Preconceptional micronutrient adequacy among women in Greece: a prospective epidemiological study

Abstract

Introduction

The importance of micronutrient intake during the preconceptional and early pregnancy period for both maternal and fetal outcomes is well-known, however, relevant data are not available for Greek pregnant women. The aim of the present study is to delineate the nutritional status preceding conception among a representative cohort of Greek pregnant women.

Methods

This was a prospective study of pregnant women from routine care, recruited at 11⁺⁰–13⁺⁶ gestational weeks, between December 2020 and October 2022, at the 3^rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece. Eligible participants for the study included healthy pregnant women aged 20 years or older, possessing a proficient understanding of the Greek language, and not engaged in specific nutritional programs. A validated Food Frequency Questionnaire was applied to gather information regarding nutritional habits in the last 6 months prior to conception. The consumption of nutrients was compared to the reference intake levels suggested by the European Food Safety Authority. Further analyses between different participants’ subgroups were performed.

Results

Overall, 1100 pregnant women (mean age: 32.4 ± 4.9 years) were enrolled. Almost all examined micronutrients’ intake was significantly different from dietary reference values. Furthermore, nutrient adequacy ratio was below 60% in 6 out of 22 micronutrients examined, and Mean Adequacy Ratio was 93%. However, Mean Adequacy Ratio is characterized by extreme variance between the examined values. Iodine, folic acid, potassium, and vitamin D intake levels were significantly lower than the recommended intake levels (p < .001 for all), while vitamin K and niacin (p < .001 for both) were consumed in great extent. Sodium median intake, without calculating extra salt addition also exceeded the reference value levels (p = .03). Notably, magnesium intake exceeded the upper safety limits in 12.4% of the sample.

Conclusion

Potential inadequacies in important micronutrients for uneventful pregnancy outcomes have been revealed.. Special attention is needed for magnesium to balance possible toxicity with evident benefits.

Keywords:

• Nutrition
• pregnancy
• preconception
• micronutrients
• mean adequacy ratio
• average intake

Introduction

There is mounting evidence from both animal [1] and human studies that the maternal nutritional status prior to conception affects the offspring’s health outcome [2]. In a recent animal study, a mouse model deficient in MTHFD1 synthetase was employed to investigate whether pregnant women with the choline deficiency might exhibit increased risk of adverse reproductive outcomes [3]. Mild choline deficiency was associated to altered maternal one-carbon metabolism and increased the risk of birth defects. Nutrition during the early stages of maternal life exerts a significant and direct impact on both developing fetuses and infants. Throughout pregnancy, the mother’s nutritional intake plays a crucial role in influencing fetal growth and development, primarily through the interaction between the mother and the developing fetus. Two essential nutrients during pregnancy, folic acid and choline, play integral roles in the production of nucleotides, phospholipids, and the process of methylation [4]. The hemoglobin (Hb) level serves as one of the assessment markers for evaluating the nutritional status of pregnant women [5]. Research has shown varying conclusions regarding the association between Hb concentration during different trimesters and birth outcomes, such as small for gestational age. Gestational diabetes mellitus is a prevalent metabolic disorder among pregnant women, significantly elevating the risk of chronic noncommunicable diseases in their offspring [6]. The role of micro and macronutrients intake in fetus and child development has been thoroughly examined. Memory impairment and neurodevelopmental abnormalities have been observed in pregnant women experiencing iron deficiencies. Folate deficiency has been linked to cognitive dysfunction and learning disabilities in children [7]. Vitamin A plays a crucial role in organogenesis, neural patterning, neuronal differentiation, neurite outgrowth, and axonal elongation [8, 9]. Choline deficiency, prevalent during pregnancy, is known to impact neurogenesis and angiogenesis in the fetal hippocampus, with studies suggesting an association between choline deficiency and neural tube defects. Polyunsaturated Fatty Acids, including Omega-3 and Omega-6, along with Docosahexaenoic Acid (DHA), are closely tied to neuronal functioning, influencing synapse maturation and myelination during development. Inadequate fatty acid intake during development is associated with an increased risk of low IQ, altered visual acuity, and impaired cognitive, language, and motor development [10–12].

