Gestational Diabetes Mellitus and Risk of Delayed Onset of Lactogenesis: A Systematic Review and Meta-Analysis

Abstract

Background:

Gestational diabetes mellitus (GDM) may be associated with delayed onset of lactogenesis (DOL), but it is still inconclusive.

Objectives:

The study aimed to evaluate the association between GDM and DOL, the prevalence and risk factors of DOL in GDM women.

Materials and Methods:

A comprehensive search was performed in 10 electronic databases from inception to June 1, 2020. To find more eligible studies, the references of finally eligible studies and relevant reviews were traced manually. A meta-analysis was conducted to calculate the pooled estimates of association, prevalence, and risk factors using random- or fixed-effects models.

Results:

Eleven eligible articles involving 8,150 women were included in this study. GDM women had a higher risk of DOL (odds ratio [OR] = 1.84, 95% confidence interval [CI] [1.34–2.52]). The prevalence of delayed lactogenesis onset in GDM women was 35.0% (effect size [ES] = 0.35, 95% CI [0.30–0.40]). Primipara (OR = 2.54, 95% CI [1.89–3.42]), advanced age (OR = 1.05, 95% CI [1.03–1.08]), prepregnancy obesity (OR = 1.55, 95% CI [1.19–2.03]), and insulin treatment (OR = 3.07, 95% CI [1.71–5.47]) were risk factors of delayed lactogenesis onset in GDM women.

Conclusion:

GDM negatively affects the timing of lactogenesis onset. The prevalence of delayed lactogenesis onset in GDM women is 35.0%. Primipara, advanced age, prepregnancy obesity, and insulin treatment are independent risk factors of delayed lactogenesis onset in GDM women.

Introduction

Gestational diabetes mellitus (GDM) refers to any degree of glucose intolerance resulting in hyperglycemia with onset or first diagnosis during pregnancy, which is the most common pregnancy-related medical complication.¹ The increasing rate of advanced age and obese pregnant women over recent decades has led to a rise in the prevalence of GDM, which has increased to 15.1% globally in 2017.^2,3 GDM may lead to short-term and long-term adverse consequences in both mother and offspring, such as maternal type 2 diabetes mellitus and neonatal hypoglycemia, leading to the rising health burden worldwide.⁴ Breastfeeding is a well-known healthy behavior that has beneficial effects against adverse maternal and infant outcomes, including GDM women and their infants. For GDM women, breastfeeding could improve postpartum glucose regulation and reduce their chances of developing type 2 diabetes.^5,6 For infants of GDM mothers, breastfeeding could mitigate the effects of neonatal hypoglycemia and reduce future risks of obesity and metabolic syndrome.^7,8 However, as shown by current evidence, GDM women are less able to exclusively breastfeed their infants or sustain longer breastfeeding duration.^9,10 Therefore, it is necessary to understand the biological reasons for suboptimal breastfeeding practice in GDM women to develop strategies to counteract this problem.

Delayed onset of lactogenesis (DOL), a crucial risk factor for suboptimal breastfeeding practice, is defined as maternal self-perception of breast hardness, fullness, or milk leakage after 72 hours postpartum or a milk transfer of <9.2 g per 60 hours.^11–13 An experimental study has shown that GDM women have a lag of rapidly increasing lactose level, a biomarker reflecting the lactogenesis onset, which means that GDM women are predisposed to DOL.¹⁴ Recent years have seen a surge of studies aimed at understanding the association between GDM and DOL, but their results are inconclusive. Although the systematic literature review of De Bortoli and Amir¹⁵ indicated that women experiencing diabetes during pregnancy are at a higher risk of DOL, the specific effect of GDM on lactogenesis onset remained unclear because no quantitative meta-analysis was performed in this systematic review, and it focused on the association between diabetes during pregnancy and DOL, including both type 1 diabetes and gestational diabetes. Thus, it is necessary to perform a systematic review and meta-analysis to summarize the evidence of the effect of GDM on the onset of lactogenesis. The aims of this study were to (1) ascertain the association between GDM and the onset of lactogenesis, (2) estimate the prevalence of DOL in women with GDM, and (3) identify potential risk factors of DOL in GDM women.

Materials and Methods

This study was performed according to PRISMA guidelines.¹⁶ The study selection, data extraction, and quality assessment were conducted independently by two authors (J.-L.W. and X.-Q.H.), and the discrepancy was resolved by consensus or consulting with the third reviewer (X.-M.J.). All analyses were based on previous published studies, thus no ethical approval and patient consent and required.

