Breastfeeding Improves Insulin Sensitivity and Fat Distribution in Women with Gestational Diabetes Mellitus: A Retrospective Pilot Study

Breastfeeding Improves Insulin Sensitivity and Fat Distribution in Women with Gestational Diabetes Mellitus: A Retrospective Pilot Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Breastfeeding Improves Insulin Sensitivity and Fat Distribution in Women with Gestational Diabetes Mellitus: A Retrospective Pilot Study Huanyu Zhou, Qing Yao, Zhou Chaomeng, Gao Jianbo, Song Zhe, Renata Belfort-DeAguiar, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4280525/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Aim: The aim of this study was to analyze the effects of breastfeeding on postpartum lipid metabolism, insulin sensitivity and body fat distribution in women with a history of gestational diabetes mellitus (GDM). Methods and Results: This was a retrospective pilot study. Participants were recruited from one-day GDM management clinics at the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University between 2017 and 2020. After obtaining their breastfeeding histories, the participants were divided into 2 groups based on their infant feeding practices: a non-breastfeeding group (n=11) and a breastfeeding group (n=20). Anthropometric measurements, insulin resistance indices (oral glucose tolerance test), questionnaires about infant feeding practices, and dietary intake and physical activity patterns were obtained at 6-28 weeks approximately 20 months postpartum. When comparing the breastfeeding and non-breastfeeding groups, body fat percentage, arm circumference, waist circumference, visceral fat area, and insulin sensitivity were significantly improved by breastfeeding ( P ≤0.05, for all). In addition, a longer duration of breastfeeding negatively correlated with arm circumference and waist circumference ( P ≤0.05, for all). Conclusions: Our study showed that breastfeeding improves lipid metabolism, body fat distribution and insulin sensitivity in women with GDM,which may be further influenced by the duration of breastfeeding. Breastfeeding gestational diabetes mellitus postpartum lipid metabolism insulin sensitivity Figures Figure 1 Figure 2 Figure 3 Introduction During pregnancy, changes in glucose and lipid metabolism lead to hyperlipidemia, fat accumulation and insulin resistance. Consequently, normal glucose metabolism is maintained by increasing the secretion of insulin. However, pregnant women with inadequate insulin secretion are unable to compensate for these physiological metabolic changes and develop gestational diabetes (GDM) as a result [1] . GDM is associated with a significant increase in the incidence of adverse pregnancy outcomes, such as preeclampsia, miscarriage, preterm birth, obstructed labor, macrosomia and fetal malformation [2] . The global average incidence of GDM varies from 9.3% to 25.5% [3] , and in mainland China, the incidence of GDM is 14.8% [4] . The levels of glucose tolerance usually return to normally after delivery in women with a history of GDM, but studies have shown that up to 35% of GDM patients do not return to normal within 3 months postpartum, but instead re-develop impaired glucose tolerance (IGT) [5] . Studies have shown that women with a previous history of GDM are at a sevenfold higher risk of developing Type II diabetes mellitus (T2DM) for 5-10 years after delivery [6] . A growing number of epidemiological studies have reported a significant inverse correlation between breastfeeding and the risk of postpartum metabolic diseases such as obesity and T2DM [7-9] . Animal and human studies have also suggested that breastfeeding could have beneficial effects on glucose tolerance, maternal weight, and body fat [10] . Some studies have shown that breastfeeding improves lipid metabolism, leading to higher high-density lipoprotein cholesterol (HDL) and lower triglycerides (TGs) [11] . Although breastfeeding is beneficial to all women, it appears to be particularly beneficial to those with a previous history of GDM [12,13] . The Study of Women, Infant Feeding, and Type 2 Diabetes after GDM Pregnancy (SWIFT), which had a racially and ethnically diverse cohort, found that an increase in breastfeeding intensity modified the circulating lipid profile in GDM women in the early postpartum period [14] . SWIFT also found that increasing the intensity and duration of breastfeeding was associated with a 57% reduction in the risk of T2DM in women with a history of GDM for the first two years after delivery [13] . In addition, several studies have shown that breastfeeding reduces insulin resistance and improves insulin secretion [15] . However, the exact mechanisms by which breastfeeding impacts lipid and glucose metabolism are not fully understood. As the incidence of metabolic diseases such as obesity and T2DM continues to increase globally [16, 17] , there is an urgent need to find methods to alleviate these conditions. The purpose of this study is to investigate the impact of postpartum breastfeeding on the risk of metabolic diseases in women with a history of GDM. We hypothesize that postpartum breastfeeding can alter body fat distribution, increase insulin secretion, and improve insulin sensitivity, thereby reducing the risk of metabolic diseases. Methods Study design and setting: Study Population: This was a retrospective, real-world study of pregnant women with a diagnosis of GDM who received routine prenatal and postnatal examinations between 2017 and 2020 at the one-day GDM management clinic of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, which guided diet, exercise and performed basic clinical tests. Gestational diabetes was diagnosed following the American Diabetes Association (ADA) recommendations during a standard 2-hour oral glucose tolerance test with 75 g of dextrose at 24-28 weeks of gestation. One or more of the three glycemic values (fasting, 1-hour and 2-hour blood glucose) must meet or exceed the glycemic threshold recommended by the ADA. Patients who fulfilled the criteria received standard treatment for GDM [18] . A study recruitment flowchart is shown in Figure 1. During the 3-year period, 392 medical records of women with GDM were reviewed. Women who fulfilled the inclusion and exclusion criteria were invited to participate in the study. Inclusion criteria: between 20 and 45 years old; outpatient and inpatient records available in the health care system, including clinical records and birth records; duration of gestation ≥35 weeks; single and live birth; history of GDM (as defined by the ACOG criteria); and glycated hemoglobin (HbA1c) < 6.5% after delivery. Exclusion criteria: women who were currently breastfeeding;pre-pregnancy diagnosis of diabetes (T1DM or T2DM, as defined by the ADA criteria);current use of any hypoglycemic drugs;use of steroids or other drugs that significantly affect glucose tolerance;pregnancy-related complications, including gestational hypertension, pregnancy with thyroid dysfunction;major congenital fetal abnormalities; hypertension before pregnancy; obesity; known mental illness, alcohol abuse, human immunodeficiency virus (HIV), hepatitis, kidney, liver disease, untreated heart disease, untreated thyroid disease, active systemic infection or malignancy;illicit drug use (self-report of cases);history of postpartum depression; dietary intake and physical activity during pregnancy that is inconsistent with the postpartum dietary intake and physical activity; weight loss supplement use or dieting for 6 months prior to the study; and prenatal and/or postnatal care not being done at the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University. After reviewing medical records, 226 women were excluded: 94 due to not having delivered at the Affiliated Changzhou No. 2 People's Hospital, 56 due to obesity, 29 due to gestational hypertension, 24 due to pregnancy with thyroid dysfunction, 7 due to diabetes prior to pregnancy, 5 due to contagious diseases prior to pregnancy, and 11 due to hypertension prior to pregnancy. One hundred sixty-six pregnant women met the inclusion and exclusion criteria. They were contacted by telephone 6-28 months after delivery. During the call, they answered a questionnaire to determine the method used to feed the baby and the frequency and intensity of breastfeeding. They were then divided into two groups: non-breastfeeding and breastfeeding. The non-breastfeeding group consisted of women who exclusively fed or primarily fed formula after delivery (who did not breastfeed at all or who breastfed for less than 3 weeks while also feeding at least 14 ounces of formula per day). The breastfeeding group consisted of women who were exclusively or primarily breastfeeding for at least 6 months after delivery (feeding no more than 6 ounces of formula per day). Among the women contacted, 83 participants were excluded due to mixed feeding methods, loss of contact and unwillingness to participate in the study. Eighty-three women (17 non-breastfeeding and 66 breastfeeding) were considered eligible and agreed to participate in the study. Of these, 6 non-breastfeeding and 46 breastfeeding women did not want to come to the in-person research visit or could not come because of a busy work schedule. Ultimately, 11 women were enrolled in the non-breastfeeding group and 20 in the breastfeeding group. They all agreed to come for a postpartum OGTT visit and signed informed consent forms. The procedures followed in this study were in line with the ethical standards established by the Human Trial Committee of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University and were approved by the committee ([2021]KY013-01). Research Visits: Data collection at the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University occurred at the following time points: Diagnosis during pregnancy (24-28 weeks of gestation), Baseline visit during pregnancy (36 weeks of gestation), Phone call after delivery (phone call between 6-28 months after delivery) and Research visit after delivery (research visit between 8-30 months after delivery). The research visit occurred approximately 2 months after the phone call (Supplementary Figure S1). Participants were diagnosed with GDM at 24-28 weeks of gestation. Prenatal clinical parameters were collected at 36 weeks of pregnancy. A phone call was conducted after delivery to identify eligible study participants. Signed informed consent for participating in the study was obtained at the in-person visit, which included permission to obtain information on perinatal outcomes from electronic databases. Diagnosis: The 75 g oral glucose tolerance test (OGTT) for the diagnosis of GDM was carried out at 24-28 weeks gestation. The cut-off points in OGTT were typically determined based on blood glucose levels. The diagnostic criteria for GDM are as follows: Fasting Plasma Glucose (FPG)≥5.1 mmol/L; 1-hour Plasma Glucose (1hPG)≥10.0 mmol/L; 2-hour Plasma Glucose (2hPG)≥8.5 mmol/L. If a pregnant woman meets any of the diagnostic criteria mentioned above in any of the tests, she can be diagnosed with GDM. The following is the classification of OGTT results based on the World Health Organization (WHO) 2019 recommendations: FPG: Normal: <6.1 mmol/L; Diabetes: ≥7.0 mmol/L; IGT: 6.1 - 6.9 mmol/L. 2hPG: Normal: <7.8 mmol/L; Diabetes: ≥11.1 mmol/L; IGT: 7.8 - 11.0 mmol/L. Based on the above cut-off points, OGTT results can be classified as normal, diabetes, or IGT. On the day before the OGTT, participants were asked to fast after dinner for at least 8 hours until the next morning (no later than 9:00 am). Participants maintained normal physical activity and a normal diet (with no less than 150 g of carbohydrates per day) during the 3 days prior to the OGTT and sat quietly and did not smoke during the visit. The ADA recommended that 75 g of glucose be dissolved in 250 ml water and taken orally within 5 minutes for adults. Blood glucose was obtained at fasting and at 60 minutes and 120 minutes after drinking the glucose solution [19] . Baseline visit: Clinical parameters and anthropometric measurements were collected at 36 weeks of pregnancy. Clinical information, including age, gravidity and parity, was obtained from the outpatient and inpatient record system of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University. Delivery information: Information such as newborn weight and cesarean section rate were completed at the time of delivery. These formed the clinical parameters of this study by reviewing the information of the hospital's medical system and the perinatal examination manual (Figure 2, Table 1). Anthropometric measurements mainly included body weight, height, body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP). Body weight was obtained using the portable Tanita® WB 100A digital scale. Before being weighed, participants were asked to take off their coats, wear a single layer of clothing, empty their pockets, and remove any accessories that might interfere with the measurement. Height was measured by a Seca portable stadiometer (Model 67029) with a range of 8 inches to 82 inches and graded in inches and centimeters. Participants were asked to remove their shoes and any hair accessories to obtain an accurate measurement. BMI was defined as weight/(height*height). SBP and DBP were measured from the left arm in a sitting position after at least 10 