Association between Homocysteine-Related Dietary Patterns and Gestational Diabetes Mellitus: A Study Using the Reduced Rank Regression Method

Research Article

Austin J Endocrinol Diabetes. 2021; 8(3): 1088.

Association between Homocysteine-Related Dietary Patterns and Gestational Diabetes Mellitus: A Study Using the Reduced Rank Regression Method

Hui W¹, Yu-Hong L³, Ling-Peng L², Min-Hui Y³, Siyu W¹, Gu-Qin L¹ and Chun-Yan S¹*

1Department of Nutrition, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China

2Department of Clinical Lab, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China

3Department of Obstetrics and Gynecology, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China

*Corresponding author: Shen Chun-Yan, Department of Nutrition, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai 200137, China

Received: July 31, 2021; Accepted: September 24, 2021; Published: October 01, 2021


Background: This study aimed to evaluate the association between homocysteine-related dietary patterns and gestational diabetes mellitus.

Methods: A total of 488 pregnant women at 24-28 weeks of gestation between January 2019 and December 2020 were included. Demographic characteristics, dietary intake, and multivitamin supplement intake information were collected using a Food Frequency Questionnaire (FFQ); fasting venous blood samples were collected for serum index detection. Serum homocysteine (Hcy), folic acid, and B12 were selected as response variables, and hyperhomocysteinemia (hHcy)-related dietary patterns were extracted using the descending rank regression method. The relationship between the score of hHcy-related dietary patterns and GDM was analyzed using a multivariate logistic regression model.

Results: Three hHcy-related dietary patterns were extracted: (Mode 1) more meat, cattle meat intake, green leafy vegetables, dark vegetables and soy, and less consumption of shrimp; (Mode 2) livestock meat, eggs and more grains, green leafy vegetables, bacteria, algae, dairy, and less nuts intake; and (Mode 3) livestock meat intake, and less soy intake. Because the explanatory variation of mode 3 was relatively small, it was not retained. Only mode 2 had a positive and significant relationship with the risk of developing GDM. After adjusting for confounding factors, the risk of GDM was significantly increased in the highest quartile array (OR=2.96, 95% Confidence Interval: 0.939-9.356, P=0.004). There was no significant correlation between dietary pattern 1 and GDM risk (P >0.05).

Conclusion: Homocysteine-related dietary patterns were positively associated with gestational diabetes mellitus.

Keywords: Reduced rank regression method; Homocysteine; Dietary patterns; Gestational diabetes mellitus


GDM: Gestational Diabetes Mellitus; hHcy: Hyperhomocysteinemia; Hcy: Homocysteine; DI: Dietary Indices; PCA: Principal Component Analysis; CA: Cluster Analysis; FA: Factor Analysis; RRR: Reduced Rank Regression; PLS: Partial Least- Squares Regression; BMI: Body Mass Index; FFQ: Food Frequency Questionnaire; OGTT: Oral Glucose Tolerance Test; FBG: Fasting Blood Glucose; 1h PG: 1-h Postprandial Blood Glucose; 2h PG: 2-h Postprandial Blood Glucose


Due to the increase in the incidence of obesity and elderly parturients, the incidence of Gestational Diabetes Mellitus (GDM) in China has been increasing by 14.8% annually; with regional variation, wherein: East China, Central China, and North China have a higher prevalence [1]. The prognosis of GDM mainly depends on early prevention and intervention, among which dietary therapy is an important strategy for its primary prevention and is the basis of all diabetes treatments [2]. Dietary pattern is a comprehensive evaluation of diet as a whole, which can accurately reflect the effect diet disease [3] and in the relationship between nutrition and health [4]. Studies have found that high homocysteine levels (hyperhomocysteinemia, hHcy) are risk factors for GDM [5], and dietary patterns affect serum homocysteine (Hcy) levels; for example, a Mediterranean diet [6] and frugal diet [7] can significantly reduce serum Hcy levels. However, whether dietary patterns affect the incidence of GDM through changes in Hcy levels and its related mechanisms remains elucidated.

There are three types of dietary pattern-extraction methods. First is the use of dietary indices (DI); second is induction, which includes Principal Component Analysis (PCA), Cluster Analysis (CA), and Factor Analysis (FA); and third is the combination of methods from the first and second classes, Reduced Rank Regression (RRR) and Partial Least-Squares Regression (PLS). Adopting different methods according to the research purpose, the RRR method can explain the reaction variables to the greatest extent, such as variables related to disease outcomes, and nutrients, explain the variations [8], contribute to the analysis of the relationship between dietary patterns and disease, and analyze its possible mechanism. The applications of RRR are expanding in the field of nutrition epidemiology [9]. Therefore, this study aimed to extract hHcy-related dietary patterns using the RRR method and analyze their relationship with the incidence of GDM to explore the possible role of dietary patterns in hcy level and GDM.



