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Risk of gestational diabetes mellitus: which lifestyle parameters should be changed?

https://doi.org/10.14341/DM8226

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Abstract

Background. Gestational diabetes mellitus (GDM) is a common complication of pregnancy. It can cause significant problems for the mother and offspring, such as caesarean delivery, birth trauma and the development of type 2 diabetes mellitus (T2DM) in the future. The identification and correction of modifiable risk factors for GDM will provide a possibility to prevent these complications.


Aim. This study aimed to identify the most significant lifestyle parameters affecting the risk of developing GDM.


Methods. The study included 680 pregnant women who underwent oral glucose tolerance test at 24–32 weeks of pregnancy and responded to a questionnaire comprising the following sections stratified in a semi-quantitative manner: the consumption of major food groups and drinks and the amount of physical activity and smoking before and during pregnancy. A logistic regression analysis was performed to identify lifestyle parameters that influence GDM development. GDM was diagnosed according to the IADPSG criteria.


Results. GDM was diagnosed in 266 women; the other 414 women formed the control group. The most significant dietary risk factor for developing GDM was the consumption of sausage(s), dried fruits and fresh fruits. Eating sausage(s) more than thrice a week during pregnancy increased the risk of developing GDM by 2.4 times [95% confidence interval (CI), 1.5–3.8; p < 0.001] and so did the consumption of dried fruits more than thrice a week during pregnancy [odds ratio (OR), 6.5; 95% CI, 2.5–16.8; p < 0.001)] compared with the risk of GDM by less consumption of these food groups. A regular consumption of fresh fruits more than 12 times a week during pregnancy reduced the risk of GDM (OR, 0.5; 95% CI, 0.3–0.8; p = 0.015). The habit of climbing at least four floors per day during pregnancy also reduced the risk of GDM (OR, 0.7; 95% CI, 0.5–1.0; p = 0.069).


Conclusions. The recommendations for GDM prevention should include limiting the consumption of sausage(s) and dried fruits, increasing the consumption of fresh fruits and introducing regular physical activities, such as climbing stairs.

For citations:


Popova P.V., Tkachuk A.S., Bolotko Ya.A., Gerasimov A.S., Demidova K.A., Pustozerov E.A., Kuznetsova L.V., Grineva E.N. Risk of gestational diabetes mellitus: which lifestyle parameters should be changed? Diabetes mellitus. 2017;20(1):85-92. (In Russ.) https://doi.org/10.14341/DM8226

Gestational diabetes mellitus (GDM) is one of the most frequently occurring diseases during pregnancy and the most common type of diabetes mellitus (DM) of pregnant women. GDM is diagnosed in 1%–18% of pregnant women, depending on the screening method, diagnostic criteria and studied population [1, 2]. Until recently, GDM was defined as a glucose metabolism disorder that first occurs during pregnancy [3]. Currently, GDM is defined as a disease that is characterised by hyperglycaemia first recognised during pregnancy but that does not meet the overt diabetes criteria [1, 4].

GDM is associated with both immediate and long-term adverse foetal and maternal outcomes, including caesarean delivery, birth injury [2] and the development of type 2 DM (T2DM) in the future [5]. GDM increases the risk of perinatal mortality, hypoglycaemia and jaundice in the newborns and gestational hypertension and pre-eclampsia in the mothers [2]. Reduction of foetal macrosomia is the best method of preventing birth injuries and lowering the caesarean rate. Approximately 15%–60% of women with GDM are expected to develop T2DM within 5 years after delivery [6]. Children of mothers with GDM have an increased risk of obesity, regardless of maternal obesity [7]. Thus, the prevention and early detection of GDM affect the health of mothers and future generations. Understanding the significance of GDM risk factors is becoming increasingly important.

Well-known nonmodifiable risk factors for GDM include GDM in anamnesis, family history of T2DM and advanced maternal age [8, 9]. However, no convincing evidence regarding the impact of changes in modifiable risk factors (diet and lifestyle) on GDM development and adverse pregnancy outcomes has yet been provided. [10]. This may be because of study limitations as well as different contributions of these factors to the development of GDM in various populations.

Aim

This study aimed to clarify the role of modifiable risk factors for GDM in Russian women and further develop recommendations for GDM prevention.

Methods

Study design

The study was conducted at the V.A. Almazov Federal North-West Medical Research Center (Saint Petersburg) during 2015 and 2016. A total of 680 pregnant women who underwent screening for GDM and agreed to participate were enrolled in the study.

