Abstract
Background
Inappropriate pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) are both linked to preterm birth (PTB); however, which one plays a dominant role in PTB risk is not yet sure. We aimed to evaluate the combined effect of pre-pregnancy BMI and GWG on the risk of PTB in singleton pregnancies conceived both spontaneously and through assisted reproductive technology (ART).
Methods
The data included all mothers (n = 17,540,977) who had a live singleton birth from the US National Vital Statistics System (NVSS) 2015–2019. Logistic regression models, quantile-g-computation, and generalized additive model were used to analyze the combined association of pre-pregnancy BMI and GWG with PTB.
Results
The singleton PTB rate was significantly higher in ART pregnancies (11.5%) than in non-ART pregnancies (7.9%). When compared to those women with pre-pregnancy normal weight and GWG within Institute of Medicine (IOM) guidelines, the highest PTB risk was observed in non-ART women with pre-pregnancy underweight and GWG below IOM guidelines (aOR 2.56; 95% CI 2.53–2.60) and in ART women with pre-pregnancy obese and GWG below IOM guidelines (aOR 2.56; 95%CI 2.36–2.78). GWG dominated the combined effect with its joint effect coefficient of − 0.281 (P < 0.05) in non-ART women and − 0.108 (P < 0.05) in ART women.
Conclusions
Inappropriate GWG played a dominant role in increasing the risk of PTB in both non-ART and ART populations. Counseling regarding pre-pregnancy BMI and especially GWG appears to be even more crucial for pregnancies conceived via ART, given their impact on PTB.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10815-024-03024-w.
Keywords: Pre-pregnancy BMI, Gestational weight gain, Preterm birth, ART
Introduction
Preterm birth (PTB) is defined as a live birth before 37 completed weeks’ gestation, which is a major and rapidly growing global public health concern. Globally, PTB increased from 9.8% in 2010 to 10.6% in 2014 [1]. PTB and its complications are the leading cause of death for children under the age of 5 around the world. Effective strategies for PTB prevention are in urgent need, but understanding the etiology of PTB is a major obstacle.
Both maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG), reflecting nutritional status before and during pregnancy, are potent independent predictors for PTB. In 2009, the Institute of Medicine (IOM) published revised guidelines on GWG, making specific recommendations for each pre-pregnancy BMI class based on the World Health Organization definitions [2]. Depending on their pre-pregnancy BMI, compared to the normal weight, underweight women are advised to gain more during pregnancy, whereas overweight and obese women are advised to gain less. Previous research suggested an inverse relationship between GWG and pre-pregnancy BMI. However, the combined effect of pre-pregnancy BMI and GWG on PTB has not been fully validated [3, 4]. A limited number of studies consistently showed that women with GWG below recommendations were associated with a higher risk of PTB, but this association was somewhat contradictory among women with GWG above recommendations [3, 5, 6], which may necessitate additional investigation.
Alternatively, assisted reproductive technology (ART) is the most popular and mature treatment for infertility, which is an important risk factor for PTB [7, 8]. Leaving aside the multiple gestations, women achieving singleton pregnancy by ART also had approximately 1.98- to 3.27-fold increased risk of PTB compared with those achieving singleton pregnancy spontaneously [9–11]. Some evidence shows that pre-pregnancy underweight, overweight, and obesity are all associated with higher rates of infertility [12] and have the potential to adversely impact ART treatment and birth outcomes, such as PTB [13–15].
It is currently uncertain whether the combined influence of maternal pre-pregnancy BMI and GWG on PTB is different in non-ART and ART women. Furthermore, it is unclear whether pre-pregnancy BMI or GWG plays a dominant role in the risk of PTB. Therefore, we sought to use a large population-based study to evaluate the combined associations of maternal pre-pregnancy BMI and GWG with the risk of preterm singleton birth in both non-ART and ART populations.
