Excessive pre-pregnancy weight is a known risk factor of pregnancy complications. The purpose of this analysis was to assess the relationship between several categories of maternal weight and the risk of developing hypertension and diabetes in pregnancy, and the relationship of these complications with the results of the newborn. It was carried out in a common cohort of pregnant women and taking into account the influence of disturbing factors. Our analysis was conducted in a prospective cohort of 912 Polish pregnant women, recruited during 2015–2016. We evaluated the women who subsequently developed diabetes with dietary modification (GDM-1) (n = 125) and with insulin therapy (GDM-2) (n = 21), as well as the women who developed gestational hypertension (GH) (n = 113) and preeclampsia (PE) (n = 24), compared to the healthy controls. Odds ratios of the complications (and confidence intervals (95%)) were calculated in the multivariate logistic regression. In the cohort, 10.8% of the women had pre-pregnancy obesity (body mass index (BMI) ≥ 30 kg/m²), and 36.8% had gestational weight gain (GWG) above the range of the Institute of Medicine recommendation. After correction for excessive GWG and other confounders, pre-pregnancy obesity (vs. normal BMI) was associated with a higher odds ratio of GH (AOR = 4.94; p < 0.001), PE (AOR = 8.61; p < 0.001), GDM-1 (AOR = 2.99; p < 0.001), and GDM-2 (AOR = 11.88; p <0.001). The threshold risk of development of GDM-2 occurred at lower BMI values (26.9 kg/m²), compared to GDM-1 (29.1 kg/m²). The threshold point for GH was 24.3 kg/m², and for PE 23.1 kg/m². For GWG above the range (vs. GWG in the range), the adjusted odds ratios of GH, PE, GDM-1, and GDM-2 were AOR = 1.71 (p = 0.045), AOR = 1.14 (p = 0.803), AOR = 0.74 (p = 0.245), and AOR = 0.76 (p = 0.672), respectively. The effect of maternal edema on all the results was negligible. In our cohort, hypertension and diabetes were associated with incorrect birth weight and gestational age at delivery. Conclusions: This study highlights the importance and influence of excessive pre-pregnancy maternal weight on the risk of pregnancy complications such as diabetes and hypertension which can impact fetal outcomes.

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.

Whether categories of family history of diabetes can act as independent risk factors for gestational diabetes mellitus (GDM-1, -2) has not yet been established, and neither has it been established how categories of body mass index (BMI) affect these relationships. A group of 912 women without chronic diseases, recruited in the first trimester, was investigated: 125 (13.7%) women developed GDM-1 (treated with diet); 21 (2.3%) women developed GDM-2 (treated with insulin); and a control group consisted of 766 non-diabetic women. A multiple logistic regression was used to evaluate adjusted odds ratios (AOR (95% confidence intervals)) of GDM-1 and GDM-2 for declared diabetes in the parents or grandparents (separately). These relationships were investigated in the whole cohort and subgroups of pre-pregnancy BMI. (1) Some categories of the family history were independent risk factors of GDM-1 or GDM-2. Compared to ‘absence of diabetes in the family’, women with diabetes in the father had a 3.68-fold increase in GDM-1 risk (AOR-b = 3.68 (2.23–6.07)), and women with diabetes in the mother had a 2.13-fold increase in GDM-1 risk (AOR-b = 2.13 (1.1–4.14)) and a 4.73-fold increase in GDM-2 risk (AOR-b = 4.73 (1.26–17.77)). Women with diabetes in the grandmother had a 2.34-fold increase in GDM-1 risk (AOR-b = 2.34 (1.29–4.24)). (2) The cumulative assessment of diabetes in the parents and/or grandparents was not related to the intensification of the risk of GDM, except for the increased risk of GDM-1 for diabetes in both mother and grandmothers simultaneously (AOR-b = 8.80 (1.16–66.57)), however, this group was very small. (3) The analyses in the subgroups of BMI categories showed that diabetes in the father was also an independent risk factor of GDM in the subgroup of pregnant women with normal BMI. In the subgroups of overweight and/or obesity, the risk of GDM for paternal and maternal diabetes was approximately twice as high as compared to the results of pregnant women with normal BMIs. Additionally, apart from the maternal influence of diabetes, the results suggest a significant influence of diabetes in the father on the risk of GDM, even (interestingly) in lean pregnant women.

Early identification of women at risk of developing pregnancy-induced hypertension (PIH) is very important. The involvement of copper (Cu) and zinc (Zn) in the oxidative balance suggests the possibility of their association with this disease, in which oxidative stress plays a key role. However, it has not been established so far whether the microelement levels in early pregnancy may be risk markers of the disease, as prospective studies are limited in number. In our innovative single-center study, we identified from a prospective cohort of healthy women in the 10–14th week of a single pregnancy: women subsequently developing pregnancy-induced hypertension (n = 121) and matched women remaining normotensive (n = 363). We measured the concentrations of microelements in the serum from 10–14 week, using the inductively coupled plasma mass spectrometry (ICP-MS). The odds ratios of the disease (and 95% confidence intervals) were assessed in logistic regression. In the whole cohort, the odds ratio (OR) of PIH was 1.52 (p = 0.174) for women in the lowest (Q1) quartile of Cu (≤1540.58 µg/L) compared with women in the highest (Q4) quartile (>1937.46 µg/L), but adjusted odds ratio (AOR) was 2.17 (p = 0.019) after adjusted for pre-pregnancy body mass index (BMI) and gestational age at recruitment. The higher levels of Cu in the subgroup of BMI ≥ 25 kg/m² compared to normal BMI were found (1847.64 vs. 1673.36 µg/L; p < 0.0001). In the subgroup of women with the normal pre-pregnancy BMI, the adjusted odds ratio of PIH was AOR = 2.95 (p = 0.040) for Q1 vs. Q4 quartile. Our results suggest that lower Cu levels in early pregnancy may be connected with higher risk of PIH, but BMI affected estimated odds ratios. Zinc levels had no effect on the risk.

