Diet Quality Is Associated with a High Newborn Size and Reduction in the Risk of Low Birth Weight and Small for Gestational Age in a Group of Mexican Pregnant Women: An Observational Study

A high-quality diet during pregnancy may have positive effects on fetal growth and nutritional status at birth, and it may modify the risk of developing chronic diseases later in life. The aim of this study was to evaluate the association between diet quality and newborn nutritional status in a group of pregnant Mexican women. As part of the ongoing Mexican prospective cohort study, OBESO, we studied 226 healthy pregnant women. We adapted the Alternated Healthy Eating Index-2010 for pregnancy (AHEI-10P). The association between maternal diet and newborn nutritional status was investigated by multiple linear regression and logistic regression models. We applied three 24-h recalls during the second half of gestation. As the AHEI-10P score improved by 5 units, the birth weight and length increased (β = 74.8 ± 35.0 g and β = 0.3 ± 0.4 cm, respectively, p < 0.05). Similarly, the risk of low birth weight (LBW) and small for gestational age (SGA) decreased (OR: 0.47, 95%CI: 0.27–0.82 and OR: 0.55, 95%CI: 0.36–0.85, respectively). In women without preeclampsia and/or GDM, the risk of stunting decreased as the diet quality score increased (+5 units) (OR: 0.62, 95%IC: 0.40–0.96). A high-quality diet during pregnancy was associated with a higher newborn size and a reduced risk of LBW and SGA in this group of pregnant Mexican women.


Introduction
Nutrition during pregnancy is a key determinant of fetal growth and newborn nutritional status. The effects of intrauterine nutrition remain until later stages of life. Hediger and colleagues [1] found that children who were born underweight or small for gestational age (SGA) tended to have a higher percentage of fat mass, insulin resistance, higher blood pressure, and metabolic alterations in infancy. Likewise, low birthweight, associated with intrauterine growth restriction (IUGR), has been related to a higher incidence of cardiovascular disease and insulin non-dependent diabetes in adult life [2].
The effects of maternal diet on newborn nutritional status have been extensively studied. It is accepted that excessive exposure to glucose and fatty acids in utero may promote a higher concentration of glucose and insulin in the fetus, resulting in an accelerated growth and higher birth weight [3]. In a secondary analysis of the ROLO study, Horan et al. [4], structural malformations in their fetuses and women with chronic use of insulin, metformin, and steroids. The OBESO cohort was approved by the Committees of Ethics, Research and Biosafety of the National Institute of Perinatology (Project. No. 3300-11402-01-575-17).

Maternal Characteristics
The recruitment was carried out at the Maternal-Fetal Medicine Department during the first trimester visit. Trained staff explained the project, invited all women who met the criteria, and collected the informed consent. At this time, the nutritionist made the first nutrition assessment to obtain the baseline characteristics and retrospectively collect information about the pre-gestational body mass index (BMI). During the follow-up visits, which occurred every four to six weeks, we obtained the patients' weight and completed a dietary assessment.

Dietary Assessment
A standardized interviewer applied a multiple-pass 24-h recall at 20 to 24, 24.1 to 28, 28.1 to 34, and ≥34 gestational weeks. To improve the portion size estimation, the interviewers used food replicas, as well as standard measuring cups, spoons, and glasses. Nutrient analysis was performed with the Food Processor SQL software (version 14.0, Esha Research, Salem, OR, USA). We standardized the recipes and included Mexican foods in the database. The intake of energy, macronutrients, fiber, mono, poly, saturated and trans fatty acids, cholesterol, vitamins A, C, and D, folate, calcium, iron, magnesium, selenium, and zinc was computed from three multiple-pass 24-h recalls. Likewise, to establish the usual energy, nutrient, and food groups intake, we considered the three dietary assessments and calculated an average for each item. Subsequently, we computed the AHEI-10P.

