An optimal control model to design strategies for reducing the spread of the Ebola virus disease

1.   Introduction

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders known to develop during pregnancy. Besides obesity and sedentary lifestyles being the main predisposing factors, dietary measures play an important role in its progression too. Risk factors for gestational diabetes mellitus (GDM) are similar to type 2 diabetes mellitus (T2DM) (older age and greater adiposity) [1]. The risk factors are classified as modifiable and non- modifiable risk factors (Figure 1). The modifiable risk factors are of prime interest, as they can be reversed thereby reducing likelihood of GDM. Studies of diet-GDM relationships suggested that high intakes of red and processed meats, saturated fats, refined grains, sweets, high fat dairy and fried foods were associated with significantly elevated risks of GDM [2]–[4]. The variation in dietary patterns has impacted the intake of the overall nutrients with dietary micronutrients contributing to the development of GDM [5].

Therefore, it is pertinent to explore the effects of maternal dietary patterns, diet quality and the micronutrient status and/or intake with the risk of GDM to prevent adverse birth outcomes. Given the lack of existing reviews specifically focusing on dietary pattern, diet quality and maternal micronutrient status in GDM, the present paper reviews latest evidences in this area across different economies of the world.

2.   Methodology

Dietary patterns and diet quality affect the nutritional status of the pregnant mothers during their physiological transition and on their birth outcomes. These factors are complex and highly diverse across different geographical locations. This paper aims to provide an update on the association between dietary patterns, diet quality and micronutrient status among mothers with GDM across the different economies of the world.

2.1.   Operational definitions

2.1.1.   Dietary pattern

It is defined as the quantities, proportions, variety or combination of different foods, drinks, and nutrients in diets, and the frequency with which they are habitually consumed [11].

2.1.2.   Diet quality

This concept involves the assessment of both quality and variety of the entire diet, enabling examination of associations between whole foods and health status, rather than just nutrients, by scoring the food patterns [12]. However, some studies interchangeably use the terms dietary pattern and diet quality.

2.2.   Search strategy

Studies published in English between 2000 and 2018 were selected. The electronic databases search included, PUBMED, Web of Science, Clinical Key, Clinical Key for Nursing, EbscoHost, Nature, Ovid, ProQuest, Science Direct, Scopus, Springer Link and Google Scholar. The key terms used in the search for relevant articles were as follows: GDM AND risk factors AND diet* patterns AND micronutrients status AND dietary intake OR Nutrient intake; Dietary patterns AND GDM AND nutrient status OR nutrient intake OR dietary intake; GDM AND diet* quality OR diet* variety OR food variety OR diet* diversity.

2.3.   Search protocol

All studies identified during the database search was assessed for relevance based on the information contained in the title, abstract and description/MESH heading. Full articles were retrieved for all studies that appeared to meet the inclusion criteria and those requiring further investigation. Studies were described in terms of design, sample characteristics, measurement of dietary pattern/quality exposure or micronutrients status/intake and outcomes across high, middle and low income countries.

2.4.   Study participants

This review considered any studies that included all pregnant women diagnosed with or without GDM.

2.5.   Types of studies

Analytical observational studies (case-control studies, cohort studies, analytical cross-sectional studies, prospective studies) and intervention studies that evaluated the risk of developing and managing GDM were included. However, systematic reviews and other categories of review papers were excluded during the search. The studies included were further categorised into economies per capita of the country according to United Nations classifications (2014) [13] and the origin where the study was conducted.

3.   Results

3.1.   Overall description of included studies

The included studies are listed according to area of focus (dietary patterns or dietary quality or micronutrients) in relation to GDM (Tables 1–7). The studies were subsequently grouped by economies according to United Nations (2014) [13] classification.

3.2.   Diagnosis of GDM

Various diagnostic criteria were used in different studies. Majority of the studies on dietary pattern and quality with GDM used the criteria used by their respective healthcare sites, informed during their pregnancy period or records retrieved from the diabetes registry of the national database. However, the Iranian study defined GDM as fasting glucose >95 mg/dL or 1-h postprandial glucose >140 mg/dL for the first time in pregnancy [28]. Only one study by Ferranti et al. (2014) [21] collected information on family history of T2DM.

On the other hand, majority of the studies investigating micronutrients with GDM had utilised American Diabetes Association guideline, World Health Organisation (WHO) as well as Carpenter and Coustan criteria. Besides, National Diabetes Data Group, International Diabetes Federation, Australasian Diabetes in Pregnancy Society guideline and United States of America (USA) National Cholesterol Education Program criteria were also used as the classification criteria for GDM in the studies.