Literature search

Ten electronic databases were systematically searched to find potential articles involving GDM and lactogenesis onset: PubMed, Web of Science, Embase, Cochrane Library, Scopus, Ovid Medline, China National Knowledge Infrastructure Database (CNKI), Wanfang Database, Chinese Scientific Journal Database (VIP), and Chinese Biomedical Database (CBM). The search strategy was developed combining Mesh terms and free words, and tailored for adapting to different databases. Those words were listed as follows: (“lactation” OR “lactogenesis” OR “lactation disorder*” OR “hypogalactia*” OR “galactorrhea*” OR “galactorrhoea” OR “lactic Secretion*” OR “milk excretion” OR “breast secretion*” OR “milk production” OR “milk secretion*” OR “milk release” OR “mammary gland secretion*” OR “lactorrhea” OR “polygalatia” OR “DOL”) AND ((pregnancy AND diabet*) OR (gestational AND diabet*) OR GDM). All databases were searched from inception until June 1, 2020 and were not set restriction of languages. Also, to ensure all potential studies were searched, we manually traced reference of finally eligible studies and relevant reviews.

Study selection

All retrieved studies were exported to EndNote X9, and duplicate articles were removed. Two authors then independently filtered the remaining studies by initially reading the title and abstract, after which full texts were screened to select eligible studies. An eligible study conformed to all of the following characteristics: (1) it was a cohort study, cross-sectional study, or case–control study. (2) The participants were adult women with a healthy singleton. (3) GDM was diagnosed using an authoritative standard. (4) DOL was categorized as a categorical variable, and defined clearly by maternal perception or testing the weight of newborns before and after breastfeeding. Although the maternal perception is a self-reported method, it has been shown to be effective for evaluating the onset of lactogenesis.¹³ (5) The study reported the number of DOL events in women with or without GDM or offered an odds ratio (OR), relative risk (RR), or hazard ratio (HR) with 95% confidence interval (95% CI) of independent risk factors of DOL in GDM women. Studies were removed from analysis when they met any of the following exclusion criteria: (1) type of study was a review, case report, conference paper, or abstract; (2) study data were incomplete or missing; or (3) duplicate publication.

Data extraction and quality assessment

A predesigned structured data form was used to extract the following information: name of the first author, publication year, country, study design, participant characteristics, the method of measuring lactogenesis onset, total sample size, the event, and total number of DOL in women with or without GDM, and risk factors and their adjusted OR, RR, and HR with 95% CI. If data were duplicated, then only the data from the study with a larger sample size were extracted. When the study design was reported in an unclear manner, we designated a prospective or retrospective study through the time of collecting the onset of lactogenesis.¹⁷ Where data were insufficient or unclear, the corresponding author was contacted through e-mail. The quality of eligible studies was appraised using the Newcastle-Ottawa Scale (NOS) from nine items, a proven, effective tool for assessing the quality and sensitivity of observational studies.¹⁸ An overall risk of bias for each included study was evaluated based on the individual scores and graded as high quality (8–9 points), medium quality (6–7 points), and low quality (<6 points).¹⁹

Data analysis

The meta-analysis was performed using STATA Version 15.0 software. The pooled OR with 95% CIs was presented to explain the meta-analysis results of association and risk factors. The pooled prevalence and its 95% CI were summarized by prevalence rate (r) and standard error (SE). SE was calculated using the formula: SE = sqrt (p × (1 − p)/n).²⁰ Heterogeneity between studies was calculated using the I² statistic value and the p-value of the Cochrane Q statistic, in which I² ≥ 50% or p < 0.05 was considered as significant heterogeneity. The DerSimonian–Laird random-effects model was conducted if heterogeneity was significant; nevertheless, the fixed-effects model was used.²¹ When heterogeneity was significant, the sensitivity analysis was undertaken to test the influence of each individual on the meta-analysis result using the leave-one-out method. Then, if sufficient data were available, subgroup analysis and meta-regression—depending on study design (prospective or retrospective study), the method of measuring the onset of lactogenesis (maternal perception or weighing), the scores of quality assessment (high quality, medium quality, or low quality), and the sample size of the GDM group (<100 or ≥100)—were conducted to explore the source of heterogeneity. In addition, a meta-regression on crude OR and adjusted OR was performed to determine whether adjusted confounding factors influenced the conclusive association between GDM and DOL.²² Begg's weighted regression test was performed to detect publication bias, and the p-value of <0.05 was considered nonsignificant statistical publication bias.

