Factors Influencing Dietary Patterns during Pregnancy in a Culturally Diverse Society

nutrients Article Factors Influencing Dietary Patterns during Pregnancy in a Culturally Diverse Society Elisabet Fernández-Gómez 1, Trinidad Luque-Vara 1, Pablo JoséMoya-Fernández 2, María López-Olivares 3,* , Miguel Ángel Gallardo-Vigil 4and Carmen Enrique-Mirón5 1Department of Nursing, Faculty of Health Sciences, Melilla Campus, University of Granada, C/Santander s/n, 52001 Melilla, Spain; [email protected] (E.F.-G.); [email protected] (T.L.-V.) 2Department of Applied Economics, Faculty of Social and Legal Sciences, Melilla Campus, University of Granada, C/Santander s/n, 52001 Melilla, Spain; [email protected] 3Doctoral Degree School, Melilla Campus, University of Granada, C/Santander s/n, 52001 Melilla, Spain 4HUM-358 Research Group, Department of Research and Diagnostic Methods in Education, Faculty of Education and Humanities, Melilla Campus, University of Granada, C/Santander s/n, 52001 Melilla, Spain; [email protected] 5 HUM-613 Research Group, Department of Inorganic Chemistry, Faculty of Health Sciences, Melilla Campus, University of Granada, C/Santander s/n, 52001 Melilla, Spain; [email protected] *Correspondence: [email protected] Received: 12 September 2020; Accepted: 21 October 2020; Published: 23 October 2020   Abstract: The aim of this study was to identify dietary patterns in pregnant women and to assess the relationships between sociodemographic, lifestyle-related, and pregnancy-related factors. This is a descriptive, correlational study involving 306 pregnant women in Melilla (Spain) in any trimester of pregnancy. A validated food frequency questionnaire was used. Dietary patterns were determined via exploratory factor analysis and ordinal logistic regression using the proportional odds model. Three dietary patterns were identified: Western, mixed, and prudent. Sociodemographic, lifestyle-related, and pregnancy-related factors influencing dietary quality were established. The Western dietary pattern was considered the least recommended despite being the most common among women who live in Melilla (p=0.03), are Christian (p=0.01), are primiparous women (p<0.001), and are in their first or second trimester (p=0.02). Unemployed pregnant women were also more likely to have a less healthy dietary pattern ( β = − 0.716; p=0.040). The prudent dietary pattern, the healthiest of the three, was most commonly observed among Muslim women (p=0.01), women with more than two children (p<0.001), and women in the third trimester of pregnancy (p=0.02). Pregnant women who engaged in no physical activity or a low level of physical activity displayed a mixed pattern (p<0.001). This study provides evidence on the factors influencing dietary patterns during pregnancy and suggests that more specific nutrition programmes should be developed to improve the nutritional status of pregnant women. Keywords: dietary patterns; pregnancy; sociodemographic factors; pregnancy-related factors; lifestyle; factor loadings 1. Introduction A range of dietary factors contribute to the development of conditions such as heart disease, stroke, type 2 diabetes, and cancer [1–3]. From the end of the 19th century, the Spanish diet gradually evolved to meet the population’s energy and nutrient requirements, although meeting these needs remained more difficult for minors, adult women, and pregnant women. However, at the end of the 20th century, as in other countries, Nutrients 2020,12, 3242; doi:10.3390/nu12113242 www.mdpi.com/journal/nutrients Nutrients 2020,12, 3242 2 of 20 energy intake increased, becoming excessive, unbalanced, and deficient in terms of the main micronutrients [4]. Pregnancy is a critical, vulnerable state, where maternal nutrition and lifestyle constitute the main influences on the health of both mother and newborn. During pregnancy, the need for nutrients, especially micronutrients, increases compared to other stages of life, leading in turn to higher nutritional requirements [ 5 , 6 ]. Inadequate maternal nutritional intake during pregnancy may lead to negative shortand long-term health consequences for both the mother and her child [ 7 – 9 ]. In the scientific literature, it is widely recognised that environmental factors such as diet during pregnancy can contribute to the development of certain diseases among offspring [ 10 – 14 ] as well as the occurrence of metabolic alterations (overweightness or obesity) in pregnant women, especially in early pregnancy, which increase the probability of obesity in their future children [15,16]. What foods should be eaten, in what amounts, and how often are questions for which answers will enable the provision of a concise nutritional assessment and appropriate guidance during pregnancy [17]. Recent studies have shown that diets with a higher intake of fruits, vegetables, pulses, and fish lead to positive outcomes during pregnancy [ 18 , 19 ]. Generally speaking, greater adherence to the Mediterranean diet during pregnancy can protect against excessive cardiometabolic risk for offspring [20]. Most studies on this topic have focused on analysing individual nutrients, while epidemiological research highlights the importance of assessing the effect of dietary quality on overall health by establishing dietary patterns. This approach has several advantages. For example, it takes into account the interactions between food components [ 21 ] and identifies statistically significant associations by random chance. The effect of a single food component may also not be large enough to be detected. This is why dietary patterns allow us to analyse sociocultural or environmental aspects and to identify the cumulative effects