Recent data from European countries suggest that women may not meet the minimum nutrient requirements stipulated in dietary guidelines and nutritional recommendations during the preconceptional and early pregnancy period [13,14] These shortcomings may compromise maternal and fetal health. Particularly, inadequate folic acid intake has been linked to altered DNA methylation and compromised fetal brain development [15]; subsequently folic acid fortification may reduce the risk of neural tube defects by up to 70% [16]. For this reason, for women planning a pregnancy or those pregnant, a minimum of 400 micrograms per day is recommended by all guidelines [14]. Furthermore, in experimental animal models, dietary restriction of iron from early gestation resulted to a 40–50% decrease in brain iron 10 days post birth [17].

According to data from Europe, not all women of reproductive age will be “nutritionally prepared” for pregnancy, even at lower reference nutrient intake levels; this applies especially to younger women [18]. However, relative data are lacking for the Greek population. Thus, the objective of this observational study was to delineate the preconceptional nutritional status of Greek pregnant women, specifically focusing on micronutrient intake.

Methods

Study participants

This was a prospective epidemiological study on a sample of Greek pregnant women. All participants were recruited from routine care, at the scheduled appointment for the first trimester scan (11⁺⁰–13⁺⁶ gestational weeks), at the 3^rd Department of Obstetrics and Gynecology (School of Medicine, Aristotle University of Thessaloniki, Greece), between December 2020 and October 2022. Pregnant women were approached by two researchers (AA, AT) with experience in interview administration and data collection. The selection criteria used to determine eligibility were ongoing pregnancy, age > 20 years and good understanding of Greek language. Women were excluded if they were on a specific nutritional program due to any health issue (e.g. malabsorption syndrome, inflammatory bowel disease, etc.) or were diagnosed with certain preexisting medical conditions, including diabetes mellitus, chronic hypertension, and autoimmune diseases.

The study design was approved by the Bioethics Committee of the Aristotle University of Thessaloniki, Greece (6.231/29.7.2020). After obtaining a written informed consent, a planned interview followed to collect all data.

Sociodemographic, medical history, and anthropometric assessment

Sociodemographic data, medical history, and relevant data were recorded; the information collected included: (1) maternal age; (2) maternal weight before pregnancy and height (the prepregnancy body mass index [BMI] was calculated and women were categorized into underweight with a BMI < 18.5 kg/m², normal weight with a BMI between 18.5 and 24.9 kg/m², overweight with a BMI between 25 and 29.9 kg/m², and obese with a BMI ≥ 30 kg/m²) [19]; (3) smoking and alcohol consumption before and during pregnancy; (4) chronic conditions, medications, and supplements used on a regular basis before and during pregnancy; (5) parity and gravidity; (6) method of conception (spontaneous or assisted reproductive technology—ART).

Dietary assessment

To record the dietary habits of the participants, a recently developed questionnaire was used, which has been previously validated in the Greek pregnant population [20]. This is a semiquantitative questionnaire based on three preexisting food consumption questionnaires for the nutritional assessment of Mediterranean populations [21–23]. The participants were asked to fill in the questionnaire recording the frequency of consumption of each food; available options of response included: “never”, “x portions daily/per week/per month”. Frequency reported per food group response was converted into daily intake. Frequency per day consumed was then quantified by multiplying with portion size reported. Finally, food grams consumed were converted into nutritional data and micronutrient intakes were calculated. The conversion was executed through a computer program, nutrisurvey, designed to translate grams of food into corresponding nutrient values. Especially for vitamin A, all carotenoids were calculated, for niacin calculation tryptophan was included and for vitamin E all tocopherols were included.

Data from the examined sample were compared to reference intake levels recommended for pregnant women by the Dietary Reference Values (DRVs) for the European population as derived by the European Food Safety Authority (EFSA) [24]. DRVs are an umbrella term for the complete set of nutrient reference values which include (1) Population Reference Intake (PRI): the level of (nutrient) intake that is enough for virtually all healthy people in a group, (2) Average Requirement (AR): the level of (nutrient) intake that is enough for half of the people in a healthy group, given a normal distribution of requirement, (3) AI: Adequate Intake is the average observed daily level of intake by a population group (or groups) of apparently healthy people that is assumed to be adequate [25]. In the present study we used AR and when this was not available AI or PRI. For calcium, the reference of 750 mg was chosen since this value is the recommended level for women ≥25 years of age (mean age of the study population was 32.4 ± 4.9 years). Supplemental Table 1 summarizes the main potential benefits and dangers from high/low consumption of and micronutrients for human health.