min of rest with an electronic sphygmomanometer with appropriate cuff sizes (ERKA Perfect-Aneroid, Germany). Two measurements were taken by trained personnel while the arm was supported at heart level. The measurements were repeated twice, five minutes apart. The values reported are the means of the two measurements. Obesity was defined as a BMI of 30 kg/m 2 or higher [20] . Chemiluminescence immunoassay (CLIA) was used for thyroid function, the clinical laboratory parameters were involved: thyroid-stimulating hormone (TSH), free thyroxine 3 (FT3) and free thyroxine 4 (FT4). Continuous monitoring method was used for liver function, the clinical laboratory parameters were involved: alanine transaminase (ALT), aspartate transaminase (AST), triglycerides (TGs), total cholesterol (TC), HDL and low-density lipoprotein cholesterol (LDL). Hemoglobin A1c (HbA1c) was also obtained at this visit. Phone call: Between 6-28 months after delivery, participants were contacted by phone to determine their interest in the study and whether they would qualify for the study. During this phone call, participants completed a screening questionnaire (including maternal and child health, condition of pregnancy, use of contraception and sociodemographic information, as well as the history of infant feeding data). It was designed to assess the frequency and intensity of breastfeeding. The eligible women were invited to participate in this study. Research visit: Study procedures at this visit occurred at 8-30 months after delivery and included anthropometric measurements, collection of blood specimens and self-and interviewer-administered questionnaires to collect data on early postpartum characteristics. Among them, blood specimens were collected to measure glucose and insulin, and for a lipid panel. Participants underwent an OGTT, in which glucose and insulin levels were obtained to calculate indices of insulin sensitivity and insulin secretion (pancreatic β cell function). Participants were asked to fill out questionnaires about diet and physical activity. Indices of glucose metabolism: On the day of the research visit, participants came to the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University for a repeat 75 g OGTT and anthropometric measurements. Indices of glucose metabolism obtained during the OGTT included the homeostasis model insulin resistance index (HOMA-IR), the insulin sensitivity-oral glucose tolerance test (IS-OGTT), the insulin secretion sensitivity index-2 (ISSI-2), and the insulinogenic index/HOMA-IR (IGI/HOMA-IR). Formulas to calculate glucose metabolism indices: HOMA-IR, an index for estimating insulin resistance, was calculated as follows: FPG*FPI/22.5 (FPI: fasting plasma insulin). IS-OGTT is an index used to determine insulin sensitivity, which has been shown to have a good correlation with the hyperinsulinemic euglycemic clamp [21] . IS-OGTT was defined as 10000/square root (FPG*FPI) * (G*I) (G: means glucose during the OGTT, I: means insulin) [21] . ISSI-2 was the primary index used to determine insulin secretion (a measurement of pancreatic β cell function). ISSI-2 was calculated as the area under the insulin curve/area under the glucose curve [22, 23] . IGI/HOMA-IR, also used as an index of pancreatic β cell function, was calculated as the ratio of the incremental change in insulin during the first 30 minutes of the OGTT to the incremental change in glucose over the same time period [24] .The composite measure of pancreatic β cell function by insulin resistance (reported as the oral disposition index (DI O )) was calculated as ΔI 0–30 /ΔG 0–30 ×1/fasting insulin [25] . Self- and interviewer-administered questionnaires: Participants completed a one-day review of dietary intakes with the food frequency questionnaire (FFQ) questionnaire, which was self-completed or completed by the interviewer. The semiquantitative FFQ consists of a list of ninety-three foods most commonly consumed in Italy [26, 27] . For this study, the food variety of the FFQ was adjusted to the most common foods consumed in the Chinese diet [27] (Table S3). During pregnancy, participants were given an electronic weight scale (Soehnle, Germany) to quantify the food portion consumed and, when away from home, to use household measures [26] . Based on the average amount of each participant's consumption, nutritional analysis of the main foods was performed to calculate participants' dietary nutrient intakes (Table S3). Additionally, based on an adapted version of the international physical activity questionnaire (IPAQ), an analysis of daily exercise time (such as fast walking and yoga) and daily leisure time was calculated for all participants [28] . Throughout pregnancy and different breastfeeding stages of the study, the participants' postpartum diet pattern, amount and frequency did not change significantly, nor did their physical activity. Body composition analysis and anthropometric measurements: The body composition analyzer INBODY770 (BIA bioimpedance detection technology) was used to measure body composition, including protein, body fat, skeletal muscle, body fat percentage, torso, arm circumference, waist circumference, visceral fat area, basal metabolic rate and other health indices. Participants were asked to stand and hang their arms straight down the sides of the body, and the tape was used around the thickest part of the upper arm to determine arm circumference. Waist circumference was measured midway between the iliac crest and the lowest lateral portion of the rib cage and anteriorly midway between the xiphoid process of the sternum and the umbilicus. Participants, who were on an empty stomach, were asked to stand and keep their feet 25 to 30 centimeters apart when measuring waist circumference. Two consecutive measurements were taken and recorded, and a third measurement was taken and recorded if the first and second measurements differed by more than 1 centimeter. Arm circumference and waist circumference were also obtained with a body composition analyzer. Because both data were very similar and to minimize human error, we opted to use the arm circumference and waist circumference data from the body composition analyzer. Body fat percentage refers to the proportion of body fat weight by total body weight. Central obesity was measured by visceral fat area (Tanita scale) and waist circumference. Statistical analysis : SPSS 18.0 statistical software was used for statistical analysis. When the data were normally distributed with similar variance, the Student’s t test was used, and the quantitative data were expressed as the mean ± standard error. When the data did not conform to a normal distribution, the Mann‒Whitney test was used, and the data were expressed as the mean (minimum, maximum). Spearman correlation analysis was required when studying whether there was a correlation between an indicator and a result. The correlation coefficient reflected the correlation. The results were visually demonstrated with a scatterplot graph. P ≤0.05 indicated that the difference was statistically significant. Results Clinical characteristics of participants The baseline characteristics during pregnancy and delivery information of the women with a history of GDM in the breastfeeding and non-breastfeeding groups are shown in Table 1. No significant differences were observed when comparing the two groups (all P ＞0.05), except for HbA1c ( P =0.052) and cesarean section rate ( P =0.034). According to the postpartum characteristics of women with a history of GDM, there was no significant difference between the breastfeeding group and the non-breastfeeding group ( P ＞0.05), except for SBP ( P =0.021), FT4 ( P =0.030) and ALT ( P =0.009) (Table S1). Breastfeeding improves body fat composition Figure 2 (and Table S1) shows the differences in the measurements of body fat content in the breastfeeding and non-breastfeeding groups. Body weight (breastfeeding: 59.9±9.7 kg vs. non-breastfeeding: 66.4±13.4 kg; P =0.130) and weight loss (breastfeeding: 8.3±7.2 kg vs. non-breastfeeding: 4.5±10.6 kg; P =0.246) from the baseline visit to the postpartum visit were not significantly different between the two groups. At the postpartum visit, measurements of body composition obtained with bioimpedance demonstrated that body fat ( P =0.053), body fat percentage ( P =0.041), arm circumference ( P =0.048), waist circumference ( P =0.046) and visceral fat area ( P =0.050) were lower in the breastfeeding group than in the non-breastfeeding group ( P ≤0.05, for all). Breastfeeding improves insulin sensitivity Figure 2 (and Table S1) shows the differences in the indices of insulin resistance and insulin secretion in the breastfeeding and non-breastfeeding groups. There was no significant difference between the breastfeeding group and the non-breastfeeding group in glucose and insulin levels during OGTT ( P ＞0.05), except the breastfeeding group had a trend for lower insulin levels at 60 minutes (breastfeeding: 63.7 (18.3-168.0) μU/mL vs. non-breastfeeding: 88.3 (11.2-168.3) μU/mL; P =0.054). HOMA-IR ( P =0.046) in the breastfeeding group was significantly lower than that in the non-breastfeeding group. Similarly, IS-OGTT ( P =0.016), an index for the measurement of insulin sensitivity, was significantly higher in the breastfeeding group than in the non-breastfeeding group. No differences in indices of insulin secretion, ISSI-2 ( P =0.335) and IGI/HOMA-IR ( P =0.761), were seen when comparing the two groups. There was no significant difference in the composite measure of pancreatic β cell function, calculated from DI O ( P =0.530), between the breastfeeding group and the non-breastfeeding group. Correlation between duration of breastfeeding and body fat composition To further understand the metabolic effects of breastfeeding in preventing obesity and T2DM, we investigated whether the duration of breastfeeding correlates with indices of body fat composition, insulin resistance and insulin sensitivity. Figure 3 (Table S2) shows that the duration of breastfeeding was inversely correlated with arm circumference and waist circumference ( P ≤0.05). There was a trend for the duration of breastfeeding and a decrease in body fat, body fat percentage, visceral fat area, HOMA-IR and IS-OGTT (all P <0.1). The duration of breastfeeding did not correlate with indices of insulin secretion (IGI/HOMA-IR) ( P =0.678) or pancreatic β cell function (DI O ) ( P =0.877). Breastfeeding ameliorates blood pressure and liver and thyroid function SBP and DBP were comparable in the breastfeeding and non-breastfeeding groups at baseline. However, at the postpartum visit, systolic blood pressure was significantly lower in the breastfeeding group than in the non-breastfeeding group (breastfeeding: 113.0±12.0 mmHg vs. non-breastfeeding: 125.0±15.0 mmHg; P =0.021), as was ALT (breastfeeding: 12.8 (9.0-20.0) U/L vs. non-breastfeeding: 26.6 (8.0-76.0) U/L; P =0.009). FT4 in the breastfeeding group was significantly higher than that in the non-breastfeeding group (breastfeeding: 21.4±3.0 pmol/L vs. non-breastfeeding: 18.9±2.4 pmol/L; P =0.030). Dietary intake and physical activity Table S1 shows the differences in dietary intake and physical activity between the breastfeeding and non-breastfeeding groups. This study confirmed that there were no significant group differences in dietary intake and physical activity. Discussion In this study, we compared the effects of breastfeeding on body fat distribution and glucose metabolism in women with a history of GDM. We found that breastfeeding decreased body fat and body fat percentage; reduced arm circumference, waist circumference, and visceral fat area; and improved insulin sensitivity; however, it did not affect pancreatic β cell function in women with a history of GDM. At the same time, we found that systolic blood pressure in the breastfeeding group was lower than that in the non-breastfeeding group. Breastfeeding meets the metabolic requirements for lipid synthesis in milk by increasing food intake, mobilizing TG stored in the body and increasing the production of liver glycogen to provide substrates for the synthesis of TG by mammary epithelial cells [29] . Breastfeeding also decreases the activity of lipoprotein lipase in adipocytes, resulting in less TG entering adipocytesand ramping up fat metabolism to increase milk production [30,31] . The current results showed that body fat, body fat percentage, arm circumference, waist circumference and visceral fat area in the breastfeeding group were significantly lower than those in the non-breastfeeding group, which is consistent with the studies described above. In addition, the type, quantity and frequency of food intake and physical activity of the participants did not change significantly during both pregnancy and breastfeeding, suggesting that the beneficial effects of breastfeeding were not due to differences in diet and exercise between the two groups but were most likely due to changes in lipid metabolism and body fat redistribution. During the first trimester of pregnancy, circulating insulin levels increase, and adipose tissue becomes more sensitive to insulin, thereby promoting the production and storage of lipids [32-34] . With the progression of pregnancy, a rise in placental hormones antagonistic to insulin leads to a switch from increased insulin sensitivity to insulin resistance, which