Results

Literature search

A total of 4,416 relevant articles were initially found through an electronic search of the mentioned databases. After eliminating duplicate articles, 1,611 items remained, whose titles and abstracts were browsed. After screening titles or abstracts further, 86 articles were eligible and screened for full text. Finally, 11 studies fulfilled all inclusion criteria and were considered for the meta-analysis.^23–33 It is worth noting that a certain degree of data overlap occurred between two articles authored by Si et al.,^27,28 while both were included in the study because they showed different outcome domains. The detailed selection process is shown using the PRISMA flowchart in Figure 1.

FIG. 1.

Flow diagram of studies selection.

Study characteristics

Eleven studies^23–33 containing 8,150 participants were included in the meta-analysis. Data from the article by Si et al.²⁷ were not included as they comprised of a small sample with data overlap. Of the 11 studies, 3 studies were from the United States,^29,30,32 5 studies from China,^24–28 and the remaining 3 were from Brazil,²³ Israel,³¹ and India.³³ Seven studies were prospective cohort studies,^{23–25,27–29,33} one study was a prospective case–control study,³¹ and three studies were retrospective cohort studies.^26,30,32 All studies used maternal perception to determine the onset of lactogenesis. As for quality assessment, the score of the included studies ranged from 5 to 8 points, and the average score was 7.09 points. Five studies were assessed as high quality,^{23,25,27–29} four studies assessed as medium quality,^{24,26,30–32} and one study assessed as low quality.³³ More general study characteristics of the included studies are depicted in Table 1.

Table 1.

General Characteristics and Quality Assessment of Included Articles

First author (publication year)	Country	Study design	Participant characteristics	No. of participants	Assessment of lactogenesis onset	Quality scores
Rocha (2020)	Brazil	Prospective cohort study	Full-term primiparous in a baby-friendly hospital	224	Participants were interviewed the degree of breast fullness during 72–96 hours postpartum	8
Ding (2020)	China	Prospective cohort study	Full-term mothers	340	Maternal perception was asked between 72 hours and 1 week postpartum	7
Huang (2019)	China	Prospective cohort study	Full-term mothers	3,282	Participants were asked to describe the first time they felt their breast fullness at 4–5 days postpartum	8
Liao (2018)	China	Retrospective cohort study	GDM mothers	394	Maternal perception was asked at 2 months postpartum	7
Si (2017)	China	Prospective cohort study	GDM mothers	284	Maternal perception was asked from 1 to 3 days postpartum	8
Si (2017)	China	Prospective cohort study	Mothers with a healthy infant	497	Maternal perception was asked from 1 to 3 days postpartum	8
Preusting (2017)	United States	Prospective cohort study	Full-term mothers	210	The timing of lactogenesis onset was tracked after eligibility	8
Haile (2017)	United States	Retrospective cohort study	≥35 weeks gestation mothers	2,053	Maternal perception was asked at 3 weeks postpartum	6
Chertok (2016)	Israel	Prospective case–control study	Full-term mothers	67	Self-reported the time of feeling fullness or other changes of breast	6
Matias (2014)	United States	Retrospective cohort study	≥35 weeks gestation mothers	883	Maternal perception was asked at 6–9 weeks postpartum	7
Salahudeen (2013)	India	Prospective cohort study	Full-term mothers	200	Maternal perception was asked after delivery	5

GDM, gestational diabetes mellitus.

The association between GDM and DOL

Eight studies of 6,873 women provided the event and total number of DOL in women with and without GDM. The results of the meta-analysis revealed that the presence of GDM was a higher risk factor for DOL in pregnant women (random, OR = 1.84, 95% CI [1.34–2.52], I² = 53.8%) (Table 2 and Supplementary Fig. S1). The sensitivity analysis revealed that no study influenced the association between GDM and DOL (Supplementary Fig. S1). To find the heterogeneity source, we performed subgroup analysis depending on sample size, study design, and study quality, which illustrated that the association between GDM and DOL was still significant in all subgroups. The heterogeneity of the small sample size, large sample size, and high-quality subgroup decreased to an acceptable range (Table 2). Meta-regression suggested that the sample size of the GDM group (p = 0.002) was the source of heterogeneity, whereas study design (p = 0.27) and study quality (p = 0.22) were not. In the post hoc analysis, the meta-regression based on crude OR and adjusted OR showed an agreement of the pooled OR between GDM and DOL whether confounding factors were adjusted (p = 0.88).

