Research Article Maternal Dietary Patterns and Gestational Diabetes Risk: a Case-Control Study
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Hindawi Journal of Diabetes Research Volume 2017, Article ID 5173926, 8 pages https://doi.org/10.1155/2017/5173926 Research Article Maternal Dietary Patterns and Gestational Diabetes Risk: A Case-Control Study 1 2 2 3 Fatemeh Sedaghat, Mahdieh Akhoondan, Mehdi Ehteshami, Vahideh Aghamohammadi, 1 4 2 Nila Ghanei, Parvin Mirmiran, and Bahram Rashidkhani 1Department of Basic Medical Sciences, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2Department of Community Nutrition, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran 3Department of Paramedical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 4Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Correspondence should be addressed to Bahram Rashidkhani; [email protected] Received 26 April 2017; Revised 22 August 2017; Accepted 24 August 2017; Published 6 December 2017 Academic Editor: Eusebio Chiefari Copyright © 2017 Fatemeh Sedaghat et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Maternal dietary patterns play an important role in the progress of gestational diabetes mellitus (GDM). The aim of the present study was to explore this association. Method. A total of 388 pregnant women (122 case and 266 control) were included. Dietary intake were collected using a food frequency questionnaire (FFQ). GDM was diagnosed using a 100-gram, 3-hour oral glucose tolerance test. Dietary pattern was identified by factor analysis. To investigate the relation between each of the independent variables with gestational diabetes, the odds ratio (OR) was calculated. Results. Western dietary pattern was high in sweets, jams, mayonnaise, soft drinks, salty snacks, solid fat, high-fat dairy products, potatoes, organ meat, eggs, red meat, processed foods, tea, and coffee. The prudent dietary pattern was characterized by higher intake of liquid oils, legumes, nuts and seeds, fruits and dried fruits, fish and poultry whole, and refined grains. Western dietary pattern was associated with increased risk of gestational diabetes mellitus before and after adjustment for confounders (OR = 1.97, 95% CI: 1.27–3.04, OR = 1.68, 95% CI: 1.04–2.27). However, no significant association was found for a prudent pattern. Conclusion. These findings suggest that the Western dietary pattern was associated with an increased risk of GDM. 1. Introduction the prevalence of GDM is thought to shadow that of type II diabetes, we expect to see a rise in GDM incidence during Gestational diabetes mellitus (GDM), defined as any degree the coming years [3]. of glucose intolerance with onset during pregnancy, is a Thus, it is crucial to detect modifiable risk factors that common complication, and its prevalence ranges between may contribute to the prevention of GDM. Food and dietary 7 and 14% worldwide [1]. factors have been reported to affect glucose homeostasis, and Incidence of GDM among Iranian women living in diet may be associated with GDM risk factors [6, 7]. Several urban areas has been reported similar to developing coun- studies found a positive association between GDM risk and tries [2–5]. However, with the prevalence of type II intake of total fat [8, 9], saturated fat [10, 11], and an inverse diabetes increasing across the world and considering that relation between the risk of GDM and polyunsaturated 2 Journal of Diabetes Research fat [10, 12]. In contrast, no significant association was found 5284 kcal) were excluded. The final sample for statistical between total dietary, saturated, and polyunsaturated fat analysis was 122 cases and 266 controls. intake and the risk of GDM in another study [13]. Informed consent was obtained from each participant However, most previous studies have traditionally prior to enrollment. The study protocol was approved by focused on the role of the single food items [14], nutrients the ethics committee at the National Nutrition and Food [15, 16], or food groups [17, 18]. Considering the limitations Technology Research Institute of Shahid Beheshti University of these kinds of studies, such as neglecting the interactions of Medical Science. and synergistic effects of nutrients [19], detecting dietary ff patterns o ers a comprehensive and complimentary method 2.2. Dietary Intake. One year before pregnancy, dietary intake in investigating the relationship between diet and disease risk of all participants were collected through validated semi- fi fl [20]. Dietary patterns are population speci c and are in u- quantitative food frequency questionnaires (FFQs) by trained enced by sociocultural factors and food availability [20]. interviewers. The FFQ consisted of 147 food items, including The results of recent systematic reviews showed that adher- some of the most common Iranian meal recipes, and has ence