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Maternal profile according to Mediterranean diet adherence and small for gestational age and preterm newborn outcomes

Published online by Cambridge University Press:  29 April 2020

Isabel Peraita-Costa
Affiliation:
Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Burjassot, Valencia46100, Spain CIBER in Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid28029, Spain
Agustín Llopis-González
Affiliation:
Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Burjassot, Valencia46100, Spain CIBER in Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid28029, Spain
Alfredo Perales-Marín
Affiliation:
Department of Obstetrics, La Fe University Hospital, Valencia, Valencia46026, Spain
Vicente Diago
Affiliation:
Department of Obstetrics, La Fe University Hospital, Valencia, Valencia46026, Spain
Jose Miguel Soriano
Affiliation:
Food & Health Lab, University of Valencia, Paterna, Valencia46980, Spain Joint Research Unit on Endocrinology, Nutrition and Clinical Dietetics, Area of Infection, Inflammation and Chronicity, University of Valencia-Health Research Institute La Fe, Valencia, Valencia46026, Spain
Agustín Llopis-Morales
Affiliation:
Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Burjassot, Valencia46100, Spain
María Morales-Suárez-Varela*
Affiliation:
Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Burjassot, Valencia46100, Spain CIBER in Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid28029, Spain
*
*Corresponding author: Email [email protected]
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Abstract

Objective:

The objective was to evaluate maternal Mediterranean diet (MD) pattern adherence during pregnancy and its association with small for gestational age (SGA) and preterm birth. A secondary objective of the current study was to describe the sociodemographic, lifestyle and obstetric profile of the mothers studied as well as the most relevant paternal and newborn characteristics.

Design:

The current study is a two-phase retrospective population-based study of maternal dietary habits during pregnancy and their effect on newborn size and prematurity. The descriptive first phase examined maternal dietary habits during pregnancy along with the maternal sociodemographic, lifestyle and obstetric profile in a cross-sectional period study. In the second phase, newborn outcomes were evaluated in a nested case–control study. Adherence to MD during pregnancy was measured with the Spanish version of Kidmed index.

Setting:

Obstetrics ward of the La Fe Hospital in Valencia.

Participants:

All mother–child pairs admitted after delivery during a 12-month period starting from January 2018 were assessed for eligibility. A total of 1118 provided complete outcome data after signing informed consent.

Results:

14·5 % met the criteria of poor adherence (PA); 34·8 %, medium adherence (MA); and 50·7 %, optimal adherence (OA). Medium adherence to MD was associated in the adjusted scenarios with a higher risk of giving birth to a preterm newborn. No association was found between MD adherence and SGA.

Conclusions:

Early intervention programmes geared towards pregnant women, where women were aided in reaching OA to MD, might reduce the risk of preterm newborn.

Type
Research paper
Copyright
© The Authors 2020

Maternal nutrition is considered one of the most important and modifiable lifestyle factors influencing fetal growth and development during pregnancy, as it plays an important role in providing the necessary energy and nutrients for fetal growth(Reference Timmermans, Steegers-Theunissen and Vujkovic1Reference Nnam3). Inadequate maternal nutrition could be a factor associated with preterm birth and low birth weight(Reference Triunfo and Lanzone4). Adequate maternal nutritional status is essential to the health of the mother and the child, as it influences fetal nutrition and endocrine status during pregnancy(Reference Mariscal-Arcas, Rivas and Monteagudo5).

Despite its popularity within the scientific community and the population at large, there is no single Mediterranean diet (MD) concept(Reference Serra-Majem, Ribas and Ngo6). MD is a dietary pattern characterised by increased consumption of mainly season-fresh unprocessed foods, including plant foods such as fruits and vegetables, pulses, nuts, whole-grain cereals and bread(Reference Willett, Sacks and Trichopoulou7Reference Serra-Majem, Ribas, Serra-Majem, Aranceta and Mataix12). Meat consumption is limited to a few times a month, and there is a higher consumption of lamb, rabbit poultry and fish, while eggs are consumed few days a week(Reference Willett, Sacks and Trichopoulou7Reference Serra-Majem, Ribas, Serra-Majem, Aranceta and Mataix12). Dairy (mainly derived from sheep or goat milk) consumption in the form of cheese and yoghurt is abundant, but milk consumption is lower than the present levels(Reference Willett, Sacks and Trichopoulou7Reference Serra-Majem, Ribas, Serra-Majem, Aranceta and Mataix12). Low consumption of animal fats, sugars and salt and moderate wine consumption are also characteristics of the traditional MD pattern(Reference Willett, Sacks and Trichopoulou7Reference Serra-Majem, Ribas, Serra-Majem, Aranceta and Mataix12). Olive oil remains a distinctive dietary element of MD, and it may be the only food common to all Mediterranean countries and peoples(Reference Serra-Majem, Ribas, Serra-Majem, Aranceta and Mataix12). The American Dietary Guidelines highlight the positive effect of MD on health and recommend it because it is a source of essential nutrients and useful in the prevention of diseases(13).

The effects of adherence to MD during the gestational period have been previously described(Reference Peraita-Costa, Llopis-González and Perales-Marín14) and associated with lower weight gain during pregnancy(Reference Mariscal-Arcas, Rivas and Monteagudo5,Reference Hillesund, Bere and Haugen15,Reference Silva-del Valle, Sanchez-Villegas and Serra-Majem16) and lower risk of miscarriage(Reference Gaskins, Rich-Edwards and Hauser17Reference Xu, Wu and Yang19), preterm birth(Reference Mariscal-Arcas, Rivas and Monteagudo5,Reference Saunders, Guldner and Costet20Reference Chatzi, Rifas-Shiman and Georgiou24) , hypertensive disorders(Reference Schoenaker, Soedamah-Muthu and Callaway25) or gestational diabetes(Reference Karamanos, Thanopoulou and Anastasiou26,Reference He, Yuan and Chen27) . Adherence to MD has also been associated with a lower risk of congenital malformations(Reference Vujkovic, Steegers and Looman28,Reference Botto, Krikov and Carmichael29) , intra-uterine growth restriction(Reference Hillesund, Bere and Haugen15,Reference Saunders, Guldner and Costet20,Reference Mikkelsen, Osterdal and Knudsen21,Reference Helmo, Alves and Moreira23,Reference Chatzi, Rifas-Shiman and Georgiou24,Reference Chatzi, Mendez and Garcia30Reference Brantsaeter, Birgisdottir and Meltzer32) and long-term effects such as better bone quality(Reference Heppe, Medina-Gomez and Hofman33,Reference Yin, Dwyer and Riley34) , a lower risk of atopy(Reference de Batlle, Garcia-Aymerich and Barraza-Villarreal35,Reference Netting, Middleton and Makrides36) and/or abdominal obesity in children(Reference Saunders, Guldner and Costet20,Reference Mikkelsen, Osterdal and Knudsen21,Reference Helmo, Alves and Moreira23,Reference Chatzi, Rifas-Shiman and Georgiou24,Reference Fernandez-Barres, Romaguera and Valvi37) .

Preterm birth is one of the leading causes of neonatal mortality and morbidity, accounting for nearly 35 % of all neonatal deaths in the United States(Reference Mathews, MacDorman and Thoma38), and can have serious long-term consequences(Reference Allen39Reference Sun, Mohay and O’Callaghan42). The incidence of preterm birth has remained close to 11 % and with an uncertain aetiology(Reference Martin, Hamilton and Osterman43). Maternal nutrition during pregnancy, as mentioned previously, has an important role in providing the necessary nutrients for fetal growth(Reference Blumfield, Hure and MacDonald-Wicks44). Maternal dietary nutrient intake has not been studied extensively in relation to preterm birth(Reference Carmichael, Yang and Shaw45,Reference Bobiński, Mikulska and Mojska46) . However, previous studies have suggested that certain maternal nutrient intakes may be associated with prematurity as well as low birth weight(Reference Imdad and Bhutta47,Reference Ota, Mori and Middleton48) .