Alternative Healthy Eating Index-2010 for Pregnancy (AHEI-10P)
This score was created as an alternative to AHEI-2010 for use during pregnancy [10]. The original index (AHEI-10) includes alcohol and sodium intake. Since alcohol is not recommended during pregnancy, we excluded this item. Regarding the dietary sodium intake, its assessment using dietary tools has numerous biases, and the standard method for its assessment, 24-h urine testing, is not part of the procedures of the OBESO cohort; thus, this item was also excluded [14]. Finally, we included calcium, iron, and folate intake due to their relevance during pregnancy [7]. With the exception of fish, calcium, iron, and folate, all items were scored according to the AHEI-2010 criteria. All components were scored from 0 (worst) to 10 (best). For intermediate values, we used the equations described in Appendix A. The total AHEI-10P score ranged from 0 (lowest diet quality) to 120 (highest diet quality). A description and calculation for each item and scoring criteria are described in Table 1. Dietary iron intake, mg/d Due to hematologic changes and increased needs during pregnancy, iron is essential. A lack of iron leads to anemia and affects physical working capacity, brain function, and behavior. Iron deficiency increases the risk of adverse perinatal outcomes. In low-resource settings, iron-deficiency anemia is prevalent and is often exacerbated by infectious diseases [7]. We established an average iron intake through a serial dietary assessment (mg/d).

≥28
Dietary folate intake, mcg/d Folate is critical for normal fetal development. Folate insufficiency before pregnancy is a proven risk factor for the development of NTDs and other congenital malformations. Additionally, folate is important in women for the prevention of macrocytic anemia and is implicated in maintaining cardiovascular health and cognitive function [7]. We established an average folate intake through a serial dietary assessment (mcg/d of DFE

Newborn Nutritional Status
A certified dietitian obtained anthropometric measures within the first 48-72 h of birth, according to Lohman's technique [17]. We used a Tanita WB-3000 Digital Physicians Scale to measure the weight (Tanita, Arlington Heights, IL, USA), a SECA infantometer model 207 (SECA, Hamburg, Deutschland) to measure the recumbent length, and a SECA measured tape model 212 to measure the head circumference (Hamburg, Deutschland). WHO-2006 and INTER-GROWTH-21St growth references were used for evaluating the weight for age (W/A), weight for length (W/L), length for age (L/A), body mass index for age (BMI/A), and head circumference for age (HC/A) in term and preterm newborns [18,19].

Potential Confounders and Intermediate Variables
Maternal age, pregestational-BMI, maternal gestational weight gain, energy intake, multivitamin use (with folic acid and iron), education level, and number of pregnancies (parity) were obtained using questionnaires that collected data on sociodemographic variables, obstetric history, and detailed information about the pregnancy.
Weight status: Maternal weight was measured at each visit using Lohman's technique with a Seca 813 Digital Scale (SECA, Hamburg, Germany) [17].
Height was measured using Lohman's technique with a Fixed Wall Stadiometer 216 for Infants and Adults (SECA, Hamburg, Germany) [17].
Weight gain was classified as adequate, insufficient, or excessive, according to the gestational age and pregestational-BMI, as recommended by the Institute of Medicine [20].
Total energy intake: Average energy intake was considered as Kcal/d from the 24 h recalls.
Multivitamin: The use of multivitamins was reported at each visit, and we analyzed only brands that provided folic acid and iron, which was dichotomized as use or not use.
Education: Level of education was reported by women and was considered as low (elementary school and/or incomplete middle school), medium (completed middle school or high school), or high (technical career, bachelor's degree and/or graduate degree).
Parity: Women were considered nulliparous (no previous pregnancy) or multiparous (one or more previous pregnancies).
Preterm birth was considered as birth at 37 weeks of gestation or less, according to the ultrasound in the first trimester; in cases where no ultrasound was available, we calculated the weeks of gestation according to the last menstrual period.
Gestational diabetes mellitus (GDM) was established using the one-step strategy for the oral glucose tolerance test at 24-28 weeks of gestation [22].
Newborn sex: The totality of the characteristics of reproductive structure, functions, phenotype, and genotype, differentiating the male from the female organism [23].