To estimate the dietary adequacy of each micronutrient, the nutrient adequacy ratio (NAR) was calculated for each of the 22 micronutrients: calcium, iron, vitamin A, C, D, E, vitamin B₁, B₂, B₆, B₁₂, K, niacin, zinc, magnesium, copper, folic acid, phosphorous, manganese, potassium, pantothenic acid, biotin, iodine. The NAR value for a given nutrient is the ratio of a respondent’s current intake of the nutrient to the AR (or the AI if AR is not available) for the corresponding age category. A NAR = 1 indicates a value that is 100% of AR, meaning that the intake equals the requirement. Since NAR only investigates one nutrient at a time, to examine the proportion of the population that meet nutrient requirements in total the mean adequacy ratio (MAR) was also calculated. This is the sum of all NARs divided by the number of nutrients assessed (n = 22) and was reported on a scale from 0 to 100.

Statistical analysis

Frequencies and descriptive statistics were expressed as n (%) and as mean (± standard deviation [SD]) for parametric data, or median (25th – 75th IQR [interquartile range]) for nonparametric data, respectively. Before hypothesis’ testing, data were examined for normality using Kolmogorov-Smirnov test. The comparison of mean intake levels of our sample and the DRV was performed with Wilcoxon signed rank test. Data was collected by food frequency questionnaires (FFQs), so qualitative analysis was performed. In order to calculate lower safety limits of intake levels 2 SDs were taken off from the AR or AI of each micronutrient [26]. Intake levels below the lower limits were consider to justify inadequacy of the micronutrient. In cases where upper safety limits were provided by the EFSA, they were used to assess the risk of toxicity. Upper safety limits were provided for Vit E, Vit A, Vit D, total folic acid, Vit B6, calcium, magnesium, zinc, iodine. In addition, to estimate the nutrition adequacy of the diet, NAR was calculated for each micronutrient. To avoid overevaluation of MAR, sensitivity analysis was performed. Specifically, NARs indicating extremely high intake levels (NAR > 1.6) were excluded and MAR was recalculated. For the evaluation of iron deficiency, the probability approach should be used ideally, since losses also occur; however, the sample consists of pregnant women, so losses are minimized.

Further comparisons of each micronutrient intake and MAR were performed between smokers and nonsmokers, participants who reported planned versus unplanned pregnancy, overweight and obese versus normal weight participants (based on prepegnancy BMI).

Data were analyzed using the Statistical Package for Social Sciences (SPSS) software program (version 23, SPSS Inc., Chicago, IL).

Results

Overall, 1100 pregnant women were enrolled in the study.

Excluded cases comprised 25 women lacking fluency in Greek, 6 women aged below 20, and 12 women adhering to specific dietary plans. The mean age was 32.5 ± 4.9 years and the median prepregnancy BMI was 22.9 (20.9–26.4). Maternal characteristics are presented in Table 1.

Table 1. Maternal characteristics (N = 1100).

Characteristic	Result
Maternal age (years ± SD)	32.4 ± 4.9
Maternal age > 35 (N (%))	340 (30.9%)
BMI (kg/m^2)	22.9 (20.9–26.4)
Weight status^a
Overweight	371 (33.8%)
Obese	146 (13.2%)
Multiple pregnancy (N (%))	22 (2%)
Parity (N (%))
0	550 (50%)
1	420 (38.2%)
2	111 (10%)
3	17 (1.5%)
Smoking (N (%))	112 (10.2%)
Planned pregnancy (N (%))	934 (84.9%)
ART (N (%))	87 (7.9%)

Abbreviations. ART: Assisted reproductive technology; BMI: Body mass index; SD, Standard deviation.

^aAs per prepregnancy BMI.

The median (25th–75th percentile) or mean ± SD nutrient consumption of the participants, the corresponding reference values and the comparisons between them are presented in Table 2. Statistically significant differences were found between the DRVs and the mean intake levels of the participants in almost all micronutrients examined. Of note, iron was the only micronutrient in our sample that was not found to be consumed in statistically significant different amounts compared to AR (p = .10).

Table 2. Mean consumption of each micronutrient, NAR for each micronutrient and results of the comparison of the mean with the presented refence values.