Birth weight is considered the main determinant of perinatal morbidity and mortality(Reference Grisaru-Granovsky, Reichman and Lerner-Geva49), both in the short and long term(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Chatzi, Mendez and Garcia30) . The concept of small-for-gestational-age (SGA) infants takes into account birth weight, gestational age and sex(Reference Schlaudecker, Munoz and Bardají50). Maternal risk factors associated with SGA can be sociodemographic variables, chronic diseases, risk factors during pregnancy and maternal lifestyle risk factors(Reference McCowan and Horgan51). Some factors that are known to increase the risk of SGA are short stature, low weight, Indian or Asian ethnicity, nulliparity, mothers born SGA, cigarette smoking, cocaine use, maternal history of chronic hypertension, renal disease, anti-phospholipid syndrome and malaria(Reference McCowan and Horgan51). Maternal smoking is the single most important risk factor for SGA in developed countries(Reference McCowan and Horgan51). It is significantly correlated with SGA, and while it affects the fetus during all stages of pregnancy, the most significant effect on the birth weight of offspring occurs during late pregnancy, especially in the case of mothers who are heavy smokers (>8–10 cigarettes per d)(Reference Ko, Tsai and Chu52). An inverse correlation between birth weight and number of cigarettes smoked per day has also been found(Reference Ko, Tsai and Chu52). Maternal nutrition is recognised as one of the main determinants of fetal growth(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Chatzi, Mendez and Garcia30) and determines the metabolic patterns of both mother and child(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Chatzi, Mendez and Garcia30,Reference Delnord, Blondel and Zeitlin53Reference Murphy, Stettler and Smith55) . Restricted fetal growth is associated with an increased risk of childhood morbidity and chronic diseases during adulthood such as respiratory infections, diabetes mellitus, obesity, CVD and psychiatric disorders(Reference Bruno, Faconti and Taddei56,Reference Werner, Savitz and Janevic57) .

Traditionally, nutritional assessment in pregnant women is performed by analysing caloric intake and intake of specific foods along with micro- and macronutrients(Reference Lee, Talegawkar and Merialdi58,Reference de Castro, Freitas Vilela and de Oliveira59) . Most studies published to date that evaluated diet during pregnancy have focused on the association between individual foods or nutrients and fetal growth(Reference Chong, Chia and Colega60). The foods or nutrients associated with a lower risk of SGA and prematurity are diverse depending on the study considered(Reference Grieger, Grzeskowiak and Clifton61Reference Thompson, Wall and Becroft65). However, nutrition is a multidimensional exposure, and foods, micro- and macronutrients are not consumed in isolation(Reference Kourlaba and Panagiotakos66). For this reason, the effect of diet as a whole or as a dietary pattern should be evaluated. Interactions between foods and nutrients could be overlooked if maternal diet is not assessed as a whole(Reference Sanchez-Villegas, Brito and Doreste-Alonso67), hence there is a growing interest in the study of dietary patterns during pregnancy(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Saunders, Guldner and Costet20,Reference de Castro, Freitas Vilela and de Oliveira59) . Studies focusing on dietary patterns, unlike those focusing on single foods and nutrients, examined the effects of a combination of foods and allowed for interactions between nutrients(Reference Newby and Tucker68,Reference Hu69) . Given this, dietary pattern studies may provide more useful information than an isolated food or nutrient studies.

The main objective of the current study was to evaluate maternal MD adherence during pregnancy and its association with SGA and preterm birth outcomes and their impact. A secondary objective of the current study was to describe the sociodemographic, lifestyle and obstetric profiles of the mothers studied as well as the most relevant paternal and newborn characteristics according to diet adherence.

Materials and methods

Study design

The current study is a two-phase retrospective population-based study of maternal dietary habits during pregnancy and their effects on newborn size and prematurity. The descriptive first phase examined maternal dietary habits during pregnancy along with the maternal sociodemographic, lifestyle and obstetric profiles in a cross-sectional period study. In the second phase, newborn outcomes were evaluated in a nested case–control study.

In the descriptive phase, the characteristics of both parents, clinical and obstetric history of the mother, data related to gestation and delivery, and data on the state of the newborn were analysed. In the analytical phase, the data collected was assessed in relation to mothers’ adherence to MD and the possible association with prematurity and newborn weight.

Level of adherence to MD was the exposure variable, which was assessed using the sixteen-item Kidmed questionnaire(Reference Serra-Majem, Ribas and Ngo6). Women were classified into three groups, depending on Kidmex scores: ≥8 optimal (OA); 4–7 medium (MA) and ≤3 poor (PA) adherence(Reference Serra-Majem, Ribas and Ngo6). Information corresponding to these three groups was obtained before classification, ensuring the homogeneity of the sample and its representativeness as much as possible.

Study population

All mother–child pairs admitted after delivery at the obstetrics ward of the La Fe Hospital in Valencia during a 12-month period starting from January 2018 were assessed for eligibility (n 5208). Mother–child pairs were excluded in a first filter if they did not belong to the health coverage area of this hospital; access to complete clinical records of pregnancy and birth was not available; the mother had a diagnosis of a chronic disease and/or she was not available for interview. Other factors such as multiple births were no reason for exclusion, and the mothers presenting these factors were included. These and other possible confounding factors were taken into account during data analysis. A total of 1446 mothers were subsequently invited to participate. Signed consent was not given by 217 women, and a further 111 women were excluded due to the data corresponding to the newborn were not made available to be consulted and/or the mother’s responses were inconsistent or incomplete. At the end, 1118 provided complete outcome data after signing consent (a participation rate of 77·3 %). Figure 1 details the subject selection process.

Fig. 1 Selection of subjects

Information collected

Data were collected via a review of mothers’ and newborns’ clinical records and complemented by a later direct and personal interview with the mothers. Medical students trained by dietitians conducted the interviews, and the questionnaires were revised by these dietitians. Information on mother’s age, country of origin, education, marital status, employment status during pregnancy, maternal physical activity, maternal diseases, parity and mothers’ cigarette exposure, drug use, alcohol use, coffee intake, caffeine drinks, prenatal vitamins use, dairy products intake during breakfast and daily dairy intake was collected. Weight and height of both parents were taken from clinical records, and BMI was calculated for both parents. Obstetric and neonatal data were obtained from clinical records.

Adherence assessment

Nutritional assessment was carried out using the Spanish version of Kidmed index, which was developed to quickly and easily assess the degree of adherence to MD(Reference Serra-Majem, Ribas and Ngo6). The development of Kidmed index was based on the principles sustaining MD patterns as well as those that undermine it(Reference Serra-Majem, Ribas and Ngo6). The index ranged from 0 to 12 and was based on a sixteen-question test that could be self-administered or conducted during an interview(Reference Serra-Majem, Ribas and Ngo6). Foods positively associated with the MD pattern, such as vegetables, legumes, fruits, nuts, cereal, fish, dairy products and olive oil, were assigned a value of +1, whereas foods with a negative association such as sweets and fast foods were assigned a value of –1 (Fig. 2). The Kidmed test has been successfully used in numerous previous studies(Reference Serra-Majem, Ribas and Ngo6,Reference Peraita-Costa, Llopis-González and Perales-Marín14,Reference Navarro-González, López-Nicolás and Rodríguez-Tadeo70Reference Dura Trave and Castroviejo Gandarias75) and is a simple and quick way to assess MD adherence insituations where the use of several day-long food journals or extensive FFQ may not be appropriate or practical, as is the present case.

Fig. 2 Kidmed test to assess the Mediterranean diet quality(Reference Newby and Tucker68)

Parental data

Data on lifestyle, dietary habits, sociodemographic and anthropometric characteristics of both parents were collected. The value used for pre-pregnancy weight was the last record available before pregnancy confirmation, and all were dated within the 1 year previous to pregnancy. Total maternal weight gain was taken from clinical records. The interview included a section dedicated to the level of physical activity in leisure time, and another to determine the level of activity during working hours. The first section considered four possible levels of activity, to each of which a score was attributed, from 0 to 3 as follows:

  • 0 – no exercise

  • 1 – light physical activity (e.g. walking or gentle gymnastics at least one time per week)

  • 2 – moderate physical activity (e.g. gymnastics, athletics, swimming, cycling at least two times per week)

  • 3 – sports training (at least three times per week)

In relation to physical activity during working hours, similar levels were considered with the following scores:

  • 0 – sitting most of the day

  • 1 – standing most of the day, without making large displacements or efforts

  • 2 – walking, carrying some weight, making frequent trips

  • 3 – performing tasks that require a great physical effort

Total physical activity was calculated as the sum of the halves of the scores awarded in both sections. However, for those women who did not work during pregnancy, the free-time exercise accounted for the total of the exercise performed.

Clinical and obstetric historical data of the mother, including data differentiating between primigravida and multigravida women and primiparous and multiparous women, were collected. Information on the number of previous miscarriages was also collected.