allows the transfer of maternal nutrients and energy to the fetus. The insulin resistance of pregnant women with GDM is especially observed in late weeks of gestation. Insulin resistance is the first metabolic abnormality observed in patients with GDM. Hyperglycemia, on the other hand, only occurs when maternal pancreatic β cells can no longer secrete enough insulin to offset insulin resistance in peripheral tissues [35] . In the current results, compared with the non-breastfeeding group, the breastfeeding group showed significantly lower HOMA-IR and higher IS-OGTT, indicating that breastfeeding improved insulin sensitivity in women with a history of GDM. Similar results showing that breastfeeding improves insulin resistance have been described by other authors [8, 36] . During breastfeeding, prolactin induces serotonin production in pancreatic β cells. Studies have shown that serotonin improves insulin secretion by increasing pancreatic β cell proliferation and reducing oxidative stress in pancreatic β cells, thereby mediating the long-term beneficial effects of breastfeeding on female metabolic health [36] . In the present findings, there was no difference in the function of pancreatic β cells between the non-breastfeeding group and the breastfeeding group. This result might be related to the fact that our participants were studied after they had already stopped breastfeeding. A study documented that increased prolactin release during breastfeeding promoted the release of serotonin, which induced pancreatic β cell proliferation and increased insulin secretion [36,37] . When breastfeeding is discontinued, maternal prolactin levels return to normal, no longer promoting pancreatic β cell proliferation and thus decreasing insulin secretion. However, the pancreatic β cell function of breastfeeding women with a history of GDM will still be in a significantly improved state [38] . A prospective study also confirmed that compared with breastfeeding for less than 3 months, a duration of breastfeeding over 12 months was associated with less insulin resistance, lower fasting blood glucose, and lower blood glucose after meals, but there was no difference in the secretion function of pancreatic β cells [8] . This study suggested that breastfeeding affects the natural history of insulin resistance but not the function of pancreatic β cells. Those results were similar to the present findings: no change in insulin secretion (ISSI-2, IGI/HOMA-IR and DI O ) but improvement in insulin resistance (HOMA-IR and IS-OGTT). The American Academy of Pediatrics (AAP) recommends that women breastfeed for at least 12 months. While this recommendation is intended to optimize early childhood nutrition, it may also provide metabolic benefits for mothers. Prior research studies demonstrated that breastfeeding has significant metabolic benefits for the mother, including increasing energy expenditure (used to produce milk), improving body fat, lowering blood glucose levels, and improving insulin sensitivity [20] . The results from these studies showed a statistically significant negative correlation between the duration of breastfeeding and body fat composition (arm circumference and waist circumference) in women with a history of GDM after weaning. Our findings confirm the results from previous studies that breastfeeding improves body fat redistribution in women with a history of GDM, and a longer duration of breastfeeding results in additional benefits in lipid metabolism. The current results also found that the duration of breastfeeding seems to be associated with indicators of response to insulin resistance and insulin sensitivity. Epidemiological studies have shown that women with an increased duration of breastfeeding had a lower long-term risk of developing T2DM, although the mechanism of this relationship is unclear [39-43] . The data of the current results did not show any change in the incidence of T2DM or/and IGT, but this may be due to the small sample size and short duration of observation (< 2 years). Further studies are needed to better understand the specific mechanisms by which breastfeeding duration affects postpartum lipid metabolism and insulin sensitivity after weaning in women with a history of GDM and the potential benefits of altering body fat redistribution in preventing T2DM and other metabolic diseases. Breastfeeding helps to reverse some metabolic changes more quickly and completely by mobilizing fat stores accumulated during pregnancy. These changes in maternal metabolism may reduce the risk of developing metabolic diseases in the future, including cardiovascular disease, fatty liver, and thyroid dysfunction. The study found that systolic blood pressure in the breastfeeding group was significantly lower than that in the non-breastfeeding group, an indication that breastfeeding may have a beneficial effect on cardiovascular disease in women with a history of GDM. ALT tends to be elevated in alcoholic and fatty liver disease [44] . In the study presented here, liver function abnormalities, such as alcoholism and fatty liver, during pregnancy and the postpartum period were explicitly excluded based on the exclusion criteria. Nevertheless, we still found that ALT in the breastfeeding group was significantly lower than that in the non-breastfeeding group. It is possible that breastfeeding may reduce fatty liver infiltration and improve liver function in women with a history of GDM [45] . Indeed, a study demonstrated that breastfeeding for more than 6 months was associated with a reduced risk of nonalcoholic fatty liver disease in midlife [44] . FT4 was significantly higher in the breastfeeding group than in the non-breastfeeding group. This result suggested that breastfeeding can improve the maternal endocrine metabolic system. A follow-up study of 550 women with previous GDM found that there was a positive correlation between the duration of breastfeeding and maternal long-term thyroid function, with a longer duration of breastfeeding being associated with higher thyroid hormone levels [46] . Our findings support the findings that breastfeeding may be beneficial to lower cardiovascular disease, fatty liver disease/fatty liver inflammation and thyroid disease. However, at present, there are limited clinical or epidemiological studies on the relationship between breastfeeding and fatty liver disease and thyroid dysfunction, and whether they may be important for preventing breastfeeding-associated cardiovascular disease. Further studies will be necessary to confirm these findings. Compared with previous studies [8,36,47] , there are some advantages to this study. First, the distribution of lipids is reflected by using a human composition analyzer. Second, indicators such as HOMA-IR, IS-OGTT, ISSI-2, IGI/HOMA-IR and DI O are used to reflect insulin resistance and pancreatic β cell function. Third, this study eliminates the confounding factors of diet and exercise by using well-validated questionnaires for the quantification of physical activity and eating patterns, in addition to measurements of breast feeding. Finally, compared with other studies, this study performs standardized diabetes screening after delivery rather than relying solely on participants' self-detection of postpartum T2DM [48,49] . However, there are some limitations to this study. First, the sample size is relatively small. Although we initially identified 392 women with a history of GDM, the number of confirmed samples was relatively small due to the strict inclusion and exclusion criteria. The present findings will extend the study period to nearly 5 years or extend the study to several nearby cities, and be further verified in animal experiments. Second, the present findings did not measure HbA1c at the postpartum visit; however, we performed an OGTT, which is one of the standard tests for the diagnosis of diabetes (ADA) [18] . Third, the cesarean section rate may be a confounding factor for this study (P<0.05 when comparing the two groups at baseline). However, whether the mode of delivery has an impact on postpartum insulin resistance and body fat composition in women with GDM is still highly controversial [50,51] . Finally, this study did not use the gold-standard methods (hyperinsulinemic-euglycemic-clamp or hyperglycemic-clamp) to evaluate pancreatic β cell function and insulin resistance but the HOMA-IR and IS-OGTT indices. Although the accuracy of HOMA-IR and IS-OGTT in measuring insulin resistance/insulin sensitivity is lower than that of the clamp method [47, 52] , they have been widely used in clinical and scientific research and are also good indices for predicting future diabetes [53] . In conclusion, this study confirms that breastfeeding improves body fat composition and enhances insulin sensitivity in women with a history of GDM. In addition, a longer duration of breastfeeding alters body fat redistribution after delivery in women with a history of GDM. This study further supports the beneficial effects of breastfeeding in ameliorating maternal glucose and fat metabolism, blood pressure, thyroid function, and liver function. Breastfeeding promotes a long-lasting healthier metabolic environment important for preventing T2DM and cardiovascular diseases in women with a history of GDM. Declarations Acknowledgments: The authors wish to thank Liulan Qian and Jianlei Gu, for their help with data analysis. Funding: This study was supported by Changzhou Sci&Tech Program (Grant No.CZ20210025). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author contributions: Study concept and design: Jinhua Wei, Renata Belfort-DeAguiar, Zhongzhi Jia. Telephone recruitment: Jinhua Wei, Huanyu Zhou, Yao Qing, Chaomeng Zhou. Specimen collection: Huanyu Zhou, Yao Qing, Chaomeng Zhou, Zhe Song. Analysis and interpretation of data: Jinhua Wei, Huanyu Zhou, Yao Qing, Chaomeng Zhou, Renata Belfort-DeAguiar, Jianbo Gao. Writing the manuscript: Huanyu Zhou, Jinhua Wei. Revising the manuscript: Jinhua Wei, Zhongzhi Jia, Renata Belfort-DeAguiar, Jianbo Gao. Competing interests: The authors indicate no potential conflicts of interest. Ethical standards: This study was reviewed and approved by [the Institutional Ethics Committee], with the approval number: [[2021]KY013-01]. All participants/patients (or their proxies/legal guardians) provided informed consent to participate in the study. All participants/patients (or their proxies/legal guardians) provided informed consent for the publication of their anonymised case details and images. References American Diabetes Association Professional Practice C, American Diabetes Association Professional Practice C, Draznin B, Aroda VR, Bakris G, Benson G, et al. 16. Diabetes Care in the Hospital: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Supplement_1):S244-S53. Mack LR TP. Gestational Diabetes: Diagnosis, Classification, and Clinical Care. Obstetrics and gynecology clinics of North America. 2017;44(2):207-17. Agarwal MM DG, Shah SM. Gestational diabetes mellitus: simplifying the international association of diabetes and pregnancy diagnostic algorithm using fasting plasma glucose. Diabetes care. 2010;33(9):2018-20. Gao C, Sun X, Lu L, Liu F, Yuan J. Prevalence of gestational diabetes mellitus in mainland China: A systematic review and meta-analysis. J Diabetes Investig. 2019;10(1):154-62. Sinha B, Brydon P, Taylor RS. Maternal ante-natal parameters as predictors of persistent postnatal glucose intolerance: a comparative study between Afro-Caribbeans, Asians and Caucasians. Diabet Med. 2003;20(5):382-6. Bellamy L, Casas JP, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet. 2009;373(9677):1773-9. Gunderson EP, Lewis CE, Lin Y, Sorel M, Gross M, Sidney S, et al. Lactation Duration and Progression to Diabetes in Women Across the Childbearing Years: The 30-Year CARDIA Study. JAMA Intern Med. 2018;178(3):328-37. Bajaj H, Ye C, Hanley AJ, Connelly PW, Sermer M, Zinman B, et al. Prior lactation reduces future diabetic risk through sustained postweaning effects on insulin sensitivity. Am J Physiol Endocrinol Metab. 2017;312(3):E215-E23. Kirkegaard H, Bliddal M, Stovring H, Rasmussen KM, Gunderson EP, Kober L, et al. Breastfeeding and later maternal risk of hypertension and cardiovascular disease - The role of overall and abdominal obesity. Prev Med. 2018;114:140-8. Brewer MM, Bates MR, Vannoy LP. Postpartum changes in maternal weight and body fat depots in lactating vs nonlactating women. Am J Clin Nutr. 1989;49(2):259-65. Gunderson EP, Kim C, Quesenberry CP, Jr., Marcovina S, Walton D, Azevedo RA, et al. Lactation intensity and fasting plasma lipids, lipoproteins, non-esterified free fatty acids, leptin and adiponectin in postpartum women with recent gestational diabetes mellitus: the SWIFT cohort. Metabolism. 2014;63(7):941-50. Gunderson EP. Impact of breastfeeding on maternal metabolism: implications for women with gestational diabetes. Curr Diab Rep. 2014;14(2):460. Gunderson EP, Hedderson MM, Chiang V, Crites Y, Walton D, Azevedo RA, et al. Lactation intensity and postpartum maternal glucose tolerance and insulin resistance in women with recent GDM: the SWIFT cohort. Diabetes Care. 2012;35(1):50-6. Zhang Z, Lai M, Piro AL, Alexeeff SE, Allalou A, Rost HL, et al. Intensive lactation among women with recent gestational diabetes significantly alters the early postpartum circulating lipid profile: the SWIFT study. BMC Med. 2021;19(1):241. Tigas S, Sunehag A, Haymond MW. Metabolic adaptation to feeding and fasting during lactation in humans. J Clin Endocrinol Metab. 