The Role of Maternal Weight in the Hierarchy of Macrosomia Predictors; Overall Effect of Analysis of Three Prediction Indicators

Lewandowska, Maria

doi:10.3390/nu13030801

Cited by 14 publications

(21 citation statements)

References 52 publications

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“…The risk profiles were not assessed in any study. Many previous studies confirmed the associations between a higher macrosomia risk and maternal obesity [13][14][15]17,18,20] or between fetal growth restriction (FGR) risk and maternal obesity [3,18,25,33] or underweight [33][34][35]. However, these studies were retrospective and also did not include subgroup analyses or risk profiles (as was the case in our study).…”

Section: Discussionsupporting

confidence: 76%

“…Interventions should be multi-directional (involving diet, physical activity, and health-promoting behavior) and should be carried out by multidisciplinary teams [1]. Dietary guidelines (worldwide and in Poland) for pregnant women have been described in our previous works [4,13].…”

Section: Discussionmentioning

confidence: 99%

“…Macrosomic neonates have a significantly higher risk of childhood obesity (by 50%) and a higher risk of premature cardiovascular death (by 35%) [1,[12][13][14][15]. This intergenerational cycle of obesity fits into the theories of fetal development non-infectious diseases 2 of 18 in line with the concept of Developmental Origins of Health and Disease (DOHaD) [1].…”

Section: Introductionmentioning

confidence: 88%

“…The definitions of birth weight in grams were as follows: macrosomia is >4000 g regardless of gestational age [12]; low birth weight (LBW) is <2500 g regardless of gestational age [10]; the correct birth weight is 2500−4000 g (which was a reference category in statistical analyses). Birth weight expressed in percentiles (for a specific population, fetal sex and gestational age) covered large-for-gestational age (LGA) (the birth weight >90th percentile), appropriate-for-gestational age (AGA) (the weight 10-90th percentile) and small-for-gestational age (SGA) (the birth weight <10th percentile without cases of fetal growth restriction), according to the Polish percentile grids as described in our earlier work [13]. SGA refers to fetuses that are constitutionally small, consistent with their (genetic) growth potential [28].…”

Section: Definitions Of Dependent Variablesmentioning

confidence: 99%

“…Macrosomia has also been linked to neuro-developmental disorders in children [3]. Many studies have shown associations of maternal obesity with macrosomia risk [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Maternal Obesity and Risk of Low Birth Weight, Fetal Growth Restriction, and Macrosomia: Multiple Analyses

Lewandowska

2021

Nutrients

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The associations between maternal pre-pregnancy obesity and low birth weight (LBW, <2500 g) remain inconclusive. Therefore, birth weight in a Polish prospective cohort of 912 mothers was investigated depending on the pre-pregnancy body mass index (BMI). The whole cohort and the subgroup of gestational weight gain (GWG) in the range of the Institute of Medicine (IOM) recommendations, as well as ‘healthy’ women (who did not develop diabetes or hypertension in this pregnancy) were investigated. Adjusted odds ratios (AOR) of the newborn outcomes (with 95% confidence intervals, CI) for obesity (BMI ≥ 30 kg/m2) vs. normal BMI (18.5−24.9 kg/m2) were calculated using multiple logistic regression. Risk profiles (in the Lowess method) were presented for BMI values (kg/m2) and threshold BMI values were calculated. (1) In the cohort, LBW affected 6.6% of pregnancies, fetal growth restriction (FGR) 2.3%, and macrosomia 10.6%. (2) The adjusted risk of macrosomia was more than three-fold higher for obesity compared to normal BMI in the whole cohort (AOR = 3.21 (1.69−6.1), p < 0.001) and the result was maintained in the subgroups. A 17-fold higher adjusted LBW risk for obesity was found (AOR = 17.42 (1.5−202.6), p = 0.022), but only in the normal GWG subgroup. The FGR risk profile was U-shaped: in the entire cohort, the risk was more than three times higher for obesity (AOR = 3.12 (1.02−9.54), p = 0.045) and underweight (AOR = 3.84 (1.13−13.0), p = 0.031). (3) The risk profiles showed that the highest BMI values were found to be associated with a higher risk of these three newborn outcomes and the threshold BMI was 23.7 kg/m2 for macrosomia, 26.2 kg/m2 for LBW, and 31.8 kg/m2 for FGR. These results confirm the multidirectional effects of obesity on fetal growth (low birth weight, fetal growth restriction, and macrosomia). The results for LBW were heavily masked by the effects of abnormal gestational weight gain.