3.3.   Dietary pattern, diet quality and micronutrients status in GDM

Eleven studies were published between 2006 and 2017 on dietary patterns and GDM. There were different definitions used for dietary pattern in the included studies. The studies from USA [14],[15] and Iran [29] labelled the dietary pattern as prudent or Western, while the other study from Iran has classified the dietary pattern as healthy and unhealthy [30]. The study from Singapore described the dietary pattern in three ways, namely vegetable-fruit-rice-based diet, seafood-noodle-based-diet and pasta-cheese-processed-meat-diet [25].

Nine studies in diet quality and GDM was published between 2012 and 2018. The diet quality measures used were; alternate HEI (aHEI) [17],[18],[21]; Mediterranean Diet [28]; adjusted Mediterranean Diet (aMED) [17]; Recommended Food Score [16]; Dietary diversity scores (DDS); Food Groups Index (FGI); Minimum Dietary Diversity-Women (MDD-W); Prime Diet Quality Score (PDQS) [26]; Healthy Eating Index (HEI)-2010 [22],[26] and Healthy Food Intake Index (HFII) [24].

Fifty-five studies published from 2000 to 2018, on maternal micronutrients status and/or intake and their associations or relationships with GDM were included (Table 4–7). The associations of micronutrients [iron (Fe), zinc (Zn), magnesium (Mg), vitamin D, selenium (Se), copper (Cu), chromium (Cr), calcium (Ca), potassium (K), folate, vitamin B₁₂, vitamin C and vitamin E] with GDM is reviewed. A total of 16 studies each for Fe and Zn, 11 studies each for Mg and vitamin D, respectively, were included in this review.

4.   Discussion

GDM is increasing exponentially worldwide. It is in tandem with the growing rates of obesity [85]. Consequences of GDM concern both the mother and the child resulting in adverse neonatal and maternal outcomes. In the recent decade, more attention has been paid to nutritional issues and their relationship with different diseases [86]. Diet plays an important role in the management of GDM. Dietary patterns reflect the dietary habits of people, the manner of consumption of food and nutrients consumption by the individual [87]. Dietary patterns and diet quality are major modifiable risk factors of GDM, which can alleviate its consequences. Diet also affects the micronutrient status of the GDM mothers due to added foetal needs. Geographically, dietary intake depends on food availability, which explains most of the countries having their own staple crop. However, the staple food may not be complemented well by healthier choices due to less disposable income, especially in the low-income countries. In contrast, higher economies have a comparatively easy access to healthier foods, due to their status as a developed nation [88]. Hence, the present paper aims to focus on the association of dietary patterns, diet quality and micronutrient status with GDM among the pregnant mothers from different economies.

Dietary pattern consistently varies across the different geographical locations too. For example, within India itself, the dietary pattern is quite diverse, ranging from more traditional vegetarian diets characterised by consumption of fruit, vegetables and pulses, to diets characterised by consumption of sweets, snacks and meat. The main differences in dietary patterns identified were attributed to the geographical region of India (with diets in the North and West being more similar to one another, as were diets in the East and South) [88]. This variation depends upon the staple food of the population, dietary practices and availability of foods. It has evolved over time across the world with unhealthy diets taking precedence in the form of fast foods and/or junk foods replacing the preferred nutrient dense healthy options. Evidence shows that Organisation for Economic Co-operation and Development (OECD) countries are by far, the closest to the WHO nutritional recommendations being increasingly similar in terms of adherence to those norms. While developing countries also show a trend towards a better diet on average, it seems that disparities within this large group of countries are increasing and not all countries are following a virtuous path. Least developed countries are the most distant from the WHO recommendations and there is no evidence of improved diets or a reduction in disparities [89], thereby justifying the need to evaluate the dietary factors with risk of GDM across different economies.