Newborn’s data

Information relating to newborns was collected both via interviews and from a review of clinical records. Data included sex and anthropometric values such as weight, height and cephalic perimeter. Newborns were classified as SGA when birth weight was below the 10th percentile(Reference Schlaudecker, Munoz and Bardají50,Reference Sellen76) compared with that expected for the same sex and gestational age according to the Spanish standards(Reference Carrascosa Lezcano, Ferrández Longás and Yeste Fernández77,Reference Carrascosa Lezcano, Fernández García and Fernández Ramos78) , or as LGA when birth weight was above the 90th percentile(Reference Sellen76). Percentiles were calculated using the Gestational Calculator v2017.4 developed by BCNatal (Centre Medicina Maternofetal i Neonatal de Barcelona of the Hospital Clínic i Provincial de Barcelona), which takes into consideration birth weight, gestational age, sex and if the pregnancy single or multiple. Information on birth complications and admission to a neonatal care unit or a neonatal intensive care unit was collected. Apgar scores, heart rate, muscle tone, reflexes and skin colour were recorded(Reference Apgar79Reference Casey, McIntire and Leveno81) along with the results of a gasometric analysis (pH, PO2, PCO2) on arterial and venous blood of the umbilical cord, which was systematically performed by the participating hospital.

Statistical analysis

Adherence to MD was the primary exposure of interest. For the descriptive part of the study, the outcome of interest was the sociodemographic, lifestyle and obstetric profiles of the mothers and the characteristics of the newborn with special attention being paid to newborn size or prematurity. Normality of distribution was assessed using the Kolmogrov–Smirnov and Shapiro–Wilk tests for the sample as a whole and within each adherence group individually. For quantitative variables, an ANOVA was used for the comparison of different variables in the levels of adherence to maternal MD, while the χ 2 test was used for qualitative variables. With adherence to MD as the independent variable, an analysis to determine the presence of statistically significant differences among the study variables was performed.

With the results obtained in the descriptive phase, a nested case–control study was carried out in a second phase to evaluate SGA v. normal for gestational age and preterm v. term birth depending on the level of adherence to MD (OA v. MA and OA v. PA). The association between adherence to MD and the outcome of interest taking confounders into account was evaluated using multivariate logistic regression models. Apart from crude OR, four adjusted models – one that includes adjustments for all the variables identified as statistically significantly different between the adherence groups and others with different combinations of these variables identified as potential confounding factors – were created. OR, adjusted OR (aOR) and 95 % CI were calculated assuming a 0·05 significance level.

To determine the relationship between adherence to MD and the risk of giving birth to an SGA or preterm newborn, OR was calculated using binary logistic regression models. A conditional multiple logistic regression model was used to obtain aOR in order to account for the effects of several potential confounders simultaneously, using different models in relation with the characteristics identified as significantly different between the adherence groups. The CI applied in all cases was 95 %.

All analyses were performed using IBM SPSS Statistics 22 software, considering P < 0·05 as significance level.

Results

Lifestyle and sociodemographic characteristics of the participants are shown in Table 1. Table 1 presents the degree of adherence to MD among the 1118 pregnant women included in the current study: 14·5 % (n 162) met the criteria of PA, 34·8 % (n 389) met the criteria of MA and 50·7 % (n 567) met the criteria of OA. The overall mean Kidmed score was 7·25 ± 2·40 with a median of 8 and a non-normal distribution displaced to higher values. The mean score of the OA group was 9·18 ± 0·98 with a median of 9 and a range between 8 and 12 and a non-normal distribution displaced to lower values. The mean score of the MA group was 5·81 ± 0·81 with a median of 6 and a range between 4 and 7 and a non-normal distribution displaced to higher values. The mean score of the PA group was 2·13 ± 1·19 with a median of 3 and a range between –2 and 3 and a non-normal distribution displaced to lower values.

Table 1 Maternal sociodemographic data and dietary habits (n 1118 pregnant women)

* P-value obtained by ANOVA (P < 0·05) for quantitative variables, by χ 2 test (P < 0·05) for qualitative variables.

Caffeinated drinks NOT including coffee such as soft drinks/soda/pop/sugary drinks/fizzy drinks and energy drinks.

(2S)-2-((4-(((2-amino-4-hydroxypteridin-6-yl)methyl)amino)phenyl)formamido)pentanedioic acid.

§ Ferrous fumarate, ferrous gluconate, ferrous succinate and ferrous sulphate.

In the PA group, the women were significantly younger with 46·3 % being under 30 years compared with 28·2 % in the MA group and 18·3 % in the OA group. There were significant differences in marital status and nationality. Those with better adherence were more likely to be married. In the OA group, women of African origin were overrepresented compared with the other two groups. Participants with PA were significantly less educated, 38·2 % of PA had no or primary studies v. 19·5 % in the MA group and 11·8 % in the OA group. Pregnant women with PA were significantly less physically active, less employed and more likely to smoke before and during pregnancy. No differences were observed in maternal drug and alcohol use during pregnancy.

Table 1 also shows the maternal dietary habits according to their adherence to MD. No significant differences were observed for the intake of coffee, tea or chocolate. Caffeinated drinks were consumed more by the PA group. Significant differences were found in folic acid supplement use and Fe supplement use, observing a lower intake in the PA group. No significant differences appeared in the use of prenatal vitamins.

In the current study, statistically significant differences were found for the following maternal anthropometric values: pre-pregnancy weight, pre-pregnancy BMI, weight at delivery, BMI at delivery, but not for weight gained during pregnancy. No differences were found in paternal anthropometric values (Table 2).

Table 2 Parental anthropometric data

* P-value obtained by ANOVA (P < 0·05) for quantitative variables, by χ 2 test (P < 0·05) for qualitative variables.

There were no statistically significant differences in maternal obstetric factors or most characteristics of newborns (Table 3). Differences were found for newborn sex with proportionally more male babies in the MA group and large for gestational age (LGA). 45·1 % of births within the PA group corresponded to male children, while 56·7 % of newborns were male in the MA group and 50·9 % in the OA group. In regard to LGA newborns, the highest percentage was seen in the MA group with 10·3 %, followed by the OA group with 9·2 % and finally the PA group with 6·2 %.

Table 3 Obstetric and neonatal data

SGA = birth weight < 10th percentile; AGA = 10th percentile ≤ birth weight ≤ 90th percentile; LGA = birth weight > 90th percentile.

* P-value obtained by ANOVA (P < 0·05) for quantitative variables, by χ 2 test (P < 0·05) for qualitative variables.

As seen in Table 4, the risk of having SGA newborns for mothers with poor or medium adherence to MD compared with those with OA was non-significant in any of the adjusted models.

Table 4 Risk of small-for-gestational-age or preterm infants associated with the level of adherence to Mediterranean diet

ORc, crude odds ratio; ORa, adjusted odds ratio.

* Adjusted for maternal age, education, physical activity, employment, smoking before and during pregnancy, and BMI before and at the end of pregnancy.

Adjusted for maternal age, education, physical activity, employment, smoking before and during pregnancy, BMI before and at the end of pregnancy, dietary supplements, folic acid supplements and Fe supplements.

Adjusted for newborn sex, maternal age, education, physical activity, employment, smoking before and during pregnancy, and BMI before and at the end of pregnancy.

§ Adjusted for newborn sex, maternal age, education, physical activity, employment, smoking before and during pregnancy, BMI before and at the end of pregnancy, dietary supplements, folic acid supplements and Fe supplements.

Reference category.

Meanwhile, the risk of having a preterm newborn in mothers with medium adherence to MD compared with those with OA was significant in both adjusted models. It had an aOR of 2·28 (95 % CI 1·10, 4·72) when adjusted for newborn sex, maternal age, education, physical activity, employment, smoking before and during pregnancy, and BMI before and at the end of pregnancy and an aOR of 3·04 (95 % CI 1·35, 6·87) when adjusted for newborn sex, maternal age, education, physical activity, employment, smoking before and during pregnancy, BMI before and at the end of pregnancy, dietary supplements, folic acid supplementation and Fe supplementation.

Discussion

Diet during pregnancy or foetal nutrition is an important health determinant for the newborn, and inadequate maternal nutrition has been linked to adverse pregnancy outcomes and chronic childhood and adult diseases(Reference Shapiro, Kaar and Crume82,Reference Godfrey and Barker83) . Therefore, a varied and balanced diet is essential to ensure infant wellbeing. In the current study, 49·3 % of pregnant women in our area followed an unbalanced diet, specifically a low adherence to MD, which is the traditional and reference dietary pattern in the geographic area studied. The loss of a traditional MD pattern is associated with increased risks of childhood and adulthood diseases(Reference Trichopoulou, Costacou and Bamia9,Reference Kastorini, Milionis and Esposito84,Reference Estruch, Martínez-González and Corella85) . This lack of adequate adherence to MD has been identified to increase the risk of preterm birth. Therefore, optimal adherence to the MD pattern could be considered a potential modifiable protective factor against preterm birth. The current study suggests that perhaps a nutritional intervention programme to improve adherence to MD might reduce the risk of preterm birth associated with poor adherence to MD. Given that it is one of the few modifiable factors in prematurity, further research on the benefits of improving maternal diet should be carried out.

