Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis

The optimal range of gestational weight gain (GWG) was recently raised in Japan. This may help reduce small-for-gestational-age (SGA) infants, but may also increase large-for-gestational-age (LGA) infants. This study performed hypothetical experiments to determine effective GWG advice based on quantile regression analysis. In a total of 354,401 singleton pregnancies registered in the perinatal database of the Japan Society of Obstetrics and Gynecology (2013–2017), the proportions of SGA and LGA were 9.33% and 11.13%, respectively. Using regression coefficients of GWG across the birth weight-for-gestational-age quantile distribution, we analyzed changes in their proportions by simulating a uniform 3-kg extra increase in GWG or an increase or decrease based on GWG adequacy. A hypothetical experiment of a uniform increase in GWG resulted in SGA and LGA proportions of 7.26% (95% confidence interval 7.15–7.36) and 14.51% (14.37–14.66), respectively. By contrast, assuming a 3-kg increase in women with inadequate GWG and a 3-kg decrease in women with excessive GWG resulted in SGA and LGA proportions of 8.42% (8.31–8.54) and 11.50% (11.37–11.62), respectively. Our real-world data analysis suggests that careful adjustment of GWG based on GWG adequacy will be effective in optimizing infant birth weight in Japan


Gestational weight gain advice to optimize infant birth weight in
Univariable linear regression analysis (OLS method) 8 Table S3 Multivariable linear regression (OLS method) and quantile regression analyses 9 Table S4 Akaike's Information Criterion (AIC) scores of the multivariable quantile regression models

Table S5
Characteristics of a subsample of 859 women 10 Table S6 Classification according to gestational weight gain adequacy at 40 weeks in the subsample population (n = 859) 2 Supporting Method 1.

Concordance of GWG adequacy over the gestational period
We performed a retrospective cohort analysis of pregnant women who delivered their newborns at Tokyo Medical and Dental University Hospital from 2013 to 2017 (1).Maternal weight measurements during gestation were performed 11.3 ± 3.1 times for each woman.For consistency with the conditions of the main analysis, included were women with a primipara singleton delivery.As a result, 859 women were eligible (Table S5).All data analyzed had a good fit in the simple linear regression for the relationship between gestational weeks and weight gain, so GWG at each gestational week, including at 40 weeks, was calculated from the rate of weight gain similar to the main analysis.
First, the women were classified as underweight, normal weight, overweight, or obese based on their prepregnancy BMI.GWG adequacy at 40 weeks was determined based on JSOG guidance (the adequate range for GWG at 40 weeks was 12-15, 10-13, and 7-10 kg for underweight, normal weight, and overweight, respectively) (2).Then, underweight, normal weight, and overweight women were further divided into the following three groups, resulting in nine groups (Table S6): inadequate, adequate, and excessive GWG.Next, GWG adequacy at each week of gestation was determined based on the GWG growth chart (3).In each of the nine groups, the proportion of GWG adequacy classifications was calculated from 15 to 40 weeks.A graph was drawn with the x-axis representing the weeks of gestation and the y-axis representing the proportion to show, for example, the result that the proportion of those with inadequate GWG exceeded 75% from 15 weeks throughout gestation in the underweight group with inadequate GWG at 40 weeks (Figure 2).Supporting Method 2.

Calculation of BWGA Z-scores after hypothetical experiments
We estimated the effects of hypothetical GWG change experiments using coefficient estimates from the quantile regression models in a similar manner to that previously described (4).
In the hypothetical experiments, GWG parameters were changed.Therefore, the resultant outcome, BWGA Z-score (post), was expressed as: Japan: A quantile regression analysis using a nationwide perinatal database Noriko Sato, MD PhD; Rei Haruyama, MD MSc; Naoyuki Miyasaka MD according to gestational weight gain adequacy at 40 weeks in the study population derived from JSOG Database (n = 354,401) 7 Table where BWGA Z-score (post) is the BWGA Z-score after a given hypothetical experiment, BWGA Zscore (pre) is the original BWGA Z-score, GWG change is the normalized value of GWG change in the hypothetical experiment, CoefGWG i and CoefGWGx BMI i are coefficient estimates of GWG and GWG × body mass index (BMI) from the quantile regression at the location of BWGA Z-score in the ith range, and BMI is the normalized log-transformed prepregnancy BMI value.

FIGURE S2.
FIGURE S2.Sensitivity analysisMultivariable quantile regression analysis, excluding the women with hypertensive disorders of pregnancy, diabetes mellitus, autoimmune disease, assisted reproductive technology, smoking during pregnancy, under 20 and over 35 years old were performed.The black dots and gray bands indicate the coefficient estimates at each quantile and 95% confidence interval (CI), respectively, which were obtained using multivariate quantile regression analysis.The red solid and dashed lines indicate the OLS coefficients (0.218) and their 95% CIs (0.214, 0.223), respectively, which were obtained using conventional multivariable linear regression analysis.The covariates were maternal age, height, prepregnancy BMI.

TABLE S1 .
Classification according to gestational weight gain adequacy at 40 weeks in the study population derived from the Japan Society of Obstetrics and Gynecology Perinatal Database,

TABLE S2 .
Univariable linear regression analysis (Ordinary least squares regression method) for maternal factors on birthweight for gestational age (BWGA) Z-score

TABLE S3 .
Multivariable linear regression (Ordinary least squares regression method) and quantile regression analyses for maternal factors on birthweight for gestational age (BWGA) Z-score -0.256, - All the p values for the association was less than 0.00001 except for maternal age at 5 th quantile ( p = *

TABLE S4 .
Akaike's Information Criterion (AIC) scores of the multivariable quantile regression

TABLE S5 .
Characteristics of a subsample of 859 women

TABLE S6 .
Classification according to gestational weight gain adequacy at 40 weeks in the subsample population (n = 859) NA, not applicable.GWG, gestational weight gain