of the nutrients in a single pattern. Foodstuffs are not consumed in isolation, and individuals eat foods that include a combination of nutrients. Dietary patterns give a broader overview of food and nutrient consumption, so they may be more predictive of the risks of developing certain diseases than individual foods or nutrients [22]. In general, studying dietary patterns constitutes a more comprehensive approach and has proven very useful in providing significant results to a given population [ 23 , 24 ]. Studying dietary patterns during pregnancy is one of the most suitable approaches for demonstrating the effect of diet on maternal and neonatal health [25]. Current patterns in preconception care emphasise that certain lifestyle factors, particularly nutrition, play an important role in pregnancy [ 17 ]. Pregnant women’s nutritional knowledge, among other factors such as social or cultural factors, can influence their food intake [ 26 ]. Religion is one cultural factor that conditions the diet of believers [ 27 , 28 ], as most religions set rules concerning the intake of certain foods, distinguish between pure and impure foods, determine times for fasting, etc. [ 29 ]. Similarly, psychological disorders such as depression, anxiety, or stress may also influence dietary choices during pregnancy [30–32]. For all these reasons, it is of paramount importance to determine the factors that may influence the adoption of certain types of dietary patterns. Several authors have recommended that further studies be conducted to specifically assess different factors as potential determinants [ 24 ], as the consequences of inadequate nutrition put not only women but also their infants at risk of poorer health outcomes for the rest of their lives. The aim of this research is to promote health and to develop effective interventions for this vulnerable population. This study seeks to determine dietary patterns in pregnant women and to assess the relationships between sociodemographic factors (place of residence, age, religion, level of education, marital status, socioeconomic status (level of income per month), and employment status), lifestyle-related factors/health-related behaviours (alcohol consumption, level of physical activity, prepregnancy body Nutrients 2020,12, 3242 3 of 20 mass index (BMI), and supplement consumption), and pregnancy-related factors (parity, trimester, and attendance at antenatal classes). 2. Materials and Methods 2.1. Study Design and Sample This was a diagnostic study of a descriptive-correlational nature, using a cross-sectional design. Data were collected through questionnaires, which were administered in person to a sample of pregnant women at the Women’s Care Unit in the autonomous city of Melilla, Spain, when attending the unit for antenatal care. Intentional (or convenience) sampling was used. The inclusion criteria were as follows: being pregnant in any of the trimesters, not having undergone assisted reproductive technologies (ARTs), not having a high-risk pregnancy, and not following any special diet. The mean number of annual births in the city where the study was being conducted (926.16 ± 104.93) was also taken into account. The sample was made up of a total of 306 pregnant women. The study sample was recruited from March 2018 to February 2019. None of the pregnant women refused to participate in the study. According to the Spanish Healthcare System, the mean number of annual births reported in Melilla during the previous 18 years was 926.16 ± 104.93. This figure was used to estimate a representative sample size (272), which was increased to 306 to ensure the representativeness of the sample. 2.2. Assessment of Dietary Patterns 2.2.1. Food Frequency Questionnaire The participants were assisted in person by a trained professional to complete an adapted version of the Cuestionario de Frecuencia de Consumo de Alimentos or Food Frequency Questionnaire (FFQ) by Trinidad Rodr í guez et al. (2008) [ 33 ]. The questionnaire asks about the number of times per day, per week, and per month they had consumed foods and drinks from a list of 39 foods and 6 drinks, with a total of 45 foods and drinks, in the last month. A second questionnaire was also used to collect sociodemographic data; data regarding lifestyle, such as level of physical activity, prepregnancy BMI, supplement consumption, and intake of alcoholic drinks; and data related to pregnancy itself, such as parity, trimester, and attendance at antenatal classes. The time required to complete the full questionnaire ranged from 15 to 20 min. 2.2.2. Preprocessing of Dietary Data To quantify the frequency categories and to standardise the intakes for one day, the data were translated into the following numerical values: (a) 0 (never), (b) 0.07 (1–3 times per month), (c) 0.15 (once a week), (d) 0.45 (2–4 times a week), (e) 0.8 (5–6 times a week), (f) 1 (once a day), (g) 2.5 (between 2 and 3 times a day), (h) 5 (5 times a day), and (i) 6 (more than 6 times a day). In the post hoc identification of dietary patterns, the 45 items in the FFQ were regrouped into 21 food groups based on similarity of nutrient profiles and comparable use (Table 1). To standardise the results, the mean intake values for each group were considered. Nutrients 2020,12, 3242 4 of 20 Table 1. Description of the food groups. Food Groups Number of Items Foods Dairy products 3 Milk, yoghurt, and homemade ice cream Cheese 2 Fresh cheese, and cured or semi-cured cheese Eggs 1 Eggs White meat 1 Chicken and turkey Cold cuts 1 Cold cuts and paté Red meat 2 Red meat (beef, pork, and lamb) and minced meat Fish 3 White fish, blue fish, and seafood Vegetables 3 Salads, greens, and vegetable garnish Fruit 3 Citrus fruits, fruit, and fresh fruit juice Nuts 1 Nuts (almonds, peanuts, hazelnuts, walnuts, etc.) Pulses 1 Pulses (lentils, chickpeas, pinto or haricot beans, and cooked peas) Cereals and pasta 2 Rice and pasta (spaghetti, noodles, macaroni, etc.) Potatoes 2 Potatoes and crisps Bread 1 Bread Cakes and pastries 7Marie biscuits, chocolate biscuits, doughnuts, muffins, cakes, pastries, and canned fruit Chocolate 1 Chocolate Sugary drinks 2 Sugary drinks and packaged fruit juices Coffee and tea 2 Coffee and tea Wine and beer 2 Wine (red wine, white wine, and rosé) and beer Alcoholic drinks 1 Brandy, gin, rum, whisky, vodka, and 40-proof spirits Diet drinks 1 Sugar-free drinks Adapted from Ciprián et al. (2013) [34]. 