Journal of Peking University (Health Sciences) ›› 2021, Vol. 53 ›› Issue (3): 467-472. doi: 10.19723/j.issn.1671-167X.2021.03.005

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Relationship between nutrients intake during pregnancy and the glycemic control effect in pregnant women with gestational diabetes mellitus

GUO Hong-ping1,ZHAO Ai2,XUE Yong3,MA Liang-kun4,ZHANG Yu-mei1,Δ(),WANG Pei-yu5,Δ()   

  1. 1. Department of Nutrition and Food Hygiene, Peking University School of Public Health, Beijing 100191, China
    2. Vanke School of Public Health, Tsinghua University, Beijing 100091, China
    3. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
    4. Department of Obstetrics and Gynecology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
    5. Department of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China
  • Received:2020-12-16 Online:2021-06-18 Published:2021-06-16
  • Contact: Yu-mei ZHANG,Pei-yu WANG E-mail:zhangyumei@bjmu.edu.cn;wpeiyu@bjmu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(81573129)

Abstract:

Objective: To explore the relationship between nutrients intake during pregnancy and the glycemic control effect in pregnant women with gestational diabetes mellitus (GDM). Methods: Pregnant women for 25-35 gestational weeks who underwent prenatal examination and completed GDM diagnostic test in two third-class hospitals in Beijing from October 2015 to October 2017 were recruited to participate in the cohort study, and were investigated at enrollment, 2 weeks after enrollment, and delivery. The cross-sectional survey data 2 weeks after enrollment was used for this study. Among them, dietary survey used the 24 h dietary records to collect the food intake of the subjects for the past day, and the intake of energy, macronutrients and micronutrients, was calculated according to the Chinese Food Composition Table. Using the data of fasting blood glucose (FBG) collected by clinical information system and referring to the Chinese Guidelines for the Diagnosis and Treatment of Pregnancy Diabetes (2014), the GDM patients with FBG ≤5.3 mmol/L were divided into the well-control group, those with FBG >5.3 mmol/L were divided into poorly-control group, and pregnant women with normal glucose tolerance were consi-dered as the normal group. Binary Logistic regression was used to analyze the association between the nutrients intake and glycemic control effect in pregnant women with GDM. Results: A total of 227 pregnant women were enrolled, including 104 GDM patients and 123 normal pregnancy women. Among them, 76 subjects in the well-control group (73.1%, 76/104) and 28 subjects in the poorly-control group (26.9%, 28/104). Compared with the well-control group and the normal group, the protein intake and its energy ratio of the poorly-control group were significantly higher, while carbohydrate energy ratio was significantly lower. In terms of micronutrients, there was no significant difference between the well-control group and the poorly-control group. After adjusting for age, gestational age and physical activity level, with the well-control group as the control group, binary Logistic regression model showed that higher protein energy ratio was positively correlated with poorly glycemic control effect in pregnant women with GDM (OR=6.12, 95%CI: 1.44-25.98), while higher carbohydrate energy ratio was negatively correlated with poorly glycemic control (OR=0.54, 95%CI: 0.32-0.91). Conclusion: Reduced protein intake and increased carbohydrate intake were associated with better glycemic control in pregnant women with GDM. It is suggested that GDM patients should adjust their dietary pattern further to achieve good glycemic control effect.

Key words: Nutrients, Glycemic control, Gestational diabetes mellitus

CLC Number: 

  • R153.1

Table 1

Socio-demographic factors and health status among participants with different glycemic control effects"

