Abstract
Obese pregnant women are more likely to develop hypertensive disorders of pregnancy (HDP), which puts them at risk for future cardiovascular events and type 2 diabetes. This study aimed to investigate the relationship between body weight and HDP in nondiabetic singleton-pregnant women. We examined the KODMO database, which included 5,120 pregnant women who gave birth at NHO Kokura Medical Center between January 2009 and December 2019, excluding those with pre-existing diabetes mellitus, hypertension, or multiple pregnancies. A multivariate logistic regression analysis of potential HDP risk factors revealed that both pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) were independent risk factors. The estimated impact was considerably greater in women with higher pre-pregnancy BMI, with odds ratios of 1.60 (95% CI: 1.18–2.18, p = 0.0025) for obesity degree 1 (25 ≤ BMI < 30 kg/m2) and 3.42 (95% CI: 2.35–5.01, p < 0.0001) for obesity degree ≥2 (BMI ≥ 30 kg/m2) (reference: normal weight [18.5 ≤ BMI < 25 kg/m2]). GWG was further investigated by stratifying BMI categories, which revealed that obese pregnant women have a risk of developing HDP even with the normal GWG defined by current guidelines. The odds ratio of HDP in pregnant women with normal GWG was 1.79 (95% CI: 1.02–3.41, p = 0.0436) in obesity degree 1 and 3.25 (95% CI: 1.57–6.74, p < 0.0001) in obesity degree ≥2. The impact of GWG as a modifiable factor of HDP varies with pre-pregnancy BMI, highlighting the importance of weight management before and during pregnancy.
Introduction
Hypertensive disorders of pregnancy (HDP) are characterized as hypertension (140/90 mm Hg or higher) during pregnancy, which can be fatal to both the mother and the child, especially if accompanied by organ damage [1]. In Japan, HDP is estimated to occur in approximately 5–10% of pregnant women [2]. HDP, along with gestational diabetes mellitus (GDM), has been linked to the mother’s later development of cardiovascular disease and type 2 diabetes [3-6].
Older age at delivery, obesity, excessive gestational weight gain (GWG), multiple pregnancies, primipara or long interpregnancy interval pregnancy, comorbidity of hypertension, diabetes mellitus including GDM, or antiphospholipid antibody syndrome, assisted reproductive technology (ART) pregnancy, smoking habit, and a family history of pre-eclampsia, type 2 diabetes mellitus, or hypertension are all considered risk factors for HDP development. In the past, there was a widespread belief in Japan that avoiding excessive weight gain during pregnancy would reduce the risk of developing gestational hypertension [7]. However, there was some concern that they may have gained less than the normal weight gain. Furthermore, many normal weight and underweight Japanese women preferred to be thin, and even during pregnancy, they aimed to keep their weight below the upper limit of gestational weight gain [8]. Low maternal body weight and poor gestational weight gain due to undernutrition are thought to increase the proportion of low birthweight (LBW) infants at high risk for future disease [9]. Indeed, despite a well-developed healthcare system, Japan has the third highest prevalence of LBW among the Organisation for Economic Co-operation and Development (OECD) countries [10].
To address these concerns, the Japan Society of Obstetrics and Gynecology and the Ministry of Health, Labour and Welfare released a new guideline for appropriate GWG in 2021. The GWG management objectives were determined for each pre-pregnancy body shape category based on BMI [11]. In comparison to previous guidelines, an additional GWG of approximately 3 kg is now considered acceptable in all categories [11].
On the other hand, excessive GWG as well as pre-pregnancy obesity, are known risk factors for the development of GDM and HDP. Regarding GDM, active screening during pregnancy, glycemic control, GWG control for prevention, and even postpartum follow-up are recommended in collaboration with obstetrics and internal medicine [11, 12]. However, there is no strong evidence that GWG influences the incidence of HDP in pregnant Japanese women. We hypothesized that the impact of GWG on the development of HDP is dependent on pre-pregnancy BMI and organized the Kokura Diabetes and Maternal Obesity (KODMO) study. Therefore, this study was aimed to investigate the relationship between varying degrees of GWG and the development of HDP in Japanese pregnant women who were stratified by their pre-pregnancy body shape in the retrospective observational KODMO study.