2.3. Sociodemographic, Lifestyle-Related, and Pregnancy-Related Factors The following sociodemographic variables were considered: age, place of residence, marital status, religion, level of education, employment status, and level of income per month. The following lifestyle-related variables were taken into account: alcohol consumption, level of physical activity, prepregnancy BMI, and supplement consumption. Finally, the pregnancy-related factors analysed were parity, gestational trimester, and attendance at antenatal classes. The response options for level of physical activity were none/low, moderate, and high. To define physical activity, we used the International Physical Activity Questionnaire (IPAQ), whereby a moderate level of physical activity may mean the following: 3 or more days of vigorous physical activity at least 20 min per day, 5 or more days of moderate physical activity and/or walking at least 30 min per day, or 5 or more days of any combination of walking and moderate or vigorous physical activity. Lower levels of physical activity are considered to be low or no physical activity, whereas higher levels are considered to be high physical activity. In order to define alcohol consumption and attendance at antenatal classes, the response options were yes, no, and sometimes. 2.4. Statistical Analysis All statistical analyses were performed using the SPSS Statistics for Windows, Version 24.0 (International Business Machines Corporation, IBM, Armonk, NY, USA). The statistical significance threshold for the results was set at p<0.05. A descriptive analysis of sociodemographic variables, lifestyle-related factors, and pregnancy-related factors was carried out. An exploratory factor analysis was conducted to identify dietary patterns based on food consumption data [ 21 , 22 , 24 , 35 ]. This approach was informed by the observation that scores for the consumption of some foods are correlated, and thus, statistical factor analyses can be used to express the total variance of dietary questionnaire scores in terms of some latent variables (factors). Nutrients 2020,12, 3242 5 of 20 The factors were identified using the minimum sum of squared residuals, followed by varimax rotation for interpretation. Of the total 21 food groups, 2 groups (alcoholic drinks and diet drinks) had to be discarded as their presence prevented factorial analysis. The factor loadings for the remaining 19 food groups were calculated. Factor loadings represent the extent to which the food group is related to a particular factor. A positive factor loading for a food group means that the factor represents preference for a food group, while a negative factor loading means that the factor represents avoidance of that food group (less than the mean frequency of consumption). Factor loadings greater than 0.2 were considered to represent an interpretable association regarding the corresponding factor and were thus used to describe and label the dietary patterns. Factor loadings below 0.2 were discarded [36]. Of the total number of factors, two were assumed based on the variance explained by the successive components of the food score matrix. These two factors explained 22.65% of the variance (Table 2). This percentage is comparable to and even slightly higher than those reported in other studies in this field [24,36,37]. Table 2. Factor loadings for the different food groups for each dietary pattern (N=306). Food Groups Prudent Pattern Western Pattern Dairy products 0.081 −0.245 Cheese 0.080 −0.030 Eggs 0.205 −0.004 White meat 0.138 −0.035 Cold cuts −0.372 0.044 Red meat 0.023 0.300 Fish 0.573 0.253 Vegetables 0.616 −0.207 Fruit 0.555 0.021 Nuts 0.581 −0.012 Pulses 0.278 0.080 Cereals and pasta 0.639 0.057 Potatoes 0.049 0.783 Bread 0.079 0.153 Cakes and pastries −0.051 0.732 Chocolate −0.067 0.315 Sugary drinks −0.083 0.673 Coffee and tea 0.193 0.067 Wine and beer −0.089 −0.103 Variance explained (%) 10.093 12.557 The labels given to the dietary patterns (prudent and Western) do not perfectly describe each underlying pattern, but they are helpful when analysing and discussing the results. The prudent dietary pattern was characterised by a high consumption of fruits, nuts, vegetables, pulses, cereals, fish, and poultry; by a moderate consumption of dairy products and cheese; and by a low consumption of red meat and cold cuts in particular. By contrast, the Western dietary pattern was characterised by high consumption of red meat and cold cuts, potatoes, cakes and pastries, chocolate, and sugary drinks and by a very low intake of pulses, fruits, and cereals (Table 2). These dietary patterns were based on the Mediterranean diet and the Spanish recommendations for pregnant women. A new variable was used as an overall measure of the participants’ relative tendency towards prudent or Western dietary patterns. This variable was calculated as the difference between the total recommended daily intake for each food group and the total daily