Methods
Study design and data sources
The data were from the US National Vital Statistics System (NVSS), an extensive data archive accessible to the public, which was conducted by the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC). NVSS collects and publishes nationwide data on births in all 50 US states and the District of Columbia from birth certificates according to Federal law. The medical and health information of the maternal and infant is extracted from the medical records by the “facility worksheet,” and the maternal characteristics are obtained from the mother during birth registration by the “mother’s worksheet.”
In this population-based study, we used birth data from January 1, 2015, to December 31, 2019 (NVSS 2015–2019), including all mothers (n = 17,540,977) who had a live singleton birth and excluding women with incomplete data on BMI, GWG, ART treatment, or PTB at birth. Specific inclusion and exclusion criteria for the study selection procedure can be seen in Supplementary Fig. 1. This study was approved as exempt from review by the Institutional Review Board at Jinan University due to the use of de-identified data from the open database. The conduct and reporting of this study followed the reporting guidelines in the Strengthening the Reporting of Observational Studies in Epidemiology statement.
Study variables
Pre-pregnancy BMI (in kg/m2) was calculated by the mother’s subjectively reported pre-pregnancy weight in kilograms divided by her height in meters squared. Women were categorized as underweight (< 18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), or obese (> 30.0 kg/m2) according to the WHO criteria [16]. GWG was defined as the difference in pounds between the weight at the delivery and the pre-pregnancy. Next, GWG was categorized as below, within, or above the IOM (2009) recommendations. Gains within the IOM recommendations were defined as 28–40 pounds, 25–35 pounds, 15–25 pounds, and 11–20 pounds for underweight, normal weight, overweight, and obese women, respectively [2]. ART treatment includes in vitro fertilization (IVF), gamete intrafallopian transfer (GIFT), and zygote intrafallopian transfer (ZIFT). In addition, PTB was defined as birth occurring before 37 completed weeks of gestation based on the obstetric estimate of gestation at the time of delivery [17].
Covariates measures
Information on maternal age (< 25 years, 25–29 years, 30–34 years, 35–39 years, ≥ 40 years), maternal race/ethnicity (non-Hispanic whites, non-Hispanic black, Hispanic, and others), maternal education (lower than high school, high school, higher than high school, and missing), marital status (married, unmarried), pre-pregnancy BMI (underweight < 18.5 kg/m2, normal weight 18.5–24.9 kg/m2, overweight 25.0–29.9 kg/m2, obesity ≥ 30.0 kg/m2), GWG (pounds), and smoking before or during pregnancy (yes, no, missing) was collected using the mother’s worksheet. Information on parity (1, 2, 3, ≥ 4), previous PTB (yes, no), previous cesarean (yes, no), initiation of prenatal care (no prenatal care, 1st–3rd month, 4th–6th month, 7th–final month, or missing), number of prenatal visits, infant sex (male or female), newborn birth weight (normal, unnormal), and infant death (yes, no) was collected using the facility worksheet.
Statistical analysis
Twelve groups (underweight-below, underweight-within, underweight-above, normal weight-below, normal weight-within, normal weight-above, overweight-below, overweight-within, overweight-above, obesity-below, obesity-within, obesity-above) are created based on the pre-pregnancy BMI and IOM-GWG categories. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for PTB according to previous references after adjusting for potential confounders, including maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, previous PTB, previous cesarean, smoking before pregnancy, smoking during pregnancy, and infant sex. For the sensitivity analysis, several models were created by changing the adjusted variables.
To analyze the influence of different maternal weight parameters on the risk of PTB, such as pre-pregnancy weight and GWG, quantile-g-computation was utilized. Quantile-g-computation is a parameterized and generalized linear model-based approach that uses a basic implementation of g-computation to estimate a mixed effect [18, 19]. A generalized additive model (GAM) was employed to investigate the functional relationship of GWG and various pre-pregnancy weights with PTB [20]. We examined values that had been adjusted for the following factors: maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, Eclampsia, cesarean section, previous PTB, previous cesarean, smoking before pregnancy, smoking during pregnancy, infant death, newborn birth weight, and infant sex.