Methods
Subjects
The KODMO study has been established as a database for pregnancy and maternal metabolic disorders, such as obesity, GDM, and HDP.
In the KODMO study, we conducted a retrospective analysis of 5,975 pregnancies that resulted in delivery after 22 weeks of gestation at the Department of Obstetrics and Gynecology, NHO Kokura Medical Center from January 2009 to December 2019. In cases where there were more than two deliveries in our hospital, each pregnancy was assigned a case number. Primary analysis was performed on 5,120 cases, excluding pregnancies with missing maternal height and weight data (pre-pregnancy or at delivery), pregnancies complicated by diabetes mellitus or hypertension, and multiple pregnancies (Fig. 1).
Fig. 1
Flow diagram of this study
HDP is characterized as hypertension (140/90 mm Hg or higher) during pregnancy [13]. In this study, we concentrated on pregnancy-induced hypertension (gestational hypertension and preeclampsia) to determine the impact of pre-pregnancy BMI and GWG. To ensure a homogeneous analysis of pregnancy-related hypertension, cases of pre-existing hypertension were excluded. Diabetes mellitus and GDM were diagnosed using the criteria established by the Japan Diabetes Society and the Japan Society of Obstetrics and Gynecology guidelines [11, 14]. The pre-pregnancy BMI, based on self-report, less than 18.5 kg/m2 was classified as underweight; between 18.5 kg/m2 and 25 kg/m2, normal weight; between 25.0 kg/m2 and 30.0 kg/m2, obesity degree 1; 30 kg/m2 and above, obesity degree ≥2, according to the Japanese obesity criteria by Japan Society for the Study of Obesity [15], which are lower than the current WHO cut-off point for obesity categories. GWG management objectives include 12 to 15 kg for underweight pregnant women, 10 to 13 kg for normal weight, and 7 to 10 kg for obesity degree 1, set individually with a maximum of 5 kg for obesity degree ≥2 (BMI ≥ 30) [11]. For obesity degree ≥2 pregnant women, we defined low GWG as <0 kg, normal GWG as 0 to 5 kg, and high GWG as >5 kg (Table 1). Threatened premature delivery was defined as labor that began before 37 weeks. Premature rupture was defined as breaking the amniotic sac before labor begins. Premature delivery was defined as birth before 37 weeks gestation. Low birth weight (LBW), normal birth weight, and high birth weight were defined as birth weights of less than 2,500 g, 2,500–4,000 g, and more than 4,000 g, respectively. Small for gestational age (SGA) and large for gestational age (LGA) were defined as birth weights less than the 10th percentile or more than 90th percentile for gestational age, respectively.
Table 1 Definitions of Pre-pregnancy category of body shape and GWG criteria
| Category |
BMI (kg/m2) |
Low GWG (kg) |
Normal GWG (kg) |
High GWG (kg) |
| Underweight |
<18.5 |
<12 |
12–15 |
>15 |
| Normal weight |
18.5–24.9 |
<10 |
10–13 |
>13 |
| Obesity degree 1 |
25.0–29.9 |
<7 |
7–10 |
>10 |
| Obesity degree ≥2 |
≥30.0 |
<0# |
0–5# |
>5# |
#For pregnant women with an obesity ≥2, GWG are determined on an individually basis. Gestational weight gain, GWG; Body mass index, BMI
Data is presented as mean ± standard deviation or medians (interquartile ranges, IQR) for continuous variables. The t-test or Wilcoxon test was used to compare parametric and nonparametric values, respectively. Categorical variables are presented as counts and percentages [n (%)], with comparisons using the chi-square (χ2) test or Cochran-Armitage test. Among the known risk factors for HDP, the data gathered from the medical records in this study included age, pre-pregnancy BMI, GWG, history of ART, occurrence of GDM, and smoking habits (passive or active). These risk factors were investigated using multivariate logistic regression analysis to determine their relationship with HDP incidence. The impact of pre-pregnancy BMI (underweight, normal weight, obesity degree 1, and obesity degree ≥2) on the development of GDM and HDP was estimated using logistic regression analysis. Additionally, the risk of developing HDP across the three GWG categories within each pre-pregnancy BMI group was evaluated using logistic regression. Because GWG depends on the gestational age at delivery, all analyses were adjusted for the gestational age at delivery. All statistical analyses were carried out using JMP Pro version 17.1.0 (SAS Institute Inc., Cary, NC, USA). p-values <0.05 were deemed statistically significant.