intake score for all food groups. The results obtained were classified into three categories based on two cutoffpoints: percentiles 33.3 and 66.6. Negative values were classified as “Western”, intermediate or moderate values in the middle of the frequency distribution were classified as “mixed”, and the most positive values were classified as “prudent”. Nutrients 2020,12, 3242 6 of 20 The association between sociodemographic, lifestyle-related, and pregnancy-related determinants and dietary patterns in each of the three dietary categories was assessed using Pearson’s chi-squared test. Finally, an ordinal logistic regression analysis was conducted to identify the relationships of sociodemographic, lifestyle-related, and pregnancy-related variables with dietary patterns during pregnancy using the proportional odds model, which is frequently used with health questionnaires. 2.5. Ethical and Legal Considerations The confidentiality of the data and the anonymity and privacy of the participants were preserved at all times, in compliance with the Spanish Organic Law 15/1999, of the 13th of December, on personal data protection. The ethical principles set out in the Declaration of Helsinki were also observed. All participants were therefore informed of the purpose of this study and participated voluntarily having signed an informed consent form. Approval was obtained from the Directorate of Health Care Management of the Health Area of Melilla with reference: PSVG/ppg on 18 October 2017, on which the Women’s Care Unit depends, as well as the midwives of the Unit. 3. Results 3.1. Characteristics of the Study Population All the sociodemographic, lifestyle-related, and pregnancy-related characteristics of the sample are listed in Table 3. Table 3. Sociodemographic, lifestyle-related, and pregnancy-related variables (frequencies and percentages, N=306). Variables Frequency (%) Living in Melilla Yes 255 (83.3) No 51 (16.7) Age <19 y.o. 5 (1.6) 20–39 y.o. 289 (94.4) >40 y.o. 12 (3.9) Marital status Single 38 (12.4) Married/In a relationship 265 (86.6) Separated/divorced 3 (1) Religion Muslim 207 (67.6) Christian 87 (28.4) Other 12 (3.9) Level of income per month <€500 12 (3.9) €501–1000 101 (33) €1001–2000 113 (36.9) €2001–5000 74 (24.2) >€5001 6 (2) Level of education No education 23 (7.5) Primary and secondary education 112 (36.6) A levels/Higher vocational training 93 (30.4) University/Postgraduate education 78 (25.5) Employment status Household chores 95 (31) Employed 144 (47.1) Unemployed 62 (20.3) Student 3 (1) On sick leave 2 (0.7) Nutrients 2020,12, 3242 7 of 20 Table 3. Cont. Variables Frequency (%) Parity None 117 (38.2) 1–2 152 (49.7) >2 37 (12.1) BMI Underweight (<18.5) 13 (4.2) Normal weight (18.5–24.9) 134 (43.8) Overweight (25.0–29.9) 94 (30.7) Obese (≥30) 65 (21.2) Level of physical activity None/Low 253 (82.7) Moderate 53 (17.3) High 0 (0) Trimester First trimester 100 (32.7) Second trimester 105 (34.3) Third trimester 101 (33) Attendance at antenatal classes Yes 119 (38.9) No 176 (57.5) Sometimes 11 (3.6) Supplement consumption Yes 282 (92.2) No 24 (7.8) Alcohol consumption Yes 2 (0.7) No 304 (99.3) y.o.: years old; BMI: Body mass index. The mean age of the sample was 29.92 ± 5.51 years old, ranging from 18 to 43 years old. Most (83.3%) of the participants were living in Melilla, while the remaining participants (16.7%) came from the other side of the border; 86.6% were married or in a relationship. Just over two thirds (67.6%) reported being Muslims, 28.4% identified as Christians, and the remaining participants had other religions or beliefs. Employment rates were as follows: 47.1% were employed, 20.3% were unemployed, and only 1.7% were studying or on sick leave. For 38.2%, it was their first pregnancy, 12.1% had more than two children, and the rest had between 1 and 2 children; 32.7% were in their first trimester of pregnancy, 34.3% were in their second, and 33% were in their third. Regarding prepregnancy BMI, just under half of the participants (43.8%) had a normal weight, while the others deviated from the norm: 30.7% were overweight, 21.2% were obese, and only 4.2% were underweight. Finally, most of the women (82.7%) engaged in no physical activity or a low level of physical activity, whereas 17.3% had a moderate level of physical activity. The most commonly used supplements were those containing folic acid, iron, iodine, and vitamin B12. Almost all (99.7%) of the sample did not consume alcoholic drinks. 3.2. Diet during Pregnancy The results of the FFQ are shown in Table 4. With regard to foods consumed daily, bread stands out as one of the most frequently consumed foods, with 63.4% of participants eating it from 2 to 3 times a day, followed by coffee/tea (39.2%), with the same frequency of consumption. Of the foods consumed only once a day, it is worth mentioning dairy products (32.7%). With respect to foods consumed weekly, just over half of pregnant women consume 2–4 eggs per week (56.5%), although a not inconsiderable percentage (13.7%) do not consume eggs on a weekly basis or never eat them. The most frequent consumption of pulses and white meat is 2–4 times a week; 48.3% eat red meat, 40.8% eat cheese, and 62.1% eat fish once a week, while 35.9% never eat nuts. Nutrients 2020,12, 3242 8 of 20 Table 4. Consumption of food groups (frequencies and percentages). Food Groups Never 1–3 Times a Month Once a Week 2–4 Times a Week 5–6 Times a Week Once a Day 2–3 Times a Day Dairy products 11 (3.6) 6 (2) 73 (23.9) 40 (13) 76 (24.8) 100 (32.7) Cheese 50 (16.3) 26 (8.5) 125 (40.8) 85 (27.8) 11 (3.6) 9 (2.9) Eggs 27 (8.8) 15 (4.9) 62 (20.3) 173 (56.5) 24 (7.8) 5 (1.6) White meat 13 (4.2) 53 (17.3) 205 (67) 29 (9.5) 6 (2) Cold meats 170 (55.6) 32 (10.5) 83 (27.1) 13 (4.2) 8 (2.6) Red meat 48 (15.7) 31 (10.1) 148 (48.3) 79 (25.8) Fish 51 (16.7) 40 (13) 190 (62.1) 25 (8.2) Vegetables 13 (4.2) 9 (2.9) 133 (43.5) 110 (35.9) 13 (4.2) 28 (9.2) Fruit 6 (2) 4 (1.3) 64 (20.9) 128 (41.8) 75 (24.5) 29 (9.5) Nuts 110 (35.9) 48 (15.7) 111 (36.3) 20 (6.5) 17 (5.6) Pulses 24 (7.8) 103 (33.7) 173 (56.5) 5 (1.6) 1 (0.3) Cereals and pasta 11 (3.6) 29 (9.5) 200 (65.3) 66 (21.6) Potatoes 15 (4.9) 26 (8.5) 159 (52) 101 (33) 5 (1.6) Bread 18 (5.9) 8 (2.6) 32 (10.5) 39 (12.7) 15 (4.9) 194 (63.4) Cakes and pastries 101 (33) 88 (28.7) 111 (36.3) 6 (2) Chocolate 108 (35.3) 8 (2.6) 57 (18.6) 93 (30.4) 19 (6.2) 12 (3.9) 9 (2.9) Sugary drinks 101 (33) 33 (10.8) 99 (32.4) 55 (18) 9 (2.9) 9 (2.9) Coffee and tea 151 (49.3) 24 (7.8) 120 (39.2) Wine and beer 293 (95.7) 10 (3.3) 3 (1) Note: As per the groups detailed in Table 1. Alcoholic and diet drinks have been excluded due to low consumption levels among participants. Nutrients 2020,12, 3242 9 of 20 Regarding foods consumed occasionally by pregnant women, 55.6% do not consume cold cuts compared with 27.1% who consume them from 2 to 4 times a week; 33% do not consume cakes or pastries, while 36.3% do so on a weekly basis, as is the case with sugary drinks (32.4%); and 30.4% report eating chocolate between 2 and 4 times a week, while 35.3% never eat it. 3.3. Sociodemographic, Lifestyle-Related, and Pregnancy-Related Determinants of Dietary Patterns The Western dietary pattern was most commonly found among women living in Melilla (p=0.03), who are Christians (p=0.01), are primiparous women (p<0.001), and are in their first or second trimester of pregnancy (p=0.02) (Table 5). On the other hand, the prudent dietary pattern was most often seen in Muslim women (p=0.01), women with more than 2 children (p<0.001), and women in their third trimester of pregnancy (p=0.02). Pregnant women who engaged in no physical activity or a low level of physical activity displayed a mixed pattern (p<0.001). Table 5. Sociodemographic, lifestyle-related, and pregnancy-related variables and dietary patterns (N=306) *. Variables Western Pattern Mixed Pattern Prudent Pattern p Living in Melilla Yes (n=255) 93 (36.5) 80 (31.4) 82 (32.2) 0.031 No (n=51) 9 (17.6) 22 (43.1) 20 (39.2) Age <19 y.o. (n=5) 2 (40.0) 3 (60) 0 0.366 20–39 y.o. (n=289) 97 (33.6) 96 (33.2) 96 (33.2) >40 y.o. (n=12) 3 (25) 3 (25) 6 (50) Religion Christian (n=87) 40 (46) 25 (28.7) 22 (25.3) 0.015 Muslim (n=207) 56 (27.1) 73 (35.3) 78 (37.7) Other (n=12) 6 (50) 4 (33.3) 2 (16.7) Marital status Single (n=38) 19 (50) 14 (36.8) 5 (13.2) 0.059 Married/In a relationship (n=265) 82 (30.9) 87 (32.8) 96 (36.2) Separated/Divorced (n=3) 1 (33.3) 1 (33.3) 1 (33.3) Level of education No education (n=23) 7 (30.4) 10 (43.5) 6 (26.1) 0.783 Primary and secondary education (n=112) 33 (29.5) 38 (33.9) 41 (36.6) A levels/Higher vocational training (n=93) 32 (34.4) 29 (31.2) 32 (34.4) University education (n=78) 30 (38.5) 25 (32.1) 23 (29.5) Employment status Household chores (n=95) 23 (24.2) 32 (33.7) 40 (42.1) 0.177 Employed (n=144) 55 (38.2) 45 (31.3) 44 (30.6) Unemployed (n=62) 24 (38.7) 23 (37.1) 15 (24.2) Student (n=3) 0 1 (33.3) 2 (66.6) On sick leave (n=2) 0 1 (50) 1 (50) Level of income per month <€500 (n=12) 1 (8.3) 9 (75) 2 (16.7) 0.058 €5001–1000 (n=101) 32 (31.7) 35 (34.7) 34 (33.7) €1001–2000 (n=113) 34 (30.1) 36 (31.9) 43 (38.1) €2001–5000 (n=74) 33 (44.6) 20 (27) 21 (28.4) >€5001 (n=6) 2 (33.3) 2 (33.3) 2 (33.3) Nutrients 2020,12, 3242 16 of 20 20. Chatzi, L.; Rifas-Shiman, S.L.; Georgiou, V.; Joung, K.E.; Koinaki, S.; Chalkiadaki, G.; Margioris, A.; Sarri, K.; Vassilaki, M.; Vafeiadi, M.; et al. Adherence to the Mediterranean diet during pregnancy and offspring adiposity and cardiometabolic traits in childhood. Pediatr. Obes. 2017,12, 47–56. [CrossRef] 21. Borges, C.A.; Rinaldi, A.E.; Conde, W.L.; Mainardi, G.M.; Behar, D.; Slater, B. Dietary patterns: A literature review of the methodological characteristics of the main step of the multivariate analyzes. Braz. J. Epidemiol. 2015,18, 837–857. [CrossRef] 22. Hu, F.B. Dietary pattern analysis: A new direction in nutritional epidemiology. Curr. Opin. Lipidol. 2002 , 13, 3–9. [CrossRef] 23. Loy, S.-L.; Mohamed, H.J.B.J. Relative validity of dietary patterns during pregnancy assessed with a food frequency questionnaire. Int. J. Food Sci. Nutr. 2013,64, 668–673. [CrossRef] [PubMed] 24. Wesołowska, E.; Jankowska, A.; Trafalska, E.; Kału˙zny, P.; Grzesiak, M.; Dominowska, J.; Hanke, W.; Calamandrei, G.; Pola´nska, K. Sociodemographic, Lifestyle, Environmental and Pregnancy-Related Determinants of Dietary Patterns during Pregnancy. Int. J. Environ. Res. Public Health 2019 ,16, 754. [CrossRef] [PubMed] 25. Maugeri, A.; Barchitta, M.; Favara, G.; La Rosa, M.C.; La Mastra, C.; Magnano San Lio, R.; Agodi, A. Maternal Dietary Patterns Are Associated with Pre-Pregnancy Body Mass Index and Gestational Weight Gain: Results from the “Mamma & Bambino” Cohort. Nutrients 2019,11, 1308. [CrossRef] 26. Lee, A.; Newton, M.; Radcliffe, J.; Belski, R. Pregnancy nutrition knowledge and experiences of pregnant women and antenatal care clinicians: A mixed methods approach. Women Birth 2018 ,31, 269–277. [CrossRef] 27. Azurmendi, M.G. Implicaciones jur í dicas de la libertad religiosa en la alimentaci ó n. Zainak. Cuad. Antropol. Etnogr. 2011,34, 391–411. 28. Vela, C.; Ballesteros, C. La influencia de las creencias religiosas en el consumo. Una aproximaci ó n desde las tres religiones del Libro. Rev. ICADE 2011,83, 393–411. 29. Am é rigo, F. La problem á tica de la alimentaci ó n religiosa y de convicci ó n en los centros educativos. Rev. Derecho Polít. 