All analyses were performed with Stata statistical software (version 14) and R statistical software (version 4.1.1). All tests were conducted 2-sided, and effects with P < 0.05 were considered statistically significant.
Results
Of the 17,540,977 singleton births, 17,398,197 (99.2%) were delivered by non-ART mothers and 142,780 (0.8%) by ART mothers. Compared to non-ART pregnancies (7.9%), the singleton PTB rate was substantially higher in ART pregnancies (11.5%) (Table 1). After adjusting for potential confounders, we found that the total PTB risk was 1.51 times (95%CI 1.48–1.53) higher in the ART group than in the non-ART group, and this difference was consistent across all groups according to pre-pregnancy BMI and IOM-GWG (Table 1).
Table 1.
The PTB rate in both ART and non-ART women and adjusting odds ratio in ART women with non-ART women as the reference, according to pre-pregnancy BMI and IOM-GWG categories
| Pre-pregnancy BMI and IOM-GWG | Non-ART (n = 17,398,197) | ART (n = 142,780) | P value* | aOR (95%CI)# | ||
|---|---|---|---|---|---|---|
| FTB, n (%) | PTB, n (%) | FTB, n (%) | PTB, n (%) | |||
| Total | 16,017,852 (92.1) | 1,380,345 (7.9) | 126,360 (88.5) | 16,420 (11.5) | < 0.001 | 1.51(1.48–1.53) |
| Underweight-below | 173,455 (84.4) | 32,034 (15.6) | 1188 (85.0) | 210 (15.0) | 0.56 | 1.43(1.22–1.69) |
| Underweight-within | 231,735 (92.8) | 17,944 (7.2) | 1435 (93.5) | 100 (6.5) | 0.309 | 1.28(1.02–1.60) |
| Underweight-above | 127,133 (94.5) | 7396 (5.5) | 436 (93.0) | 33 (7.0) | 0.145 | 1.55(1.06–2.25) |
| Normal weight-below | 1,725,141 (88.0) | 235,912 (12) | 14,805 (84.8) | 2651 (15.2) | < 0.001 | 1.47(1.40–1.54) |
| Normal weight-within | 2,684,222 (93.8) | 176,736 (6.2) | 28,643 (91.5) | 2651 (8.5) | < 0.001 | 1.47(1.40–1.53) |
| Normal weight-above | 2,594,502 (95.5) | 122,589 (4.5) | 22,069 (93.1) | 1635 (6.9) | < 0.001 | 1.62(1.54–1.71) |
| Overweight-below | 561,059 (87.5) | 80,455 (12.5) | 3320 (79.7) | 846 (20.3) | < 0.001 | 1.58(1.45–1.72) |
| Overweight-within | 1,127,412 (91.3) | 107,977 (8.7) | 8680 (85.6) | 1458 (14.4) | < 0.001 | 1.54(1.45–1.64) |
| Overweight-above | 2,554,061 (94.1) | 160,394 (5.9) | 20,603 (90.4) | 2188 (9.6) | < 0.001 | 1.52(1.45–1.59) |
| Obesity-below | 905,079 (88.3) | 119,978 (11.7) | 4436 (78.8) | 1191 (21.2) | < 0.001 | 1.58(1.47–1.69) |
| Obesity-within | 1,022,676 (90.0) | 113,527 (10.0) | 6186 (82.9) | 1280 (17.1) | < 0.001 | 1.45(1.36–1.55) |
| Obesity-above | 2,311,377 (91.8) | 205,403 (8.2) | 14,559 (87.0) | 2177 (13.0) | < 0.001 | 1.37(1.31–1.44) |
*P < 0.05 represents that chi-square test results are significant
#aOR represents adjusting odds ratio from logistic regression of PTB in ART women compared with the reference group (non-ART), which are adjusted for maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, previous preterm birth, previous cesarean, smoking before pregnancy, smoking during pregnancy, and infant sex
ART, assisted reproductive technology; GWG, gestational weight gain; BMI, body mass index; IOM, Institute of Medicine; FTB, full-term birth; PTB, preterm birth
According to IOM guidelines, women with pre-pregnancy normal weight and GWG within IOM guidelines are the optimal pregnancy weight; thus, we used it as the reference group for logistic regression analysis. We found that compared to the reference group, the highest PTB risk was observed in non-ART women with pre-pregnancy underweight and GWG below IOM guidelines (aOR 2.56; 95%CI 2.53–2.60), while in ART women with pre-pregnancy obese and GWG below IOM guidelines (aOR 2.56; 95%CI 2.36–2.78) (Fig. 1).