2002;87(1):302-7. Wright SM, Aronne LJ. Causes of obesity. Abdom Imaging. 2012;37(5):730-2. American Diabetes A. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020;43(Suppl 1):S14-S31. American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2013;36 Suppl 1:S67-74. Lipsky BA, Senneville E, Abbas ZG, Aragon-Sanchez J, Diggle M, Embil JM, et al. Guidelines on the diagnosis and treatment of foot infection in persons with diabetes (IWGDF 2019 update). Diabetes Metab Res Rev. 2020;36 Suppl 1:e3280. Apovian CM. Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 2016;22(7 Suppl):s176-85. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22(9):1462-70. Retnakaran R, Shen S, Hanley AJ, Vuksan V, Hamilton JK, Zinman B. Hyperbolic relationship between insulin secretion and sensitivity on oral glucose tolerance test. Obesity (Silver Spring). 2008;16(8):1901-7. Retnakaran R, Qi Y, Goran MI. Evaluation of proposed oral disposition index measures in relation to the actual disposition index. Diabet Med. 2009;26(12):1198-203. Kahn SE. The relative contributions of insulin resistance and beta-cell dysfunction to the pathophysiology of Type 2 diabetes. Diabetologia. 2003;46(1):3-19. Utzschneider KM, Prigeon RL, Faulenbach MV, Tong J, Carr DB, Boyko EJ, et al. Oral disposition index predicts the development of future diabetes above and beyond fasting and 2-h glucose levels. Diabetes Care. 2009;32(2):335-41. Fidanza F, Gentile MG, Porrini M. A self-administered semiquantitative food-frequency questionnaire with optical reading and its concurrent validation. Eur J Epidemiol. 1995;11(2):163-70. Hong X, Ye Q, Wang Z, Yang H, Chen X, Zhou H, et al. Reproducibility and validity of dietary patterns identified using factor analysis among Chinese populations. Br J Nutr. 2016;116(5):842-52. Craig C, Marshall A, SJÖSTRÖM Michael, et al. International Physical Activity Questionnaire: 12-Country Reliability and Validity. Med Sci Sports Exerc. 2003;35(8):1381-1395. Rudolph MC, Neville MC, Anderson SM. Lipid synthesis in lactation: diet and the fatty acid switch. J Mammary Gland Biol Neoplasia. 2007;12(4):269-81. Ghio A, Bertolotto A, Resi V, Volpe L, Di Cianni G. Triglyceride metabolism in pregnancy. Adv Clin Chem. 2011;55:133-53. Patel OV, Casey T, Dover H, Plaut K. Homeorhetic adaptation to lactation: comparative transcriptome analysis of mammary, liver, and adipose tissue during the transition from pregnancy to lactation in rats. Funct Integr Genomics. 2011;11(1):193-202. Einstein FH, Fishman S, Muzumdar RH, Yang XM, Atzmon G, Barzilai N. Accretion of visceral fat and hepatic insulin resistance in pregnant rats. Am J Physiol Endocrinol Metab. 2008;294(2):E451-5. Ramos-Roman MA. Prolactin and lactation as modifiers of diabetes risk in gestational diabetes. Horm Metab Res. 2011;43(9):593-600. Rieck S, Kaestner KH. Expansion of beta-cell mass in response to pregnancy. Trends Endocrinol Metab. 2010;21(3):151-8. Petersen MC, Shulman GI. Mechanisms of Insulin Action and Insulin Resistance. Physiol Rev. 2018;98(4):2133-223. Moon JH, Kim H, Kim H, Park J, Choi W, Choi W, et al. Lactation improves pancreatic beta cell mass and function through serotonin production. Sci Transl Med. 2020;12(541). McManus RM, Cunningham I, Watson A, Harker L, Finegood DT. Beta-cell function and visceral fat in lactating women with a history of gestational diabetes. Metabolism. 2001;50(6):715-9. Kim H, Toyofuku Y, Lynn FC, Chak E, Uchida T, Mizukami H, et al. Serotonin regulates pancreatic beta cell mass during pregnancy. Nat Med. 2010;16(7):804-8. Perrine CG, Nelson JM, Corbelli J, Scanlon KS. Lactation and Maternal Cardio-Metabolic Health. Annu Rev Nutr. 2016;36:627-45. Jager S, Jacobs S, Kroger J, Fritsche A, Schienkiewitz A, Rubin D, et al. Breast-feeding and maternal risk of type 2 diabetes: a prospective study and meta-analysis. Diabetologia. 2014;57(7):1355-65. Schwarz EB, Brown JS, Creasman JM, Stuebe A, McClure CK, Van Den Eeden SK, et al. Lactation and maternal risk of type 2 diabetes: a population-based study. Am J Med. 2010;123(9):863 e1-6. Stuebe AM, Rich-Edwards JW, Willett WC, Manson JE, Michels KB. Duration of lactation and incidence of type 2 diabetes. JAMA. 2005;294(20):2601-10. Villegas R, Gao YT, Yang G, Li HL, Elasy T, Zheng W, et al. Duration of breast-feeding and the incidence of type 2 diabetes mellitus in the Shanghai Women's Health Study. Diabetologia. 2008;51(2):258-66. Ajmera VH, Terrault NA, VanWagner LB, Sarkar M, Lewis CE, Carr JJ, et al. Longer lactation duration is associated with decreased prevalence of non-alcoholic fatty liver disease in women. J Hepatol. 2019;70(1):126-32. Belfort R, Harrison SA, Brown K, Darland C, Finch J, Hardies J, et al. A placebo-controlled trial of pioglitazone in subjects with nonalcoholic steatohepatitis. N Engl J Med. 2006;355(22):2297-307. Panuganti PL, Hinkle SN, Rawal S, Grunnet LG, Lin Y, Liu A, et al. Lactation Duration and Long-Term Thyroid Function: A Study among Women with Gestational Diabetes. Nutrients. 2018;10(7). Gunderson EP, Matias SL, Hurston SR, Dewey KG, Ferrara A, Quesenberry CP, Jr., et al. Study of Women, Infant Feeding, and Type 2 diabetes mellitus after GDM pregnancy (SWIFT), a prospective cohort study: methodology and design. BMC Public Health. 2011;11:952. Rosenbloom JI, Blanchard MH. Compliance with Postpartum Diabetes Screening Recommendations for Patients with Gestational Diabetes. J Womens Health (Larchmt). 2018;27(4):498-502. Nouhjah S, Shahbazian H, Amoori N, Jahanfar S, Shahbazian N, Jahanshahi A, et al. Postpartum screening practices, progression to abnormal glucose tolerance and its related risk factors in Asian women with a known history of gestational diabetes: A systematic review and meta-analysis. Diabetes Metab Syndr. 2017;11 Suppl 2:S703-S12. Powe CE, Allard C, Battista MC, Doyon M, Bouchard L, Ecker JL, et al. Heterogeneous Contribution of Insulin Sensitivity and Secretion Defects to Gestational Diabetes Mellitus. Diabetes Care. 2016;39(6):1052-5. Benhalima K, Van Crombrugge P, Moyson C, Verhaeghe J, Vandeginste S, Verlaenen H, et al. Characteristics and pregnancy outcomes across gestational diabetes mellitus subtypes based on insulin resistance. Diabetologia. 2019;62(11):2118-28. Rickels MR, Kong SM, Fuller C, Dalton-Bakes C, Ferguson JF, Reilly MP, et al. Insulin sensitivity index in type 1 diabetes and following human islet transplantation: comparison of the minimal model to euglycemic clamp measures. Am J Physiol Endocrinol Metab. 2014;306(10):E1217-24. Bergman RN, Prager R, Volund A, Olefsky JM. Equivalence of the insulin sensitivity index in man derived by the minimal model method and the euglycemic glucose clamp. J Clin Invest. 1987;79(3):790-800. Tables Table 1 Clinical parameters b etween the non-breastfeeding group and breastfeeding group. Non-breastfeeding group (n=11) Breastfeeding group (n=20) P values Pregnancy 24-28w Diagnosis-OGTT 0min, mmol/L 5.0±0.6 4.9±0.6 0.650 Diagnosis-OGTT 60min, mmol/L 10. 3±1.3 9.8±2.0 0.402 Diagnosis-OGTT 120min, mmol/L 8.3±1.2 8.8±1.9 0.434 Pregnancy 36w Age, years 31.1±4.7 30.5±3.8 0.680 Height, m 1.6±0.1 1.6±0.0 0.662 Weight, kg 70.9±13.5 68.2±12.9 0.586 Gravidity, times 2.1(1.0-4.0) 2.2(1.0-6.0) 0.743 Parity, times 1.5(1.0-2.0) 1.6(1.0-3.0) 0.611 BMI, kg/m 2 27.2±4.2 26.4±4.6 0.653 SBP, mmHg 118.4±14.0 111.9±10.7 0.156 DBP, mmHg 73.9±9.3 72.6±6.4 0.634 HbA1c , % 5.1±0.3 5.5±0.3 0.052 ALT, U/L 18.6±17.3 15.3±9.8 0.501 AST, U/L 18.8±11.7 17.5±4.5 0.651 TG, mmol/L 3.1±1.1 3.0±1.2 0.812 TC, mmol/L 5.4±1.3 5.7±0.9 0.493 HDL, mmol/L 1.8±0.3 1.9±0.5 0.687 LDL, mmol/L 2.5±0.7 2.9±0.7 0.131 TSH, μIU/mL 1.9±1.1 1.4±0.5 0.093 FT3, pmol/L 3.6±0.3 3.8±0.5 0.432 FT4, pmol/L 13.3±1.4 14.1±2.4 0.359 Delivery information Week of delivery, weeks 38.5±0.7 39.4±0.8 0.003 Newborn weight, kg 3259.1±355.5 3415.0±303.1 0.207 Pregnancy outcome (Cesarean section rate), % 81.8 35.0 0.034 Note: BMI: body mass index, SBP: systolic blood pressure, DBP: diastolic blood pressure, OGTT: oral glucose tolerance test, HbA1c: hemoglobin A1c, ALT: alanine transaminase, AST: aspartate transaminase, TG: triglyceride, TC: total cholesterol, HDL: high-density lipoprotein cholesterol, LDL: low-density lipoprotein cholesterol, TSH: thyroid-stimulating hormone, FT3: free thyroxine 3, FT4: free thyroxine 4, HbA1c: hemoglobin A1c. P values are calculated by T-student test or Mann-Whitney test. T-student test is used, and the data are expressed as Mean ± Standard error, P values are calculated by T-student test; Mann-Whitney test was used, and the data were expressed as Mean (Minimum, Maximum), P values are calculated by Mann-Whitney test. P values ≤ 0.05 indicates that the difference is statistically significant. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigureandTable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4280525","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":294141937,"identity":"a2b8c567-2d99-4ca0-93c3-41f41deaa3fb","order_by":0,"name":"Huanyu Zhou","email":"","orcid":"","institution":"Wuxi No.2 People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huanyu","middleName":"","lastName":"Zhou","suffix":""},{"id":294141938,"identity":"80a5f2a5-ced5-4fb1-ad9c-68697b9ca657","order_by":1,"name":"Qing Yao","email":"","orcid":"","institution":"Nanchong Central 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Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jinhua","middleName":"","lastName":"Wei","suffix":""}],"badges":[],"createdAt":"2024-04-17 08:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4280525/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4280525/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55510376,"identity":"d590e051-4938-4313-9a17-9ad70b6fd6bf","added_by":"auto","created_at":"2024-04-29 12:29:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52633,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe flow chart of the study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4280525/v1/8ecea4e43ff55a2154a0a258.jpg"},{"id":55510285,"identity":"9f84d801-cc1c-4dc4-86fd-8ee2f6c26427","added_by":"auto","created_at":"2024-04-29 12:28:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":130320,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of glucose metabolism indices and body composition between the non-breastfeeding group and breastfeeding group.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4280525/v1/537b6587d0404b7c4ff6f40e.jpg"},{"id":55510277,"identity":"16052b1e-ff46-4c03-a0ed-973c3289a8ec","added_by":"auto","created_at":"2024-04-29 12:28:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":132610,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between duration of breastfeedingand insulin resistance and body composition.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4280525/v1/8a0deec0bbc5e83ac94801e6.jpg"},{"id":57126035,"identity":"577c5f38-d177-4d2a-8e47-bd774dcb6dba","added_by":"auto","created_at":"2024-05-25 07:31:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1113136,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4280525/v1/b5d22310-c5fe-4d0f-8d50-3321f8b8b162.pdf"},{"id":55510287,"identity":"c146a2c6-a666-48b2-8c8e-2a3e49a73026","added_by":"auto","created_at":"2024-04-29 12:28:58","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":97550,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureandTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4280525/v1/d1a8ed6a512d2b042750372b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Breastfeeding Improves Insulin Sensitivity and Fat Distribution in Women with Gestational Diabetes Mellitus: A Retrospective Pilot Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDuring pregnancy, changes in glucose and lipid metabolism lead to hyperlipidemia, fat accumulation and insulin resistance. Consequently, normal glucose metabolism is maintained by increasing the secretion of insulin. However, pregnant women with inadequate insulin secretion are unable to compensate for these physiological metabolic changes and develop gestational diabetes (GDM) as a result \u003csup\u003e[1]\u003c/sup\u003e. GDM is associated with a significant increase in the incidence of adverse pregnancy outcomes, such as preeclampsia, miscarriage, preterm birth, obstructed labor, macrosomia and fetal malformation \u003csup\u003e[2]\u003c/sup\u003e.