2016,97, 141–178. [CrossRef] 30. Fowles, E.R.; Stang, J.; Bryant, M.; Kim, S. Stress, depression, social support, and eating habits reduce diet quality in the first trimester in low-income women: A pilot study. J. Acad. Nutr. Diet. 2012 ,112, 1619–1625. [CrossRef] 31. Fowles, E.R.; Timmerman, G.M.; Bryant, M.; Kim, S. Eating at fast-food restaurants and dietary quality in low-income pregnant women. West. J. Nurs. Res. 2011,33, 630–651. [CrossRef] [PubMed] 32. Lindsay, K.L.; Buss, C.; Wadhwa, P.D.; Entringer, S. The Interplay between Maternal Nutrition and Stress during Pregnancy: Issues and Considerations. Ann. Nutr. Metabol. 2017 ,70, 191–200. [CrossRef] [PubMed] 33. Trinidad Rodr í guez, I.; Fern á ndez Ballart, J.; Cuc ó Pastor, G.; Biarn é s Jord à , E.; Arija Val, V. Validation of a short questionnaire on frequency of dietary intake: Reproducibility and validity. Nutr. Hosp. 2008 ,23, 242–252. 34. Cipri á n, D.; Navarrete-Muñoz, E.M.; Garc í a de la Hera, M.; Gim é nez-Monzo, D.; Gonz á lez-Palacios, S.; Quiles, J.; Vioque, J. Mediterranean and Western dietary patterns in adult population of a Mediterranean area; a cluster analysis. Nutr. Hosp. 2013,28, 1741–1749. [CrossRef] [PubMed] 35. Doyle, I.-M.; Borrmann, B.; Grosser, A.; Razum, O.; Spallek, J. Determinants of dietary patterns and diet quality during pregnancy: A systematic review with narrative synthesis. Public Health Nutr. 2017 ,20, 1009–1028. [CrossRef] [PubMed] 36. Steenweg-de Graaff, J.; Tiemeier, H.; Steegers-Theunissen, R.P.M.; Hofman, A.; Jaddoe, V.W.V.; Verhulst, F.C.; Roza, S.J. Maternal dietary patterns during pregnancy and child internalising and externalising problems. The Generation R Study. Clin. Nutr. 2014,33, 115–121. [CrossRef] 37. Crozier, S.R.; Inskip, H.M.; Godfrey, K.M.; Robinson, S.M. Dietary patterns in pregnant women: A comparison of food-frequency questionnaires and 4 d prospective diaries. Br. J. Nutr. 2008,99, 869–875. [CrossRef] 38. Ma, E.; Ohira, T.; Sakai, A.; Yasumura, S.; Takahashi, A.; Kazama, J.; Shimabukuro, M.; Nakano, H.; Okazaki, K.; Maeda, M.; et al. Associations between Dietary Patterns and Cardiometabolic Risks in Japan: A Cross-Sectional Study from the Fukushima Health Management Survey, 2011–2015. Nutrients 2020 ,12, 129. [CrossRef] 39. Kowalkowska, J.; Lonnie, M.; Wadolowska, L.; Czarnocinska, J.; Jezewska-Zychowicz, M.; Babicz-Zielinska, E. Healthand Taste-Related Attitudes Associated with Dietary Patterns in a Representative Sample of Polish Girls and Young Women: A Cross-Sectional Study (GEBaHealth Project). Nutrients 2018 ,10, 254. [CrossRef] Nutrients 2020,12, 3242 17 of 20 40. Santin, F.; Canella, D.; Borges, C.; Lindholm, B.; Avesani, C.M. Dietary Patterns of Patients with Chronic Kidney Disease: The Influence of Treatment Modality. Nutrients 2019,11, 1920. [CrossRef] 41. Shin, D.; Lee, K.W.; Song, W.O. Pre-Pregnancy Weight Status Is Associated with Diet Quality and Nutritional Biomarkers during Pregnancy. Nutrients 2016,8, 162. [CrossRef] 42. Gontijo, C.A.; Cabral, B.B.M.; Balieiro, L.C.T.; Teixeira, G.P.; Fahmy, W.M.; Maia, Y.C.P.; Crispim, C.A. Time-related eating patterns and chronotype are associated with diet quality in pregnant women. Chronobiol. Int. 2019,36, 75–84. [CrossRef] 43. Nash, D.M.; Gilliland, J.A.; Evers, S.E.; Wilk, P.; Campbell, M.K. Determinants of Diet Quality in Pregnancy: Sociodemographic, Pregnancy-specific, and Food Environment Influences. J. Nutr. Educ. Behav. 2013 ,45, 627–634. [CrossRef] 44. Parker, H.W.; Tovar, A.; McCurdy, K.; Vadiveloo, M. Associations between pre-pregnancy BMI, gestational weight gain, and prenatal diet quality in a national sample. PLoS ONE 2019 ,14, e0224034. [CrossRef] [PubMed] 45. Yong, H.Y.; Mohd Shariff, Z.; Mohd Yusof, B.N.; Rejali, Z.; Tee, Y.Y.S.; Bindels, J.; van der Beek, E.M. Pre-Pregnancy BMI Influences the Association of Dietary Quality and Gestational Weight Gain: The SECOST Study. Int. J. Environ. Res. Public Health 2019,16, 3735. [CrossRef] [PubMed] 46. Cespedes, E.M.; Hu, F.B. Dietary patterns: From nutritional epidemiologic analysis to national guidelines. Am. J. Clin. Nutr. 2015,101, 899–900. [CrossRef] 47. Waijers, P.M.C.M.; Feskens, E.J.M.; Ock é , M.C. A critical review of predefined diet quality scores. Br. J. Nutr. 2007,97, 219–231. [CrossRef] [PubMed] 48. Ferrer, C.; Garc í a-Esteban, R.; Mendez, M.; Romieu, I.; Torrent, M.; Sunyer, J. Social determinants of dietary patterns during pregnancy. Gac. Sanit. 2009,23, 38–43. [CrossRef] 49. Arkkola, T.; Uusitalo, U.; Kronberg-Kippilä, C.; Männistö, S.; Virtanen, M.; Kenward, M.G.; Veijola, R.; Knip, M.; Ovaskainen, M.-L.; Virtanen, S.M. Seven distinct dietary patterns identified among pregnant Finnish women—Associations with nutrient intake and sociodemographic factors. Public Health Nutr. 2008 , 11, 176–182. [CrossRef] 50. Fransen, H.P.; May, A.M.; Stricker, M.D.; Boer, J.M.A.; Hennig, C.; Rosseel, Y.; Ock é , M.C.; Peeters, P.H.M.; Beulens, J.W.J. A Posteriori Dietary Patterns: How Many Patterns to Retain? J. Nutr. 2014 ,144, 1274–1282. [CrossRef] 51. Northstone, K.; Emmett, P.; Rogers, I. Dietary patterns in pregnancy and associations with socio-demographic and lifestyle factors. Eur. J. Clin. Nutr. 2008,62, 471–479. [CrossRef] 52. Tucker, K.L. Dietary patterns, approaches, and multicultural perspectiveThis is one of a selection of papers published in the CSCN-CSNS 2009 Conference, entitled Can we identify culture-specific healthful dietary patterns among diverse populations undergoing nutrition transition? Appl. Phys. Nutr. Metab. 