In the face of the obesity epidemic around the world, attention should be focused on the role of maternal obesity in the development of pregnancy. The purpose of this analysis was to evaluate the prediction of preeclampsia (PE) and isolated gestational hypertension (GH) for a number of maternal factors, in order to investigate the importance of pre-pregnancy obesity (body mass index, BMI ≥ 30 kg/m²), compared to other risk factors (e.g., prior PE, pregnancy weight gain (GWG), infertility treatment, interpregnancy interval, family history, the lack of vitamin supplementation, urogenital infection, and socioeconomic factors). In total, 912 women without chronic diseases were examined in a Polish prospective cohort of women with a single pregnancy (recruited in 2015–2016). Separate analyses were performed for the women who developed GH (n = 113) vs. 775 women who remained normotensive, as well as for those who developed PE (n = 24) vs. 775 controls. The probability of each disease was assessed for the base prediction model (age + primiparity) and for the model extended by one (test) variable, using logistic regression. Three measures were used to assess the prediction: area under curve (AUC) of the base and extended model, integrated discrimination improvement (IDI) (the index shows the difference between the value of the mean change in the predicted probability between the group of sick and healthy women when a new factor is added to the model), and net reclassification improvement (NRI) (the index focuses on the reclassification table describing the number of women in whom an upward or downward shift in the disease probability value occurred after a new factor had been added, including results for healthy and sick women). In the GH prediction, AUC increased most strongly when we added BMI (kg/m²) as a continuous variable (AUC = 0.716, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.068, p < 0.001). The addition of BMI as a continuous variable or BMI ≥ 25 kg/m² improved the classification for healthy and sick women the most (NRI = 0.571, p < 0.001). In the PE prediction, AUC increased most strongly when we added BMI categories (AUC = 0.726, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.050, p = 0.080). The addition of BMI categories improved the classification for healthy and sick women the most (NRI = 0.688; p = 0.001). After summing up the results of three indexes, the probability of hypertension in pregnancy was most strongly improved by BMI, including BMI ≥ 25 kg/m² for the GH prediction, and BMI ≥ 30 kg/m² for the PE prediction. Main conclusions: Pre-pregnancy BMI was the most likely factor to increase the probability of developing hypertension in pregnancy, compared to other risk factors. Hierarchies of PE and GH risk factors may suggest different (or common) mechanisms of their development.

Microelements involved in the oxidative balance have a significant impact on human health, but their role in pregnancy are poorly studied. We examined the relationships between first trimester levels of selenium (Se), iron (Fe), zinc (Zn), and copper (Cu), as well as maternal characteristics and pregnancy results. The data came from a Polish prospective cohort of women in a single pregnancy without chronic diseases. A group of 563 women who had a complete set of data, including serum microelements in the 10–14th week was examined, and the following were found: 47 deliveries <37th week; 48 cases of birth weight 90th percentile; 13 intrauterine growth restriction (IUGR) cases; 105 gestational hypertension (GH) and 15 preeclampsia (PE) cases; and 110 gestational diabetes mellitus (GDM) cases. The microelements were quantified using mass spectrometry. The average concentrations (and ranges) of the elements were as follows: Se: 60.75 µg/L (40.91–125.54); Zn: 618.50 µg/L (394.04–3238.90); Cu: 1735.91 µg/L (883.61–3956.76); and Fe: 1018.33 µg/L (217.55–2806.24). In the multivariate logistic regression, we found that an increase in Se of 1 µg/L reduces the risk of GH by 6% (AOR = 0.94; p = 0.004), the risk of IUGR by 11% (AOR = 0.89; p = 0.013), and the risk of birth <34th week by 7% (but close to the significance) (AOR = 0.93; p = 0.061). An increase in Fe of 100 µg/L reduces the risk of PE by 27% (AOR = 0.73; p = 0.009). In the multivariable linear regression, we found negative strong associations between prepregnancy BMI, Se (β = −0.130; p = 0.002), and Fe (β = −0.164; p < 0.0001), but positive associations with Cu (β = 0.320; p < 0.000001). The relationships between Se and maternal age (β = 0.167; p < 0.0001), Se and smoking (β = −0.106; p = 0.011) and Cu, and gestational age from the 10–14th week (β = 0.142; p < 0.001) were also found. Secondary education was associated with Zn (β = 0.132; p = 0.004) and higher education was associated with Cu (β = −0.102; p = 0.023). A higher financial status was associated with Fe (β = 0.195; p = 0.005). Other relationships were statistically insignificant. Further research is needed to clarify relationships between first trimester microelements and pregnancy complications. In addition, attention should be paid to lifestyle-related and socioeconomic factors that affect microelement levels.