Fig. 1.
PTB odds ratios and 95% confidence intervals in non-ART and ART populations, according to pre-pregnancy BMI and IOM-GWG. Adjusted for maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, previous preterm birth, previous cesarean, smoking before pregnancy, smoking during pregnancy, and infant sex. ART, assisted reproductive technology; GWG, gestational weight gain; BMI, body mass index; IOM, Institute of Medicine
In both ART and non-ART groups, the PTB risk progressively decreased with the increase of GWG in each pre-pregnancy BMI class (Fig. 1). In each pre-pregnancy BMI class, when compared to women with GWG within IOM guidelines, we found that those with GWG below IOM guidelines all had an increased risk of PTB, while those with GWG above IOM guidelines all had decreased risk of PTB in both non-ART and ART groups. In addition, the results of sensitivity analysis demonstrate the robustness of our results when adjusting for different potential confounders (Supplementary Table 1).
To explore the weights and joint effects of pre-pregnancy BMI and GWG on PTB, we performed a quantile-g-computation analysis to explore the truth, and it showed that GWG was negative and pre-pregnancy BMI was positive in terms of the effect on PTB in both non-ART and ART groups (Fig. 2). However, in the non-ART population, pre-pregnancy BMI had little effect (0.00252), and ultimately, the combined effect was dominated by GWG with its joint effect coefficient of − 0.281 (P < 0.05). On the contrary, in the ART population, pre-pregnancy BMI played a larger role (0.144), even though GWG still played a dominant role with its joint effect coefficient of -0.108 (P < 0.05) (Table 2).
Fig. 2.
PTB odds ratios and 95% confidence intervals in ART and non-ART populations, compared to women with GWG within IOM in each pre-pregnancy BMI. Adjusted for maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, previous preterm birth, previous cesarean, smoking before pregnancy, smoking during pregnancy, and infant sex. ART, assisted reproductive technology; BMI, body mass index; IOM, Institute of Medicine
Table 2.
Qgcomp model regression weights and joint effects (95% CI) of GWG/pre-pregnancy BMI in preterm birth in non-ART and ART populations
| Coefficients | Joint effect (95% CI) | P value | |
|---|---|---|---|
| Non-ART | |||
| GWG | − 0.283 | − 0.281 (− 0.283, − 0.278) | < 0.001* |
| Pre-pregnancy BMI | 0.00252 | ||
| ART | |||
| GWG | − 0.252 | − 0.108 (− 0.133, − 0.083) | < 0.001* |
| Pre-pregnancy BMI | 0.144 |
The quantile-g-computation models were adjusted by maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, previous preterm birth, previous cesarean, smoking before pregnancy, smoking during pregnancy, and infant sex
ART, assisted reproductive technology; GWG, gestational weight gain; BMI, body mass index
*P value < 0.05
To get further insight into their relationship, a GAM model that used PTB (yes/no) as a binary response and a smoothing spline function of GWG as an univariable predictor is shown in Fig. 3. A wide range of potential confounders were adjusted including maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, eclampsia, cesarean section, previous PTB, previous cesarean, smoking before pregnancy, smoking during pregnancy, infant death, newborn birth weight, and infant sex. The effective degree of freedom (EDF) greater than 1 indicated a nonlinear fit between PTB risk and GWG in both non-ART groups (underweight: EDF = 3.987, normal weight: EDF = 3.983, overweight: EDF = 3.962, obese: EDF = 3.942) and ART groups (underweight: EDF = 3.77, normal weight: EDF = 3.525, overweight: EDF = 3.435, obese: EDF = 3.153), and P values were all less than 0.05 (Fig. 3).