2010 ,35, 211–218. [CrossRef] 53. Cuc ó , G.; Fern á ndez-Ballart, J.; Sala, J.; Viladrich, C.; Iranzo, R.; Vila, J.; Arija, V. Dietary patterns and associated lifestyles in preconception, pregnancy and postpartum. Eur. J. Clin. Nutr. 2006 ,60, 364–371. [CrossRef] [PubMed] 54. Long, J.S.; Freese, J. Regression Models for Categorical Dependent Variables Using Stata; Stata Press: College Station, TX, USA, 2014; Available online: https://www.scholars.northwestern.edu/en/publications/regressionmodels-for-categorical-dependent-variables-using-stata (accessed on 1 September 2020). 55. Agresti, A. Analysis of Ordinal Categorical Data; John Wiley & Sons: Hoboken, NJ, USA, 2010. 56. Liu, I.; Mukherjee, B. Proportional Odds Model. In Wiley Encyclopedia of Clinical Trials; Wiley & Sons, Inc.: Hoboken, NJ, USA, 2008; pp. 1–8. [CrossRef] 57. Fitzgerald, K.C.; Tyry, T.; Salter, A.; Cofield, S.S.; Cutter, G.; Fox, R.; Marrie, R.A. Diet quality is associated with disability and symptom severity in multiple sclerosis. Neurology 2018 ,90, e1–e11. [CrossRef] [PubMed] 58. Mitku, A.A.; Zewotir, T.; North, D.; Jeena, P.; Naidoo, R.N. Modeling Differential Effects of Maternal Dietary Patterns across Severity Levels of Preterm Birth Using a Partial Proportional Odds Model. Sci. Rep. 2020 ,10. [CrossRef] [PubMed] 59. Valentino, G.; Acevedo, M.; Villablanca, C.; Á lamos, M.; Orellana, L.; Adasme, M.; Baraona, F.; Navarrete, C.; Valentino, G.; Acevedo, M.; et al. Five o’clock tea and the risk of metabolic syndrome. Rev. M é dica Chile 2019 , 147, 693–702. [CrossRef] Nutrients 2020,12, 3242 18 of 20 60. Gil, Á .; de Victoria, E.M.; Olza, J. Indicators for the evaluation of diet quality. Nutr. Hosp. 2015 ,31, 128–144. [CrossRef] 61. Jard í , C.; Aparicio, E.; Bedmar, C.; Aranda, N.; Abajo, S.; March, G.; Basora, J.; Arija, V.; Study Group, T.E. Food Consumption during Pregnancy and Post-Partum. ECLIPSES Study. Nutrients 2019,11, 2447. [CrossRef] 62. Teixeira, J.A.; Castro, T.G.; Grant, C.C.; Wall, C.R.; da Castro, A.L.S.; Francisco, R.P.V.; Vieira, S.E.; Saldiva, S.R.D.M.; Marchioni, D.M. Dietary patterns are influenced by socio-demographic conditions of women in childbearing age: A cohort study of pregnant women. BMC Public Health 2018 ,18, 301. [CrossRef] 63. Gonz á lez Jim é nez, E.; Aguilar Cordero, M.J.; Garc í a Garc í a, C.J.; Garc í a L ó pez, P.; Á lvarez Ferre, J.; Padilla L ó pez, C.A.; Ocete Hita, E. Influence of family environment of the development of obesity and overweight in a population of school children in Granada (Spain). Nutr. Hosp. 2012,27, 177–184. [CrossRef] 64. Rivas, A.; Romero, A.; Mariscal, M.; Monteagudo, C.; Hern á ndez, J.; Olea-Serrano, F. Validation of questionnaires for the study of food habits and bone mass. Nutr. Hosp. 2009 ,24, 521–528. [CrossRef] [PubMed] 65. Newby, P.K.; Tucker, K.L. Empirically derived eating patterns using factor or cluster analysis: A review. Nutr. Rev. 2004,62, 177–203. [CrossRef] [PubMed] 66. Hoffmann, J.F.; Nunes, M.A.A.; Schmidt, M.I.; Olinto, M.T.A.; Melere, C.; Ozcariz, S.G.I.; Buss, C.; Drhemer, M.; Manzolli, P.; Soares, R.M.; et al. Dietary patterns during pregnancy and the association with sociodemographic characteristics among women attending general practices in southern Brazil: The ECCAGe Study. Cad. Saúde Pública 2013,29, 970–980. [CrossRef] [PubMed] 67. Völgyi, E.; Carroll, K.N.; Hare, M.E.; Ringwald-Smith, K.; Piyathilake, C.; Yoo, W.; Tylavsky, F.A. Dietary Patterns in Pregnancy and Effects on Nutrient Intake in the Mid-South: The Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study. Nutrients 2013 ,5, 1511–1530. [CrossRef] [PubMed] 68. Boylan, S.; Lallukka, T.; Lahelma, E.; Pikhart, H.; Malyutina, S.; Pajak, A.; Kubinova, R.; Bragina, O.; Stepaniak, U.; Gillis-Januszewska, A.; et al. Socio-economic circumstances and food habits in Eastern, Central and Western European populations. Public Health Nutr. 2011,14, 678–687. [CrossRef] [PubMed] 69. Stefler, D.; Pajak, A.; Malyutina, S.; Kubinova, R.; Bobak, M.; Brunner, E.J. Comparison of food and nutrient intakes between cohorts of the HAPIEE and Whitehall II studies. Eur. J. Public Health 2016 ,26, 628–634. [CrossRef] 70. Fowles, E.R.; Bryant, M.; Kim, S.; Walker, L.O.; Ruiz, R.J.; Timmerman, G.M.; Brown, A. Predictors of Dietary Quality in Low-Income Pregnant Women: A Path Analysis. Nurs. Res. 2011,60, 286–294. [CrossRef] 71. Parker, H.W.; Tovar, A.; McCurdy, K.; Vadiveloo, M. Socio-economic and racial prenatal diet quality disparities in a national US sample. Public Health Nutr. 2020,23, 894–903. [CrossRef] 72. Kritsotakis, G.; Chatzi, L.; Vassilaki, M.; Georgiou, V.; Kogevinas, M.; Philalithis, A.E.; Koutis, A. Social capital, tolerance of diversity and adherence to Mediterranean diet: The Rhea Mother-Child Cohort in Crete, Greece. Public Health Nutr. 2015,18, 1300–1307. [CrossRef] 73. Tsigga, M.; Filis, V.; Hatzopoulou, K.; Kotzamanidis, C.; Grammatikopoulou, M.G. Healthy Eating Index during pregnancy according to pre-gravid and gravid weight status. Public Health Nutr. 2011 ,14, 290–296. [CrossRef] 74. Rifas-Shiman, S.L.; Rich-Edwards, J.W.; Kleinman, K.P.; Oken, E.; Gillman, M.W. Dietary Quality during Pregnancy Varies by Maternal Characteristics in Project Viva: A US Cohort. J. Am. Diet. Assoc. 2009 ,109, 1004–1011. [CrossRef] [PubMed] 75. Wall, C.R.; Gammon, C.S.; Bandara, D.K.; Grant, C.C.; Atatoa Carr, P.E.; Morton, S.M.B. Dietary Patterns in Pregnancy in New Zealand—Influence of Maternal Socio-Demographic, Health and Lifestyle Factors. Nutrients 2016,8, 300. [CrossRef] [PubMed] 76. Hillesund, E.R.; Bere, E.; Haugen, M.; Øverby, N.C. 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. 2014,17, 1909–1918. [CrossRef] 77. Uusitalo, U.; Arkkola, T.; Ovaskainen, M.