Eligibility criteria

The exclusion criteria for the study are as follows: presence of type 1 or type 2 DM, presence of other diseases affecting glucose metabolism and patient's refusal to participate in the study.

Study conditions

Women from all districts of Saint Petersburg and the Leningrad region were examined at the V.A. Almazov Federal North-West Medical Research Centre. All women underwent oral glucose tolerance tests (OGTT) during GDM screening, and they were interviewed while being tested.

Description of medical intervention

Pregnant women who gave informed consent for participation underwent OGTT at 24–32 weeks' gestation. We measured the fasting glucose level as well as glucose levels at 1 and 2 h after a 75-g oral glucose load. Before the test was performed, the women were asked to continue their usual diet for at least 3 days. The test was performed in the morning after an 8–14-h overnight fast.

Laboratory glucose testing was performed at the clinical laboratory of the centre, using the Hitachi 902 chemistry analyser (Roche Diagnostics, Basel, Switzerland) and kits by Roche Diagnostics (Basel, Switzerland).

All women were examined by an endocrinologist. We also collected clinical data from the medical records of the patients, including weight before pregnancy, GDM and/or arterial hypertension (AH) in anamnesis, impaired glucose tolerance (IGT) before pregnancy and family history of DM.

Study participants completed a questionnaire that covered the following issues: frequency of consumption of the main groups of food products and drinks (fruits, cakes, pastry, chocolate, full-fat milk products, low-fat milk products, beans, meat, sausages, dried fruits, fish, whole-wheat bread, any bread, sauces, vegetables in any form, raw vegetables, alcohol, sugary drinks and coffee), level of physical activity (duration of walking: <30 min per day, 30–60 min per day or >60 min per day; climbing stairs: <4 floors per day, 4–16 floors per day or >16 floors per day; frequency of exercise for >30 min per week) and smoking history before and during pregnancy. The variables were stratified in a semiquantitative manner.

Main outcome of the study

The main outcome measure was the presence/absence of GDM.

Subgroup analysis

Two groups were formed in accordance with the OGTT results: the GDM group and the control group (including women without glucose metabolism disorders).

The diagnosis of GDM was established on the basis of OGTT results, according to the recommendations of the Russian National Consensus Statement on GDM [1] (fasting glucose levels were ≥5.1 mmol/L and/or postprandial glucose levels after 1 h were ≥10.0 mmol/L and/or after 2 h were ≥8.5 mmol/L). Women diagnosed with GDM were followed up at the perinatal centre of the V.A. Almazov Federal North-West Medical Research Centre.

Ethical review

The study protocol was approved by the Ethics Committee of the V.A. Almazov Federal North-West Medical Research Centre (Protocol No. 119 from 13.07.15).

Statistical analysis

Statistical data analysis was performed using SPSS 22.0 (SPSS Inc., USA). The data are expressed as М ± SD, where M is a mean value and SD is the standard deviation. To perform intergroup comparisons, Pearson's χ2 test was used for categorical variables, and Student's t test was used for continuous variables. The differences were considered significant when p < 0.05.

Binomial logistic regression was used for the assessment of associations between various lifestyle parameters and GDM. The presence or absence of GDM was considered a dependent variable (GDM present = 1; GDM absent = 0). Twenty-two variables were analysed as possible predictors of GDM: 16 variables were related to the intake of certain foods (fruits, cakes, pastry, chocolate, full-fat milk products, low-fat milk products, beans, meat, sausages, dried fruits, fish, whole-wheat bread, any bread, sauces, vegetables in any form and raw vegetables), three variables were associated with the intake of drinks (alcohol, sugary drinks and coffee) and three variables were related to physical activity (walking, climbing stairs and exercise). An ordinal scale comprising three levels was introduced to evaluate the intensity of these variables.

Results

Study population

The mean age of the study participants was 30.1 ± 4.9 years; the mean body mass index (BMI) before pregnancy was 24.7 ± 5.8 kg/m2. GDM was diagnosed in 266 women, and the remaining 414 women comprised the control group.

Table 1 contains the details of the study population. Women with GDM were older and tended to have a higher BMI before pregnancy. IGT, AH and GDM in anamnesis were more frequent among the participants with GDM. In addition, a family history of DM was slightly more often noted in these women, but the difference failed to reach statistical significance.