Dietary intake is characterized, by high consumption of vegetables, fruits, and dietary fibre and low consumption of high-fat/high-sugar foods, red and processed meat, associated with lower risks of GDM [90]. Most prospective cohort studies from the high-income countries reported that prudent dietary pattern was significantly and inversely associated with GDM risk. These studies have also shown that, intakes of red and processed meats were significantly associated with a higher risk of GDM. A study from Singapore by de Seymour et al. (2016) [25], reported that there was a significant association between consumption of a seafood-noodle based diet during pregnancy and a lower risk of GDM. Meanwhile, studies from the upper middle-income countries focused on the dietary patterns of the GDM mothers rather than their diet quality [27],[29],[30]. Their diets typically consisted of traditional, mixed or Western pattern [27]; Western and prudent [29]; unhealthy and healthy [30]. Despite in an earlier publication by Nascimento et al. (2016) [27] reported that there was no difference among GDM incidence, in relation to the three dietary patterns (traditional, mixed or western), Sedaghat et al. (2017) [29] reported otherwise; they found that the risk of developing GDM in the second median of Western dietary pattern scores was higher, as compared to the first median. The inconsistent findings may be due to the differences in their stratification of the dietary patterns. Nevertheless, both studies concluded that Western diet (comprising of white bread, mayonnaise, sugar sweetened beverages, salty snacks, organ meats, processed meat, pasta, pizza, candies, and cookies) was unhealthy and associated with increased risk of GDM.

Diet quality indices generally aim to measure the overall quality of a diet and its adherence to evidence-based dietary guidelines (e.g. HEI or ARFS) or its contribution to a health outcome (e.g. DASH or MED) [12]. As the indices involve scoring food/dietary patterns and nutrients tailored to the specific population, hence in this review, a wide variation of tools and their associations with risks of GDM is reported across the different economies. Several maternal diet quality indices were associated with an inversed risk of GDM although the results were equivocal. The population-specific scoring as per the national dietary recommendations and guidelines resulted in the wide variation in the indices between studies, limited the ability to elucidate a clear relationship between diet quality and GDM.

Inconsistent relationships between high scores of diet quality indices and risks of GDM were observed across the studies. Three papers from the same prospective cohort Nurses' Health Study (USA) published in different years reported higher scores of diet quality associated with lower risks of GDM [17],[18],[26]. The diet quality indices used in the earlier papers were the aMED, aHEI, DASH and HEI while the most recent studies added the dietary diversity scores besides aHEI-2010 and PDQS. Using comparable diet quality indices (DASH and MED); the Iranian study representing the upper middle-income country also reported similar findings [28]. However, in the Australian Longitudinal Study on Women's Health, conflicting evidence was reported as diet quality by quintile was not associated by GDM [23]. The inconsistent findings for GDM and diet quality indices might be explained by the types of food groups and nutrients incorporated into the national dietary guidelines as the basis of the diet quality indices. ARFS covered more food and food groups in the scoring criteria, despite the common elements of the indices included (high intake of fruit, vegetables, whole grains, nuts and legumes, and low intake of red and processed meats). Similar to dietary patterns, the selections of food groups and nutrients in the diet quality indices are unique to the particular country or culture affecting the quality and variety of the entire diet, thereby limiting the direct comparison across economies.

Micronutrients have a specific role during pregnancy. Fe transports oxygen, helps in cell growth and differentiation, also regulates gene expression [91],[92]. In contrast, Fe overload, could result in oxidative stress which impairs the insulin response in the liver, muscle and adipose tissue [93]. Such reactions are common in GDM, which results in an increased risk of glucose intolerance. Results from the high-income countries revealed high Fe intake, particularly the heme Fe, which significantly increased the risk of GDM among normoglycemic mothers. The positive association with increased risk of GDM was also reported among those consuming red meat, rich in heme iron [14]. However, non-heme Fe showed negative correlation with the risk of GDM. Findings from the upper middle-income countries on Fe is in line with the outcomes of high-income countries; serum Fe, ferritin and haemoglobin levels were found significantly higher among the GDM mothers. Lower middle-income population reported similar findings too. The outcomes from all the studies on Fe indicated a significant positive correlation between Fe and GDM.

Zn, an important component for more than 1000 of proteins, such as antioxidant enzymes and metalloenzymes, is involved in carbohydrate and protein metabolism, DNA and RNA synthesis, cellular replication and differentiation as well as hormone regulation [91]. Zn is also crucial for the growth and development of foetus during pregnancy; the deficiency of which may result in adverse pregnancy outcomes [94]. Zn has the ability to mimic and amplify the pancreatic and peripheral functions of insulin; GDM could be related to the shift in Zn balance of the maternal physiological changes [91]. Findings from the high-income population showed a negative association between maternal Zn intakes with GDM. Similar findings were reported for the upper middle-income countries; the lower the maternal Zn status or intake, the higher the chances of GDM during pregnancy. On the other hand, study from the lower middle-income population showed no significant difference between maternal Zn status and GDM. Results from the low-income countries and high and upper-middle income countries, reported a significant lower serum Zn level among the GDM mothers from the 2^nd and 3^rd trimester. The only intervention trial from Singapore investigating the association of maternal dietary patterns during pregnancy and risk of GDM in multi-ethnic Asian population reported similar results. A seafood-noodle based diet (rich in Zn) was associated with a lower risk of GDM [25]. All the evidences point towards a potential preventive role of Zn in GDM.