Statistical Analysis
Univariate analysis included the means and standard deviations for normally distributed variables, median and interquartile range for variables with a different distribution, and proportions for categorical variables. We used the quartile categorization of the AHEI-10P score for the bivariate analysis. The maternal baseline characteristics and pregnancy outcomes were described across the quartiles of AHEI-10P. The differences in the AHEI-10P scores according to the maternal characteristics, potential confounders, intermediate variables, and newborn nutritional status were evaluated using the T-student test, U-Mann Whitney test, one-way ANOVA, or Kruskal-Wallis. The chi-square test was used for categorical variables. Post hoc analyses were performed with a Bonferroni test for One-way ANOVA and with the U-Mann Whitney between pairs for non-parametric variables, and the statistical significance was adjusted in order to prevent type I errors (p < 0.008). In order to determine the association between diet quality and newborn weight, length, head circumference, BMI, and z-scores of the nutrition indices, we developed multiple linear regression models, including the AHEI-10P score as an independent variable. Likewise, the association between diet quality (AHEI-10P score) and low birth weight, SGA, stunting, low head circumference, being overweight, and obesity was evaluated with multiple logistic regressions models. In order to test the effect of energy intake on the relationship between diet quality and newborn nutritional status, we created an interaction term between total energy intake and diet quality; for models with a significant interaction term, this variable was reported in the results; otherwise, we report results without the interaction term in the model. We excluded preterm newborns when analyzing weight, length, head circumference, and low birth weight. Finally, we stratified the models according to the presence/absence of preeclampsia or gestational diabetes mellitus. The sample size was calculated using the difference between two independent means (birthweight) of the two different groups (high-and low-quality diets), considering a 5% probability for type I errors (p < 0.05) and a statistical power of 20%. The final sample was 196 women [24]. The statistical power was computed according to the effect size approach for linear multiple regression and logistic models. The analyses were performed using the statistical software package, SPSS Statistics (version 22.0, IBM, Mexico City, Mexico). The statistical significance was considered using a 95%CI and a p value < 0.05.
The mean gestational weight gain in the third trimester (34.3 ± 1.7 gestational weeks) was 8.8 ± 5.2 kg, and 33.6% (n = 76) had excessive and 30.5% (n = 69) insufficient weight gain. Regarding adverse pregnancy outcomes, 8.6% (n = 19) of women had preeclampsia, 10.6% (n = 24) had GDM, 6.6% (n = 15) of newborns were preterm, and 17.3% (n = 39) had low birth weight. Table 2 presents the diet quality score and baseline characteristics according to the AHEI-10P quartiles. The statistical significance (p < 0.05) was tested with the T-student or ANOVA (P a ) test for the means and chi-square or Fisher's exact tests (P b ) for the frequencies. GDM: gestational diabetes mellitus.
Women that lived with a partner had higher diet quality scores than single women (61.7 ± 12.7 vs. 57.8 ± 12.7, p = 0.037). Compared to the first, second, and third quartiles, women in the highest diet quality group had the lowest frequency of preeclampsia and preterm newborns. Even though the statistical significance was obtained for GDM and low birth weight frequencies, no differences were found between the highest and lowest diet quality groups. Table 3 describes the mean energy and nutrient intake according to the AHEI-10P quartiles.

AHEI-10P and Nutrients Intake
The energy intake was higher in the highest diet quartile, compared to the lowest diet quality group (2043.7 vs. 1723.5 kcal). While the macronutrient intakes were higher in the highest quartile, compared to the lowest, in proportion to the total energy, the intake of protein, lipids, and carbohydrates were no different in these groups (Table 3). When adjusted per 1000 kcal, the fiber intake was higher in the highest diet quality group, compared to the lowest diet quality group (15.2 vs. 9.5 g/d); the intake of omega 3 and 6 fatty acids was also higher in women in this diet quartile versus the lowest diet quartile (0.9 g/d vs. 0.6 and 7.2 g/d vs. 5.0 g/d, respectively, p < 0.01) ( Table 3). Regarding the micronutrient intake, we found that the intake of vitamins A, C, and D, folate, calcium, magnesium, selenium, iron, and zinc was higher in the highest diet quality group, compared to the lowest diet quality group (p < 0.05) ( Table 3).

Diet Quality Effect on Anthropometric Markers and Nutritional Status Alterations
According to linear regression models, for every increase of five units in the AHEI-10P score, a higher weight, length, and W/A was observed (overall 72.70 ± 34.3 g, 0.35 ± 0.17 cm and 0.17 ± 0.07 z-score, respectively, p < 0.05; women without preeclampsia and/or GDM: 96.75 ± 34.71 g, 0.53 ± 0.18 cm and 0.23 ± 0.07 z-score, respectively, p < 0.01). In women without preeclampsia and/or GDM, the L/A increased (0.19 ± 0.09, p = 0.03). A trend towards a higher head circumference and HC/A was observed in newborns of women without preeclampsia and/or GDM (0.21 ± 0.12 cm, p = 0.07 and 0.16 ± 0.08 z-score, p = 0.06, respectively) ( Table 5). The risk of low birth weight decreased as the diet quality increased; for every five units of rise in the AHEI-10P score, the risk was 1.22 lower in all women and 1.27 lower in women without preeclampsia and/or GDM (p < 0.01). Likewise, for each five units of rise in the AHEI-10P score, the risk of SGA was 0.92 lower in all women, and it was 1.6 lower in women without preeclampsia and/or GDM (p < 0.01) ( Table 6). Additionally, in women without preeclampsia and/or GDM, the risk of stunting was 0.6 lower for each 5 units of increase in the AHEI-10P score (p = 0.03) ( Table 6).