to a healthier dietary pattern, like Mediterranean dietary been previously shown to be valid and reproducible for use pattern, and reducing the intake of sugar sweetened cola, in Iranian adults [27]. Subjects were asked to mention their potatoes, fatty foods, sweets, and food with high heme iron consumption frequency of a given serving of each food content can decrease the incidence of GDM, especially in item during the past year, on a daily, weekly, monthly, women at higher risk and before getting pregnant [7, 21]. or yearly basis. Common household measures (measuring However, the majority of the studies to date have been cups, spoons, and palm of hand) were used for better esti- conducted in western populations [17, 22, 23]. Conversely, mation of the real portion consumed by the subjects [28]. studies investigating dietary patterns in relation to GDM in Portion sizes consumed from each food item were then Asian women, who are at a much greater risk of developing converted to daily gram intake using the household scales GDM compared to others ethnics, are sparse [24, 25]. Due [28]. In addition to the daily energy, macronutrient and to the growing trend of gestational diabetes and a shortage micronutrient consumption for participants was calculated ff of research on the e ect of dietary patterns on the prevention using the United States Department of Agriculture Food of GDM in Asian women, this study aimed to investigate the Composition Databases (USDA FCT). However, for some association between prepregnancy dietary patterns and risk dairy products such as Kashk, wild plum, mint, sweet canned of GDM in Iranian women. cherry, and sour cherry that are not listed in the USDA FCT, Iranian FCT was used alternatively [28]. 2. Materials and Methods 2.1. Participants. This hospital-based case-control study was 2.3. Assessment of Nondietary Exposures. Information on age, conducted in Tehran, a province of Iran at high-risk of diabe- prepregnancy weight, education level, socioeconomic status, tes. Cases (n = 123) with pregnant women aged 18–40 years cigarette smoking, family history of diabetes, and taking who visited major general hospitals in different regions of supplements were obtained from all cases and controls by Tehran (11 million inhabitants) were included. Pregnant trained professional interviewers using a questionnaire. women were screened for gestational diabetes between the The weight of each subject was measured with minimum clothing, and 100 g sensitivity and height was measured 24th and 28th weeks of gestation with a 50 g, 1 hr glucose fi challenge test (GCT). If the screening test was positive (blood with using a nonstretch tape-meter xed to a wall and glucose greater than 130 mg per ml), diagnostic testing was was recorded to the nearest 0.5 cm. Body mass index (BMI) was computed subsequently by the formula (weight in kg)/ performed using a 100 g, 3-hour oral glucose tolerance test 2 (OGTT). Women meeting the Carpenter and Coustan criteria (height in meter) . [26], fasting 5.3 mmol/l, 1 h 10.0 mmol/l, 2 h 8.6 mmol/l, and Physical activity level before pregnancy and average ff 3 h, 7.8 mmol/l, were diagnosed with GDM (any two values time per day spent on di erent intensity activities was at or above established thresholds). evaluated using a validated self report-based questionnaire Controls were pregnant women (n = 268) whose GCT [29] and was expressed as metabolic equivalents hours/day ff tests at 24–28 weeks of pregnancy were in the normal range. (METs-h/d) in which nine di erent MET levels were ranged The exclusion criteria were multiple pregnancies, history of on a scale from sleep/rest (0.9 METs) to high-intensity phys- > gestational diabetes or diabetes (prepregnancy), and under- ical activities ( 6 METs). By multiplying the time spent on going a weight-reduction diet one year before pregnancy. each activity level by the MET value of each activity, the Furthermore, controls were followed up until the end of MET-time for an activity was computed. Based on question- pregnancy. If they developed GDM, they were excluded naire data, we estimated a total activity score by adding the fi from the study. In this study, two controls were recruited speci c activities together. within the same medical center for each case. Controls were matched to cases on age (within 5 years). During anal- 2.4. Statistical Analysis. All analyses were performed using the ysis, three patients (1 case and 2 controls) with extreme Statistical Package for Social Sciences software version 16 energy intakes that probably reflected careless completion (SPSS Inc., Chicago, IL, USA), and a two-sided p value < 0.05 of the dietary questionnaire (below or above the mean ± 3 was considered significant. The Kaiser–Meyer–Olkin test SD for log-transformed calories; cutpoints: 244 kcal and (KMO = 0.7) indicated adequacy of sampling.