\u0026nbsp;The global\u0026nbsp;average incidence of GDM varies from 9.3% to 25.5% \u003csup\u003e[3]\u003c/sup\u003e, and in mainland China, the incidence of GDM is 14.8% \u003csup\u003e[4]\u003c/sup\u003e. The levels of glucose tolerance usually return to normally after delivery in women with a history of GDM, but studies have shown that up to 35% of GDM patients do not return to normal within 3 months postpartum, but instead re-develop impaired glucose tolerance (IGT) \u003csup\u003e[5]\u003c/sup\u003e. Studies have shown that women with a previous history of GDM are at a sevenfold higher risk of developing Type II diabetes mellitus (T2DM) for 5-10 years after delivery \u003csup\u003e[6]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA growing number of epidemiological studies have reported a significant inverse correlation between breastfeeding and\u0026nbsp;the\u0026nbsp;risk of postpartum metabolic diseases such as obesity and T2DM \u003csup\u003e[7-9]\u003c/sup\u003e. Animal and human studies have also suggested that breastfeeding could have beneficial effects on glucose tolerance, maternal weight, and body fat \u003csup\u003e[10]\u003c/sup\u003e. Some studies have shown that breastfeeding improves lipid metabolism, leading to higher high-density lipoprotein cholesterol (HDL) and lower\u0026nbsp;triglycerides (TGs) \u003csup\u003e[11]\u003c/sup\u003e. Although breastfeeding is beneficial to all women, it appears to be particularly beneficial to those with a previous history of GDM \u003csup\u003e[12,13]\u003c/sup\u003e. The Study of Women, Infant Feeding, and Type 2 Diabetes after GDM Pregnancy (SWIFT), which had a racially and ethnically diverse cohort, found that an increase in breastfeeding intensity modified\u0026nbsp;the\u0026nbsp;circulating lipid profile in GDM women in the early postpartum period \u003csup\u003e[14]\u003c/sup\u003e. SWIFT also found that increasing the intensity and duration of breastfeeding was associated with a 57% reduction in the risk of T2DM in women with a history of GDM for the first two years after delivery \u003csup\u003e[13]\u003c/sup\u003e. In addition, several studies have shown that breastfeeding reduces insulin resistance and improves insulin secretion \u003csup\u003e[15]\u003c/sup\u003e. However, the exact mechanisms\u0026nbsp;by which\u0026nbsp;breastfeeding impacts lipid and glucose metabolism are not fully understood.\u003c/p\u003e\n\u003cp\u003eAs the incidence of metabolic diseases such as obesity and T2DM continues to increase globally \u003csup\u003e[16, 17]\u003c/sup\u003e, there is an urgent need to find methods to alleviate these conditions. The purpose of this study is to investigate the impact of postpartum breastfeeding on the risk of metabolic diseases in women with a history of GDM. We hypothesize that postpartum breastfeeding can alter body fat distribution, increase insulin secretion, and improve insulin sensitivity, thereby reducing the risk of metabolic diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and setting:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Population:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a retrospective, real-world study of pregnant women with\u0026nbsp;a\u0026nbsp;diagnosis of GDM\u0026nbsp;who\u0026nbsp;received routine prenatal and postnatal\u0026nbsp;examinations\u0026nbsp;between 2017 and 2020 at the one-day GDM management clinic of the Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University, which guided diet, exercise and\u0026nbsp;performed\u0026nbsp;basic clinical tests. Gestational diabetes was diagnosed following the American Diabetes Association (ADA) recommendations during a standard 2-hour oral glucose tolerance test with\u0026nbsp;75\u0026nbsp;g\u0026nbsp;of dextrose at 24-28 weeks of gestation. One or more of the three glycemic values (fasting, 1-hour and 2-hour blood glucose) must meet or exceed the glycemic threshold recommended by the ADA. Patients\u0026nbsp;who\u0026nbsp;fulfilled the criteria received standard treatment for GDM \u003csup\u003e[18]\u003c/sup\u003e.\u0026nbsp;A\u0026nbsp;study recruitment\u0026nbsp;flowchart\u0026nbsp;is\u0026nbsp;shown in Figure 1. During the 3-year period, 392 medical records of women with GDM were reviewed. Women\u0026nbsp;who\u0026nbsp;fulfilled the inclusion and exclusion criteria were invited to participate in the study. \u003cstrong\u003eInclusion criteria:\u003c/strong\u003e between 20 and 45 years old; outpatient and inpatient records available in the health care system, including clinical records and birth records; duration of gestation\u0026nbsp;\u0026ge;35 weeks; single and live birth; history of GDM (as defined by the ACOG criteria); and glycated hemoglobin (HbA1c) \u0026lt; 6.5% after delivery. \u003cstrong\u003eExclusion criteria:\u003c/strong\u003e women who were currently breastfeeding;pre-pregnancy diagnosis of diabetes (T1DM or T2DM, as defined by the ADA criteria);current use of any hypoglycemic drugs;use of steroids or other drugs that significantly affect glucose tolerance;pregnancy-related complications, including gestational hypertension, pregnancy with thyroid dysfunction;major congenital fetal abnormalities;\u0026nbsp;hypertension before pregnancy; obesity; known mental illness, alcohol abuse, human immunodeficiency virus (HIV), hepatitis, kidney, liver disease, untreated heart disease, untreated thyroid disease, active systemic infection or malignancy;illicit drug use (self-report of cases);history of postpartum depression; dietary intake and physical activity during pregnancy that is inconsistent with the postpartum dietary intake and physical activity; weight loss supplement use or dieting for 6 months prior to the study; and prenatal and/or postnatal care not being done at the Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University. After reviewing medical records,\u0026nbsp;226 women were excluded: 94 due to not having delivered at the Affiliated Changzhou No. 2 People\u0026apos;s Hospital, 56 due to obesity, 29 due to gestational hypertension, 24 due to\u0026nbsp;pregnancy with thyroid dysfunction, 7 due to diabetes prior to pregnancy, 5 due to contagious diseases prior to pregnancy, and 11 due to hypertension prior to pregnancy. One hundred sixty-six pregnant women met the inclusion and exclusion criteria. They were contacted by telephone 6-28 months after delivery. During the call,\u0026nbsp;they answered a questionnaire to determine\u0026nbsp;the method used to feed the\u0026nbsp;baby and\u0026nbsp;the\u0026nbsp;frequency and intensity of breastfeeding. They were then divided\u0026nbsp;into\u0026nbsp;two groups:\u0026nbsp;non-breastfeeding\u0026nbsp;and breastfeeding. The\u0026nbsp;non-breastfeeding\u0026nbsp;group consisted of women who exclusively fed or primarily fed formula after delivery (who did not\u0026nbsp;breastfeed\u0026nbsp;at all or who\u0026nbsp;breastfed\u0026nbsp;for less than 3 weeks while also feeding at least 14 ounces of formula per day). The breastfeeding group consisted of women who were exclusively or primarily breastfeeding for at least 6 months after delivery (feeding no more than 6 ounces of formula per day). Among the women contacted, 83 participants were excluded due to mixed feeding methods, loss of contact and unwillingness to participate in the study. Eighty-three women (17\u0026nbsp;non-breastfeeding\u0026nbsp;and 66 breastfeeding) were considered eligible and agreed to participate in the study. Of these, 6\u0026nbsp;non-breastfeeding\u0026nbsp;and 46 breastfeeding women did not want to come to the in-person research visit or could not come because of\u0026nbsp;a\u0026nbsp;busy work schedule. Ultimately, 11 women were enrolled in the\u0026nbsp;non-breastfeeding\u0026nbsp;group and 20 in the breastfeeding group. They all agreed to come for a postpartum OGTT visit and signed informed consent\u0026nbsp;forms. The procedures followed in this study were in line with the ethical standards established by the Human Trial Committee of the Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University and were approved by the committee ([2021]KY013-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Visits:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection at the Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University occurred at the following time points:\u0026nbsp;Diagnosis during pregnancy\u0026nbsp;(24-28 weeks of gestation),\u0026nbsp;Baseline visit during pregnancy\u0026nbsp;(36 weeks of gestation),\u0026nbsp;Phone call after delivery\u0026nbsp;(phone call between 6-28 months after delivery)\u0026nbsp;and Research visit after delivery\u0026nbsp;(research visit between 8-30 months after delivery).\u0026nbsp;\u0026nbsp;The research visit occurred approximately 2 months after\u0026nbsp;the\u0026nbsp;phone call (Supplementary Figure S1). Participants were diagnosed with GDM at 24-28 weeks of gestation. Prenatal clinical parameters were collected at 36 weeks\u0026nbsp;of\u0026nbsp;pregnancy.\u0026nbsp;A phone\u0026nbsp;call was conducted after delivery to identify eligible study participants. Signed informed consent for participating in the study was obtained\u0026nbsp;at\u0026nbsp;the in-person visit,\u0026nbsp;which included permission to obtain information on perinatal outcomes from electronic databases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDiagnosis:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe\u0026nbsp;75 g\u0026nbsp;oral glucose tolerance test (OGTT) for the diagnosis of GDM was carried out at 24-28 weeks gestation. The cut-off points in OGTT were typically determined based on blood glucose levels. The diagnostic criteria for GDM are as follows: Fasting Plasma Glucose (FPG)\u0026ge;5.1 mmol/L; 1-hour Plasma Glucose (1hPG)\u0026ge;10.0 mmol/L; 2-hour Plasma Glucose (2hPG)\u0026ge;8.5 mmol/L. If a pregnant woman meets any of the diagnostic criteria mentioned above in any of the tests, she can be diagnosed with GDM. The following is the classification of OGTT results based on the World Health Organization (WHO) 2019 recommendations: FPG: Normal: \u0026lt;6.1 mmol/L; Diabetes:\u0026nbsp;\u0026ge;7.0 mmol/L; IGT: 6.1 - 6.9 mmol/L. 2hPG: Normal: \u0026lt;7.8 mmol/L; Diabetes:\u0026nbsp;\u0026ge;11.1 mmol/L; IGT: 7.8 - 11.0 mmol/L. Based on the above cut-off points, OGTT results can be classified as normal, diabetes, or IGT. On the day before the OGTT, participants were asked to fast after dinner for at least 8 hours until the next morning (no later than 9:00 am). Participants\u0026nbsp;maintained\u0026nbsp;normal physical activity and\u0026nbsp;a\u0026nbsp;normal diet (with no less than\u0026nbsp;150 g\u0026nbsp;of carbohydrates per day) during the 3 days prior to\u0026nbsp;the\u0026nbsp;OGTT and\u0026nbsp;sat\u0026nbsp;quietly and\u0026nbsp;did\u0026nbsp;not smoke during the visit. The ADA recommended that\u0026nbsp;75\u0026nbsp;g\u0026nbsp;of glucose\u0026nbsp;be\u0026nbsp;dissolved in\u0026nbsp;250 ml\u0026nbsp;water and taken orally within 5 minutes for adults. Blood glucose was obtained at fasting and at 60 minutes and 120 minutes after drinking the glucose solution \u003csup\u003e[19]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBaseline visit:\u003c/em\u003e\u003c/strong\u003eClinical parameters and anthropometric measurements were collected at 36 weeks\u0026nbsp;of\u0026nbsp;pregnancy.\u0026nbsp;Clinical information,\u0026nbsp;including age, gravidity and parity,\u0026nbsp;was obtained from\u0026nbsp;the\u0026nbsp;outpatient and inpatient record system of the Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University. \u003cstrong\u003eDelivery information:\u003c/strong\u003e Information such as newborn weight and cesarean section rate were completed at the time of delivery. These formed the\u0026nbsp;clinical\u0026nbsp;parameters of this study by reviewing the information of the hospital\u0026apos;s medical system and the perinatal examination manual (Figure 2, Table 1).\u003c/p\u003e\n\u003cp\u003eAnthropometric measurements mainly included body weight, height, body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP). Body weight was obtained using the portable Tanita\u0026reg; WB 100A digital scale. Before being weighed, participants were asked to take off their coats, wear a single layer of clothing, empty their pockets, and remove any accessories that might interfere with the measurement. Height was measured by a Seca portable stadiometer (Model 67029)\u0026nbsp;with a range of 8 inches to 82 inches and graded in inches and centimeters. Participants were asked to remove their shoes and any hair accessories to\u0026nbsp;obtain\u0026nbsp;an accurate measurement. BMI was defined as weight/(height*height). SBP and DBP were measured from the left arm in a sitting position after at least 10 min of rest with an electronic sphygmomanometer with appropriate cuff sizes (ERKA Perfect-Aneroid, Germany). Two measurements were taken by trained personnel while the arm was supported at heart level. The measurements were repeated twice, five minutes apart. The values reported\u0026nbsp;are\u0026nbsp;the means of the two measurements. Obesity was defined as a BMI of 30 kg/m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eor higher \u003csup\u003e[20]\u003c/sup\u003e. Chemiluminescence immunoassay (CLIA) was used for thyroid function, the clinical laboratory parameters were involved: thyroid-stimulating hormone (TSH), free thyroxine 3 (FT3) and free thyroxine 4 (FT4).\u0026nbsp;Continuous monitoring method was used for liver function, the clinical laboratory parameters were involved: alanine transaminase (ALT), aspartate transaminase (AST), triglycerides (TGs), total cholesterol (TC), HDL and low-density lipoprotein cholesterol (LDL).