A study reported on the level of adherence among pregnant women in Spain and Greece using another method of classification(Reference Chatzi, Mendez and Garcia30) with results (~44 % PA) similar to the current study. Another study carried out in Spain showed that 36·1 %(Reference Chatzi, Torrent and Romieu86) of mothers followed a low-quality MD during pregnancy when assessed using the MD score(Reference Trichopoulou, Kouris-Blazos and Wahlqvist87). Similarly, another study found that 43·2 % of women from southern Spain did not follow an MD(Reference Mariscal-Arcas, Lopez-Martinez and Granada88).

The finding that younger single women with a lower level of education show worse adherence to MD ratifies the results of numerous previous studies(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Peraita-Costa, Llopis-González and Perales-Marín14,Reference Hillesund, Bere and Haugen15,Reference de Castro, Freitas Vilela and de Oliveira59,Reference Rodriguez-Bernal, Rebagliato and Iniguez64,Reference Leon-Munoz, Guallar-Castillon and Graciani89Reference Zazpe, Estruch and Toledo91) . A possible explanation to this consistent finding is that women who fall under this profile are less aware of the effect of their diet on their own health and that of their child.

Educational level and employment status can both be indicators of the socioeconomic status, which has been found to be associated with dietary pattern adherence(Reference de Castro, Freitas Vilela and de Oliveira59,Reference Olmedo-Requena, Fernández and Prieto90,Reference Alvarez Alvarez, Aguinaga Ontoso and Marin Fernandez92) . Given that higher-quality products tend to be more expensive, it seems normal that women of lower socioeconomic status would resort to cheaper, lower-quality products, and this could explain the difference found in the current study regarding employment status(Reference Alvarez Alvarez, Aguinaga Ontoso and Marin Fernandez92).

An unhealthy diet has been associated with unhealthy habits such as smoking and a sedentary lifestyle(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Hillesund, Bere and Haugen15,Reference Leon-Munoz, Guallar-Castillon and Graciani89,Reference Olmedo-Requena, Fernández and Prieto90,Reference Hu, Toledo and Diez-Espino93) . In the current study, the PA group had a lower level of physical activity and a higher proportion of smokers both before and during pregnancy, corroborating the findings of previous studies(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Hillesund, Bere and Haugen15,Reference Leon-Munoz, Guallar-Castillon and Graciani89,Reference Hu, Toledo and Diez-Espino93) .

During pregnancy, certain dietary changes are recommended(Reference Okubo, Miyake and Tanaka63,Reference Lawson, LeMasters and Wilson94Reference Chen, Bell and Browne98) . The WHO guideline on caffeine intake during pregnancy recommends an intake <300 mg/d(99), which was followed by the majority of women in the current study and is in agreement with previous findings(Reference Hillesund, Bere and Haugen15,Reference Chen, Bell and Browne98) . However, there is a significant difference in the intake of caffeinated drinks among the sample, and therefore it is important to monitor this trend due to the high caffeine and sugar content of these drinks(Reference Vartanian, Schwartz and Brownell100).

Micronutrient deficiencies are increasingly common, especially among the women of childbearing age(Reference Mariscal-Arcas, Rivas and Monteagudo5,Reference Black, Victora and Walker101) , and may be exacerbated during gestation by increased nutritional requirements(Reference Haider and Bhutta102,Reference Rodríguez, Méndez and Martínez103) . Some studies have reported a greater contribution of some of these micronutrients (vitamins C, E, B, folate, Mg, Ca, Fe, vitamin D or Zn) associated with MD(Reference Mikkelsen, Osterdal and Knudsen21,Reference Rodriguez-Bernal, Rebagliato and Iniguez64,Reference Feart, Alles and Merle104,Reference Castro-Quezada, Roman-Vinas and Serra-Majem105) .

In a recent review, Haider & Bhutta(Reference Haider and Bhutta102) found the possible benefits of using multivitamins, including folic acid and Fe, as supplementation could perhaps compensate dietary deficiencies. Notably in the current study, women with non-OA consumed significantly more general dietary supplements than women with OA. This seems to suggest that women with a non-OA to MD tend to compensate their poor diet quality with the use of dietary supplements. However, the results showed that the use of supplements had no beneficial effect in this case. When it comes to other types of supplements, women with non-OA were significantly less likely to consume specific Fe supplements and even less likely to consume folic acid supplements. An increase in the use of folic acid and Fe supplements within these groups might positively affect the mothers and newborns.

The only significant differences in parental anthropometric data were found for maternal weight and BMI both before pregnancy and at delivery. The PA group had higher weights and BMI before pregnancy and at delivery. While no differences were observed, it must be noted that the average paternal BMI values would fall into the overweight range in all groups.

The association between parity and adherence to a healthy dietary pattern is unclear as some studies have found worse adherence among primiparous women(Reference Hillesund, Bere and Haugen15,Reference Abreu, Santos and Moreira106) , while other studies associate greater parity to a lower adherence to a healthy dietary pattern(Reference de Castro, Freitas Vilela and de Oliveira59,Reference Northstone, Emmett and Rogers107) . In the sample studied, there was no significant difference in adherence in relation to gravidity or parity. It would be logical, however, to expect multiparous women to follow healthier diets during pregnancy due to the knowledge gained from previous pregnancies. Also, previous childbirths could contribute to a greater adherence to the Mediterranean pattern since more attention might be given to the diet(Reference Alvarez Alvarez, Aguinaga Ontoso and Marin Fernandez92).

As regards the characteristics of newborns, significant differences were found in the sex of newborns and for LGA. Sex of the newborn did not follow a set pattern according to the adherence level. Women with better adherence were noticeably more likely to have an LGA baby. This association between diet quality and size of newborn corroborates the results of previous studies(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Rodriguez-Bernal, Rebagliato and Iniguez64,Reference Ferland and O’Brien108) . The mean scores for 1- and 5-min Apgar test were adequate in the sample studied. In this sense, there are no studies with consistent results relating the Apgar test and the maternal diet during gestation(Reference Gresham, Byles and Bisquera109). The results of gasometric cord blood analysis, which provides an objective measure of foetal condition prior to birth(Reference Alegria and Cerda110), of all adherence groups were within normal ranges, and no studies have been found with which to compare our results.

Previous studies have found that adherence to MD protects against SGA(Reference Peraita-Costa, Llopis-González and Perales-Marín14,Reference Mendez, Plana and Guxens111) , and Mediterranean dietary patterns have been associated with higher birth weights and a lower risk of SGA offspring(Reference Poon, Yeung and Boghossian112). However, one study could not establish a significant relation between maternal diet and the risk of SGA, low birth weight and inadequate infant growth(Reference Schenker, Yang and Perez113).

In the current study, the adjusted models, taking into account the variables identified as statistically significantly different among the adherence groups, found no association between MA or PA and SGA. This lack of association between non-OA and SGA is nuanced and, therefore, must be interpreted carefully. The use of a model adjusted for all variables identified as statistically significantly different among the adherence groups for a sample like ours might introduce errors in results. Dietary patterns are usually accompanied by many other factors that may be important sources of confounding and even more so due to possible synergistic or antagonistic effects(Reference Timmermans, Steegers-Theunissen and Vujkovic1,Reference Hillesund, Bere and Haugen15,Reference Leon-Munoz, Guallar-Castillon and Graciani89,Reference Hu, Toledo and Diez-Espino93,Reference Martinez-Carrasco, Brugarolas and Martinez-Poveda114) . It may be advisable to avoid stating that there is no association between non-OA to MD and SGA newborns given the sample size and evidence from previous studies to the contrary.

Preterm birth is an underlying factor in about half of all deaths among normally formed infants, and survivors often suffer from permanent handicaps(Reference Pless115). Further research is needed as very few causal factors have been identified. In the current study, there were no significant differences in the duration of pregnancy or prematurity, which contrasts with the results of other studies in which adherence to MD was a protective factor against preterm birth(Reference Mariscal-Arcas, Rivas and Monteagudo5,Reference Mikkelsen, Osterdal and Knudsen21) . For the population studied, mothers with OA curiously had a higher percentage of preterm newborns. This could be explained, in part, by older child-bearing age, resorting more to assisted reproduction techniques and having a higher proportion of twins. In the current study, the risk of having a preterm newborn in mothers with medium adherence to MD was significant in both the adjusted models. Meanwhile, none of the models showed a risk for preterm birth within the PA group. Previous studies examining the MD have reached contradictory conclusions regarding prematurity.