Research ethics statement
This study was planned following the Ethical Guidelines for Medical and Biological Research Involving Human Subjects by the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government, as well as the World Medical Association Declaration of Helsinki, and approved by the NHO Kokura Medical Center Ethics Committee (Approval number: COI2022-014), which dismissed the requirement for individual informed consent based on the “opt-out” principle.
Results
This study screened 5,975 cases, and 5,120 cases were included in the analysis, excluding subjects with missing data, those with pregnancies complicated by diabetes or hypertension, and multiple gestations (Fig. 1). Table 2 shows the background characteristics of pregnant women in general, as well as groups with and without HDP.
Table 2 Background characteristics
|
All, N = 5,120 |
HDP (–), n = 4,743 |
HDP (+), n = 377 |
p value |
| Maternal age |
31.8, 5.7 |
31.7, 5.7 |
32.1, 5.7 |
0.1987 |
| Primipara (%) |
2,670/5,120 (52.1) |
2,425/4,743 (51.1) |
245/377 (65.0) |
<0.0001 |
| ART (%) |
611/5,120 (11.9) |
561/4,743 (11.8) |
50/377 (13.2) |
0.4082 |
| Smoking (%) |
1,353/3,606 (37.5) |
1,264/3,335 (37.9) |
89/271 (32.8) |
0.0490 |
| Height (cm) |
157.3, 5.5 |
157.3, 5.5 |
157.7, 5.3 |
0.1799 |
| Pre-pregnancy body weight (kg) |
52.0 (47.0, 58.0) |
51.2 (47.0, 57.0) |
54.0 (48.0, 63.0) |
<0.0001 |
| Pre-pregnancy BMI (kg/m2) |
20.8 (19.1, 23.1) |
20.7 (19.1, 22.9) |
21.7 (19.7, 25.0) |
<0.0001 |
| Underweight (%) |
847/5,120 (16.5) |
807/4,743 (17.0) |
40/377 (10.6) |
<0.0001 |
| Normal weight (%) |
3,552/5,120 (69.4) |
3,309/4,743 (69.8) |
243/377 (64.5) |
| Obesity, 1 (%) |
532/5,120 (10.5) |
476/4,743 (10.0) |
56/377 (14.9) |
| Obesity, 2 (%) |
189/5,120 (3.7) |
151/4,743 (3.2) |
38/377 (10.1) |
| Gestational weight gain (%) |
19.7, 9.5 |
19.6, 9.4 |
19.5, 10.7 |
0.7695 |
| Gestational week at delivery |
37.5, 2.7 |
37.6, 2.6 |
36.8, 3.2 |
<0.0001 |
| GDM (%) |
211/5,120 (4.1) |
196/4,743 (4.1) |
15/377 (4.0) |
0.8852 |
| GDM, underweight (%) |
23/847 (2.7) |
21/807 (2.6) |
2/40 (5.0) |
|
| GDM, normal weight (%) |
112/3,552 (3.2) |
106/3,309 (3.2) |
6/243 (2.4) |
|
| GDM, obesity, 1 (%) |
49/532 (9.2) |
43/476 (9.0) |
6/56 (10.7) |
|
| GDM, obesity, 2 (%) |
27/189 (14.2) |
26/151 (17.2) |
1/38 (2.6) |
|
| Threatened premature delivery (%) |
1,743/5,120 (34.0) |
1,669/4,743 (35.2) |
74/377 (19.6) |
<0.0001 |
| Premature rupture (%) |
362/5,120 (7.0) |
347/4,743 (7.3) |
15/377 (4.0) |
0.0150 |