\u0026nbsp;Hemoglobin A1c (HbA1c) was also obtained at this visit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePhone call:\u003c/em\u003e\u003c/strong\u003e Between 6-28 months after delivery, participants were contacted by phone to determine their interest in the study and whether they would qualify for the study. During this phone call, participants completed a screening questionnaire (including maternal and child health, condition of pregnancy, use of contraception and sociodemographic information, as well as the history of infant feeding data). It was designed to assess the frequency and intensity of breastfeeding. The eligible women were invited to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResearch visit:\u003c/em\u003e\u003c/strong\u003eStudy procedures at this visit occurred at 8-30 months after delivery and included anthropometric measurements, collection of blood specimens and self-and interviewer-administered\u0026nbsp;questionnaires\u0026nbsp;to collect data on early postpartum characteristics. Among them, blood specimens were collected to measure glucose and insulin, and for a lipid panel. Participants underwent an OGTT, in which glucose and insulin levels were obtained to calculate indices of insulin sensitivity and insulin secretion (pancreatic \u0026beta; cell function). Participants were asked to fill out questionnaires about diet and physical activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndices of glucose metabolism:\u0026nbsp;\u003c/strong\u003eOn the day of the research visit, participants came to the\u0026nbsp;Affiliated Changzhou No. 2 People\u0026apos;s Hospital of Nanjing Medical University\u0026nbsp;for a repeat\u0026nbsp;75 g\u0026nbsp;OGTT and anthropometric measurements.\u0026nbsp;Indices of glucose metabolism obtained during the OGTT included the homeostasis model insulin resistance index (HOMA-IR), the insulin sensitivity-oral glucose tolerance test (IS-OGTT), the insulin secretion sensitivity index-2 (ISSI-2),\u0026nbsp;and\u0026nbsp;the insulinogenic index/HOMA-IR (IGI/HOMA-IR). Formulas to calculate glucose metabolism indices:\u0026nbsp;HOMA-IR, an index for estimating insulin resistance, was calculated as\u0026nbsp;follows: FPG*FPI/22.5 (FPI: fasting plasma insulin). IS-OGTT is an index used to determine insulin sensitivity, which has been shown to have a good correlation with the hyperinsulinemic euglycemic clamp \u003csup\u003e[21]\u003c/sup\u003e. IS-OGTT was defined as\u0026nbsp;10000/square\u0026nbsp;root (FPG*FPI) * (G*I) (G: means glucose during the OGTT, I: means insulin) \u003csup\u003e[21]\u003c/sup\u003e. ISSI-2 was the primary index used to determine insulin secretion (a measurement of pancreatic \u0026beta; cell function). ISSI-2 was calculated as\u0026nbsp;the\u0026nbsp;area under the insulin curve/area under the glucose curve \u003csup\u003e[22, 23]\u003c/sup\u003e. IGI/HOMA-IR, also used as an index of pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function, was calculated as the ratio of the incremental change in insulin during the first 30 minutes of the OGTT to the incremental change in glucose over the same time period \u003csup\u003e[24]\u003c/sup\u003e.The composite measure of pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function by insulin resistance (reported as the oral disposition index (DI\u003csub\u003eO\u003c/sub\u003e)) was calculated as \u0026Delta;I\u003csub\u003e0\u0026ndash;30\u003c/sub\u003e/\u0026Delta;G\u003csub\u003e0\u0026ndash;30\u003c/sub\u003e\u0026times;1/fasting insulin \u003csup\u003e[25]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelf- and interviewer-administered questionnaires:\u003c/strong\u003e Participants completed a one-day review of dietary intakes with the food frequency questionnaire (FFQ) questionnaire,\u0026nbsp;which was self-completed or\u0026nbsp;completed\u0026nbsp;by the interviewer. The\u0026nbsp;semiquantitative\u0026nbsp;FFQ consists of a list of ninety-three foods most commonly consumed in Italy \u003csup\u003e[26, 27]\u003c/sup\u003e. For this study, the food variety of the FFQ was adjusted to the most common foods consumed in the Chinese diet \u003csup\u003e[27]\u003c/sup\u003e (Table S3). During pregnancy, participants were given an electronic weight scale (Soehnle, Germany) to quantify\u0026nbsp;the\u0026nbsp;food portion consumed and, when away from home, to use household measures \u003csup\u003e[26]\u003c/sup\u003e. Based on the average amount of each participant\u0026apos;s consumption, nutritional analysis of the main foods was performed to calculate participants\u0026apos; dietary nutrient intakes (Table S3).\u0026nbsp;Additionally,\u0026nbsp;based on an adapted version of the international physical activity questionnaire (IPAQ),\u0026nbsp;an\u0026nbsp;analysis of daily exercise time (such as fast walking and\u0026nbsp;yoga) and daily leisure time was calculated for all participants \u003csup\u003e[28]\u003c/sup\u003e. Throughout pregnancy and different breastfeeding stages of the study, the participants\u0026apos; postpartum diet pattern, amount and frequency did not change significantly,\u0026nbsp;nor did their\u0026nbsp;physical activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody composition\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eanalysis and anthropometric measurements:\u0026nbsp;\u003c/strong\u003eThe body composition analyzer INBODY770 (BIA bioimpedance detection technology) was used to measure body composition, including protein, body fat, skeletal muscle, body fat percentage, torso, arm circumference, waist circumference, visceral fat area, basal metabolic rate and other health indices. Participants were asked to stand and hang their arms straight down the sides of the body, and the tape was used around the thickest part of the upper arm to determine arm circumference. Waist circumference was measured midway between the iliac crest and the lowest lateral portion of the rib cage and anteriorly midway between the xiphoid process of the sternum and the umbilicus. Participants, who were on an empty stomach, were asked to stand and keep their feet 25 to 30 centimeters apart when measuring waist circumference. Two consecutive measurements were taken and recorded, and a third measurement was taken and recorded if the first and second measurements\u0026nbsp;differed by\u0026nbsp;more than 1 centimeter. Arm circumference and waist circumference were also obtained with\u0026nbsp;a\u0026nbsp;body composition analyzer. Because both data were very similar and to minimize human error, we opted to use the arm circumference and waist circumference data from the body composition analyzer. Body fat percentage\u0026nbsp;refers\u0026nbsp;to the proportion of body fat weight by total body weight. Central obesity was\u0026nbsp;measured\u0026nbsp;by visceral fat area (Tanita scale) and waist circumference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eSPSS 18.0 statistical software was used for statistical analysis. When the data were normally distributed with similar variance, the\u0026nbsp;Student\u0026rsquo;s t test\u0026nbsp;was used, and the quantitative data were expressed as\u0026nbsp;the mean \u0026plusmn; standard\u0026nbsp;error. When the data did not conform to\u0026nbsp;a\u0026nbsp;normal distribution, the Mann‒Whitney test was used, and the data were expressed as\u0026nbsp;the mean (minimum, maximum). Spearman\u0026nbsp;correlation\u0026nbsp;analysis\u0026nbsp;was required when studying whether there was a correlation between an indicator and a result.\u0026nbsp;The correlation coefficient\u0026nbsp;reflected the correlation. The results were visually demonstrated with a scatterplot graph. \u003cem\u003eP\u003c/em\u003e\u0026le;0.05 indicated that the difference was statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eClinical characteristics of participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics during pregnancy and delivery information of the women with a history of GDM in the breastfeeding and\u0026nbsp;non-breastfeeding\u0026nbsp;groups are shown in Table 1. No\u0026nbsp;significant\u0026nbsp;differences were observed when comparing the two groups (all \u003cem\u003eP\u003c/em\u003e＞0.05), except for HbA1c (\u003cem\u003eP\u003c/em\u003e=0.052) and cesarean section rate (\u003cem\u003eP\u003c/em\u003e=0.034). According to the postpartum characteristics of women with a history of GDM, there was no\u0026nbsp;significant\u0026nbsp;difference between the breastfeeding group and the\u0026nbsp;non-breastfeeding\u0026nbsp;group (\u003cem\u003eP\u003c/em\u003e＞0.05), except\u0026nbsp;for\u0026nbsp;SBP (\u003cem\u003eP\u003c/em\u003e=0.021), FT4 (\u003cem\u003eP\u003c/em\u003e=0.030) and ALT\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e=0.009) (Table S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBreastfeeding improves body fat composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2 (and Table S1) shows the differences in the measurements of body fat content in the breastfeeding and\u0026nbsp;non-breastfeeding\u0026nbsp;groups. Body weight (breastfeeding: 59.9\u0026plusmn;9.7 kg vs.\u0026nbsp;non-breastfeeding: 66.4\u0026plusmn;13.4 kg; \u003cem\u003eP\u003c/em\u003e=0.130) and weight loss (breastfeeding: 8.3\u0026plusmn;7.2 kg vs.\u0026nbsp;non-breastfeeding: 4.5\u0026plusmn;10.6 kg; \u003cem\u003eP\u003c/em\u003e=0.246) from\u0026nbsp;the\u0026nbsp;baseline visit to\u0026nbsp;the\u0026nbsp;postpartum visit were not\u0026nbsp;significantly\u0026nbsp;different\u0026nbsp;between\u0026nbsp;the two groups. At\u0026nbsp;the\u0026nbsp;postpartum visit, measurements of body composition obtained with\u0026nbsp;bioimpedance\u0026nbsp;demonstrated that body fat (\u003cem\u003eP\u003c/em\u003e=0.053), body fat percentage (\u003cem\u003eP\u003c/em\u003e=0.041), arm circumference (\u003cem\u003eP\u003c/em\u003e=0.048), waist circumference (\u003cem\u003eP\u003c/em\u003e=0.046) and visceral fat area \u0026nbsp;(\u003cem\u003eP\u003c/em\u003e=0.050) were lower in the breastfeeding group than in the\u0026nbsp;non-breastfeeding\u0026nbsp;group\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e\u0026le;0.05, for all).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBreastfeeding improves insulin sensitivity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2 (and Table S1) shows the differences in the indices of insulin resistance and insulin secretion in the breastfeeding and\u0026nbsp;non-breastfeeding\u0026nbsp;groups. There was no\u0026nbsp;significant\u0026nbsp;difference between the breastfeeding group and the\u0026nbsp;non-breastfeeding\u0026nbsp;group in glucose and insulin levels during OGTT (\u003cem\u003eP\u003c/em\u003e＞0.05), except the breastfeeding group had a trend for lower insulin levels at 60 minutes (breastfeeding: 63.7 (18.3-168.0) \u0026mu;U/mL vs.\u0026nbsp;non-breastfeeding: 88.3 (11.2-168.3) \u0026mu;U/mL; \u003cem\u003eP\u003c/em\u003e=0.054). HOMA-IR (\u003cem\u003eP\u003c/em\u003e=0.046) in the breastfeeding group was significantly lower than that\u0026nbsp;in\u0026nbsp;the\u0026nbsp;non-breastfeeding\u0026nbsp;group. Similarly, IS-OGTT (\u003cem\u003eP\u003c/em\u003e=0.016), an index for\u0026nbsp;the\u0026nbsp;measurement of insulin sensitivity, was significantly higher in the breastfeeding group than in the\u0026nbsp;non-breastfeeding\u0026nbsp;group. No differences in indices of insulin secretion, ISSI-2 (\u003cem\u003eP\u003c/em\u003e=0.335) and IGI/HOMA-IR (\u003cem\u003eP\u003c/em\u003e=0.761), were seen when comparing the two groups. There was no\u0026nbsp;significant\u0026nbsp;difference in the composite measure of pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function, calculated from DI\u003csub\u003eO\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e=0.530), between the breastfeeding group and the\u0026nbsp;non-breastfeeding\u0026nbsp;group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between duration of breastfeeding and body fat composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further understand the metabolic effects of breastfeeding in preventing obesity and T2DM, we investigated whether\u0026nbsp;the\u0026nbsp;duration of breastfeeding correlates with indices of body fat composition, insulin resistance and insulin sensitivity. Figure 3 (Table S2) shows that\u0026nbsp;the\u0026nbsp;duration of breastfeeding\u0026nbsp;was\u0026nbsp;inversely correlated with arm circumference and waist circumference (\u003cem\u003eP\u003c/em\u003e\u0026le;0.05).\u0026nbsp;There was a trend for\u0026nbsp;the\u0026nbsp;duration of breastfeeding and\u0026nbsp;a\u0026nbsp;decrease in body fat, body fat percentage, visceral fat area, HOMA-IR and IS-OGTT (all \u003cem\u003eP\u003c/em\u003e\u0026lt;0.1).\u0026nbsp;The duration\u0026nbsp;of breastfeeding did not correlate with indices of insulin secretion (IGI/HOMA-IR) (\u003cem\u003eP\u003c/em\u003e=0.678)\u0026nbsp;or\u0026nbsp;pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function (DI\u003csub\u003eO\u003c/sub\u003e) (\u003cem\u003eP\u003c/em\u003e=0.877).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBreastfeeding ameliorates blood pressure and\u003c/strong\u003e\u003cstrong\u003eliver and thyroid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSBP and DBP were comparable in the breastfeeding and non-breastfeeding groups at baseline. However, at\u0026nbsp;the\u0026nbsp;postpartum visit, systolic blood pressure was significantly lower in the breastfeeding group than in the\u0026nbsp;non-breastfeeding\u0026nbsp;group (breastfeeding: 113.0\u0026plusmn;12.0 mmHg vs.\u0026nbsp;non-breastfeeding: 125.0\u0026plusmn;15.0 mmHg; \u003cem\u003eP\u003c/em\u003e=0.021), as\u0026nbsp;was\u0026nbsp;ALT (breastfeeding: 12.8 (9.0-20.0) U/L vs.\u0026nbsp;non-breastfeeding: 26.6 (8.0-76.0) U/L; \u003cem\u003eP\u003c/em\u003e=0.009). FT4 in the breastfeeding group was significantly higher than that in the\u0026nbsp;non-breastfeeding\u0026nbsp;group (breastfeeding: 21.4\u0026plusmn;3.0 pmol/L vs.