A prospective cohort study carried out in Denmark found a decrease in the risk of early preterm birth related to adherence to MD during pregnancy(Reference Mikkelsen, Osterdal and Knudsen21). In the TIMOUN study, adherence to MD was associated with a lower risk of preterm birth only in overweight and obese women(Reference Saunders, Guldner and Costet20). Another study found that preterm risk tended to be lower by around 29 % in the MD group, while the risk of early preterm birth was 72 % lower and statistically significant(Reference Mikkelsen, Osterdal and Knudsen21). An intervention study showed that MD reduced the incidence of preterm birth(Reference Khoury, Henriksen and Christophersen22). Another study supports recent evidence that increasing regular consumption of healthy food is more important than reducing the consumption of unhealthy food(Reference Englund-Ogge, Brantsaeter and Sengpiel116).In a Norwegian cohort study, no association was found between adherence to MD and preterm birth(Reference Haugen, Meltzer and Brantsæter117). In the National Birth Defects Prevention Study, no association with preterm birth was found(Reference Carmichael, Yang and Shaw45). The conflicting study results may be a consequence of variations across studies in the definitions of MD(Reference Martinez-Gonzalez, Holgado and Gibney118,Reference Noah and Truswell119) . Also, the times of diet assessment and data collection vary, which might contribute to the inconsistency of findings. While a comparison with the current study may not be perfect given the differences in the definition of MD and other methodological differences among the studies, it is important to highlight that a loss of healthy eating pattern and its possible effects on newborns is a widespread issue.

Strengths and limitations

A homogeneous selection method within a single hospital is one of the strengths of the current study. All the data were collected by identically trained professionals using the same questionnaire and later contrasted and/or completed with clinical records. Another strength is the evaluation of a diet as a whole by the degree of adherence, which will provide a greater ease in managing dietary patterns in clinical practice(Reference Hillesund, Bere and Haugen15,Reference Sanchez-Villegas, Brito and Doreste-Alonso67) .

It should be noted that the sample size hindered appropriate control for confounders. It is advisable to increase the sample size in future studies to obtain more consistent and reliable results. Maternal and paternal SGA is an important possible confounder when studying SGA outcomes of newborns, which was not considered in the current study as a majority of parents were unable to provide this information. Collection of data after birth could ignore variations in dietary habits during gestation(Reference Saunders, Guldner and Costet20). However, a previous study has found no significant differences in dietary patterns across different periods of pregnancy(Reference Cuco, Fernandez-Ballart and Sala120). Also, data were obtained retrospectively and might have been affected by recall bias.

Previous studies have shown that frequency-of-use questionnaires are appropriate to estimate intake during pregnancy(Reference Silva-del Valle, Sanchez-Villegas and Serra-Majem16,Reference Chatzi, Mendez and Garcia30) . Several studies on pregnant women have adapted the general population indices for the exclusion of alcohol use(Reference de Castro, Freitas Vilela and de Oliveira59,Reference Rodriguez-Bernal, Rebagliato and Iniguez64,Reference Abreu, Santos and Moreira106) . The Kidmed index used here in pregnant women was validated for a population between 2 and 24 years, and meat (red/white) and alcohol are not included(Reference Serra-Majem, Ribas and Ngo6,Reference Štefan, Prosoli and Juranko74) . It may not be as effective as other diet questionnaires in obtaining an accurate picture of adherence to MD for adults given these exclusions. The Kidmed index does not assess intake quantitatively, which could be a problem since previous studies have found that it may be more important to increase the variety of healthy foods than to reduce the regular consumption of unhealthy foods(Reference Michels and Wolk121,Reference Zazpe, Sánchez-Tainta and Toledo122) . However, it was used in an attempt to make dietary assessment as simple as possible for the persons being assessed.

Conclusion

In the population studied, optimal adherence to the MD pattern among pregnant women was about 50 %. Non-OA to MD was associated with a higher risk of a preterm newborn. Optimal adherence to the MD pattern might be a protective factor against preterm newborns. The use of dietary supplements during pregnancy does not combat the negative effects of a poor-quality diet, and their use cannot replace a balanced and diverse diet. Early intervention programmes geared towards pregnant women to raise awareness of a healthy lifestyle and balanced diet would be beneficial. An appropriate nutritional intervention to aid women in reaching OA to MD could reduce the risk attributable to preterm newborn. As other factors responsible for prematurity are not modifiable, it is important to act on those that are modifiable, such as diet, to reduce the risks of preterm birth as much as possible. Further studies are needed to better understand the mechanisms of the effects of diet on SGA newborns, prematurity and the most relevant window of exposure. A further follow-up of this cohort will allow more accurate determination of the effects of adherence to MD and whether these effects persist in older children.

Acknowledgements

Acknowledgements: The authors would like to thank all the mothers who participated in the current study. Financial support: This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Conflict of interest statement: None. Authorship: conceptualisation: I.P.-C., A.L.-G., A.P.M. and M.M.-S.-V.; data curation: A.P.M., J.M.S. and A.L.-M.; formal analysis: I.P.-C., A.L.-G., A.P.M. and M.M.-S.-V.; investigation: A.P.M., J.M.S. and A.L.-M.; methodology: I.P.-C., A.L.-G., A.L.-M. and M.M.-S.-V.; project administration: M.M.-S.-V.; resources: A.P.M. and V.D.; supervision: M.M.-S.-V.; writing – original draft: I.P.-C., A.L.-G., V.D. and M.M.-S.-V.; writing – review and editing: I.P.-C., A.L.-G., A.P.M., V.D., J.M.S., A.L.-M. and M.M.-S.-V. Ethical standards disclosure: This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving study participants were approved by the Ethics Committee of La Fe Hospital (CEIC 2014/0116). All participants gave their informed consent, which included a confidentiality agreement according to the Protection of Data of Official Nature Organic Law 15/1999 of December 13.