Items Normal group (n=123) Well-control group (n=76) Poorly-control group (n=28) P
Age/years, $\bar{x} \pm s$ 32.4±3.3 33.0±4.1 35.7±3.7*# <0.001
Gestational age/weeks, M (P25, P75) 33.3 (30.4, 34.9) 31.1 (29.2, 33.1)* 33.6 (31.6, 35.0)# <0.001
Pregnancy BMI/(kg/m2), M (P25, P75) 21.5 (19.5, 23.4) 21.5 (20.2, 23.6) 21.8 (20.7, 25.4) 0.218
Nation, n (%) 0.051
Han 115 (93.5) 67 (88.2) 22 (78.6)
Other 8 (6.5) 9 (11.8) 6 (21.4)
Education level, n (%)a 0.766
Junior college or blow 4 (3.5) 10 (14.1) 2 (7.4)
University 62 (54.9) 33 (46.5) 16 (59.3)
Postgraduate or above 47 (41.6) 28 (39.4) 9 (33.3)
Occupation, n (%) 0.210
Home or unemployed 6 (4.9) 10 (13.2) 2 (7.1)
Work 100 (81.3) 54 (71.1) 20 (71.4)
Other 17 (13.8) 12 (15.8) 6 (21.4)
Family monthly income per person/Yuan, n (%)a 0.507
≤8 000 35 (29.2) 24 (32.9) 7 (25.0)
>8 000-14 000 40 (33.3) 29 (39.7) 13 (46.4)
>14 000 45 (37.5) 20 (27.4) 8 (28.6)
Subject’s average monthly income/Yuan, n (%)a 0.070
≤6 000 31 (25.8) 26 (37.1) 5 (18.5)
>6 000-10 000 53 (44.2) 23 (32.9) 8 (29.6)
>10 000 36 (30.0) 21 (30.0) 14 (32.7)
Physical activity, n (%) <0.001
High 20 (16.3) 34 (44.7)* 10 (35.7)
Medium 84 (68.3) 35 (46.1)* 16 (57.1)
Low 19 (15.4) 7 (9.2)* 2 (7.1)
Passive smoking, n (%) 0.225
Yes 28 (23.0) 8 (10.8) 4 (15.4)
No 88 (72.1) 60 (81.1) 20 (76.9)
Unclear 6 (4.9) 6 (8.1) 2 (7.7)
Family history of diabetes, n (%) 0.869
Yes 52 (42.3) 35 (46.1) 12 (42.9)
No 71 (57.7) 41 (53.9) 16 (57.1)
Parity, n (%) 0.105
0 100 (81.3) 53 (69.7) 19 (67.9)
≥1 23 (18.7) 23 (30.3) 9 (32.1)
Insulin usage, n (%) 0.721
Yes 4 (5.3) 1 (3.6)
No 72 (94.7) 27 (96.4)

Table 2

Macronutrients intake among participants with different glycemic control effects"

Nutrients Reference intakea Normal group (n=123) Well-control group (n=76) Poorly-control group (n=28) P
Energy/kcal, $\bar{x} \pm s$ 1 809.2±466.9 1 685.4±551.9 1 793.0±448.5 0.222
Carbohydrate/g, $\bar{x} \pm s$ 130b 275.2±81.3 262.5±94.6 248.2±72.5 0.258
Carbohydrate energy ratio/%, $\bar{x} \pm s$ 50-65c 61.0±8.9 61.9±10.3 55.4±8.6*# 0.006
Protein/g, M (P25, P75) 85d 73.7 (62.5, 87.4) 76.5 (57.2, 92.9) 85.9 (76.8, 104.2)*# 0.011
Protein energy ratio/%, M (P25, P75) 15-20c 17.0 (15.0, 19.0) 18.0 (16.0, 20.0)* 21.0 (18.0, 23.0)*# <0.001
Fat/g, M (P25, P75) 47.6 (34.4, 63.2) 39.9 (26.7, 53.5) 51.3 (38.4, 60.1) 0.021
Fat energy ratio/%, M (P25, P75) 20-30c 25.0 (20.0, 31.0) 22.0 (18.0, 29.0) 25.0 (22.0, 33.0) 0.074

Table 3

Micronutrients intake among participants with different glycemic control effects"