Fig. 3.
Plots of estimated smoothing spline function of PTB risk for the generalized additive model when the response variable was GWG, according to different pre-pregnancy BMI. (A) The univariable smooth function of PTB risk in non-ART people (underweight: EDF = 3.987, P < 0.001; normal weight: EDF = 3.983, P < 0.001; overweight: EDF = 3.962, P < 0.001; obese: EDF = 3.942, P < 0.001). (B) The univariable smooth function of PTB risk in ART people (underweight: EDF = 3.77, P < 0.001; normal weight: EDF = 3.525, P < 0.001; overweight: EDF = 3.435, P < 0.001; obese: EDF = 3.153, P < 0.001). The generalized additive model was adjusted by maternal age, race/ethnicity, education, marital status, parity, initiation of prenatal care, number of prenatal visits, Eclampsia, cesarean section, previous preterm birth, previous cesarean, smoking before pregnancy, smoking during pregnancy, infant death, newborn birth weight, and infant sex. ART, assisted reproductive technology; GWG, gestational weight gain; BMI, Body Mass Index
In addition, the non-ART group has the lowest PTB risk in the 45 to 75 pounds GWG range. When GWG is below 45 pounds (the crossover point), those non-ART women with lower pre-pregnancy BMI have a higher risk of PTB. But the PTB risk falls as GWG grows, and the lower the pre-pregnancy weight, the greater the risk reduction. The gradually stabilized PTB risk peak indicates that extra GWG only has a slight additional impact on PTB risk (Fig. 3A). However, such associations were not completely repeated in the ART population. The ART group has the lowest PTB risk in the 45 to 60 pounds GWG range. Compared with the non-ART group, the ideal GWG range of the ART group is relatively narrower. Besides, the curve of the ART pre-pregnancy underweight group fluctuated irregularly, which could be attributed to the limited sample size (Fig. 3B). Detailed plots of the estimated smoothing spline function of PTB risk with a 95% confidence band for the generalized additive model can be seen in Supplementary Figs. 2 and 3.
Discussion
Preliminary finding
This study used the 2015–2019 NVSS singleton live birth database to assess the combined effect of pre-pregnancy BMI and GWG on PTB risk in ART and non-ART populations. In this study, we found that ART women had a significantly increased risk of PTB than non-ART even after adjusting for potential confounders, and a similar trend was seen in different pre-pregnancy BMI and IOM-GWG groups. These results suggest that the main cause of PTB is different in ART and non-ART populations. Because of the marked difference, the non-ART and ART groups should be analyzed separately when considering the effect of maternal weight on PTB. In the separate analysis, we found that compared to women with pre-pregnancy normal weight and GWG within IOM guidelines, both ART and non-ART women with GWG below IOM guidelines were all associated with increased risk of PTB regardless of maternal pre-pregnancy BMI. On the other hand, both ART and non-ART women with GWG above IOM guidelines had a relatively low risk of PTB, which seems to imply that sufficient GWG has a protective effect against the risk of PTB.
Context with the existing literature on the topic
Here, we not only confirm these previous studies that only consider insufficient GWG on PTB risk [21, 22] but also give a fuller account with a combination of pre-pregnancy BMI. Several similar research to ours reported partially inconsistent findings. For instance, two Chinese studies discovered that underweight women with insufficient GWG showed no significant association with PTB, which may be due to the limited sample size and potential racial/ethnic bias [23, 24]. Moreover, we found that among non-ART women with insufficient GWG, the risk of PTB decreased with increasing BMI class, which is consistent with those of Lengyel et al. [25] and Santos et al. [5] in ordinary pregnant women, implicating maternal nutritional depletion associated with PTB.