Results from the high and lower middle-income population showed no significant differences in the Mg level among the healthy and GDM mothers. However, results from the randomized placebo control trial using Mg supplement in the upper middle-income population showed a significant reduction in the fasting plasma glucose, serum insulin levels, HOMA-IR and significant increment on the quantitative insulin-sensitivity check index. This could be closely related to Mg's functions as a cofactor in enzymatic reactions for energy metabolism, carbohydrate oxidation, insulin regulation and insulin-mediated-glucose uptake [66]. Pregnant women are susceptible to Mg loss and this condition is more prominent among the GDM women; suggesting that an elevation in female hormones and Mg deficiency during pregnancy impairs insulin sensitivity [66].

Vitamin D has a negative association with the occurrence of T2DM [44],[47]. However, findings were equivocal [47],[91]. Vitamin D deficiency might be associated with altered glucose homeostasis during pregnancy [91] and possible pancreatic β-cell dysfunction [44]. A significant inversed association between maternal vitamin D status with GDM, especially during the 1^st and 2^nd trimester was observed. Similar findings from vitamin D supplementation studies, in upper-middle income countries were reported. There was a significant improvement on the GDM indicators in the vitamin D supplementation group, which includes fasting plasma glucose, serum insulin levels, HOMA-IR and the quantitative insulin-sensitivity check index. Findings from the lower middle-income country also showed significant lower maternal vitamin D status among the GDM group.

GDM is highly associated with oxidative stress; in the recent years, the antioxidant functions of Se are gaining more attention for its association with GDM [95]. Se regulates the thyroid hormone and modulates oxidative stress [96]. In addition, it plays a role in reducing the severity of insulin resistance, maintenance of normal glucose uptake as well as regulation of cellular glucose utilisation. Thus, Se is hypothesized to demonstrate insulin-like properties [91]. Findings from both the high and upper middle-income countries reported a significant negative association between Se and GDM. However, the lower-middle income countries showed no significant difference. More studies are needed to validate these findings.

In the present review, associations of other micronutrients with GDM reported inconclusive findings. Results obtained from the high-income countries revealed a significant linear association between Ca and K with GDM; inversed association between vitamin C and GDM; but no significant association of Cr with GDM. However, a lower Cr serum level among the lower middle-income group was reported. All the included studies reported a linear association of Cu with GDM. Vitamin E intakes were observed to be lower among the GDM mothers in the upper middle-income population. Ca supplementation has showed a significant improvement on the fasting plasma glucose, serum insulin levels, HOMA-IR and the quantitative insulin-sensitivity check index. Inversed association was detected for vitamin B₁₂ and folate with GDM among the lower middle-income population.

5.   Strengths and limitations of the review

To the best of our knowledge, this is the first review to explore the association between maternal dietary patterns, diet quality and micronutrient status in GDM across different economies. Although findings were inconsistent due to the varied dietary patterns, diet quality and lack of standardization in assessing GDM, yet, a summary of the present state of the problem and its methodological implications for further studies is shown. Particularly in terms of the use of standardized GDM criteria and measures for dietary patterns and quality.

This review has some limitations. The review process itself may be biased by the exclusion of studies published in other languages besides English. The key limitations are in the evidence base itself; particularly in the heterogeneity of the studies and their measures of dietary patterns, diet quality and GDM standards. Hence, cannot be progressed into a meta-analysis. This review could not establish a causal relationship between dietary factors and GDM. Besides the methodological heterogeneity, comparison was challenging, as each included study reported within the context of their geographical, cultural and behavioural determinants. We were unable to assess the true magnitude and draw definitive conclusions about the associations between these dietary measures with risks of GDM due to diverse methods of diagnosis of GDM and diet quality indices. Hence a systematic review is warranted to arrive at conclusive findings.

6.   Conclusion

There is a need for valid measures of dietary pattern and diet quality to ascertain the maternal dietary intake and their risks of GDM. The dietary pattern and quality differ according to the geographical region, culture and the economies per capital of a particular country as well as their population. They in turn, affect the micronutrients status of a mother directly or indirectly, and may result in compromised fetal outcomes. More studies on the relationship between dietary pattern, diet quality and various micronutrients with GDM are required, especially among the population from the low-income countries, which is currently limited. Hence, further research should be conducted to have a better understanding on the relationship between the variables, by standardizing all the determinants.