Nutrients Reference
intakea
Normal group (n=123) Well-control group (n=76) Poorly-control group (n=28) P
Dietary fiber/g, M (P25, P75) 12 (8.6, 17.4) 13.8 (9.3, 18.4) 16.5 (9.5, 21.9) 0.263
Vitamin A/μgRE, M (P25, P75) 770 1 538.2 (584.9, 1 946.5) 1 824.5 (837.4, 2 977.8)* 1 801.2 (558.4, 2 607.9) 0.003
Carotene/μg, M (P25, P75) 1 377.3 (750.4, 3 099.1) 1 956.7 (1 176.1, 2 713.0) 1 843.8 (1 121.5, 3 488.6) 0.136
Retinol/μg, M (P25, P75) 1 342.5 (212.7, 1 495.1) 1 470.4 (319.2, 1 606.8)* 1 374.5 (160.9, 1511) 0.008
Vitamin B1/mg, M (P25, P75) 1.5 2.1 (1.0, 2.7) 2.2 (1.3, 2.9) 2.3 (1, 3.1) 0.274
Vitamin B2/mg, M (P25, P75) 1.5 2.5 (1.0, 3.0) 2.6 (1.5, 3.4) 2.9 (1.2, 3.7) 0.039
Niacin/mg, M (P25, P75) 12 27.4 (11.7, 32.6) 27.9 (16.0, 34.5) 29.2 (14.9, 38.2) 0.308
Vitamin C/mg, M (P25, P75) 115 153.5 (88.5, 229.6) 201.4 (134.5, 262.0)* 198.8 (110.9, 440.4) 0.005
Vitamin E/mg, M (P25, P75) 14b 30.7 (13.4, 39.6) 31.8 (20.5, 40.9) 33.4 (15.0, 44.3) 0.360
α-tocopherol/mg, M (P25, P75) 5.2 (3.6, 7.4) 4.8 (3.4, 6.0) 4.7 (3.4, 6.3) 0.359
Calcium/mg, M (P25, P75) 1 000 737.1 (530.1, 926.3) 879.8 (660.6, 1 096.7)* 906.1 (803.1, 1 137.2)* <0.001
Phosphorus/mg, M (P25, P75) 720 1 272.5 (993.6, 1 546.2) 1 423.4 (1 145.1, 1 833.4)* 1 588.6 (1 387.2, 1 965.2)* <0.001
Potassium/mg, M (P25, P75) 2 000b 1 763.2 (1 435.6, 2 245.8) 1 811.6 (1 458.9, 2 233.9) 1 893.0 (1 649.5, 2 344.3) 0.217
Sodium/mg, M (P25, P75) 1 500b 750.7 (385.2, 1 367.1) 496.7 (402.7, 786.4)* 574.2 (396.7, 1 166.7) 0.029
Magnesium/mg, M (P25, P75) 370 313 (235, 403.5) 350.0 (284.7, 474.7)* 418.2 (276.3, 552.5)* 0.002
Iron/mg, M (P25, P75) 29 77.9 (30.4, 106.7) 80.1 (41.8, 115.8) 104.5 (33, 139.7) 0.132
Zinc/mg, M (P25, P75) 9.5 15.6 (10.5, 18.8) 16.8 (12.4, 21.3) 19.5 (14.4, 27.3)* 0.002
Selenium/μg, M (P25, P75) 65 49.0 (35.1, 62.4) 45.2 (32.8, 58.4) 51.0 (39.4, 57.7) 0.500
Copper/mg, M (P25, P75) 0.9 2.5 (1.8, 3.1) 2.6 (2.0, 3.3) 2.8 (2.0, 3.6) 0.192
Manganese/mg, M (P25, P75) 4.9b 4.5 (3.3, 5.8) 5.7 (3.8, 7.9)* 6.0 (4.5, 7.9)* <0.001

Table 4

Binary Logistic regression analyze the relationship between nutrients intake and glycemic control effect in pregnant women with GDMa"