-L.; Kronberg-Kippilä, C.; Kenward, M.G.; Veijola, R.; Simell, O.; Knip, M.; Virtanen, S.M. Unhealthy dietary patterns are associated with weight gain during pregnancy among Finnish women. Public Health Nutr. 2009,12, 2392–2399. [CrossRef] [PubMed] Nutrients 2020,12, 3242 19 of 20 78. Zuccolotto, D.C.C.; Crivellenti, L.C.; Franco, L.J.; Sarotelli, D.S. Dietary patterns of pregnant women, maternal excessive body weight and gestational diabetes. Rev. Saúde Pública 2019,53, 52. [CrossRef] [PubMed] 79. Gardner, B.; Croker, H.; Barr, S.; Briley, A.; Poston, L.; Wardle, J. Psychological predictors of dietary intentions in pregnancy. J. Hum. Nutr. Diet. 2012,25, 345–353. [CrossRef] [PubMed] 80. Fowler, J.K.; Evers, S.E.; Campbell, M.K. Inadequate Dietary Intakes: Among Pregnant Women. Can. J. Diet. Pract. Res. 2012,73, 72–77. [CrossRef] 81. Laraia, B.A.; Bodnar, L.M.; Siega-Riz, A.M. Pregravid body mass index is negatively associated with diet quality during pregnancy. Public Health Nutr. 2007,10, 920–926. [CrossRef] [PubMed] 82. Castro, M.B.T.; Vilela, A.A.F.; Oliveira, A.S.D.; Cabral, M.; Souza, R.A.G.; Kac, G.; Sichieri, R. Sociodemographic characteristics determine dietary pattern adherence during pregnancy. Public Health Nutr. 2016,19, 1245–1251. [CrossRef] [PubMed] 83. Ministry of Health, Social Services and Equality. Clinical Practice Guide for Care in Pregnancy and the Puerperium; Clinical Practice Guidelines in the SNS: AETSA 2011/10; Andalusian Health Technology Assessment Agency: Andaluc í a, Spain, 2014; Available online: https://www.mscbs.gob.es/organizacion/sns/planCalidadSNS/pdf/ Guia_practica_AEP.pdf (accessed on 25 September 2020). 84. McDonald, S.D.; Park, C.K.; Pullenayegum, E.; Bracken, K.; Sword, W.; McDonald, H.; Neupane, B.; Taylor, V.H.; Beyene, J.; Mueller, V.; et al. Knowledge translation tool to improve pregnant women’s awareness of gestational weight gain goals and risks of gaining outside recommendations: A non-randomized intervention study. BMC Pregnancy Childbirth 2015,15, 105. [CrossRef] 85. Bosaeus, M.; Hussain, A.; Karlsson, T.; Andersson, L.; Hulth é n, L.; Svelander, C.; Sandberg, A.-S.; Larsson, I.; Ellegård, L.; Holmäng, A. A randomized longitudinal dietary intervention study during pregnancy: Effects on fish intake, phospholipids, and body composition. Nutr. J. 2015,14, 1. [CrossRef] [PubMed] 86. Emmett, R.; Akkersdyk, S.; Yeatman, H.; Meyer, B.J. Expanding Awareness of Docosahexaenoic Acid during Pregnancy. Nutrients 2013,5, 1098–1109. [CrossRef] [PubMed] 87. Fallah, F.; Pourabbas, A.; Delpisheh, A.; Veisani, Y.; Shadnoush, M. Effects of Nutrition Education on Levels of Nutritional Awareness of Pregnant Women in Western Iran. Int. J. Endocrinol. Metabol. 2013 ,11, 175–178. [CrossRef] [PubMed] 88. Hui, A.L.; Back, L.; Ludwig, S.; Gardiner, P.; Sevenhuysen, G.; Dean, H.J.; Sellers, E.; McGavock, J.; Morris, M.; Jiang, D.; et al. Effects of lifestyle intervention on dietary intake, physical activity level, and gestational weight gain in pregnant women with different pre-pregnancy Body Mass Index in a randomized control trial. BMC Pregnancy Childbirth 2014,14, 331. [CrossRef] [PubMed] 89. Khoramabadi, M.; Dolatian, M.; Hajian, S.; Zamanian, M.; Taheripanah, R.; Sheikhan, Z.; Mahmoodi, Z.; Seyedi-Moghadam, A. Effects of Education Based on Health Belief Model on Dietary Behaviors of Iranian Pregnant Women. Glob. J. Health Sci. 2016,8, 230–239. [CrossRef] [PubMed] 90. McGowan, C.A.; Walsh, J.M.; Byrne, J.; Curran, S.; McAuliffe, F.M. The influence of a low glycemic index dietary intervention on maternal dietary intake, glycemic index and gestational weight gain during pregnancy: A randomized controlled trial. Nutr. J. 2013,12, 140. [CrossRef] [PubMed] 91. Noronha, J.A.; Bhaduri, A.; Bhat, H.V.; Kamath, A. Interventional study to strengthen the health promoting behaviours of pregnant women to prevent anaemia in southern India. Midwifery 2013 ,29, e35–e41. [CrossRef] 92. Oken, E.; Guthrie, L.B.; Bloomingdale, A.; Platek, D.N.; Price, S.; Haines, J.; Gillman, M.W.; Olsen, S.F.; Bellinger, D.C.; Wright, R.O. A pilot randomized controlled trial to promote healthful fish consumption during pregnancy: The Food for Thought Study. Nutr. J. 2013,12, 33. [CrossRef] 93. Shivalli, S.; Srivastava, R.K.; Singh, G.P. Trials of Improved Practices (TIPs) to Enhance the Dietary and Iron-Folate Intake during Pregnancy—A Quasi Experimental Study among Rural Pregnant Women of Varanasi, India. PLoS ONE 2015,10, e0137735. [CrossRef] 94. Hanson, M.A.; Bardsley, A.; De-Regil, L.M.; Moore, S.E.; Oken, E.; Poston, L.; Ma, R.C.; McAuliffe, F.M.; Maleta, K.; Purandare, C.N.; et al. The International Federation of Gynecology and Obstetrics (FIGO) recommendations on adolescent, preconception, and maternal nutrition: “Think Nutrition First”. Int. J. Gynecol. Obstet. 2015,131, S213–S253. [CrossRef] 95. Spanish Nutrition Foundation. White Paper on Nutrition in Spain; FEN: Madrid, Spain, 2013; Available online: https://www.seedo.es/images/site/documentacionConsenso/Libro_Blanco_Nutricion_Esp-2013.pdf (accessed on 25 September 2020). Nutrients 2020,12, 3242 20 of 20 96. Ministry of Health, Consumption and Social Welfare. Recommendations to Prevent Obesity and Overweight and Maintain Good Nutritional Status during Pregnancy; MSCBS: Madrid, Spain, 2019; Available online: http: //www.mscbs.gob.es/ciudadanos/proteccionSalud/mujeres/recomendaciones/recEmbarazo.htm (accessed on 25 September 2020). 97. McCann, S.E.; Marshall, J.R.; Brasure, J.R.; Graham, S.; Freudenheim, J.L. Analysis of patterns of food intake in nutritional epidemiology: Food classification in principal components analysis and the subsequent impact on estimates for endometrial cancer. Public Health Nutr. 2001,4, 989–997. [CrossRef] [PubMed] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).