	Reference value	Consumption total, N = 1100^a	NAR total, N = 1100
Biotin (μg)	AI 40 μg/d	19.7 (14.9–26.2)*	0.49 (0.37–0.66)
Calcium (mg)	AI 750 mg/d	698.4 (526.5–901.7)*	0.93 (0.69–1.19)
Copper (mg)	AI 1.5 mg/d	1.56 (1.32–1.87)*	1.04 (0.88–1.24)
Iodine (μg)	AI 200 μg/d	92.4 (74.7–110.9)*	0.46 (0.37–0.55)
Iron (mg)	AR 7 mg/d	6.78 (5.76–8.03)**	0.97 (0.82–1.15)
Magnesium (mg)	AI 300 mg/d	186.9 (159–221.9)*	0.62 (0.53–0.74-
Manganese (mg)	AI 3 mg/d	1.57 (1.17–2.22)*	0.52 (0.39–0.74)
Niacin (eq) (mg)	AR 10 mg/d	16.2 (13.5–19.4)*	2 (1.73–2.37)
Pantothenic acid (mg)	AI 5 mg/d	3 (2.46–3.63)*	0.60 (0.49–0.73)
Phosphorus (mg)	AI 550 mg/d	806.8 (644.9–984.2)*	1.46 (1.17–1.79)
Potassium (mg)	AI 3,500 mg/d	1764.8 (1468.5–2108.8)*	0.50 (0.42–0.60)
Sodium (mg)	SFA 2,000 mg/d	2015 (1594.3–2455.08)***	1 (0.79–1.23)
Total Folic acid (μg)	AI 400 μg/d	144.7 (119.1–174)*	0.24 (0.20–0.29)
Vitamin A (μg)	AR 540 μg/d	803.2 (604.2–975)*	1.49 (0.9–1.8)
Vitamin B1 (mg)	AR 1 mg/d	0.5 (0.4–0.62)*	1.16 (0.93–1.36)
Vitamin B12 (μg)	AI 4.5 μg/d	3.14 (2.34–4)*	0.70 (0.52–0.89)
Vitamin B2 (mg)	AR 1.5 mg/d	0.80 (0.61–1.05)*	0.54 (0.41–0.70)
Vitamin B6 (mg)	AR 1.5 mg/d	0.99 (0.82–1.17)*	0.66 (0.55–0.78)
Vitamin C (mg)	AR 80, AR*** 115 mg/d	82.3 (63.8–101.8)*	1 (0.80–1.27)
Vitamin D (μg)	AI 15 μg/d	0.94(0.54–1.51)*	0.07 (0.04–0.10)
Vitamin E (eq) (mg)	AI 11 mg/d	8.96(7.14–11.25)*	0.82 (0.64–1.02)
Zinc (mg)	AR 7.5 mg/d	8.19(6.95–9.65)*	1.09 (0.93–1.29)
MAR (all nutrients)	0.93 (93%) (0.69–1.05)
MAR excluding high intake	0.78 (78%) (0.65–0.88)

Parametric data are given in mean ± SD, nonparametric data are presented in median (25th–75th percentile).

Abbreviations. AR, Average requirement; AI, Adequate intake; NAR, Nutrient adequacy ratio; MAR, Mean adequacy ratio.

^aWilcoxon signed rank test, level of significance p < ≤ .05.

*p < .001, **p = .10, ***p = .03; AR***: vitamin C recommendations for smokers.

Table 2 presents calculated NAR for each of the nutrients examined. This ranged from 0.07 for vitamin D to 2 for niacin. This resulted to a MAR of 93% (or 78% if we do not include NAR > 1.5), meaning that 7% (or 22%) of women did not meet nutrient adequacy in total with the main three nutrients (other to vitamin D which is difficult to be obtained from diet) being folic acid, biotin, and iodine. When MAR was calculated by planned pregnancy or not, the proportion that met requirements were 93% and 92%, respectively. Comparison between them did not come to a significant result (p = .851).

When lower limits of intake levels were calculated by taking off 2 SD from the intake level of our sample from the AR or AI of each micronutrient, the percentage of the participants that were found to consume extremely low amounts of each vitamin or mineral was lower than 1%. When micronutrient consumption was related to the Upper Levels set by EFSA for safety (not available for all nutrients), a potential risk was found only for magnesium intake for 12.8% of the women.

Different patient subgroups were compared regarding micronutrient consumption. Data are presented in Table 3. Comparisons between subgroups regarding planned pregnancy did not result in significant outcomes.