Nutrients Model 1b Model 2c
OR 95%CI P OR 95%CI P
Protein 1.25 1.05, 1.50 0.013 1.20 0.98, 1.46 0.075
Protein energy ratio 7.69 2.08, 28.36 0.002 6.12 1.44, 25.98 0.014
Carbohydrate energy ratio 0.51 0.31, 0.82 0.006 0.54 0.32, 0.91 0.022
Fat energy ratio 1.69 1.00, 2.86 0.050 1.76 0.97, 3.19 0.065
Phosphorus 1.01 1.00, 1.02 0.010 1.01 1.00, 1.02 0.060
[1] 杨慧霞, 徐先明, 王子莲, 等. 妊娠合并糖尿病诊治指南(2014)[J]. 糖尿病天地(临床), 2014,8(11):489-498.
[2] International Diabetes Federation. IDF diabetes atlas[M]. 9th ed. Belgium: International Diabetes Federation, 2019: 53-54.
[3] Gao C, Sun X, Lu L, et al. Prevalence of gestational diabetes mellitus in mainland China: A systematic review and meta-analysis[J]. J Diabetes Investig, 2019,10(1):154-162.
doi: 10.1111/jdi.2019.10.issue-1
[4] 宋耕, 杨慧霞. 妊娠期高血糖环境对后代的近远期影响及干预措施[J]. 中国医刊, 2019,54(11):1166-1169.
[5] Metzger BE, Lowe LP, Dyer AR, et al. Hyperglycemia and adverse pregnancy outcomes[J]. N Engl J Med, 2008,358(19):1991-2002.
doi: 10.1056/NEJMoa0707943
[6] McIntyre HD, Catalano P, Zhang C, et al. Gestational diabetes mellitus[J]. Nat Rev Dis Primers, 2019,5(1):47.
doi: 10.1038/s41572-019-0098-8 pmid: 31296866
[7] Morris MA, Hutchinson J, Gianfrancesco C, et al. Relationship of the frequency, distribution, and content of meals/snacks to glycaemic control in gestational diabetes: the myfood24 GDM pilot study[J]. Nutrients, 2019,12(1):3.
doi: 10.3390/nu12010003
[8] 冯茹. 不完善的血糖管理与妊娠期糖尿病的不良妊娠结局的相关性研究[D]. 济南: 山东大学, 2018.
[9] 刘敏舜. 基于HbA1c的血糖控制效果对妊娠期糖尿病孕产妇妊娠结局的影响[D]. 广州: 南方医科大学, 2019.
[10] Elvebakk T, Mostad IL, Mørkved S, et al. Dietary intakes and dietary quality during pregnancy in women with and without gestational diabetes mellitus: a norwegian longitudinal study[J]. Nutrients, 2018,10(11):1811.
doi: 10.3390/nu10111811
[11] Macfarlane D, Chan A, Cerin E. Examining the validity and reliability of the Chinese version of the International Physical Activity Questionnaire, long form (IPAQ-LC)[J]. Public Health Nutr, 2011,14(3):443-450.
doi: 10.1017/S1368980010002806 pmid: 20939939
[12] 樊萌语, 吕筠, 何平平. 国际体力活动问卷中体力活动水平的计算方法[J]. 中华流行病学杂志, 2014,35(8):961-964.
[13] 杨月欣. 中国食物成分表(2002)[M]. 北京: 北京大学医学出版社, 2002: 24-336.
[14] 杨月欣. 中国食物成分表(2004)[M]. 北京: 北京大学医学出版社, 2005: 77-216.
[15] Metzger BE, Gabbe SG, Persson B, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy[J]. Diabetes Care, 2010,33(3):676-682.
doi: 10.2337/dc09-1848 pmid: 20190296
[16] Ma WY, Yu TY, Wei JN, et al. Plasma apelin: A novel biomarker for predicting diabetes[J]. Clin Chim Acta, 2014,435:18-23.
doi: 10.1016/j.cca.2014.03.030
[17] Kampmann U, Knorr S, Fuglsang J, et al. Determinants of maternal insulin resistance during pregnancy: An updated overview[J]. J Diabetes Res, 2019,2019:5320156.
doi: 10.1155/2019/5320156 pmid: 31828161
[18] Bgeginski R, Ribeiro PAB, Mottola MF, et al. Effects of weekly supervised exercise or physical activity counseling on fasting blood glucose in women diagnosed with gestational diabetes mellitus: A systematic review and meta-analysis of randomized trials[J]. J Diabetes, 2017,9(11):1023-1032.
doi: 10.1111/1753-0407.12519 pmid: 28032459
[19] Halse RE, Wallman KE, Newnham JP, et al. Home-based exercise training improves capillary glucose profile in women with gestational diabetes[J]. Med Sci Sports Exerc, 2014,46(9):1702-1709.
doi: 10.1249/MSS.0000000000000302
[20] Zhou X, Chen R, Zhong C, et al. Maternal dietary pattern characterised by high protein and low carbohydrate intake in pregnancy is associated with a higher risk of gestational diabetes mellitus in Chinese women: a prospective cohort study[J]. Br J Nutr, 2018,120(9):1045-1055.
doi: 10.1017/S0007114518002453
[21] Promintzer M, Krebs M. Effects of dietary protein on glucose homeostasis[J]. Curr Opin Clin Nutr Metab Care, 2006,9(4):463-468.
doi: 10.1097/01.mco.0000232909.84483.a9
[22] Snorgaard O, Poulsen GM, Andersen HK, et al. Systematic review and meta-analysis of dietary carbohydrate restriction in patients with type 2 diabetes[J]. BMJ Open Diabetes Res Care, 2017,5(1):e000354.
doi: 10.1136/bmjdrc-2016-000354
[23] Moreno-Castilla C, Hernandez M, Bergua M, et al. Low-carbohydrate diet for the treatment of gestational diabetes mellitus: a randomized controlled trial[J]. Diabetes Care, 2013,36(8):2233-2238.
doi: 10.2337/dc12-2714 pmid: 23564917
[24] Tajima R, Yachi Y, Tanaka Y, et al. Carbohydrate intake during early pregnancy is inversely associated with abnormal glucose challenge test results in Japanese pregnant women[J/OL]. Diabetes Metab Res Rev, 2017, 4(2017-04-18)[2020-05-20]. https://onlinelibrary.wiley.com/doi/full/10.1002/dmrr.2898.
[25] Hernandez TL, van Pelt RE, Anderson MA, et al. A higher-complex carbohydrate diet in gestational diabetes mellitus achieves glucose targets and lowers postprandial lipids: a randomized crossover study[J]. Diabetes Care, 2014,37(5):1254-1262.
doi: 10.2337/dc13-2411 pmid: 24595632
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