\u0026nbsp;non-breastfeeding: 18.9\u0026plusmn;2.4 pmol/L; \u003cem\u003eP\u003c/em\u003e=0.030).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDietary intake and physical activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable S1 shows the differences in dietary intake and physical activity between the breastfeeding and\u0026nbsp;non-breastfeeding\u0026nbsp;groups. This study confirmed that there were no\u0026nbsp;significant\u0026nbsp;group differences in dietary intake and physical activity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we compared the effects of breastfeeding on body fat distribution and glucose metabolism in women with\u0026nbsp;a\u0026nbsp;history of GDM. We found that\u0026nbsp;breastfeeding decreased body fat and body fat percentage; reduced arm circumference, waist circumference,\u0026nbsp;and\u0026nbsp;visceral fat area; and improved insulin sensitivity; however, it did not affect pancreatic \u0026beta; cell function\u0026nbsp;in women with\u0026nbsp;a\u0026nbsp;history of GDM. At the same time, we found that systolic blood pressure in the breastfeeding group was lower than\u0026nbsp;that\u0026nbsp;in the\u0026nbsp;non-breastfeeding\u0026nbsp;group.\u003c/p\u003e\n\u003cp\u003eBreastfeeding meets the metabolic requirements for lipid synthesis in milk by increasing food intake, mobilizing TG stored in the body and increasing the production of liver glycogen to provide substrates for the synthesis of TG by mammary epithelial cells \u003csup\u003e[29]\u003c/sup\u003e. Breastfeeding\u0026nbsp;also decreases the activity of lipoprotein lipase in adipocytes, resulting in less TG entering adipocytesand\u0026nbsp;ramping\u0026nbsp;up fat metabolism to increase milk production\u003csup\u003e\u0026nbsp;[30,31]\u003c/sup\u003e. The current results showed that body\u0026nbsp;fat, body fat percentage, arm circumference, waist circumference and visceral fat area in the breastfeeding group were significantly lower than those in the\u0026nbsp;non-breastfeeding\u0026nbsp;group, which is consistent with the studies described above. In addition,\u0026nbsp;the\u0026nbsp;type, quantity and frequency of food intake and physical activity of the participants did not change significantly during both pregnancy and breastfeeding, suggesting that the beneficial effects of breastfeeding were not due to differences in diet and exercise between the two groups but\u0026nbsp;were\u0026nbsp;most likely due to changes in lipid metabolism and body fat redistribution.\u003c/p\u003e\n\u003cp\u003eDuring the first trimester of pregnancy, circulating insulin levels increase,\u0026nbsp;and adipose tissue becomes more sensitive to insulin, thereby promoting the production and storage of\u0026nbsp;lipids\u0026nbsp;\u003csup\u003e[32-34]\u003c/sup\u003e. With\u0026nbsp;the\u0026nbsp;progression of pregnancy, a rise in placental hormones antagonistic to insulin leads to a switch from increased insulin sensitivity to insulin resistance, which\u0026nbsp;allows the\u0026nbsp;transfer\u0026nbsp;of maternal nutrients and energy to the fetus. The insulin resistance of pregnant women with GDM is especially observed in late weeks of gestation. Insulin resistance is the first metabolic abnormality observed in patients with GDM.\u0026nbsp;Hyperglycemia, on the other\u0026nbsp;hand, only occurs when maternal pancreatic \u0026beta; cells can no longer secrete enough insulin to offset insulin resistance in peripheral tissues \u003csup\u003e[35]\u003c/sup\u003e.\u0026nbsp;In the current results, compared with the\u0026nbsp;non-breastfeeding\u0026nbsp;group, the breastfeeding group showed\u0026nbsp;significantly\u0026nbsp;lower HOMA-IR and higher IS-OGTT, indicating that breastfeeding improved insulin sensitivity in women with\u0026nbsp;a\u0026nbsp;history of GDM. Similar results showing that breastfeeding improves insulin resistance have been described by other authors \u003csup\u003e[8, 36]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDuring breastfeeding, prolactin induces serotonin production in pancreatic \u0026beta; cells.\u0026nbsp;Studies have shown that serotonin improves insulin secretion by increasing pancreatic \u0026beta; cell proliferation and reducing oxidative stress in pancreatic \u0026beta; cells, thereby mediating\u0026nbsp;the long-term beneficial effects of breastfeeding on female metabolic health\u0026nbsp;\u003csup\u003e[36]\u003c/sup\u003e. In the present findings, there was no difference in the function of pancreatic \u0026beta;\u0026nbsp;cells\u0026nbsp;between the\u0026nbsp;non-breastfeeding\u0026nbsp;group and the breastfeeding group. This result\u0026nbsp;might be related to the fact that our participants were\u0026nbsp;studied\u0026nbsp;after they had already stopped breastfeeding. A study documented that increased prolactin release during breastfeeding promoted the release of serotonin, which induced pancreatic \u0026beta; cell proliferation and increased\u0026nbsp;insulin secretion\u0026nbsp;\u003csup\u003e[36,37]\u003c/sup\u003e.\u0026nbsp;When breastfeeding is discontinued, maternal prolactin levels return to normal, no longer promoting pancreatic \u0026beta; cell proliferation and thus decreasing insulin secretion. However, the pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function of breastfeeding women with a history of GDM will still be in a significantly improved state\u0026nbsp;\u003csup\u003e[38]\u003c/sup\u003e.\u0026nbsp;A prospective study also confirmed that compared with breastfeeding for less than 3 months,\u0026nbsp;a\u0026nbsp;duration of breastfeeding over 12 months was associated with\u0026nbsp;less\u0026nbsp;insulin resistance, lower fasting blood glucose, and lower blood glucose after meals, but\u0026nbsp;there was\u0026nbsp;no difference in the secretion function of\u0026nbsp;pancreatic\u0026nbsp;\u0026beta; cells\u0026nbsp;\u003csup\u003e[8]\u003c/sup\u003e. This study suggested that breastfeeding\u0026nbsp;affects\u0026nbsp;the natural history of insulin resistance but not the function of pancreatic \u0026beta;\u0026nbsp;cells. Those results were similar to the present findings: no change in insulin secretion (ISSI-2, IGI/HOMA-IR and DI\u003csub\u003eO\u003c/sub\u003e) but improvement in insulin resistance (HOMA-IR and IS-OGTT).\u003c/p\u003e\n\u003cp\u003eThe American Academy of Pediatrics (AAP) recommends that women breastfeed for at least 12 months. While this recommendation is intended to optimize early childhood nutrition, it may also provide metabolic benefits for mothers. Prior research studies demonstrated that breastfeeding has significant metabolic benefits for the mother, including increasing energy expenditure (used to produce milk), improving body fat, lowering blood glucose levels, and improving insulin sensitivity\u003csup\u003e\u0026nbsp;[20]\u003c/sup\u003e. The results from these studies showed a statistically significant negative correlation between\u0026nbsp;the\u0026nbsp;duration of breastfeeding and body fat composition (arm circumference and waist circumference) in women with a history of GDM after weaning. Our findings confirm the results from previous studies that breastfeeding improves body fat redistribution in women with a history of GDM,\u0026nbsp;and\u0026nbsp;a\u0026nbsp;longer duration of breastfeeding results in additional benefits in lipid metabolism. The current results also found that the duration of breastfeeding seems to be associated with indicators of response to insulin resistance and insulin sensitivity. Epidemiological studies have shown that women with\u0026nbsp;an\u0026nbsp;increased duration of breastfeeding had\u0026nbsp;a\u0026nbsp;lower long-term risk of developing T2DM, although the mechanism of this relationship is unclear \u003csup\u003e[39-43]\u003c/sup\u003e. The data of the current results did not show any change in the incidence of T2DM or/and IGT, but this may be due to\u0026nbsp;the\u0026nbsp;small sample size and short duration of observation (\u0026lt; 2 years). Further studies are needed to better understand the specific mechanisms\u0026nbsp;by which\u0026nbsp;breastfeeding duration affects postpartum lipid metabolism and insulin sensitivity after weaning in women with a history of GDM and the potential benefits of altering body fat redistribution in preventing T2DM and other metabolic\u0026nbsp;diseases.\u003c/p\u003e\n\u003cp\u003eBreastfeeding helps to reverse some metabolic changes more quickly and completely by mobilizing fat stores accumulated during pregnancy. These changes\u0026nbsp;in\u0026nbsp;maternal metabolism may reduce the risk of developing metabolic diseases in the future, including cardiovascular disease, fatty liver, and thyroid dysfunction. The study found that systolic blood pressure in the breastfeeding\u0026nbsp;group was significantly lower than\u0026nbsp;that\u0026nbsp;in the\u0026nbsp;non-breastfeeding\u0026nbsp;group, an indication that breastfeeding may have a beneficial effect\u0026nbsp;on\u0026nbsp;cardiovascular disease in women with a history of GDM. ALT tends to be elevated in alcoholic and fatty liver disease \u003csup\u003e[44]\u003c/sup\u003e. In the study presented here, liver function abnormalities, such as alcoholism and fatty liver, during pregnancy and\u0026nbsp;the\u0026nbsp;postpartum period\u0026nbsp;were\u0026nbsp;explicitly excluded based on the exclusion criteria.\u0026nbsp;Nevertheless, we still found that ALT in the breastfeeding group was significantly\u0026nbsp;lower than that in the\u0026nbsp;non-breastfeeding\u0026nbsp;group. It is possible that breastfeeding may reduce fatty liver infiltration and improve liver function in women with a history of GDM \u003csup\u003e[45]\u003c/sup\u003e. Indeed, a study demonstrated that breastfeeding for more than 6 months was associated with a reduced risk of nonalcoholic fatty liver disease in midlife\u0026nbsp;\u003csup\u003e[44]\u003c/sup\u003e. FT4 was significantly higher in the breastfeeding group than in the\u0026nbsp;non-breastfeeding\u0026nbsp;group.\u0026nbsp;This result\u0026nbsp;suggested that breastfeeding can improve\u0026nbsp;the\u0026nbsp;maternal endocrine metabolic system. A follow-up study of 550 women with previous GDM found that there was a positive correlation between the duration of breastfeeding and maternal long-term thyroid function, with\u0026nbsp;a\u0026nbsp;longer duration of breastfeeding\u0026nbsp;being\u0026nbsp;associated with higher thyroid hormone levels\u0026nbsp;\u003csup\u003e[46]\u003c/sup\u003e. Our findings support the findings that breastfeeding may be beneficial to lower cardiovascular disease, fatty liver disease/fatty liver inflammation and thyroid disease. However, at present,\u0026nbsp;there are limited clinical or epidemiological studies on the relationship between breastfeeding and fatty liver disease and thyroid dysfunction, and whether they may be important for preventing breastfeeding-associated cardiovascular disease. Further studies will be necessary to\u0026nbsp;confirm\u0026nbsp;these findings.\u003c/p\u003e\n\u003cp\u003eCompared with previous studies \u003csup\u003e[8,36,47]\u003c/sup\u003e,\u0026nbsp;there are some advantages to this study.\u0026nbsp;First, the distribution of\u0026nbsp;lipids\u0026nbsp;is reflected by using\u0026nbsp;a\u0026nbsp;human composition analyzer.\u0026nbsp;Second,\u0026nbsp;indicators such as HOMA-IR, IS-OGTT, ISSI-2, IGI/HOMA-IR and DI\u003csub\u003eO\u003c/sub\u003e are used to reflect insulin resistance and pancreatic \u0026beta;\u0026nbsp;cell\u0026nbsp;function.\u0026nbsp;Third, this study eliminates the confounding factors of diet and exercise by using well-validated questionnaires for the quantification of physical activity and eating patterns,\u0026nbsp;in addition to measurements of breast feeding. Finally, compared with other studies, this study performs standardized diabetes screening after delivery rather than relying solely on participants\u0026apos; self-detection of postpartum T2DM\u0026nbsp;\u003csup\u003e[48,49]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, there are some limitations to this study.\u0026nbsp;First, the sample size is relatively small. Although we initially identified 392 women with a history of GDM, the number of confirmed samples was relatively small due to the strict inclusion and exclusion criteria. The present findings will extend the study period to nearly 5 years or extend the study to several nearby cities, and be further verified in animal experiments.\u0026nbsp;Second, the present findings did not measure HbA1c\u0026nbsp;at\u0026nbsp;the postpartum visit;\u0026nbsp;however,\u0026nbsp;we\u0026nbsp;performed\u0026nbsp;an OGTT,\u0026nbsp;which is one of the standard tests for\u0026nbsp;the\u0026nbsp;diagnosis of diabetes (ADA) \u003csup\u003e[18]\u003c/sup\u003e.