Of note, in ART women, the opposite trend was observed, i.e., those ART women with pre-pregnancy obesity and insufficient GWG had the highest PTB risk. Why pre-pregnancy obesity does not compensate for insufficient GWG in ART women as did non-ART women, and the specific reasons behind this can only be speculated. Morbid obesity is one of the contributing factors to infertility. Polycystic ovary syndrome (PCOS) is the leading cause of infertility in women, and obesity has been reported in up to 30–75% of women with PCOS [26]. Maternal PCOS was associated with more than a two-fold increased risk of preterm and cesarean delivery. That said, when women with insufficient GWG, non-ART women can be partially compensated for by good pre-pregnancy nutritional status, thereby decreasing PTB risk, but it does not work in ART women.
Principal findings
When we focused on the women whose GWG was within the IOM guidelines, we found that pre-pregnancy overweight/obesity still had a greater risk of PTB in both non-ART and ART women, but the effect was more pronounced in the ART population, supporting the preceding finding. In our study, the risk of PTB was significantly higher in the ART group compared to the non-ART group for each pre-pregnancy BMI and IOM-GWG category. Women with pre-pregnancy overweight/obesity had a greater effect on the risk of PTB in the ART population than in the non-ART population when compared to those with pre-pregnancy normal weight. What is more, we found a more interesting phenomenon among both non-ART and ART women with GWG above IOM guidelines: the risk of PTB increased with increasing pre-pregnancy BMI class, similar to what Li et al. [23] and Gao et al. [27] found in general pregnant women. Therefore, in order to prevent PTB, ART women with pre-pregnancy overweight/obesity may require more intensive interventions for weight reduction before pregnancy than non-ART women.
Possible explanations for the findings
The IOM guidelines recommend that a woman with a higher pre-pregnancy BMI should have a lower GWG, and there might be a concealed danger of insufficient essential nutrients. Maternal obesity is mainly caused by excessive accumulation of fat [28], but this does not imply that other vital nutrients, including vitamins, minerals, fatty acids, and essential amino acids, are likewise deposited in large quantities. For example, Forrest et al. found that obesity was significantly independent of vitamin D deficiency [29], and Astrup’s research showed that obesity was associated with low intakes of numerous nutrients, such as iron, zinc, calcium, and folic acid [30]. Inadequate nutritional intake during pregnancy may induce nutrient deficiencies in the fetus and poor resistance in the mother, which can further lead to adverse pregnancy outcomes such as PTB and infection [31]. Feeding the fetus through lipolysis instead of adequate nutrition intake during pregnancy is clearly not a wise decision. On the contrary, we should enable mothers, even obese ones, to get adequate energy and nutrient intake to prevent the cascade of conditions that lead to premature birth.
Further findings
However, which plays a more important role in increasing the risk of PTB: pre-pregnancy BMI or GWG? A study from China showed that excessive GWG played a positive role in reducing the incidence of PTB in the majority of pre-pregnancy BMIs except pre-pregnancy obesity [23]. One additional retrospective cohort study revealed that GWG above IOM recommendations was associated with increased PTB for all BMI classes [25], and we observed that there were few adjusted variables in logistic regression in this analysis, meaning that the influence of other potential covariates could not be excluded. To resolve the controversy, we used quantile-g-computation to further verify which dominated the combined effect between pre-pregnancy BMI and GWG on PTB risk. Here, we found that GWG still played a dominant role in both non-ART and ART populations, whereas pre-pregnancy BMI played a larger role in the ART population than in the non-ART population. These results suggest that controlling the GWG within the appropriate range is more crucial than controlling pre-pregnancy BMI for the prevention of PTB, and ART women should pay more attention to weight control before pregnancy. So, what range of GWG can be controlled to achieve a lower risk of PTB? The plots of the estimated smoothing spline function were used to evaluate the influence of GWG changes on PTB risk. We discovered that non-ART women when GWG ranges from 45 to 75 pounds were associated with a relatively lower risk of PTB, whereas the range is narrower for ART women (45–60 pounds), as most of the ART women accompanied by underlying disease (such as PCOS, hypertension, diabetes mellitus, and inflammation) and excessive GWG can further exacerbate the risk of PTB.