References

Timmermans, S, Steegers-Theunissen, RP, Vujkovic, M et al. (2012) The Mediterranean diet and fetal size parameters: the Generation R Study. Br J Nutr 108 13991409.10.1017/S000711451100691XCrossRefGoogle ScholarPubMed
Wu, G, Bazer, FW, Cudd, TA et al. (2004) Maternal nutrition and fetal development. J Nutr 134, 21692172.CrossRefGoogle ScholarPubMed
Nnam, N (2015) Improving maternal nutrition for better pregnancy outcomes. Proc Nutr Soc 74, 454459.CrossRefGoogle ScholarPubMed
Triunfo, S & Lanzone, A (2015) Impact of maternal under nutrition on obstetric outcomes. J Endocrinol Invest 38, 3138.CrossRefGoogle ScholarPubMed
Mariscal-Arcas, M, Rivas, A, Monteagudo, C et al. (2009) Proposal of a Mediterranean diet index for pregnant women. Br J Nutr 102, 744749.CrossRefGoogle ScholarPubMed
Serra-Majem, L, Ribas, L, Ngo, J et al. (2004) Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents. Public Health Nutr 7, 931935.CrossRefGoogle ScholarPubMed
Willett, WC, Sacks, F, Trichopoulou, A et al. (1995) Mediterranean diet pyramid: a cultural model for healthy eating. Am J Clin Nutr 61, Suppl. 6, 1402S1406S.CrossRefGoogle ScholarPubMed
Panagiotakos, DB, Pitsavos, C & Stefanadis, C (2006) Dietary patterns: a Mediterranean diet score and its relation to clinical and biological markers of cardiovascular disease risk. Nutr Metab Cardiovasc Dis 16, 559568.CrossRefGoogle ScholarPubMed
Trichopoulou, A, Costacou, T, Bamia, C et al. (2003) Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med 348, 25992608.CrossRefGoogle Scholar
Machowetz, A, Poulsen, HE, Gruendel, S et al. (2007) Effect of olive oils on biomarkers of oxidative DNA stress in Northern and Southern Europeans. FASEB J 21, 4552.CrossRefGoogle ScholarPubMed
Trichopoulou, A & Lagiou, P (1997) Healthy traditional Mediterranean diet: an expression of culture, history, and lifestyle. Nutr Rev 55, 383389.CrossRefGoogle Scholar
Serra-Majem, L & Ribas, L (1995) Hábitos alimentarios y consumo dealimentos en España. Dieta mediterránea (Eating habits and food consumption in Spain. Mediterranean diet.). In Nutrición y Salud Pública. Métodos, Bases Científicas y Aplicaciones (Nutrition and Public Health. Methods, Scientific Bases and Applications), pp. 303310 [Serra-Majem, L, Aranceta, J & Mataix, J, editor]. Barcelona: Masson.Google Scholar
US Department of Health and Human Services, US Department of Agriculture (2015) 2015–2020 Dietary Guidelines for Americans. Washington, DC: US Department of Health and Human Services and US Department of Agriculture. https://health.gov/sites/default/files/2019-09/2015-2020_Dietary_Guidelines.pdf (accessed February 2019).Google Scholar
Peraita-Costa, I, Llopis-González, A, Perales-Marín, A et al. (2018) A retrospective cross-sectional population-based study on prenatal levels of adherence to the Mediterranean diet: maternal profile and effects on the newborn. Int J Environ Res Public Health 15, 1530.CrossRefGoogle Scholar
Hillesund, ER, Bere, E, Haugen, M et al. (2014) Development of a New Nordic diet score and its association with gestational weight gain and fetal growth – a study performed in the Norwegian Mother and Child Cohort Study (MoBa). Public Health Nutr 17, 19091918.CrossRefGoogle Scholar
Silva-del Valle, MA, Sanchez-Villegas, A & Serra-Majem, L (2013) Association between the adherence to the Mediterranean diet and overweight and obesity in pregnant women in Gran Canaria. Nutr Hosp 28, 654659.Google ScholarPubMed
Gaskins, AJ, Rich-Edwards, JW, Hauser, R et al. (2014) Prepregnancy dietary patterns and risk of pregnancy loss. Am J Clin Nutr 100, 11661172.CrossRefGoogle ScholarPubMed
Di Cintio, E, Parazzini, F, Chatenoud, L et al. (2001) Dietary factors and risk of spontaneous abortion. Eur J Obstet Gynecol Reprod Biol 95, 132136.CrossRefGoogle ScholarPubMed
Xu, G, Wu, Y, Yang, L et al. (2014) Risk factors for early miscarriage among Chinese: a hospital-based case–control study. Fertil Steril 101, 16631670.CrossRefGoogle ScholarPubMed
Saunders, L, Guldner, L, Costet, N et al. (2014) Effect of a Mediterranean diet during pregnancy on fetal growth and preterm delivery: results from a French Caribbean Mother-Child Cohort Study (TIMOUN). Paediatr Perinat Epidemiol 28, 235244.CrossRefGoogle Scholar
Mikkelsen, TB, Osterdal, ML, Knudsen, VK et al. (2008) Association between a Mediterranean-type diet and risk of preterm birth among Danish women: a prospective cohort study. Acta Obstet Gynecol Scand 87, 325330.CrossRefGoogle ScholarPubMed
Khoury, J, Henriksen, T, Christophersen, B et al. (2005) Effect of a cholesterol-lowering diet on maternal, cord, and neonatal lipids, and pregnancy outcome: a randomized clinical trial. Am J Obstet Gynecol 193, 12921301.CrossRefGoogle ScholarPubMed
Helmo, FR, Alves, EAR, Moreira, RAA et al. (2018) Intrauterine infection, immune system and premature birth. J Matern Fetal Neonatal Med 31, 12271233.CrossRefGoogle ScholarPubMed
Chatzi, L, Rifas-Shiman, S, Georgiou, V et al. (2017) Adherence to the Mediterranean diet during pregnancy and offspring adiposity and cardiometabolic traits in childhood. Pediatr Obes 12, 4756.CrossRefGoogle ScholarPubMed
Schoenaker, DA, Soedamah-Muthu, SS, Callaway, LK et al. (2015) Prepregnancy dietary patterns and risk of developing hypertensive disorders of pregnancy: results from the Australian Longitudinal Study on Women’s Health. Am J Clin Nutr 102, 94101.CrossRefGoogle ScholarPubMed
Karamanos, B, Thanopoulou, A, Anastasiou, E et al. (2014) Relation of the Mediterranean diet with the incidence of gestational diabetes. Eur J Clin Nutr 68, 813.CrossRefGoogle ScholarPubMed
He, JR, Yuan, MY, Chen, NN et al. (2015) Maternal dietary patterns and gestational diabetes mellitus: a large prospective cohort study in China. Br J Nutr 113, 12921300.CrossRefGoogle ScholarPubMed
Vujkovic, M, Steegers, EA, Looman, CW et al. (2009) The maternal Mediterranean dietary pattern is associated with a reduced risk of spina bifida in the offspring. BJOG 116, 408415.CrossRefGoogle ScholarPubMed
Botto, LD, Krikov, S, Carmichael, SL et al. (2016) Lower rate of selected congenital heart defects with better maternal diet quality: a population-based study. Arch Dis Child Fetal Neonatal Ed 101, F43F49.CrossRefGoogle ScholarPubMed
Chatzi, L, Mendez, M, Garcia, R et al. (2012) Mediterranean diet adherence during pregnancy and fetal growth: INMA (Spain) and RHEA (Greece) mother-child cohort studies. Br J Nutr 107, 135145.CrossRefGoogle ScholarPubMed
Olsen, SF, Halldorsson, TI, Willett, WC et al. (2007) Milk consumption during pregnancy is associated with increased infant size at birth: prospective cohort study. Am J Clin Nutr 86, 11041110.CrossRefGoogle ScholarPubMed
Brantsaeter, AL, Birgisdottir, BE, Meltzer, HM et al. (2012) Maternal seafood consumption and infant birth weight, length and head circumference in the Norwegian Mother and Child Cohort Study. Br J Nutr 107, 436444.CrossRefGoogle ScholarPubMed
Heppe, DH, Medina-Gomez, C, Hofman, A et al. (2013) Maternal first-trimester diet and childhood bone mass: the Generation R Study. Am J Clin Nutr 98, 224232.CrossRefGoogle ScholarPubMed
Yin, J, Dwyer, T, Riley, M et al. (2010) The association between maternal diet during pregnancy and bone mass of the children at age 16. Eur J Clin Nutr 64, 131137.CrossRefGoogle ScholarPubMed
de Batlle, J, Garcia-Aymerich, J, Barraza-Villarreal, A et al. (2008) Mediterranean diet is associated with reduced asthma and rhinitis in Mexican children. Allergy 63, 13101316.CrossRefGoogle ScholarPubMed
Netting, MJ, Middleton, PF & Makrides, M (2014) Does maternal diet during pregnancy and lactation affect outcomes in offspring? A systematic review of food-based approaches. Nutrition 30, 12251241.CrossRefGoogle ScholarPubMed
Fernandez-Barres, S, Romaguera, D, Valvi, D et al. (2016) Mediterranean dietary pattern in pregnant women and offspring risk of overweight and abdominal obesity in early childhood: the INMA birth cohort study. Pediatr Obes 11, 491499.CrossRefGoogle ScholarPubMed
Mathews, T, MacDorman, MF & Thoma, ME (2015) Infant mortality statistics from the 2013 period linked birth/infant death data set. Natl Vital Stat Rep 64, 130.Google Scholar
Allen, MC (2008) Neurodevelopmental outcomes of preterm infants. Curr Opin Neurol 21, 123128.CrossRefGoogle ScholarPubMed
