declare that there are no conflicts of interest.