Table 1. Characteristics of women in the GDM and control groups

 

GDM

Control

Р

Age, years

31,5±4,9

29,1±4,7

<0,0001

BMI before pregnancy, kg/m2

26,7±6,6

23,7±5,1

<0,0001

Family history of DM, %

45,1

38,3

0,062

AH before pregnancy, %

22

8

<0,0001

GDM in anamnesis, %

7,4

1,1

0,004

IGT in anamnesis, %

5,7

2,2

0,025

Note: AH, arterial hypertension; BMI, body mass index; GDM, gestational diabetes mellitus; IGT, impaired glucose tolerance.

Main results of the study

We used the data from participant interviews to study the dietary habits and physical activity before and during pregnancy of women from both (GDM and control) groups.

Fig. 1 displays the frequency of consumption of the main food products and drinks before pregnancy; Fig. 2 shows the levels of physical activity before and during pregnancy in the two groups.

Figure 1. Nutrition history of the GDM and non-GDM women before pregnancy

Note. Figure 1 displays the discrete parameters for the consumption of certain foods and drinks. We performed the stratification of the consumption level for each product by introducing an ordinal scale comprising three levels: low, medium and high. The limits of the scale varied depending on the product type: fruits: <6 times per week, 6–12 times per week or >12 times per week; cakes: <2 times per week, 2–4 times per week or >4 times per week; pastry: <2 times per week, 2–4 times per week or >4 times per week; chocolate: <2 times per week, 2–4 times per week or >4 times per week; full-fat milk products: <3 times per week, 3–6 times per week or >6 times per week; low-fat milk products: <3 times per week, 3–6 times per week or >6 times per week; ; meat: <3 times per week, 3–6 times per week or >6 times per week; dried fruits: 0 times per week, 1–3 times per week or >3 times per week; fish: <3 times per week, 3–6 times per week or >6 times per week; ; whole-wheat bread: <1 time per week, 1–3 times per week or >3 times per week; any bread: <1 time per week, 1–3 times per week or >12 times per week; ; sauces: <1 time per week, 2–4 times per week or >4 times per week; vegetables: <6 times per week, 6–12 times per week or >12 times per week; raw vegetables: <6 times per week, 6–12 times per week or >12 times per week; alcohol: <1 time per week, 1–3 times per week or > 3 times per week; sugary drinks: <2 times per week, 2–4 times per week or >4 times per week; coffee: 0–1 time per day, 2–3 times per day or >3 times per day; sausages: <1 time per week, 1–3 times per week or >3 times per week ('<' means 'less than'; '>' means 'more than').

Figure 2. Physical activity of the GDM and non-GDM women

Note. Figure 2 displays the discrete parameters of physical activity. The limits of the scale varied depending on the type of physical activity. There were three levels: low, medium and high. Walking for <30 min per day, 30–60 min per day or >60 min per day; climbing stairs: <4 floors per day, 4–16 floors per day or >16 floors per day; sports (exercise for >30 min) <2 times per week, 2–3 times per week or >3 times per week ('<' means 'less than'; '>' means 'more than').

Significant differences were observed in the consumption of dried fruits (р < 0.001) and sausages (р < 0.001) before pregnancy and in the fresh fruit intake (р = 0.015) and the frequency of climbing stairs (р = 0.013) during pregnancy between the groups. The frequencies of consumption of other food products and drinks and the levels of other types of physical activity did not significantly vary across the study population. Due to the absence of differences in the consumption of various food products and drinks during pregnancy (except for fresh fruits), the data are not presented in graphs. We identified no difference in the frequency of smoking between the groups (before pregnancy: 41.5% and 36.5%, р = 0.137; during pregnancy: 11.9% and 9.3%, р = 0.443, among the GDM and non-GDM women, respectively).

We used a logistic regression model to estimate the impact of the consumption of certain food products and of physical activity on the risk of GDM. The results are presented in Fig. 3.

Figure 3. Lifestyle parameters and the risk of GDM [odds ratio (95% confidence interval) for GDM development, logistic regression]

Note: * - before pregnancy, ** - during pregnancy.

The following factors were most important in terms of GDM development: consumption of sausages, dried fruits and fresh fruits. Sausage intake of >3 times per week increased the risk of GDM 2.4-fold [95% confidence interval (CI), 1.5–3.8; р < 0.001]. The risks of developing GDM were 6.5-fold higher (95% CI, 2.5–16.8; р < 0.001) among women consuming dried fruits >3 times per week before pregnancy than among those consuming dried fruits 0 time per week. Conversely, the frequent intake of fresh fruits (>12 times per week) during pregnancy was associated with a decreased risk of GDM [odds ratio (OR), 0.5; 95% CI, 0.3–0.8; р = 0.015). Among the evaluated parameters of physical activity, the habit of climbing stairs for >4 floors per day during pregnancy was most important in terms of GDM prevention (OR, 0.7; 95% CI, 0.5–1.0; р = 0.069).