| Premature delivery (%) |
1,032/5,120 (20.1) |
906/4,743 (19.1) |
126/377 (33.4) |
<0.0001 |
| Cesarean section (%) |
1,673/5,120 (32.7) |
1,532/4,743 (32.3) |
141/412 (37.4) |
0.0421 |
| Neonatal weight at birth (g) |
2,765.7, 580.8 |
2,786.5, 558.9 |
2,504.3, 761.8 |
<0.0001 |
| Low BW (%) |
1,275/5,120 (24.9) |
1,119/4,743 (23.6) |
156/377 (41.4) |
<0.0001 |
| Normal BW (%) |
3,817/5,120 (74.6) |
3,598/4,743 (75.9) |
219/377 (58.1) |
| High BW (%) |
27/5,120 (0.5) |
25/4,743 (0.5) |
2/377 (0.5) |
| SGA (%) |
225/5,120 (4.4) |
197/4,743 (4.2) |
28/377 (7.4) |
0.0028 |
| LGA (%) |
160/5,120 (3.1) |
155/4,743 (3.3) |
5/377 (1.3) |
0.0370 |
Hypertensive disorders of pregnancy, HDP; Assisted reproductive technology, ART; Gestational weight gain, GWG; body mass index, BMI; Gestational diabetes mellitus, GDM; birth weight, BW; small for gestational age, SGA; Large for gestational age, LGA
Of the 5,120 cases studied, 377 (7.4 %) developed HDP, while 211 (4.1 %) developed GDM. The maternal age was 31.8 ± 5.7 years. Pre-pregnancy BMI was 20.8 (19.1, 23.1) kg/m2. Unlike the group that did not develop HDP [HDP (–)], the group that developed HDP [HDP (+)] had a higher prevalence of primipara (65.0% vs. 51.1%), higher pre-pregnancy body weight and BMI (54.0 vs. 51.2 kg, 21.7 vs. 20.7 kg/m2, respectively), and a greater proportion of women with obesity 1 and obesity ≥2 (obesity 1: 14.9 vs. 10.0 %, obesity ≥2 10.1 vs. 3.2%, respectively). The complication rate for GDM was similar, at 4.0% vs. 4.1%. Compared to the HDP (–) group, the HDP (+) group had an earlier gestational age at delivery (mean ± SD 36.8 ± 3.2 vs. 37.6 ± 2.6 weeks) and significantly higher rates of premature delivery (33.4 vs.19.1%), Cesarean section (37.4 vs. 32.3 %), LBW and SGA (41.4 vs. 23.6 % and 7.4 vs. 4.2%, respectively).
Because pre-pregnancy BMI is a known risk factor for HDP and GDM, a logistic regression analysis was performed to estimate the risk of 4 categories of pre-pregnancy BMI for the development of HDP and GDM (Fig. 2). The odds ratios for developing HDP (reference: normal weight) were 1.60 (95% CI [confidence interval]: 1.180–2.176, p = 0.0025) for obesity degree 1 and 3.43 (95% CI: 2.346–5.005, p < 0.0001) for obesity degree ≥2; by contrast, underweight had a lower odds ratio of 0.67 (95% CI: 0.479–0.951, p = 0.0248). The odds ratios for developing GDM (reference: normal weight) were 3.12 (95% CI: 2.198–4.417, p < 0.0001) for obesity degree 1 and 5.11 (95% CI: 3.268–8.018, p < 0.0001) for obesity degree ≥2.