Strengths and limitations
We compared non-ART and ART pregnancies separately, as the physical health condition of ART-pregnant women is quite different from ordinary pregnant women. Currently, there is no recommendation on GWG for ART women to date, so this study provides a scientific reference on clinical management of body weight both before and during pregnancy. What is undeniable is that the study has several limitations. The pre-pregnancy weight data were mostly self-reported, which increased the risk of error bias. The GWG in this study was not dynamically observed, and the analysis only based on the weight difference at delivery and before pregnancy may ignore some changes during pregnancy; the GWG rate at different gestational weeks or trimesters could not be determined yet. In addition, we were unable to distinguish between spontaneous and nonspontaneous PTB. We did not adjust for hypertension and diabetes since both of them are highly correlated with maternal pre-pregnancy BMI. Although we adjusted for potentially confounding variables, we cannot completely exclude the possibility that residual confounding influenced our findings. Despite these limitations, the results of this study have important clinical and public health implications.
Conclusion
In conclusion, compared to pre-pregnancy BMI, inappropriate GWG played a dominant role in increasing the risk of PTB in both non-ART and ART populations. Moreover, ART women had a higher risk of PTB than non-ART women, and the safety range of appropriate GWG was narrower for ART women. Thus, ART women should first place more focus on preventing both insufficient and excessive GWG; attention should also be paid to achieving appropriate weight before pregnancy. Counseling regarding pre-pregnancy BMI and especially GWG appears to be even more crucial for pregnancies conceived via ART, given their impact on PTB. Hence, this study provides some guidance for the management of maternal body weight before and during pregnancy.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 81903294) and the (202102020120). JH and CQL conceived the idea. SYL undertook data analysis. SYL, YH, JYL, and CQL wrote the draft of the manuscript. SYL, YH, JYL, JYN, MLL, JXZ, and CQL contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content. All authors were involved in data analysis, drafting the article, or revising it critically for important intellectual content, and all authors approved the final version to be published.
Abbreviations
- aOR
Adjusted odds ratio
- ART
Assisted reproductive technology
- BMI
Body mass index
- CDC
Centers for Disease Control and Prevention
- CI
Confidence interval
- EDF
Effective degree of freedom
- GAM
Generalized additive model
- GIFT
Gamete intrafallopian transfer
- GWG
Gestational weight gain
- IOM
Institute of Medicine
- IVF
In vitro fertilization
- NCHS
National Center for Health Statistics
- NVSS
US National Vital Statistics System
- PCOS
Polycystic ovary syndrome
- PTB
Preterm birth
- ZIFT
Zygote intrafallopian transfer
Funding
National Natural Science Foundation of China,No.81903294,Liu chaoqun,Guangzhou Basic and Applied Basic Research Foundation,202102020120,Liu chaoqun
Data availability
This research data was from the US National Vital Statistics System (NVSS), an extensive data archive accessible to the public. The data presented in this study are available on reasonable request from the corresponding author.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Shaoyan Lian, Ying Huang, and Jieying Li contributed equally to this work.
Contributor Information
Jiang He, Email: hejiang01@smu.edu.cn.
Chaoqun Liu, Email: chaoqunliu@jnu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
This research data was from the US National Vital Statistics System (NVSS), an extensive data archive accessible to the public. The data presented in this study are available on reasonable request from the corresponding author.