Additional results of the study

After inclusion of the classic risk factors for GDM (age, BMI, family history of DM and IGT in anamnesis) into the statistical model, age and BMI were the most significant risk factors associated with GDM. Each additional year (of participant age) increased the risk of GDM by 10% (OR, 1.1; 95% CI, 1.05–1.15; р < 0.001); increasing the BMI by 1 kg/m2 increased the risk of GDM by 8% (OR, 1.08; 95% CI, 1.04–1.12; р < 0.001). The positive correlation between the frequency of dried fruit intake and GDM development remained significant (OR, 5.8; 95% CI, 1.7–19.7; р < 0.001) after adjusting for covariates; the frequency of sausage consumption became even more significant (OR, 5.1; 95% CI, 2.5–10.5; р < 0.001).

Discussion

Summary of the main study results

Among the lifestyle parameters (diet and physical activity) analysed in the study, the frequent consumption of dried fruits and sausages before pregnancy, rare consumption of fresh fruits during pregnancy and low levels of physical activity (i.e. rare use of stairs during pregnancy) were the most significant risk factors associated with GDM development. We confirmed the role of the following known risk factors for GDM: older age, being overweight and obese, family history of DM, IGT, AH, and GDM in anamnesis [11, 12].

Discussion of the main study results

Our results suggest that the frequency of intake of certain foods can influence the risk of GDM. Several studies have established a correlation between diet and GDM risk [13, 14, 15].

In the current study, the frequent (>3 times a week) consumption of sausages before pregnancy increased the risk of GDM 2.4-fold. Our results are consistent with publications describing a positive association between a Western diet, which is characterised by a high intake of animal fats, and the development of GDM in pregnant women [14].

Bowers et al. reported that higher animal fat and cholesterol intakes are significantly associated with elevated GDM risk. [15]. Moreover, they demonstrated that the replacement of energy from carbohydrates with energy from fats significantly increased the risk of GDM [15].

Although the exact mechanisms underlying the impact of excess cholesterol and animal fat consumption on glucose homeostasis and the risk of GDM are unknown, the detected association is plausible in terms of physiology. Elevated levels of free fatty acids can inhibit insulin-stimulated glucose uptake, thus contributing to the development of insulin resistance [16]. According to data obtained from animal models, the accumulation of cholesterol in beta cells fosters a violation of glucose tolerance due to the dysfunction of beta cells [17].

We identified a positive correlation between the frequency of dried fruit consumption before pregnancy and the risk of GDM in the studied population. We failed to detect similar findings in the comparable works of other authors and in studies focusing on the relationship between dried fruit consumption during pregnancy and the risk of GDM or DM. Conversely, Keast et al. demonstrated that the consumption of dried fruits was associated with a lower frequency of obesity and being overweight [18]. The negative impact of dried fruits on glucose metabolism that was observed in our study is likely to be explained by the fact that many dried fruits are additionally sweetened with sugar during their production.

The increased intake of fresh fruits during pregnancy reduced the risk of GDM. Our results confirm the findings of several foreign authors [13, 14]. For example, the Nurses' Health Study demonstrated that a diet characterised by the lowest level of fruit and vegetable consumption was associated with an increased risk of GDM compared with a diet characterised by the highest consumption of these products [15].

Although the exact mechanisms underlying the negative correlation between the consumption of fresh fruits and the development of GDM are still unclear, this effect can probably be attributed to the high fibre and low caloric content of fruits. In addition, fruits are rich in vitamins, including vitamin C, which has a preventive effect for the development of GDM [19].

We also analysed the level of physical activity as one of the factors associated with GDM. The results of previous studies and their meta-analyses suggest that higher levels of physical activity before and in early pregnancy are associated with a lower risk of GDM [20]. Our data are in agreement with these results and demonstrate a negative correlation between the level of physical activity and the probability of GDM development.

Limitations of the study

This study has several limitations. The cross-sectional study design allowed us to only hypothesise a causal relationship between the lifestyle parameters before and during pregnancy and the risk of GDM, but we could not prove it. Because the data on lifestyle parameters were self-reported by the participants, we could not eliminate inaccuracy in determining the consumption frequency of certain foods and the amount of physical activity. However, this is a typical drawback of any diet-related epidemiological study. Another possible source of bias is associated with the different data presented by women from different subgroups. For example, women with excessive body weight or those who gain weight during pregnancy can often underestimate the actual consumption of food considered harmful as it is known that it is quite difficult to estimate such consumption. In addition, the relatively small sample size and low statistical power may account for the wide confidence intervals reported in our study.