Sammallahti, S, Lahti, M, Pyhälä, R et al. (2015) Infant growth after preterm birth and mental health in young adulthood. PLoS ONE 10, e0137092.CrossRefGoogle ScholarPubMed
Ong, KK, Kennedy, K, Castañeda‐Gutiérrez, E et al. (2015) Postnatal growth in preterm infants and later health outcomes: a systematic review. Acta Paediatr 104, 974986.CrossRefGoogle ScholarPubMed
Sun, J, Mohay, H & O’Callaghan, M (2009) A comparison of executive function in very preterm and term infants at 8 months corrected age. Early Hum Dev 85, 225230.CrossRefGoogle ScholarPubMed
Martin, J, Hamilton, B, Osterman, M et al. (2013) Births: Final data for 2012. Natl Vital Stat Rep 62, 168.Google ScholarPubMed
Blumfield, ML, Hure, AJ, MacDonald-Wicks, LK et al. (2012) Dietary balance during pregnancy is associated with fetal adiposity and fat distribution. Am J Clin Nutr 96, 10321041.CrossRefGoogle ScholarPubMed
Carmichael, SL, Yang, W, Shaw, GM et al. (2013) Maternal dietary nutrient intake and risk of preterm delivery. Am J Perinatol 30, 579588.Google ScholarPubMed
Bobiński, R, Mikulska, M, Mojska, H et al. (2015) Assessment of the diet components of pregnant women as predictors of risk of preterm birth and born baby with low birth weight. Ginekol Pol 86, 292299.10.17772/gp/2076CrossRefGoogle ScholarPubMed
Imdad, A & Bhutta, ZA (2012) Routine iron/folate supplementation during pregnancy: effect on maternal anaemia and birth outcomes. Paediatr Perinat Epidemiol 26, 168177.CrossRefGoogle ScholarPubMed
Ota, E, Mori, R, Middleton, P et al. (2015) Zinc supplementation for improving pregnancy and infant outcome. Cochrane Database Syst Rev issue 6, CD000230.CrossRefGoogle ScholarPubMed
Grisaru-Granovsky, S, Reichman, B, Lerner-Geva, L et al. (2012) Mortality and morbidity in preterm small-for-gestational-age infants: a population-based study. Am J Obstet Gynecol 206, 150.e1150.e7.CrossRefGoogle ScholarPubMed
Schlaudecker, EP, Munoz, FM, Bardají, A et al. (2017) Small for gestational age: case definition & guidelines for data collection, analysis, and presentation of maternal immunisation safety data. Vaccine 35, 65186528.CrossRefGoogle ScholarPubMed
McCowan, L & Horgan, RP (2009) Risk factors for small for gestational age infants. BJOG 23, 779793.Google ScholarPubMed
Ko, T, Tsai, L, Chu, L et al. (2014) Parental smoking during pregnancy and its association with low birth weight, small for gestational age, and preterm birth offspring: a birth cohort study. Pediatr Neonatol 55, 2027.CrossRefGoogle ScholarPubMed
Delnord, M, Blondel, B & Zeitlin, J (2015) What contributes to disparities in the preterm birth rate in European countries? Curr Opin Obstet Gynecol 27, 133142.CrossRefGoogle ScholarPubMed
Morrison, JL & Regnault, TR (2016) Nutrition in pregnancy: optimising maternal diet and fetal adaptations to altered nutrient supply. Nutrients 8, 342346.CrossRefGoogle ScholarPubMed
Murphy, MM, Stettler, N, Smith, KM et al. (2014) Associations of consumption of fruits and vegetables during pregnancy with infant birth weight or small for gestational age births: a systematic review of the literature. Int J Womens Health 6, 899912.CrossRefGoogle ScholarPubMed
Bruno, RM, Faconti, L, Taddei, S et al. (2015) Birth weight and arterial hypertension. Curr Opin Cardiol 30, 398402.CrossRefGoogle ScholarPubMed
Werner, EF, Savitz, DA, Janevic, TM et al. (2012) Mode of delivery and neonatal outcomes in preterm, small-for-gestational-age newborns. Obstet Gynecol 120, 560564.CrossRefGoogle ScholarPubMed
Lee, SE, Talegawkar, SA, Merialdi, M et al. (2013) Dietary intakes of women during pregnancy in low- and middle-income countries. Public Health Nutr 16, 13401353.CrossRefGoogle ScholarPubMed
de Castro, MB, Freitas Vilela, AA, de Oliveira, AS et al. (2016) Sociodemographic characteristics determine dietary pattern adherence during pregnancy. Public Health Nutr 19, 12451251.CrossRefGoogle ScholarPubMed
Chong, MF, Chia, A, Colega, M et al. (2015) Maternal protein intake during pregnancy is not associated with offspring birth weight in a multiethnic Asian population. J Nutr 145, 13031310.Google ScholarPubMed
Grieger, JA, Grzeskowiak, LE & Clifton, VL (2014) Preconception dietary patterns in human pregnancies are associated with preterm delivery–3. J Nutr 144, 10751080.CrossRefGoogle Scholar
Lu, M, Chen, Q, He, J et al. (2016) Maternal dietary patterns and fetal growth: a large prospective cohort study in China. Nutrients 8, 257.CrossRefGoogle ScholarPubMed
Okubo, H, Miyake, Y, Tanaka, K et al. (2015) Maternal total caffeine intake, mainly from Japanese and Chinese tea, during pregnancy was associated with risk of preterm birth: the Osaka Maternal and Child Health Study. Nutr Res 35, 309316.CrossRefGoogle ScholarPubMed
Rodriguez-Bernal, CL, Rebagliato, M, Iniguez, C et al. (2010) Diet quality in early pregnancy and its effects on fetal growth outcomes: the Infancia y Medio Ambiente (Childhood and Environment) Mother and Child Cohort Study in Spain. Am J Clin Nutr 91, 16591666.CrossRefGoogle Scholar
Thompson, JM, Wall, C, Becroft, DM et al. (2010) Maternal dietary patterns in pregnancy and the association with small-for-gestational-age infants. Br J Nutr 103, 16651673.CrossRefGoogle ScholarPubMed
Kourlaba, G & Panagiotakos, DB (2009) Dietary quality indices and human health: a review. Maturitas 62, 18.CrossRefGoogle ScholarPubMed
Sanchez-Villegas, A, Brito, N, Doreste-Alonso, J et al. (2010) Methodological aspects of the study of dietary patterns during pregnancy and maternal and infant health outcomes. A systematic review. Matern Child Nutr 6, Suppl. 2, 100111.CrossRefGoogle Scholar
Newby, P & Tucker, KL (2004) Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev 62, 177203.CrossRefGoogle ScholarPubMed
Hu, FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 39.CrossRefGoogle ScholarPubMed
Navarro-González, I, López-Nicolás, R, Rodríguez-Tadeo, A et al. (2014) Adherence to the Mediterranean diet by nursing students of Murcia (Spain). Nutr Hosp 30, 165172.Google Scholar
San Mauro-Martin, I, Onrubia-Gonzalez-De la Aleja, J, Garicano-Vilar, E et al. (2016) Analysis of the nutritional status and body composition of persons with intellectual disability. Rev Neurol 62, 493501.Google ScholarPubMed
Rodriguez, F, Palma, X, Romo, A et al. (2013) Eating habits, physical activity and socioeconomic level in university students of Chile. Nutr Hosp 28, 447455.Google Scholar
Alacid, F, Vaquero-Cristobal, R, Sanchez-Pato, A et al. (2014) Habit based consumptions in the Mediterranean diet and the relationship with anthropometric parameters in young female kayakers. Nutr Hosp 29, 121127.Google ScholarPubMed
Štefan, L, Prosoli, R, Juranko, D et al. (2017) The reliability of the Mediterranean diet quality index (KIDMED) questionnaire. Nutrients 9, 419.CrossRefGoogle ScholarPubMed
Dura Trave, T & Castroviejo Gandarias, A (2011) Adherence to a Mediterranean diet in a college population. Nutr Hosp 26, 602608.Google Scholar
Sellen, D (1995) Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. WHO Technical Report Series no. 854, pp. 452. Geneva: WHO. Swiss Fr 71.00.Google Scholar
Carrascosa Lezcano, A, Ferrández Longás, A, Yeste Fernández, D et al. (2008) Estudio transversal español de crecimiento 2008. Parte I: valores de peso y longitud en recién nacidos de 26–42 semanas de edad gestacional (Spanish cross-sectional study of growth 2008. Part I: weight and length values in newborns aged 26–42 weeks of gestation). Anal Pediatr 68, 544551.10.1157/13123286CrossRefGoogle Scholar
Carrascosa Lezcano, A, Fernández García, J, Fernández Ramos, C et al. (2008) Estudio transversal español de crecimiento 2008. Parte II: valores de talla, peso e índice de masa corporal desde el nacimiento a la talla adulta (Spanish cross-sectional study of growth 2008. Part II: height, weight, and body mass index values from birth to adult height). Anal Pediatr 68, 552569.CrossRefGoogle Scholar
Apgar, V (1953) A proposal for a new method of evaluation of the newborn infant. Originally published in July , volume 32, pages 250–259. Anesth Analg 120, 10561059.CrossRefGoogle Scholar
Finster, M & Wood, M (2005) The Apgar score has survived the test of time. Anesthesiology 102, 855857.CrossRefGoogle ScholarPubMed
Casey, BM, McIntire, DD & Leveno, KJ (2001) The continuing value of the Apgar score for the assessment of newborn infants. N Engl J Med 344, 467471.CrossRefGoogle ScholarPubMed