A total of 512 pregnant women at 24 - 28 weeks of gestation who underwent regular obstetric examinations at our hospital between January 2019 and December 2020 were included in the study. Inclusion criteria were single pregnancy, normal expression and understanding ability, and informed consent. Exclusion criteria were: history of diabetes mellitus, hypertension, and thyroid disease; acute or chronic infectious diseases with obvious symptoms; and other major diseases. This study was approved by the Medical Ethics Committee of our hospital. All study participants provided informed consent.

Research methods

General demographic characteristics: Sociodemographic data (age, education, and gestational age) and pregnancy history (number of pregnancies/births) were collected by trained investigators. Height and weight were measured using uniform standards and specifications, and body mass index (BMI) before pregnancy was calculated to record weight gain during pregnancy.

Dietary questionnaire survey: The Food Frequency Questionnaire (FFQ) used a dietary review method and a food model to collect the dietary intake and multivitamin supplement intake of pregnant women during pregnancy in the form of face-to-face interviews. According to the food classification principles in the Chinese food composition List (sixth edition) [10], food types are classified and sorted into 24 types of food groups. All food intake data were standardized using NutriStar software (Yingkang Technology Company). The specific method was as follows: the intake of each food/group was equal to each intake multiplied by the daily intake times. The daily intake times were converted from the intake frequency. Food with an intake proportion ≦5% (crab/shell, egg tarts/shaomai, coffee/tea, and condiments) were not included in the dietary pattern analysis. In addition, subjects whose intake frequency of the 24 food groups was >99% with an energy intake of ≦800kcal were excluded. Finally, 488 cases were included in the analysis.

Diagnostic criteria for gestational diabetes: Pregnant women were screened for gestational diabetes mellitus at 24-28 weeks of gestation (referred to as “glucose screening). Glucose screening was a 75g Oral Glucose Tolerance Test (OGTT), China’s Guidelines for the Diagnosis and Treatment of Gestational Diabetes Mellitus (2014) [11] GDM is diagnosed if the blood glucose level reaches or exceeds the lower limit as follows: Fasting Blood Glucose (FBG) 5.1mmol/L, 1-h postprandial blood glucose (1h PG) 10.0mmol/L, and 2-h postprandial blood glucose (2h PG) 8.5mmol/L. According to the results from the OGTT, patients were divided into normal and GDM groups.

Serum index detection: The blood glucose in the OGTT was measured using the hexokinase method with a Beckman automatic biochemical analyzer (AU5800). Serum Hcy was detected using the enzyme cycle method with a Beckman automatic biochemical analyzer (AU5811). Serum Folic Acid (FA) and B12 folic acid were determined by the chemiluminescence method using an Abbott Automatic Immunoanalyzer (I1000S). Quality control was performed for all tests prior to testing. When the quality was not controlled, the specific reasons were analyzed and dealt with accordingly. Finally, tests were performed after re-controlling.

Statistical methods

Differences between the GDM and normal groups were compared using the t-test or Χ² test. RRR analysis was performed with the option (METHOD=RRR) in the PLS process of SAS software version 9.4 (SAS Institute, North Carolina, USA). Serum Hcy, FA, and B12 values were used as response variables, and as the RRR method could obtain at most the same number of dietary patterns as the number of response variables, three dietary patterns explaining hHcy variation could be obtained in this study. The dietary pattern factor load represented the size and direction of each food group’s contribution to hHcy-related dietary patterns, and the dietary pattern score was obtained by multiplying the dietary pattern factor load by the standardized food intake. The relationship between the scores of the three dietary patterns and the intake of each food group was evaluated using Pearson’s correlation. The subjects were divided into four groups according to the quartile of dietary pattern score, the characteristics of the subjects were analyzed, and a trend analysis was performed. The quartiles of dietary scores were used as independent variables, and logistic regression was used to analyze the relationship between hHcy-related dietary pattern scores and GDM after adjusting for age, educational background, gestational grade, BMI before pregnancy, weight gain during pregnancy, energy intake, and multivitamin intake.


General features

There was no difference in educational background and weight gain during pregnancy in the GDM group compared to the normal group (P<0.01). However, patients in the GDM group were older, the proportion of postpartum women was higher, and the pre-pregnancy BMI and energy intake levels were higher (P<0.01). The intake of folate in the GDM group was lower than that in the normal group, but there was no difference in the intake of B12 and B6 between the two groups (P>0.01). Serum Hcy levels were higher in the GDM group, but FA and B12 levels were lower in the GDM group than in the normal group (P<0.01) (Table 1).