Table 2.

The Results of Meta Analysis and Subgroup Analysis

Study or subgroup	No. of studies	No. of participants	Effects model	Pooled OR (95% CI)	Heterogeneity
Study or subgroup	No. of studies	No. of participants	Effects model	Pooled OR (95% CI)	I² (%)	p
The association between GDM and DOL
Original results	8	6,873	Random	1.84 (1.34–2.52)	53.8	0.03
Sample size of the GDM group
Sample of GDM groups <100	5	1,041	Fixed	2.83 (1.86–4.30)	15.7	0.32
Sample of GDM groups ≥100	3	5,832	Fixed	1.37 (1.12–1.67)	0.00	0.81
Study design
Prospective studies design	7	4,820	Random	2.06 (1.41–3.01)	56.0	0.034
Retrospective studies design	1	2,053	Random	1.25 (0.83–1.88)	NA	NA
Study quality
High quality (8–9 points)	4	4,213	Fixed	1.48 (1.19–1.83)	43.1	0.15
Medium quality (6–7 points)	3	2,460	Random	2.14 (1.01–4.50)	68.1	0.04
Low quality (<6 points)	1	200	NA	4.72 (1.43–15.63)	NA	0.01
The prevalence of DOL in GDM
Original results	10	2,073	Random	0.35 (0.30–0.40)	75.6	<0.001
Sample size of the GDM group
Sample of GDM groups <100	5	125	Fixed	0.46 (0.37–0.54)	25.8	0.25
Sample of GDM groups ≥100	5	1,948	Random	0.31 (0.26–0.36)	81.7	<0.001
Study design
Prospective studies design	7	719	Random	0.39 (0.29–0.49)	79.5	<0.001
Retrospective studies design	3	1,354	Random	0.33 (0.29–0.37)	51.3	0.13
Study quality
High quality (8–9 points)	4	635	Random	0.35 (0.24–0.45)	81.8	0.001
Medium quality (6–7 points)	5	1,426	Random	0.34 (0.30–0.49)	58.1	0.05
Low quality (<6 points)	1	12	Random	0.58 (0.30–0.86)	NA	NA
The risk factors of GDM women for predicting DOL
Primipara versus multipara	2	678	Fixed	2.54 (1.89–3.42)	0.00	0.39
Advance age versus normal	3	1,576	Fixed	1.05 (1.03–1.08)	49.3	0.14
Prepregnancy obesity versus normal	2	1,277	Fixed	1.55 (1.19–2.03)	0.00	0.96
Insulin versus diet modification only	2	1,277	Fixed	3.07 (1.72–5.47)	0.00	0.97

CI, confidence interval; DOL, delayed onset of lactogenesis; GDM, gestational diabetes mellitus; NA, no access; OR, odds ratio.

The prevalence of DOL in GDM

Ten studies totaling 2,073 women reported the prevalence of DOL in GDM women, and the pooled prevalence was between 22.9% and 58.3%. The results of the meta-analysis showed that the prevalence of DOL in GDM women was 35.0% (random, effect size [ES] = 0.35, 95% CI [0.30–0.40], I² = 75.6%) (Table 2 and Supplementary Fig. S2). The sensitivity analysis showed that the pooled prevalence was relatively stable and ranged from 31.0% to 36.0% (Supplementary Fig. S2). Simultaneously, we found that the I² value decreased significantly from 75.6% to 50.9% by omitting the study reported by Huang et al. (Table 3).²⁵ Three subgroup analyses based on study design, study quality, and sample size were established to explain further the high heterogeneity, which illustrated no significant decrease in heterogeneity except for the small sample size, retrospective study design, and medium-quality subgroup (Table 2). Sensitivity analysis of subgroups was performed since there was still higher heterogeneity in a large sample, prospective study design, and high-quality subgroup, which showed that the heterogeneity of the subgroups mentioned above decreased significantly when the study reported by Huang et al.²⁵ was removed (Table 3). Meta-regression analysis indicated that sample size (p = 0.01) and study design (p = 0.01) were the causes of high heterogeneity, but study quality was not (p = 0.39).

Table 3.