Table 3. Results of the comparison of micronutrients’ NAR between different subgroups: aged ≤ 35 versus aged > 35, smokers versus nonsmokers and overweight and obese versus normal weight participants.

	Maternal age		Smoking		BMI
Nutrients	≤35 (n = 760, 69%)	>35 (n = 340, 30.9%)	Yes (n = 112, 10.2%)	No (n = 988, 89.8%)	Overweight (n = 371, 30.8%)	Obese (n = 146, 13.2%)
	The intake was higher among women ≤ 35	The intake was higher among women >35	The intake was higher among smokers	The intake was higher among nonsmokers	The intake was higher among overweight than normal weight	The intake was higher among obese than normal weight
Biotin		p = .001		p = .043	NS	NS
Calcium		p = .042	NS	NS	NS	p = .032
Copper	NS	NS	NS	NS	p = .008	p = .008
Iodine		p = .001	NS	NS	p = .001	p = .007
Magnesium		p = .009	NS	NS	NS	NS
Pantothenic Acid		p = .003	NS	NS	NS	NS
Potassium		p = .042	NS	NS	NS	NS
Phosphorus		p = .006	NS	NS	NS	NS
Total folic acid		p = .007	NS	NS	NS	NS
Vit A		p = .036	NS	NS	NS	NS
Vit B2	NS	NS	NS	NS	NS	p = .021
Vit B12	NS	NS	p = .002		NS	NS
Vit C		p = .047		p < .001	NS	NS
Zinc	NS	NS	p = .028		p = .005	NS

Abbreviations. NS, Nonsignificant; NAR, Nutrient adequacy ratio.

Mann-Whitney Test, level of significance p ≤ .05.

Discussion

This prospective epidemiological study provides a snapshot of the prepregnancy micronutrient intake status of Greek pregnant women. The aim of the study to describe the nutritional status of a representative sample of Greek women was achieved with the findings of the study revealing that the preconceptional nutrition of Greek women significantly deviates from the average intakes’ recommendations by EFSA in almost all micronutrients. Although our results could not justify inadequacy in the consumption of any micronutrient, as extremely low intake—below 2 SD from AR or AI—was observed in minor portion of our population, there are some findings that we should be concerned about. Vit D, total folic acid, potassium, biotin, manganese, magnesium, and iodine were found to be consumed in quite lower amounts than DRVs. Comparing our sample’s intake levels with upper limits suggested by the EFSA, magnesium was found to exceed safety limits in 12.8% of the participants, indicating possible toxicity for them. While the 12.8% of the sample exceeding recommended magnesium intake may not substantially impact the mean, this proportion remains significant and warrants consideration. The potential for magnesium intake levels to reach toxic thresholds in the limited sample size should not divert our attention from the crucial observation that the mean magnesium intake fell below the recommended DRVs. It is also important to underline that sodium intake levels seemed to exceed the recommended value and our calculations included only sodium consumed from foods without extra salt addition. Out of the 22 nutrients assessed, vitamin B₂, B₆, D, magnesium, potassium, pantothenic acid, biotin and total folic acid, manganese and iodine showed an adequacy ratio below 70% of AR (NAR < 0.7), showing possible deficiency for these nutrients. The MAR was calculated 0.93, 78% through sensitivity analysis. Although this seems to be satisfactory, we should not disregard the fact that does not came from balanced data, as there are serious deficiency indications for Vit D, folic acid, biotin, potassium, and iodine. These are important elements for the developing fetus and the healthy outcome of a pregnancy.

Most women in Greece are prescribed several micronutrients, such as folate, iodine, and Vit D, before or during pregnancy to improve maternal and perinatal outcomes. A review examining folic acid fortification’s use before pregnancy suggests that preconceptional folic acid supplementation or at least folate nutritional status evaluation is necessary [27]. Administering prenatal folic acid supplements has demonstrated favorable effects on the neurodevelopmental outcomes of offspring. This included enhanced intellectual development and a lower likelihood of exhibiting traits associated with autism, attention-deficit/hyperactivity disorder, behavioral issues, and language difficulties. Additionally, excessive folic acid supplementation during pregnancy did not lead to improved brain development in offspring. In fact, it may have a detrimental impact on their neurodevelopmental outcomes [28].