\u0026nbsp;Third, the\u0026nbsp;cesarean section rate may be a confounding factor for this study\u0026nbsp;(P\u0026lt;0.05 when comparing the two groups at baseline). However, whether the mode of delivery has an impact on postpartum insulin resistance and body fat composition in women with GDM is still highly controversial \u003csup\u003e[50,51]\u003c/sup\u003e. Finally, this study did not use the gold-standard methods (hyperinsulinemic-euglycemic-clamp or hyperglycemic-clamp) to evaluate pancreatic \u0026beta; cell function and insulin resistance but\u0026nbsp;the\u0026nbsp;HOMA-IR and IS-OGTT indices. Although the accuracy of HOMA-IR and IS-OGTT in measuring insulin\u0026nbsp;resistance/insulin\u0026nbsp;sensitivity is lower than\u0026nbsp;that of\u0026nbsp;the clamp method \u003csup\u003e[47, 52]\u003c/sup\u003e, they have been widely used in clinical and scientific research and are also good indices for predicting future diabetes \u003csup\u003e[53]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study confirms that breastfeeding improves body fat composition and enhances insulin sensitivity in women with a history of GDM. In addition, a longer duration of breastfeeding alters body fat redistribution after delivery in women with a history of GDM. This study further supports the beneficial effects of breastfeeding in ameliorating maternal glucose and fat metabolism, blood pressure, thyroid\u0026nbsp;function, and liver function. Breastfeeding promotes a long-lasting healthier metabolic environment important for preventing T2DM and cardiovascular diseases in women with\u0026nbsp;a\u0026nbsp;history of GDM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank Liulan Qian and Jianlei Gu, for their help with data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Changzhou Sci\u0026amp;Tech Program (Grant No.CZ20210025). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design: Jinhua Wei,\u0026nbsp;Renata Belfort-DeAguiar, Zhongzhi Jia. Telephone recruitment: Jinhua Wei, Huanyu Zhou, Yao Qing,\u0026nbsp;Chaomeng Zhou. Specimen collection:\u0026nbsp;Huanyu Zhou, Yao Qing,\u0026nbsp;Chaomeng Zhou, Zhe Song. Analysis and interpretation of data: Jinhua Wei, Huanyu Zhou, Yao Qing, Chaomeng Zhou, Renata Belfort-DeAguiar, Jianbo Gao. Writing the manuscript: Huanyu Zhou, Jinhua Wei. Revising the manuscript: Jinhua Wei, Zhongzhi Jia, Renata Belfort-DeAguiar, Jianbo Gao.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors indicate no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical standards:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by [the Institutional Ethics Committee], with the approval number: [[2021]KY013-01]. All participants/patients (or their proxies/legal guardians) provided informed consent to participate in the study. All participants/patients (or their proxies/legal guardians) provided informed consent for the publication of their anonymised case details and images.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice C, American Diabetes Association Professional Practice C, Draznin B, Aroda VR, Bakris G, Benson G, et al. 16. Diabetes Care in the Hospital: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Supplement_1):S244-S53.\u003c/li\u003e\n\u003cli\u003eMack LR TP. Gestational Diabetes: Diagnosis, Classification, and Clinical Care. Obstetrics and gynecology clinics of North America. 2017;44(2):207-17.\u003c/li\u003e\n\u003cli\u003eAgarwal MM DG, Shah SM. Gestational diabetes mellitus: simplifying the international association of diabetes and pregnancy diagnostic algorithm using fasting plasma glucose. 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Compliance with Postpartum Diabetes Screening Recommendations for Patients with Gestational Diabetes. J Womens Health (Larchmt). 2018;27(4):498-502.\u003c/li\u003e\n\u003cli\u003eNouhjah S, Shahbazian H, Amoori N, Jahanfar S, Shahbazian N, Jahanshahi A, et al. Postpartum screening practices, progression to abnormal glucose tolerance and its related risk factors in Asian women with a known history of gestational diabetes: A systematic review and meta-analysis. Diabetes Metab Syndr. 2017;11 Suppl 2:S703-S12.\u003c/li\u003e\n\u003cli\u003ePowe CE, Allard C, Battista MC, Doyon M, Bouchard L, Ecker JL, et al. Heterogeneous Contribution of Insulin Sensitivity and Secretion Defects to Gestational Diabetes Mellitus. Diabetes Care. 2016;39(6):1052-5.\u003c/li\u003e\n\u003cli\u003eBenhalima K, Van Crombrugge P, Moyson C, Verhaeghe J, Vandeginste S, Verlaenen H, et al. Characteristics and pregnancy outcomes across gestational diabetes mellitus subtypes based on insulin resistance. Diabetologia. 2019;62(11):2118-28.\u003c/li\u003e\n\u003cli\u003eRickels MR, Kong SM, Fuller C, Dalton-Bakes C, Ferguson JF, Reilly MP, et al. Insulin sensitivity index in type 1 diabetes and following human islet transplantation: comparison of the minimal model to euglycemic clamp measures. Am J Physiol Endocrinol Metab. 2014;306(10):E1217-24.\u003c/li\u003e\n\u003cli\u003eBergman RN, Prager R, Volund A, Olefsky JM. Equivalence of the insulin sensitivity index in man derived by the minimal model method and the euglycemic glucose clamp. J Clin Invest. 1987;79(3):790-800.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Clinical parameters b\u003c/strong\u003e\u003cstrong\u003eetween\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe non-breastfeeding group\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ebreastfeeding group.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-breastfeeding group (n=11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreastfeeding group (n=20)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalues\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnancy 24-28w\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis-OGTT 0min, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e5.0\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e4.9\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis-OGTT 60min, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e10. 3\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e9.8\u0026plusmn;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis-OGTT 120min, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e8.3\u0026plusmn;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e8.8\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnancy 36w\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e31.1\u0026plusmn;4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e30.5\u0026plusmn;3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight, m\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight, kg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e70.9\u0026plusmn;13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e68.2\u0026plusmn;12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGravidity, times\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e2.1(1.0-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e2.2(1.0-6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity, times\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e1.5(1.0-2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e1.6(1.0-3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e27.2\u0026plusmn;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e26.4\u0026plusmn;4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e118.4\u0026plusmn;14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e111.9\u0026plusmn;10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e73.9\u0026plusmn;9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e72.6\u0026plusmn;6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003cstrong\u003e, %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e5.1\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e5.5\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALT, U/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e18.6\u0026plusmn;17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e15.3\u0026plusmn;9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAST, U/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e18.8\u0026plusmn;11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e17.5\u0026plusmn;4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.651\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e3.1\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e3.0\u0026plusmn;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e5.4\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e5.7\u0026plusmn;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.493\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e1.8\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e1.9\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL, mmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e2.5\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTSH, \u0026mu;IU/mL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e1.9\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e1.4\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT3, pmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e3.6\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e3.8\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT4, pmol/L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u0026plusmn;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e14.1\u0026plusmn;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelivery information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek of delivery, weeks\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e38.5\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e39.4\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNewborn weight, kg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e3259.1\u0026plusmn;355.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e3415.0\u0026plusmn;303.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.177215189873415%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnancy outcome (Cesarean section rate), %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.933092224231466%\" valign=\"top\"\u003e\n \u003cp\u003e81.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.220614828209765%\" valign=\"top\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.669077757685352%\" valign=\"top\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eNote: BMI: body mass index, SBP: systolic blood pressure, DBP: diastolic blood pressure, OGTT: oral glucose tolerance test, HbA1c: hemoglobin A1c, ALT: alanine transaminase, AST: aspartate transaminase, TG: triglyceride, TC: total cholesterol, HDL: high-density lipoprotein cholesterol, LDL: low-density lipoprotein cholesterol, TSH: thyroid-stimulating hormone, FT3: free thyroxine 3, FT4: free thyroxine 4, HbA1c: hemoglobin A1c. \u003cem\u003eP\u0026nbsp;\u003c/em\u003evalues are calculated by T-student test or Mann-Whitney test. T-student test is used, and the data are expressed as Mean \u0026plusmn; Standard error,\u003cem\u003e\u0026nbsp;P\u003c/em\u003e values are calculated by T-student test; Mann-Whitney test was used, and the data were expressed as Mean (Minimum, Maximum),\u003cem\u003e\u0026nbsp;P\u003c/em\u003e values are calculated by Mann-Whitney test. \u003cem\u003eP\u003c/em\u003e values\u003cem\u003e\u0026le;\u003c/em\u003e 0.05 indicates that the difference is statistically significant.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breastfeeding, gestational diabetes mellitus, postpartum, lipid metabolism, insulin sensitivity","lastPublishedDoi":"10.21203/rs.3.rs-4280525/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4280525/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Aim: \u003c/strong\u003eThe aim of this study was to analyze the effects of breastfeeding on postpartum lipid metabolism, insulin sensitivity and body fat distribution in women with a history of gestational diabetes mellitus (GDM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods and Results: \u003c/strong\u003eThis was a retrospective pilot study. Participants were recruited from one-day GDM management clinics at the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University between 2017 and 2020. After obtaining their breastfeeding histories, the participants were divided into 2 groups based on their infant feeding practices: a non-breastfeeding group (n=11) and a breastfeeding group (n=20). Anthropometric measurements, insulin resistance indices (oral glucose tolerance test), questionnaires about infant feeding practices, and dietary intake and physical activity patterns were obtained at 6-28 weeks approximately 20 months postpartum. When comparing the breastfeeding and non-breastfeeding groups,\u003cstrong\u003e \u003c/strong\u003ebody fat percentage, arm circumference, waist circumference, visceral fat area, and insulin sensitivity were significantly improved by breastfeeding (\u003cem\u003eP\u003c/em\u003e≤0.05, for all). In addition, a longer duration of breastfeeding negatively correlated with arm circumference and waist circumference (\u003cem\u003eP\u003c/em\u003e≤0.05, for all).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur study showed that breastfeeding improves lipid metabolism, body fat distribution and insulin sensitivity in women with GDM,which may be further influenced by the duration of breastfeeding.\u003c/p\u003e","manuscriptTitle":"Breastfeeding Improves Insulin Sensitivity and Fat Distribution in Women with Gestational Diabetes Mellitus: A Retrospective Pilot Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 12:26:43","doi":"10.21203/rs.3.rs-4280525/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1b2c123-beeb-43c8-add7-d71a1775199c","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-25T07:23:47+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 12:26:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4280525","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4280525","identity":"rs-4280525","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}