Fig. 2
Incidence and odds ratio of HDP (A) or GDM (B) depending on different categories of pre-pregnancy BMI.
Multivariate logistic regression analyses for known HDP risk factors revealed that pre-pregnancy BMI, GWG, primipara, and smoking habits were independent risk factors (Table 3). Smoking habits were protective of HDP in line with previous research [16]. The mechanism is unknown, but quitting smoking should be strongly recommended during pregnancy. The analyses were also conducted in stratified populations without GDM, because medical intervention is initiated once GDM is diagnosed, pre-pregnancy BMI, GWG, and primipara were independent risk factors (Table 3). Because GWG depends on the gestational age at delivery, these analyses included it as a variable, even though it is not a risk factor for HDP.
Table 3 Multivariate logistic regression analysis of the risk for HDP
| all, N = 5,120 |
β |
SE |
p |
OR |
95% CI |
| Pre-pregnancy BMI |
0.123 |
0.017 |
<.0001 |
1.131 |
1.094–1.168 |
| GWG |
0.036 |
0.008 |
<.0001 |
1.037 |
1.021–1.053 |
| Primipara |
0.430 |
0.071 |
<.0001 |
2.365 |
1.787–3.128 |
| Smoking+ |
–0.141 |
0.070 |
0.0448 |
0.755 |
0.573–0.993 |
| ART+ |
–0.036 |
0.099 |
0.7177 |
0.931 |
0.632–1.371 |
| Maternal age |
0.016 |
0.012 |
0.1803 |
1.016 |
0.993–1.041 |
| GDM+ |
0.118 |
0.145 |
0.4174 |
0.790 |
0.448–1.396 |
| Gestational age at delivery |
–0.159 |
0.021 |
<.0001 |
0.853 |
0.819–0.889 |
| without GDM, n = 4,909 |
β |
SE |
p |
OR |
95% CI |
| Pre-pregnancy BMI |
0.129 |
0.018 |
<.0001 |
1.138 |
1.099–1.178 |
| GWG |
0.035 |
0.008 |
<.0001 |
1.035 |
1.019–1.052 |
| Primipara |
0.449 |
0.074 |
<.0001 |
2.453 |
1.835–3.279 |
| Smoking+ |
–0.120 |
0.072 |
0.0947 |
0.787 |
0.594–1.042 |
| ART+ |
–0.054 |
0.105 |
0.6057 |
0.897 |
0.595–1.354 |
| Maternal age |
0.008 |
0.012 |
0.4938 |
1.008 |
0.984–1.033 |
| Gestational age at delivery |
–0.156 |
0.021 |
<.0001 |
0.855 |
0.820–0.892 |
Hypertensive disorders of pregnancy, HDP; Body mass index, BMI; Assisted Reproductive Technology, ART; Gestational weight gain, GWG; Gestational diabetes mellitus, GDM.
We further investigated the impact of GWG on the development of HDP according to four categories of pre-pregnancy BMI; underweight, normal weight, obesity degree 1, obesity degree ≥2. The odds ratios of HDP were examined by low, normal, or high GWG (Table 1). We performed logistic regression analyses adjusting for gestational age in Model 1 (Fig. 3A), gestational age and primipara in Model 2 (Fig. 3B), and gestational age, primipara, maternal age, smoking (passive or active), GDM status, and ART in Model 3 (Fig. 3C). In the normal weight population, the odds ratio of developing HDP was elevated by high GWG. Notably, obesity degree 1 and ≥2 populations have significantly higher odds of developing HDP, regardless of normal or high GWG (Fig. 3B). The odds ratios for developing HDP by normal GWG (reference: normal weight and normal GWG) were 1.79 (95% CI: 1.02–3.14, p = 0.0436) in the obesity degree 1 population and 3.25 (95% CI: 1.57–6.74, p < 0.0015) in obesity degree ≥2 population in Model 2 (Fig. 3B, Supplementary Table 1). In contrast, low GWG in normal and underweight pregnant women was linked to a lower odds ratio of HDP in Models 1, 2, and 3.