The Results of Sensitivity Analyses for Prevalence of Delayed Onset of Lactogenesis in Gestational Diabetes Mellitus Women

Before sensitivity analysis				Method of sensitivity analyses	After sensitivity analysis
Outcomes no. of studies	Pooled ES (95% CI)	I² (%)	p	Method of sensitivity analyses	No. of studies	Pooled ES (95% CI)	I² (%)	p
Original results
10	0.35 (0.30–0.40)	75.6	<0.001	Removing Huang 2019	9	0.36 (0.32–0.40)	50.9	0.04
Subgroup of sample of GDM groups ≥100
5	0.31 (0.26–0.36)	81.7	<0.001	Removing Huang 2019	4	0.34 (0.32–0.36)	27.2	0.25
Subgroup of prospective studies design
7	0.39 (0.29–0.49)	79.5	<0.001	Removing Huang 2019	6	0.37 (0.33–0.42)	53.6	0.06
Subgroup of high quality (8–9 points)
4	0.35 (0.24–0.45)	81.8	0.001	Removing Huang 2019	3	0.36 (0.30–0.41)	48.7	0.14

CI, confidence interval; ES, effect size; GDM, gestational diabetes mellitus.

Risk factors of DOL in GDM

Three articles of 1,561 women addressed the independent risk factors of DOL in GDM women, comprising primipara, advanced age, prepregnancy obesity, insulin treatment, and failure to re-examine glucose regularly.^26,27,32 We performed a meta-analysis for risk factors that were reported two times or more. The results suggested that primipara (fixed, OR = 2.54, 95% CI [1.89–3.42], I² = 0.0%), advanced age (fixed, OR = 1.05, 95% CI [1.03–1.08], I² = 49.3%), prepregnancy obesity (body mass index [BMI] ≥30 kg/m²) (fixed, OR = 1.55, 95% CI [1.19–1.03], I² = 0.0%), and insulin treatment during pregnancy (fixed, OR = 3.07, 95% CI [1.72–5.47], I² = 0.0%) were independent risk factors for DOL in GDM women (Table 2).

Publication bias

Begg's test was conducted according to the main outcome of the association between GDM and DOL to estimate publication bias, which suggested that no significant publication bias was detected (p = 0.17).

Discussion

The systematic review and meta-analysis of 11 studies presented a relatively comprehensive overview of GDM and DOL. The findings of our study suggested that GDM women were more likely to experience DOL, with its prevalence being 35.0%. Furthermore, primipara, advanced age, prepregnancy obesity, and insulin treatment during pregnancy were risk factors for DOL in GDM women.

This study indicated that GDM had an adverse effect on the timely onset of lactogenesis, which was similar to the conclusion of the review by De Bortoli and Amir.¹⁵ However, our study further provided quantitative and clear evidence that GDM women presented 1.84 times more risk of DOL than women without GDM. Although the mechanisms underlying the correlation between GDM and DOL have not been sufficiently studied, several plausible reasons may explain why GDM women have a higher risk of DOL. The onset of lactogenesis refers to breast tissue starts producing copious human milk after delivery, a process triggered by the high maintenance of prolactin when progesterone concentration drops dramatically after delivery.²⁵ GDM is a metabolic disease characterized by defective insulin secretion and/or defective insulin sensitivity.²⁸ However, previous studies have confirmed that insulin has a positive effect on prolactin production by contributing to prolactin mRNA accumulation and gene transcription.³⁴ Moreover, insulin could participate in lactocyte differentiation and the expression of milk protein synthesis gene directly.³⁵ Hence, these present pieces of evidence implicate that a relative lack of insulin may interfere with the hormonal pathways involved in lactogenesis onset, which is a possible reason why GDM causes the delay lactogenesis onset.^36,37 More experimental and mechanistic research should be conducted to verify this hypothesis.

The results of this meta-analysis illustrated that primipara, advanced age, prepregnancy obesity, and insulin treatment during pregnancy were independent risk factors of DOL in women with GDM. (1) Compared with multipara, the pooled OR of DOL in primiparous women with GDM was 2.54. The practicable reason for this is that due to inadequate breastfeeding experience, primiparas are prone to anxiety or less effective sucking by infants, which influences the level of prolactin postpartum.^14,38 (2) Compared with the appropriate age of GDM women, the pooled OR of advanced age was 1.05. This discrepancy may be because advanced age women are more likely to develop carbohydrate intolerance with the declining ability of hormone regulation.³⁷ (3) Compared with GDM women with a normal BMI, the pooled OR of prepregnancy obesity was 1.55, which was analogous to the previous meta-analysis of Garcia et al.³⁹ A possible explanation for this finding is that obese mothers experience higher insulin resistance.⁴⁰ (4) Compared with diet modification only, the pooled OR of insulin treatment was 3.07. One possible explanation is that women receiving insulin treatment have a more severe β-cell impairment and lower insulin sensitivity.⁴¹ Aside from the above findings, the risk factors of advanced age, prepregnancy obesity, and insulin treatment indicate that the severity of glucose metabolism dysfunction in GDM mothers may further hinder the timely onset of lactogenesis; however, verification is needed in the future.