Discussion
There are few studies evaluating diet quality during pregnancy and its association with newborn nutritional status in Latin America. As far as we know, this is the second study with this purpose in Mexico. We observed that pregnant women with higher diet quality scores (AHEI-10P) had a lower risk of low birth weight and SGA newborns and improved nutritional status markers at birth.
In the previous study conducted in Mexico, using the MDQS, the authors observed a reduced risk of LBW in the highest adherence group, compared to the lowest adherence group (OR: 0.34; 95%CI: 0.11-0.90) [13]. In other studies, that used the AHEI or pregnancy adaptations of the AHEI, Rifas and colleagues, [11], showed a lower risk of SGA in women with a high-quality diet score (OR: 0.92, 95%CI: 0.82-1.02). Similar results were found in a secondary analysis of the prospective cohort, "New Hampshire Birth Cohort Study" [25]. Rodríguez and colleagues, [24], applied an adapted version of the AHEI-2002, and they observed that birth weight and length was higher in women in the fifth diet quality quintile, compared with the lowest quintile (β = 114.1 g; 95%CI: 27.1-201.2 g and β = 0.41 cm; 95%CI: 0.03-0.80 cm). González and colleagues, [26], observed that for each unit of increase in the score of AHEI-10, the W/A z-score increased by 0.01 (95%CI: 0.002-0.02); however, when the models were adjusted, the statistical significance was lost. Similar results have been reported using other diet quality indices. In an analysis of the Australian Longitudinal Study on Women's Health, Gresham and colleagues [27], found that, compared with women in the first quintile, those in the fifth quintile of the Australian recommended food score showed a lower risk of low birth weight (OR = 0.4; 95%CI: 0.2-0.9). In a study in two population-based mother-child cohorts in Spain and Greece, adherence to the Mediterranean diet pattern, using an a priori score, was evaluated. Women with a high adherence had a lower risk of delivering a growth-restricted newborn (RR: 0.5; 95%CI: 0.3-0.9). In smoking mothers, a higher adherence to the Mediterranean diet pattern increased weight and length at birth (Atlantic cohort β = 319 ± 124.3 g and β = 1.3 ± 0.6 cm, respectively and Mediterranean cohort β = 200 ± 81.5 g and β = 0.8 ± 0.4 cm, respectively) [28].
Our results showed that a high-quality diet was related with a greater intake of fiber, omega 3 and 6 fatty acids, vitamins A, C, and D, folate, calcium, iron, magnesium, selenium, and zinc. Dietary patterns involve a matrix of different foods that contain a number of nutrients; many of them are correlated, so it is difficult to separate their effects. However, some of these nutrients are associated with an improvement in neonatal nutrition status [29]. Fiber intake during pregnancy is important for both the mother's health and fetal growth, and it has been associated with a higher birth weight [30]. Omega-3 long chain polyunsaturated fatty acids, in particular, have been associated with a longer gestation, higher birth weight, and less preterm birth [31]. Additionally, essential fatty acids are crucial to fetal development, particularly for cell membranes and the brain [32]. Maternal intakes of vitamins C and D and folate have been associated with higher values for length at birth. Similarly, vitamins A and D intakes have been associated with a higher head circumference in a Japanese cohort [33]. Iron supplementation appears to increase birth weight through an increase in maternal hemoglobin concentrations in the third trimester [34]. Finally, folate, vitamin A, C, and D, magnesium, selenium, and zinc have fetal programming implications that, in turn, are closely related with nutrition status at birth [2].
Besides diet quality, gestational weight gain was another factor associated with a higher newborn body mass. An excessive weight gain was related with higher values of newborn weight and BMI, and it was a protecting factor of SGA. In a population-based cohort study in the United States, Ludwing and colleagues [35], found that newborns of women who gained more than 24 kg during pregnancy were 148.9 g (95%CI: 141.7-156.0 g) heavier at birth than were infants of women who gained 8-10 kg. In a systematic review, Goldstein and colleagues, [36], found that a weight gain below IOM recommendations was related to a higher risk of SGA (OR: 1.53, 95%CI: 1.44-1.64, I2 = 82.8%).
Like excessive weight gain, energy intake was positively associated with weight and length at birth. Crume and colleagues, [37], found that newborn fat mass was increased by 4.2 g and 2.9 g for each 100 kcal from fat and carbohydrates, respectively. While the association between maternal energy intake and length at birth has been less frequently studied, Gala and colleagues, [38], found a significantly positive correlation between percentage of energy intake recommendation (RDA) and length at birth.