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Section: Discussionsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 88%

Section: Definitions Of Dependent Variablesmentioning

confidence: 99%

“…Macrosomia has also been linked to neuro-developmental disorders in children [3]. Many studies have shown associations of maternal obesity with macrosomia risk [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Maternal Obesity and Risk of Low Birth Weight, Fetal Growth Restriction, and Macrosomia: Multiple Analyses

Lewandowska

2021

Nutrients

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Maternal Height Is an Independent Risk of Adverse Outcomes in Women with Gestational Diabetes Mellitus

Du,

Muhuza,

Tang

et al. 2023

Diabetes Ther

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Introduction Maternal height has been shown to be associated with adverse outcomes in women with gestational diabetes mellitus (GDM). The aim of this study is to evaluate the association between maternal height and adverse outcomes stratified for gestational weight gain (GWG) and pre-pregnancy body mass index (BMI) in women with GDM. Methods We conducted a retrospective study that included 2048 women diagnosed with GDM during 24–28 gestational weeks from July 1, 2017, to June 30, 2018, in Zhejiang Province, China. Demographic data, maternal characteristics and pregnancy complications were extracted from medical records. Maternal height was divided into three categories by tertiles. Chi-square was used to evaluate categorical data while one-way ANOVA was utilized to analyze continuous variables. The relationship between maternal height and adverse outcomes was examined using logistic regression. Results We found that shorter women had higher rates of low birth weight (LBW) ( p = 0.003) and primary cesarean section (primary CS) ( p < 0.001) while taller women had higher rates of abnormal neonatal ponderal index ( p < 0.001), postpartum hemorrhage ( p = 0.044) and macrosomia ( p < 0.001). In taller women who had excess GWG, maternal height was positively associated with the risk of macrosomia (aOR 1.97, 95% CI 0.95–4.10). In shorter women who had inadequate GWG, maternal height was significantly associated with LBW (aOR 2.20, 95% CI 1.13–4.29) and primary CS (aOR 2.08, 95% CI 1.38–3.12). Maternal height was a protective factor of postpartum hemorrhage (aOR 0.15, 95% CI 0.03–0.72) in shorter women with excess GWG. In women with normal pre-pregnancy BMI, maternal height was positively associated with LBW (aOR 2.00, 95% CI 1.15–3.49) and primary CS (aOR 1.71, 95% CI 1.28–2.28) in shorter women while it was negatively associated with the risk of abnormal neonatal ponderal index in both shorter and taller women compared to average height women (aOR 0.71, 95% CI 0.55–0.92; aOR 0.66, 95% CI 0.51–0.85). Conclusion The association between maternal height and adverse pregnancy outcomes varies with pre-pregnancy BMI and GWG in GDM women. Taking maternal height, pre-pregnancy BMI and GWG into account and using personalized prenatal management may reduce the risk of adverse pregnancy outcomes in GDM.

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Prevalence and risk factors of gestational diabetes in the health region of Lleida: a retrospective observational cohort study

Orós

Perejón

Serna

et al. 2023

J Endocrinol Invest

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Background Diabetes is a very common metabolic condition during pregnancy. The number of cases increases with age and obesity. The prevalence of pre-gestational diabetes and gestational diabetes (GD) differs between different ethnic groups. Objective The aim of the study was to analyse the prevalence of pre-gestational diabetes and GD in the health region of Lleida. We also studied the GD risk factors during pregnancy according to the country of origin of the pregnant woman. Methods We performed a retrospective observational cohort study among pregnant women between 2012 and 2018 in the health region of Lleida. A multivariate model was performed with the different variables analysed by calculating the regression coefficient and its 95% confidence interval (CI). Results In our sample of 17,177 pregnant women, we observed a prevalence of pre-gestational diabetes and GD of 8.2% and 6.5%, respectively. We found a relationship of gestational diabetes with different factors: age, with 6.8% in 30–34 year-old women and 11.3% in women over 35 (OR 1.78 and 3.29, respectively); overweight, with 8.29% (OR 1.89); and obesity, with 12.9% (OR 3.15). Finally, women from Asia and the Middle East and the Maghreb had a higher risk of diabetes, with 12.2% (OR 2.1) and 9.91% (OR 1.3), respectively, and Sub-Saharan women had a lower risk of it 6.07% (OR 0.71). Conclusions GD has different risk factors, such as age, overweight, and obesity. Non-related conditions include hypothyroidism, arterial hypertension, and dyslipidaemia. Finally, pregnant women from the Maghreb, and Asia and the Middle East, are at higher risk of developing diabetes during pregnancy; meanwhile, Sub-Saharan origin is protector factor.

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The Role of Maternal Weight in the Hierarchy of Macrosomia Predictors; Overall Effect of Analysis of Three Prediction Indicators

Cited by 14 publications

References 52 publications

Maternal Obesity and Risk of Low Birth Weight, Fetal Growth Restriction, and Macrosomia: Multiple Analyses

Maternal Obesity and Risk of Low Birth Weight, Fetal Growth Restriction, and Macrosomia: Multiple Analyses

Maternal Height Is an Independent Risk of Adverse Outcomes in Women with Gestational Diabetes Mellitus

Prevalence and risk factors of gestational diabetes in the health region of Lleida: a retrospective observational cohort study

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