Another limitation of the study is that the V.A. Almazov Federal North-West Medical Research Centre provides healthcare services primarily for those women who already have risk factors for GDM. This resulted in a relatively high frequency (39%) of GDM among the participants. Therefore, this work should not be considered as a population study, and the results do not reflect the prevalence of GDM in the Russian population.

Conclusion

We identified an association with the consumption frequency of certain foods and the levels of physical activity with the probability of GDM development; this finding corresponds with the general concepts of healthy lifestyle and the data obtained from other research. Our recommendations for a healthy lifestyle (i.e. increased consumption of fresh fruits and vegetables, limited consumption of sausages and dried fruits with added sugar, and regular physical activity) among reproductive-aged women may contribute to the prevention of GDM and related adverse pregnancy outcomes. Randomised clinical trials are needed to confirm the effectiveness for GDM prevention of these proposed measures, which are to be employed before and especially during pregnancy. Additional investigation of the pathophysiological, molecular and genetic mechanisms underlying the impact of diet characteristics and physical activity levels on the development of GDM and on the foetus is also required.

Additional information

FUNDING

The study was conducted with the financial support of the Russian Science Foundation (project No. 15-14-30012).

Conflict of interest

The authors declare no conflicts of interest related to the current manuscript.

Author contributions

P.V. Popova: development of the study design, statistical data analysis and drafting the manuscript; A.S. Tkachuk: data collection, patient counselling and drafting the manuscript; Ya.A. Bolotko: data collection, patient counselling and drafting the manuscript; A.S. Gerasimov: data collection and patient counselling; K.A. Demidova: data collection and drafting the manuscript; E.A. Pustozerov: statistical data analysis and preparation of graphic images; L.V. Kuznetsova: data collection, patient counselling and drafting the manuscript; E.N. Grineva: coordination of the study and analysis of the results.

References

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About the Authors

Polina Viktorovna Popova

Almazov Federal North-West Medical Research Centre; St Petersburg Pavlov State Medical University


Russian Federation

MD, PhD


Competing Interests:

No conflict of interests



Aleksandra Sergeevna Tkachuk

Almazov Federal North-West Medical Research Centre


Russian Federation

research associate


Competing Interests:

No conflict of interests



Yana Alexeevna Bolotko

Almazov Federal North-West Medical Research Centre


Russian Federation

MD, junior research associate


Competing Interests:

No conflict of interests



Andrey Sergeevich Gerasimov

Almazov Federal North-West Medical Research Centre


Russian Federation

research associate


Competing Interests:

No conflict of interests



Ksenia Alexandrovna Demidova

St Petersburg Pavlov State Medical University


Russian Federation

clinical resident


Competing Interests:

No conflict of interests



Evgenii Anatol'evich Pustozerov

Almazov Federal North-West Medical Research Centre; St Petersburg State Electrotechnical University


Russian Federation

assistant lecturer


Competing Interests:

No conflict of interests



Liubov Vladimirovna Kuznetsova

Almazov Federal North-West Medical Research Centre


Russian Federation

MD, PhD


Competing Interests:

No conflict of interests



Elena Nikolaevna Grineva

Almazov Federal North-West Medical Research Centre; St Petersburg Pavlov State Medical University


Russian Federation

MD, PhD, Professor


Competing Interests:

No conflict of interests



Supplementary files

1. Рис. 1. Характеристика питания до беременности женщин с ГСД и группы контроля.
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2. Рис. 2. Распределение по уровню физической активности женщин с ГСД и группы контроля.
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Type Исследовательские инструменты
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3. Рис. 3. Параметры образа жизни и риск развития ГСД (отношение шансов (95% ДИ) развития ГСД для факторов образа жизни при применении логистической регрессии)
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Type Исследовательские инструменты
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Indexing metadata ▾

Review

For citations:


Popova P.V., Tkachuk A.S., Bolotko Ya.A., Gerasimov A.S., Demidova K.A., Pustozerov E.A., Kuznetsova L.V., Grineva E.N. Risk of gestational diabetes mellitus: which lifestyle parameters should be changed? Diabetes mellitus. 2017;20(1):85-92. (In Russ.) https://doi.org/10.14341/DM8226

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ISSN 2072-0351 (Print)
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