Adequate vitamin D status has been associated with lower preeclampsia risk [29]. Further benefits, as the reduction in eczema risk for the newborn have been addressed by higher vitamin D levels in cord blood [30]. A recent systematic review and meta-analysis [31] aimed to synthesize and critically appraise the literature for studies that examined the association between exposure to vitamin D status during pregnancy and the risk of congenital anomalies in the offspring concluded that vitamin D supplementation at doses of up to 4000 IU per day during pregnancy did not show significant differences in the incidence of congenital anomalies. However, the risk ratio in the meta-analysis tended to favor supplementation due to the effect few and small studies.

There is evidence demonstrating that even mild maternal iodine deficiency could affect child neurodevelopment [32]. One metanalysis including international data examined the prevalence of insufficient iodine intake [33] and found insufficient iodine intake in 53% of the sample. Another meta-analysis examined the prevalence of excessive iodine intake [34] in pregnancy and showed excessive iodine intake in 52% of the sample. A recent study [35] tried to conduct a thorough systematic review of existing evidence from meta-analyses. This was done to address areas of contention regarding the necessity of iodine supplementation during pregnancy and to offer guidance for clinical decision-making, even in regions with mild to moderate deficiency. The results of this study [35] suggested that although epidemiological meta-analyses show some association between iodine status and outcomes for mothers and neonates, intervention trial meta-analyses do not provide evidence of an effect of iodine supplementation in countries with mild deficiency. As a result of this lack of agreement, there is unexpectedly no clear consensus regarding the actual benefits of iodine supplementation during pregnancy and this may be explained by lack of straightforward evidence.

Serious health impairments have been only reported in extreme deficiency or adequacy in levels of vitamin A, B₁, B₂, B₆, and E [36]. The practice of supplementing with multivitamins during pregnancy has been widespread and has shown promising results. Nevertheless, relevant studies have yielded conflicting findings. One recent cohort study failed to demonstrate a preventive effect of multivitamin consumption during the periconceptional or postconceptional period on the risk of congenital heart defects in offspring [37]. Surpassing our expectations, in one study from China [38] maternal exposure to a multivitamin supplement, which not only included higher doses of folic acid (0.8 mg) but also vitamin A (1.2 mg), vitamin D (12.5 μg), iron (60 mg), and zinc (7.5 mg), was associated with a statistically significant increase in the risk of genitourinary defects and abnormal chromosomes. One plausible explanation is that the excessive accumulation of fat-soluble vitamins from the multivitamin might elevate the risk of certain subtypes of birth defects [39]. Multivitamin products available in China contain vitamin A, which has the potential to accumulate in the body at higher concentrations. Exposure to elevated levels of vitamin A could potentially interfere with fetal palatogenesis by disrupting cell proliferation, as evidenced in animal studies related to neural tube closure, organ development, and limb development [40]. While this study did not measure the maternal exposure’s specific vitamin A levels, limiting the ability to establish a direct causal link between multivitamins and birth defects, it is advisable to exercise caution when recommending the use of multivitamins to expectant mothers in the early stages of pregnancy.

Our results indicate that sodium intake exceeded the reference value. Evidence from Denmark [41] has shown that lower sodium intake during pregnancy is related to a lower risk of hypertensive disorders during pregnancy. One study from Greece on general population showed that salt intake was, on average, double than the current WHO recommendations, confirming that sodium intake is exceeded and we should be concerned about possible implications [42]. Regarding magnesium, the calculated adequacy ratio was 0.65, showing adequacy for our population. However, a remarkable 12.4% of the participants, is in danger of toxicity, as magnesium levels overwhelm the upper limit suggested for the nutrient by the EFSA. Magnesium is an important element for pregnancy as supporting scientific evidence reveals; oral supplementation of magnesium may reduce the risk of preeclampsia, which may be more remarkable in high-risk pregnant women. Healthcare professionals should be extremely cautious to balance between possible hazards and benefits regarding magnesium supplementation in pregnancy. Targeted nutrition guidance could cover the needed intake, in order to avoid further supplementation for the entire population, but in high-risk pregnant women fortification may be the proper choice to avoid complications.