There was some degree of heterogeneity in the meta-analysis of association and prevalence. After performing the sensitivity analysis, subgroup analysis, and meta-regression, we found that sample size was the main source of heterogeneity in the meta-analysis of the association between GDM and DOL, and the heterogeneity in the meta-analysis of prevalence could be attributed to the study of Huang et al.,²⁵ sample size, study design, and study quality. In the study reported by Huang et al.,²⁵ the lower prevalence might be because all participants included in this study participated in regular obstetric examinations, which may contribute to maintaining a stable blood sugar level and weaken the negative effects of GDM on lactogenesis onset.²⁷ In addition, the heterogeneity of sample size, study design, and study quality could be due to lack of sufficient representativeness of small population size, the recall bias due to the retrospective study design, and the effect of study quality on accuracy and reliability of results.

To our knowledge, this is the first systematic review and meta-analysis with comprehensive and quantitative analysis of the association between GDM and DOL, and the prevalence and risk factors of DOL in GDM women. In light of this study findings, clinicians should consider onset of lactogenesis in GDM women, specifically those with primipara, advanced age, and obesity, and encourage them to maintain normal insulin levels by diet modification and appropriate exercise (not insulin) during pregnancy. In addition, early breastfeeding-friendly support, such as breastfeeding within 1 hour after birth, rooming-in, and frequent nipple sucking, should be provided to GDM mothers to facilitate lactogenesis onset and subsequent breastfeeding practice. However, in clinical practice, GDM women and their infants have a higher possibility of mother–infant separation due to a higher risk of neonatal hypoglycemia.¹⁴ A new study has suggested that expressing breastfeeding from 36 gestational weeks is an effective and no-harm measure for pregnant women at low risk of complications with diabetes.⁴² Although not widely used in clinical practice, this strategy provides a feasible solution for the current clinical status.

There were also some limitations to this study. First, despite the sensitivity analysis suggesting that the evidence was stable and robust, heterogeneity in the association and prevalence was observed, which limited the interpretation of the results. Meanwhile, we detected the sample size, study design, and study quality as the main causes of heterogeneity, which indicates that larger sample size, high quality, and prospective studies may be designed to solve the limitations in the future. Second, there were clinical differences in the studies included in gestational age, mother–infant separation, and breastfeeding culture. These characteristics were, however, not analyzed in detail because of limited numbers or inaccurate characterization. Third, although the language was not restricted during the search, the studies included were published only in Chinese and English, suggesting a potential selection bias. Fourth, the pooled OR of association between GDM and DOL was calculated using original data that may not have considered the role of other residual confounding factors. Although we have checked the consistency between crude OR and adjusted OR, we believe that the pooled effect size should be estimated with data adjusted for confounding factors in the future. Finally, owing to the inadequate number of studies on risk factors, there may be a possibility that this meta-analysis does not comprehensively reflect the potential risk factors of DOL in GDM women. Therefore, it is necessary to perform more studies on these aspects to solve the deficiency.

Conclusion

A systematic review and meta-analysis found that GDM women have a higher risk of DOL, and their prevalence of DOL is 35%. The primipara, advanced age, prepregnancy obesity, and insulin treatment during pregnancy are independent risk factors for predicting DOL in women with GDM. Considering the limitations of included studies, large sample, high quality, and correcting the confounding factors, prospective studies are needed to more accurately quantify the degree of risk and prevalence of DOL in GDM women. In addition, more studies aimed to explore risk factors of DOL in GDM women should be conducted to develop a predictive risk model, which could help identify high-risk women in clinical practice and develop targeted prevention programs to prompt GDM women lactogenesis onset timely.

Footnotes

Disclosure Statement

No competing financial interests exist.

Funding Information

The study was supported by Nursing Research Fund of Fujian Maternity and Child Health Hospital (YCXMH 20-03).

Supplementary Material

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