Fig. 3
Odds ratios of HDP depending on different categories of pre-pregnancy BMI and GWG. Odds ratios were determined by logistic regression analyses adjusted for gestational age in the Model 1 (A), gestational age and primipara in the Model 2 (B), and gestational age, primipara, maternal age, smoking (passive or active), GDM status, and ART in the Model 3 (C).
Discussion
The key findings of the KODMO study are as follows; (1) A relatively large database of Japanese women revealed that HDP and GDM onset were associated with pre-pregnancy BMI. (2) GWG was identified as an independent risk factor for HDP. (3) The impact of GWG on the risk of HDP varies according to pre-pregnancy BMI.
Pre-pregnancy body shape and the risk of GDM and HDP
In Japan, unlike women in their 20s (20.7% for underweight, 8.9% for obesity, respectively), women in their 30s and 40s are less thin and more obese (30s: 16.4% for underweight, 15.0% for obesity; 40s: 12.9% for underweight, 16.6% for obesity, respectively) [17]. Furthermore, the average age of first childbirth among Japanese women is more than 30 years old, with the majority of pregnant women giving birth in their 30s, indicating an aging pregnant population [17]. The perinatal risk of adverse pregnancy outcomes (APOs) varies with pre-pregnancy body shape. Obesity specifically raises the risk of HDP, GDM, and pregnancy loss among APOs [18]. Furthermore, obesity increases the mother’s risk of developing cardiovascular disease after APOs [3].
Our study found that pregnant women who were obese prior to conception were more likely to develop HDP (Fig. 2), which is consistent with a previous report [2]. Pregnancy causes numerous vascular, metabolic, and physiological changes in the maternal body. These adaptations include increased insulin resistance, fat deposition, hypercoagulability, cardiac remodeling, and reduced vascular resistance. However, pregnancy’s physiological stress can unmask APO, including GDM and HDP, in women who already have elevated cardiometabolic risk factors or genetic predispositions [19]. Maternal obesity is a common risk factor for GDM and HDP, but neonatal outcomes vary. LGA increases in GDM, as do LBW and SGA in HDP. LGA was significantly more common in the GDM (+) group than in the GDM (–) group (6.6 vs. 3.0%, p = 0.0028), although the findings are not presented. HDP increases the risk of LBW and SGA due to placental insufficiency and an increased tendency to terminate pregnancies prematurely to save maternal life. This study also found that the HDP (+) group had a significantly earlier gestational age and a significantly higher rate of premature delivery, Cesarean section, LBW, and SGA than the HDP (–) group. Preventing HDP may also result in fewer LBW newborns in Japan, where pregnant women are becoming older and more obese. The risk of HDP greatly rises in pregnant women who were obese before conception, according to our data (Fig. 2); thus, preconception care is increasingly important.