Shapiro, AL, Kaar, JL, Crume, TL et al. (2016) Maternal diet quality in pregnancy and neonatal adiposity: the Healthy Start Study. Int J Obes 40, 1056.CrossRefGoogle ScholarPubMed
Godfrey, KM & Barker, DJ (2000) Fetal nutrition and adult disease. Am J Clin Nutr 71, 1344S1352S.CrossRefGoogle ScholarPubMed
Kastorini, C, Milionis, HJ, Esposito, K et al. (2011) The effect of Mediterranean diet on metabolic syndrome and its components: a meta-analysis of 50 studies and 534,906 individuals. J Am Coll Cardiol 57, 12991313.CrossRefGoogle ScholarPubMed
Estruch, R, Martínez-González, MA, Corella, D et al. (2006) Effects of a Mediterranean-style diet on cardiovascular risk factors: a randomized trial. Ann Intern Med 145, 111.CrossRefGoogle ScholarPubMed
Chatzi, L, Torrent, M, Romieu, I et al. (2008) Mediterranean diet in pregnancy is protective for wheeze and atopy in childhood. Thorax 63, 507513.10.1136/thx.2007.081745CrossRefGoogle ScholarPubMed
Trichopoulou, A, Kouris-Blazos, A, Wahlqvist, ML et al. (1995) Diet and overall survival in elderly people. BMJ 311, 14571460.CrossRefGoogle ScholarPubMed
Mariscal-Arcas, M, Lopez-Martinez, C, Granada, A et al. (2010) Organochlorine pesticides in umbilical cord blood serum of women from Southern Spain and adherence to the Mediterranean diet. Food Chem Toxicol 48, 13111315.CrossRefGoogle ScholarPubMed
Leon-Munoz, LM, Guallar-Castillon, P, Graciani, A et al. (2012) Adherence to the Mediterranean diet pattern has declined in Spanish adults. J Nutr 142, 18431850.CrossRefGoogle ScholarPubMed
Olmedo-Requena, R, Fernández, JG, Prieto, CA et al. (2014) Factors associated with a low adherence to a Mediterranean diet pattern in healthy Spanish women before pregnancy. Public Health Nutr 17, 648656.CrossRefGoogle ScholarPubMed
Zazpe, I, Estruch, R, Toledo, E et al. (2010) Predictors of adherence to a Mediterranean-type diet in the PREDIMED trial. Eur J Nutr 49, 9199.CrossRefGoogle ScholarPubMed
Alvarez Alvarez, I, Aguinaga Ontoso, I, Marin Fernandez, B et al. (2015) Cross-sectional study of factors influencing adherence to the Mediterranean diet in pregnancy. Nutr Hosp 31, 18451852.Google ScholarPubMed
Hu, EA, Toledo, E, Diez-Espino, J et al. (2013) Lifestyles and risk factors associated with adherence to the Mediterranean diet: a baseline assessment of the PREDIMED trial. PLoS ONE 8, e60166.CrossRefGoogle ScholarPubMed
Lawson, CC, LeMasters, GK & Wilson, KA (2004) Changes in caffeine consumption as a signal of pregnancy. Reprod Toxicol 18, 625633.CrossRefGoogle ScholarPubMed
Sengpiel, V, Elind, E, Bacelis, J et al. (2013) Maternal caffeine intake during pregnancy is associated with birth weight but not with gestational length: results from a large prospective observational cohort study. BMC Med 11, 42.CrossRefGoogle Scholar
Bech, BH, Obel, C, Henriksen, TB et al. (2007) Effect of reducing caffeine intake on birth weight and length of gestation: randomised controlled trial. BMJ 334, 409.CrossRefGoogle ScholarPubMed
Hollins Martin, C (2014) Higher coffee intake in pregnancy linked to prolonged gestation, and higher caffeine intake linked with babies being small for gestational age. Evid Based Nurs 17, 106.CrossRefGoogle ScholarPubMed
Chen, L, Bell, EM, Browne, ML et al. (2014) Exploring maternal patterns of dietary caffeine consumption before conception and during pregnancy. Matern Child Health J 18, 24462455.CrossRefGoogle ScholarPubMed
World Health Organization (2002) The World Health Report 2002: Reducing Risks, Promoting Healthy Life. World Health Organization.Google Scholar
Vartanian, LR, Schwartz, MB & Brownell, KD (2007) Effects of soft drink consumption on nutrition and health: a systematic review and meta-analysis. Am J Public Health 97, 667675.CrossRefGoogle ScholarPubMed
Black, RE, Victora, CG, Walker, SP et al. (2013) Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382, 427451.CrossRefGoogle ScholarPubMed
Haider, BA & Bhutta, ZA (2015) Multiple-micronutrient supplementation for women during pregnancy. Cochrane Database Syst Rev issue 11, CD004905.CrossRefGoogle ScholarPubMed
Rodríguez, ML, Méndez, JS, Martínez, MS et al. (2010) Suplementos en embarazadas: controversias, evidencias y recomendaciones (Supplements in pregnant women: controversies, evidence, and recommendations). Inf Terapéutica del SNS 34, 117128.Google Scholar
Feart, C, Alles, B, Merle, B et al. (2012) Adherence to a Mediterranean diet and energy, macro-, and micronutrient intakes in older persons. J Physiol Biochem 68, 691700.CrossRefGoogle ScholarPubMed
Castro-Quezada, I, Roman-Vinas, B & Serra-Majem, L (2014) The Mediterranean diet and nutritional adequacy: a review. Nutrients 6, 231248.CrossRefGoogle ScholarPubMed
Abreu, S, Santos, PC, Moreira, P et al. (2014) Predictors of adherence to the Mediterranean diet from the first to the second trimester of pregnancy. Nutr Hosp 31, 14031412.Google ScholarPubMed
Northstone, K, Emmett, P & Rogers, I (2008) Dietary patterns in pregnancy and associations with socio-demographic and lifestyle factors. Eur J Clin Nutr 62, 471479.CrossRefGoogle ScholarPubMed
Ferland, S & O’Brien, HT (2003) Maternal dietary intake and pregnancy outcome. J Reprod Med 48, 8694.Google ScholarPubMed
Gresham, E, Byles, JE, Bisquera, A et al. (2014) Effects of dietary interventions on neonatal and infant outcomes: a systematic review and meta-analysis. Am J Clin Nutr 100, 12981321.CrossRefGoogle ScholarPubMed
Alegria, X & Cerda, M (2009) Gases en cordón umbilical (Umbilical cord gases). Rev Obstet Ginecol – Hosp Santiago Oriente Dr. Luis Tisné Brousse 4, 7881.Google Scholar
Mendez, MA, Plana, E, Guxens, M et al. (2010) Seafood consumption in pregnancy and infant size at birth: results from a prospective Spanish cohort. J Epidemiol Community Health 64, 216222.CrossRefGoogle ScholarPubMed
Poon, AK, Yeung, E, Boghossian, N et al. (2013) Maternal dietary patterns during third trimester in association with birthweight characteristics and early infant growth. Scientifica 2013, 786409.CrossRefGoogle ScholarPubMed
Schenker, S, Yang, Y, Perez, A et al. (1998) Antioxidant transport by the human placenta. Clin Nutr 17, 159167.CrossRefGoogle ScholarPubMed
Martinez-Carrasco, L, Brugarolas, M & Martinez-Poveda, A (2004) Análisis de las tendencias actuales en la alimentación de los españoles: posibilidades de difusión de la dieta mediterránea (Analysis of current trends in the diet of Spaniards: possibilities of spreading the Mediterranean diet). REEAP, 151164.Google Scholar
Pless, IB (1994) The Epidemiology of Childhood Disorders. Oxford University Press on Demand.Google Scholar
Englund-Ogge, L, Brantsaeter, AL, Sengpiel, V et al. (2014) Maternal dietary patterns and preterm delivery: results from large prospective cohort study. BMJ 348, g1446.CrossRefGoogle ScholarPubMed
Haugen, M, Meltzer, HM, Brantsæter, AL et al. (2008) Mediterranean-type diet and risk of preterm birth among women in the Norwegian Mother and Child Cohort Study (MoBa): a prospective cohort study. Acta Obstet Gynecol Scand 87, 319324.CrossRefGoogle ScholarPubMed
Martinez-Gonzalez, M, Holgado, B, Gibney, M et al. (2000) Definitions of healthy eating in Spain as compared to other European Member States. Eur J Epidemiol 16, 557564.CrossRefGoogle ScholarPubMed
Noah, A & Truswell, AS (2001) There are many Mediterranean diets. Asia Pac J Clin Nutr 10, 29.CrossRefGoogle ScholarPubMed
Cuco, G, Fernandez-Ballart, J, Sala, J et al. (2006) Dietary patterns and associated lifestyles in preconception, pregnancy and postpartum. Eur J Clin Nutr 60, 364371.CrossRefGoogle ScholarPubMed
Michels, KB & Wolk, A (2002) A prospective study of variety of healthy foods and mortality in women. Int J Epidemiol 31, 847854.CrossRefGoogle ScholarPubMed
Zazpe, I, Sánchez-Tainta, A, Toledo, E et al. (2014) Dietary patterns and total mortality in a Mediterranean cohort: the SUN project. J Acad Nutr Diet 114, 3747.CrossRefGoogle Scholar
Figure 0

Fig. 1 Selection of subjects

Figure 1

Fig. 2 Kidmed test to assess the Mediterranean diet quality(68)

Figure 2

Table 1 Maternal sociodemographic data and dietary habits (n 1118 pregnant women)

Figure 3

Table 2 Parental anthropometric data

Figure 4

Table 3 Obstetric and neonatal data

Figure 5

Table 4 Risk of small-for-gestational-age or preterm infants associated with the level of adherence to Mediterranean diet