Background Self-reported pre-pregnancy weight and weight measured in the first trimester are both used to estimate pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) but there is limited information on how they compare, especially in low- and middle-income countries, where access to a weight scale can be limited. Thus, the main goal of this study was to evaluate the agreement between self-reported pre-pregnancy weight and weight measured during the first trimester of pregnancy among Brazilian women so as to assess whether self-reported pre-pregnancy weight is reliable and can be used for calculation of BMI and GWG. Methods Data from the Brazilian Maternal and Child Nutrition Consortium (BMCNC, n = 5563) and the National Food and Nutritional Surveillance System (SISVAN, n = 393,095) were used to evaluate the agreement between self-reported pre-pregnancy weight and weights measured in three overlapping intervals (30–94, 30–60 and 30–45 days of pregnancy) and their impact in BMI classification. We calculated intraclass correlation and Lin’s concordance coefficients, constructed Bland and Altman plots, and determined Kappa coefficient for the categories of BMI. Results The mean of the differences between self-reported and measured weights was < 2 kg during the three intervals examined for BMCNC (1.42, 1.39 and 1.56 kg) and about 1 kg for SISVAN (1.0, 1.1 and 1.2 kg). Intraclass correlation and Lin’s coefficient were > 0.90 for both datasets in all time intervals. Bland and Altman plots showed that the majority of the difference laid in the ±2 kg interval and that the differences did not vary according to measured first-trimester BMI. Kappa coefficient values were > 0.80 for both datasets at all intervals. Using self-reported pre-pregnancy or measured weight would change, in total, the classification of BMI in 15.9, 13.5, and 12.2% of women in the BMCNC and 12.1, 10.7, and 10.2% in the SISVAN, at 30–94, 30–60 and 30–45 days, respectively. Conclusion In Brazil, self-reported pre-pregnancy weight can be used for calculation of BMI and GWG when an early measurement of weight during pregnancy is not available. These results are especially important in a country where the majority of woman do not initiate prenatal care early in pregnancy.
Pooled data analysis in the field of maternal and child nutrition rarely incorporates data from low- and middle-income countries and existing studies lack a description of the methods used to harmonize the data and to assess heterogeneity. We describe the creation of the Brazilian Maternal and Child Nutrition Consortium dataset, from multiple pooled longitudinal studies, having gestational weight gain (GWG) as an example. Investigators of the eligible studies published from 1990 to 2018 were invited to participate. We conducted consistency analysis, identified outliers, and assessed heterogeneity for GWG. Outliers identification considered the longitudinal nature of the data. Heterogeneity was performed adjusting multilevel models. We identified 68 studies and invited 59 for this initiative. Data from 29 studies were received, 21 were retained for analysis, resulting in a final sample of 17,344 women with 72,616 weight measurements. Fewer than 1% of all weight measurements were flagged as outliers. Women with pre-pregnancy obesity had lower values for GWG throughout pregnancy. GWG, birth length and weight were similar across the studies and remarkably similar to a Brazilian nationwide study. Pooled data analyses can increase the potential of addressing important questions regarding maternal and child health, especially in countries where research investment is limited.
Objectives To evaluate the association of pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) on infant gut microbiota diversity and abundance and the role of breastfeeding on this association. Methods Prospective cohort conducted in Rio de Janeiro, Brazil. Maternal pre-pregnancy BMI (< 25; ≥ 25 kg/m², normal/excessive) and GWG adequacy (adequate; excessive) were the exposures and breastfeeding practice status (exclusively breastfeeding EBF; predominant/complementary feeding PCF) was analyzed as an effect modifier. Infant stool samples were collected for 56 infants between 26–45 days. Samples were sequenced using 16S rRNA gene sequencing (MiSeq). Analysis included alpha diversity indexes (Shannon, Faith-PD, and Observed species), beta diversity metrics and Wilcoxon-Mann-Whitney Test, linear regression, permutational multivariate analysis of variance and linear discriminant analysis effect size. Results A higher median alpha diversity in infants born from mothers with excessive GWG was observed (Mann-Whitney Test: P = 0.005) and infants born from mothers with excessive GWG were positively associated with alpha diversity (β = 0.351; SE = 0.146; p-value = 0.020). Gut microbiota of infants born from mothers with excessive pre-pregnancy BMI were enriched with Dialister genus and Lactobacillus Ruminis, Haemophilus Parainfluenzae and Veillonella Parvula species and those born from mother with excessive GWG had higher abundance of Staphylocococcus genus, Staphylococcaceae family, Bacillales order and Bacilli class. Infant gut microbiota diversity and abundance did not differ according to combined categories of pre-pregnancy BMI and breastfeeding status and GWG and breastfeeding. Conclusions Maternal gestational weight gain was associated with diversity of the infant gut microbiota. Breastfeeding did not an effect modifier in this association. Funding Sources Foundation for the Support of Research of the State of Rio de Janeiro, National Council for Scientific and Technological Development and Columbia University Grant.
Objectives To evaluate the association between gestational weight gain (GWG) classified according to three international charts and adverse child outcomes in the Brazilian population. Methods Data from 12 cohorts conducted in Brazil (1990-2018) were combined in a pooled dataset of 15,066 women. Weight and gestational age were measured. Adult (18-48 years) women with singleton pregnancies and free of hypertension and diabetes were included. Selected centiles of three international charts were used [Life-cycle project – L charts, Intergrowth-21st - I chart and Hutcheon – H charts]. Total GWG was calculated as: difference between the weight measured up to 14 days before delivery and the weight measured in the 1st trimester (I chart) or the pre-pregnancy self-reported weight (L and H charts). The outcomes were small and large for gestational age infants (SGA/LGA, < 10th/ > 90th - Intergrowth centile), low birth weight (LBW, < 2500g) and macrosomia (> 4000g). Multinomial logistic regressions were fitted for selected centiles (lowest: 3rd, 5th, 10th, 25th; highest: 75th, 90th, 95th, 97th) to evaluate the charts’ performance in the prediction of the outcomes. Results A total of 7,456 women were included in the analysis. Total GWG was 12.1 kg (SD = 5.9) and GWG from the 1st trimester to delivery 10.9 kg (SD = 4.8). The prevalence of SGA was 6.6%, LGA, 14.9%, LBW, 6.5% and macrosomia, 4.7%. For all charts, women who gained weight in the lowest centiles presented higher prevalences of SGA and LBW in comparison to those on the highest centiles, while women with gains in the highest centiles, presented higher prevalences of LGA and macrosomia. L charts presented a better performance to predict outcomes, i.e., women with gains in the highest centiles were associated with increased odds of LGA and macrosomia and those in the lowest centiles with increased odds for SGA and LBW. Analysis based on H charts provided similar results. The poorest performance was observed for I charts, in which only women with gains on the higher centiles were associated with the occurrence of LGA (Figure). Conclusions L charts seem to better predict the occurrence of child outcomes. Further investigation is needed to decide the most appropriate chart and cutoffs for GWG recommendations for the Brazilian population, considering maternal and child adverse outcomes. Funding Sources The Brazilian National Council for Scientific and Technological Development and Bill and Melinda Gates Foundation. Supporting Tables, Images and/or Graphs
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