GWG cut points for obese pregnant women
GWG, a modifiable factor following pregnancy, has been identified as another risk factor for the development of HDP and GDM. GWG management may also help to prevent HDP and GDM. Appropriate cut-off points for GWG to prevent the development of GDM have yet to be defined, but active screening, and adequate energy intake levels, weight and glycemic control interventions, and postpartum follow-up are all recommended [11, 12]. On the other hand, there is no strong evidence linking GWG and HDP, and no recommendation for collaboration between obstetrics and internal medicine has been made. In the KODMO study, GWG was discovered to be an independent risk factor for HDP, with or without GDM. However, in the obese 1 and obese ≥2 populations, both normal and high GWG significantly increased the odds ratio of HDP. Although the study did not provide a comprehensive review of the severity of HDP, the proportion of cases with severe hypertension and proteinuria was higher in the obese 1 and obese ≥2 populations with low GWG than in the normal weight group with normal GWG (Supplementary Table 2). Severe cases were likely to require antihypertensive medications, consistent with clinical management guidelines for HDP. The current guidelines are based on an analysis of 419,114 deliveries from the Japan Society of Obstetrics and Gynecology perinatal database from 2015 to 2017 and are aimed at reducing the number of LBW newborns in Japan [20]. The guidelines for GWG cut-off points are based on the relative risks of six outcomes: preterm delivery <34 weeks’ gestation, LBW, macrosomia, emergency cesarean delivery, instrumental delivery, and preeclampsia as HDP. However, the absolute risks of perinatal adverse outcomes may vary according to pre-pregnancy BMI. We consider that the GWG cut-offs should be based on outcomes with high absolute risks, such as HDP and GDM in obese women. Based on our findings, if we consider only HDP, the optimal GWG for obese pregnant women may be lower than the current guideline [21].
GWG cut points for underweight pregnant women
In the KODMO study, we found that underweight pregnant women are less likely to develop HDP if they gain less weight. However, in underweight pregnant women, the absolute risk of HDP is low, as shown in this study (Fig. 2), and the risks of undernutrition and LBW are deemed more important; thus, it may be unnecessary to strictly limit GWG, supporting current guidelines.
Clinical perspectives
Our findings contribute Japanese cohort-specific evidence to the global understanding of BMI and GWG’s impact on HDP risk. Notably, we found that the HDP risk remains elevated in obese women even within the guideline-concordant GWG, implying that the current cut-off values may not be protective enough. HDP makes a significant contribution to LBW, preterm delivery, and maternal complications. Therefore, refining GWG recommendations based on pre-pregnancy BMI— particularly for obese women—is a clinical priority.
Preconception weight control and tailored GWG targets may help reduce both immediate pregnancy complications and long-term maternal cardiovascular risks, while also promoting better neonatal outcomes.
Limitations
The authors point out the study’s limitations. First, while this study was based on the registration of all consecutive births in a single hospital, the data may have been skewed due to missing data and the hospital’s characteristics, which admit many pregnant women with complications. Second, the impact of GWG on the development of GDM based on pre-pregnancy BMI is also significant. However, the rate of GDM in this study was lower than previously reported in Japanese subjects [22]. It is possible that a higher rate of preterm births resulted in fewer women being screened for GDM. Furthermore, because the diagnostic criteria for GDM changed in 2010, patients enrolled in this study prior to 2010 were diagnosed using the previous criteria, which may have resulted in an underestimation of GDM. Third, patients with GDM may have received medical interventions such as diet, insulin injections, and weight control during pregnancy, which may have influenced their weight gain. Fourth, the weight gain could have been due to fluid retention, particularly in cases of severe HDP with organ damage, and the weight trajectory and timing of HDP onset were not thoroughly investigated. Although all analyses were adjusted for the gestational age at delivery, it should also be note that 20.1% of the study population was preterm, as GWG depends on the gestational age at delivery.
In conclusion, the impact of GWG as a modifiable factor of HDP varies with pre-pregnancy BMI, highlighting the importance of body weight management before and during pregnancy (Graphical Abstract).
Graphical Abstract
Acknowledgments
We would like to thank all of the physicians and obstetricians who contributed to this study.
Authors’ Contribution
Y.M. designed the study, defined its objectives, and was the primary author of the manuscript. K.K. and N.O. helped data collection, and Y.O. critically read and reviewed the manuscript for significant intellectual content. M.I., N.T., K.Y., N.I., K.H., J.A., and N.O. all contributed significantly to the interpretation of the findings. All authors reviewed and approved the final version of the manuscript.
Disclosure
The authors declare no conflicts of interest.
Funding Sources
Y.O. received research funding from the Sasebo Kyosai Hospital, Saisei Mirai Medical Corporation.
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