Another factor that was a determinant of newborn nutritional status was education level. Our results showed that women with a medium education level had a lower risk of neuro-developmental risk. In the same way, in a secondary analysis of the Generation R Study, it was found that head circumference in the first, third, and sixth month of age was lower in infants of women with a low versus those with a high education level [39]. This is important, considering that HC/A is a chronic nutritional status index, and lower education levels may be related with nutrition inequalities. Multivitamin use (including iron and folic acid) also determined a lower risk of newborn overweight or obesity. Contrary to our results, in a population-based cohort of women without GDM, Hua and colleagues, [40], observed that women that used iron and folic acid supplements were more likely to deliver a macrosomic or LGA infant (OR: 1.32, 95%CI: 1.08-1.49 and OR: 1.42, 95%CI: 1.24-1.61, respectively), as compared with women who did not take supplements. It should be noted that multivitamin use in our study was heterogeneous, and we did not control the dose, administration, duration, and/or nutrient composition.
The development and validation of a diet quality index carries some challenges. First, there is no standard reference for diet quality assessment; and second, dietary assessment has a series of biases that make it difficult to validate. We adapted the Alternate Healthy Eating Index-2010 for use during pregnancy (AHEI-10P). We believe that this version of AHEI is applicable in the Mexican population, considering the high prevalence of coronary heart disease and diabetes, and because it includes different food groups that provide different relevant nutrients in the prenatal stage [41].
In order to guarantee consistency and reduce measurement bias, interviewers were trained with a standardized methodology, and the multiple-pass version of the 24-h recall was used in three occasions to gain a closer view of the usual intake. The multiple-pass version of the 24-h recall reduces memory and portion size estimation error and may aid in providing a better food description [42]. In addition, the diet quality score was positively associated with the intake of healthy nutrients (fiber, magnesium, and folate), supporting construct validity.
As in any other dietary assessment study, heterogeneity is present. Items and cutoff points that integrate diet quality indices are not standardized, considering different food groups and different ratings systems; in addition, the dietary assessment method used can also vary (i.e., 24-h record, food frequency). The database used for analyzing nutritional composition is another source of variability. We used the Food Processor Nutrition Analysis Software (SQL). This program uses an extensive database (including some data from Mexico) and allows for the inclusion of new foods or recipes. Finally, in the case of maternal diet quality, the moment during pregnancy in which a dietary assessment is made differs among studies.
To our knowledge, this is the first study that adapted the AHEI-10P for use in Mexican pregnant women, demonstrating that a high-quality diet is not only associated with a lower risk of chronic diseases, but also with better perinatal outcomes. This study adds to the limited literature on diet quality during pregnancy in low-income countries. The estimated effects in this study reached a statistical power greater than 80%, except for BMI, BMI/A, W/L, L/A, and HC/A. Even though more research is necessary to confirm our findings, this study shows that diet quality assessment during pregnancy could contribute to the implementation of timely nutritional strategies that may contribute to a lower incidence of low birth weight and SGA newborns.
Our study has some weaknesses that should be addressed. While we used several 24-h recalls for estimating dietary intake, it is possible that individual and inter-individual dietary intake variations were not completely measured, and bias may therefore be an issue [43,44]. For the significant effect of diet quality on newborn L/A in the group of women without preeclampsia and/or GDM, the statistical power was low (53%). The relatively small sample size may have introduced a type II error. We did not consider physical activity, intergenesic period, or smoking habits as factors that can determine newborn nutrition status, and we did not consider anemia or pregnancy resolutions [45]. All these aspects should be considered in future studies.

Conclusions
A high-quality diet during pregnancy was associated with a higher newborn weight, length, and reduced risk of low birth weight and SGA. Women who did not develop preeclampsia and/or GDM also showed this association and had a lower risk of stunting. AHEI-10P is an alternative for evaluating diet quality in pregnant women, focusing on important nutrients for maternal and fetal health. More studies evaluating diet (quantity and quality) and its effects on newborn nutrition status in developing countries are necessary.