Published data on the effect of maternal nutrition status on perinatal outcomes have identified potential preconceptional risk factors [43,44]. However, a recent comprehensive systematic review and meta-analysis examining the effect of periconceptional interventions on birth and maternal outcomes, highlighted that there is currently not enough high-quality evidence to clearly understand the effect of a range of possible preconceptional interventions on birth and maternal outcomes; nutritional (primarily micronutrient or food supplementation), health (general preconception health, early adverse pregnancy outcome prevention, noncommunicable disease and infectious disease prevention and management), and social interventions (reproductive planning) were assessed [45]. A similar study from the USA [46] among a large, representative cohort of nulliparous individuals regarding preconceptional diet showed that women of younger age, higher booking BMI, lower educational attainment, periconceptional smoking, and below the federal poverty threshold were more prone to lower quality nutritional habits. Also, poorer diet quality was associated with increased odds of receiving a gestational diabetes diagnosis. Further, well-designed research is required in this issue.

A systematic review showed that blood concentration of folate was lower among pregnant women who smoked than those who were not; the same association was generally seen in cord blood [47]. Although our study did not examine blood concentration of folate, no significant differences were observed between smokers and nonsmokers concerning folate consumption.

Another study examining the association between maternal age and nutritional status found that women aged ≤ 19 years old reported higher intake of foods that are typically viewed as snack items (including crisps, chocolate, biscuits and cake) and moderate intake of processed meat [48]. Moreover, one UK study found an association between dietary pattern and maternal age with healthier nutritional patterns being associated with increasing age [49]; this is in accordance to our findings. A study conducted in New Zealand similarly also found a positive association between increasing maternal age and healthy dietary patterns [50].

This study has certain limitations. First, although the analysis was based on a representative, quite large sample of Greek pregnant women, this could be even bigger. To this direction, our study will continue developing in the following years. Moreover, the lack of relevant data from Greece led to comparison with European reference intake levels; thus, our results may not be as specific as expected. However, there was an effort to reach to safe conclusions and use the most relevant comparable data based on the most similar population data available. Another limitation of this study is the utilization of data obtained from a food frequency questionnaire, which falls short of being considered the gold standard. The selection of this method was motivated by its convenience in gathering information. Finally, our results may have been affected by recall bias. Furthermore, the present study has several strengths. To our knowledge, this is the largest epidemiological study examining preconceptional nutrition in Greece. The data collection process was in accordance to methodological principles. Additionally, a systematic method was used to analyze available data and interpret the results.

According to the results of our study, the low public health awareness of preconceptional nutrition, as a strategy for disease prevention, needs to be readdressed at both individual and population levels. The lack of proper information with regards to an appropriate nutritional status is an important issue for both fetal and maternal health. Moreover, the long-term consequences of harmful or unhealthy nutritional habits have been well-studied [51,52]. Thus, these findings may provide further insights regarding nutritional guidance in the preconceptional and early pregnancy periods and highlight the need for the adoption of preventive strategies. Physicians could focus on reproductive-aged women consulting on the importance of proper body preparation for possible pregnancy. Specifically, the importance of elements such us iodine, vit D and folate in the preconception period could be an advice. Data from the present study will probably affect the policy makers on the public health preventive strategies that probably need to be adopted for the preconceptional period.

Authors’ contribution

Conceptualization: A.A. and A.T.; Methodology: A.A., A.T., E.T., and V.C. Software: A.T. and N.P.; Formal Analysis: A.A., A.T., and I.T.; Investigation: A.A, I.K., L.C., and V.C.; Writing—Original Draft Preparation: A.A.; Writing—Review and Editing: I.T., T.D., E.M.; Visualization: T.D. and E.M.; Supervision: T.D., E.M., and M.C.; Project Administration: M.C.

Abbreviations
AI	=	Adequate intake
AR	=	Average requirement
ART	=	Assisted reproductive technology
BMI	=	Body mass index
CVD	=	Cardiovascular danger
DHA	=	Docosahexaenoic acid
DRVs	=	Dietary reference values
EFSA	=	European Food Safety Authority
FFQ	=	Food frequency questionnaire
IQR	=	Interquartile range
MAR	=	Mean adequacy ratio
NAR	=	Nutrient adequacy ratio
PRI	=	Population reference intake
RI	=	Reference intake
SD	=	Standard deviation
UK	=	United Kingdom
WIC	=	Special Supplemental Nutrition Program for Women, Infants, and Children

Disclosure statement

The authors declare no conflict of interest.

Data availability statement

Due to ethical restrictions supporting data is not available.

Additional information

Funding

This research received no external funding.