3.1.1 Maternal social demographic characteristics A total of 15,980 pregnant women who met the requirements were included in the study, aged 17 to 47 years (27.6 ± 4.5). There were 8501 (53.2%) male infants and 7479 (46.8%) female infants; they were aged between 0 to 12 months (6.6±2.6), and the birth weight was 1050-6250g (3279.9±454.6g). The basic characteristics of the research object were shown in Table 1.
3.1.2 Newborn birth weight In this study, the average weight of newborns in urban areas was 3339.2±461.6g, 3230.7±451.0g in rural areas, 3263.7±453.3g in southern Shaanxi, 3290.3±464.7g in northern Shaanxi, and 3252.6±450.9g in middle region. When there was no stratification, 783 newborns with birth weight of <2500g, accounting for 4.9%, and 703 newborns with birth weight >4000g, accounting for 4.4%; the incidence of SGA and LGA was 14.7% and 7.6%, respectively. (Table 2).
3.2 Pregnancy dietary pattern
3.2.1 Dietary patterns during pregnancy in women of childbearing age Factor analysis was used to extract four dietary patterns during pregnancy: "vegetarian pattern", "balance pattern", "traditional pattern" and "processing pattern". Food groups with high factor loadings on dietary pattern 1 included 3 kinds of vegetables, 4 kinds of fruits, pasta, rice/porridge, soy products, fungus mushrooms, it was worth noting that animal protein foods were absent in this model. Food groups with high factor loadings on dietary pattern 2 included 6 kinds of animal protein foods, 3 kinds of vegetables, pasta, rice/porridge, soy products, potatoes, fungus mushrooms, kelp seaweed, melon fruits, nuts, etc, which was characterized by a variety of foods. Dietary pattern 3 was characterized by high factor loadings for rice/porridge, pasta, steamed rice noddles, eggs, milk and dairy, soy products, potatoes, vegetables and fruits, etc. Dietary pattern 4 was characterized by high factor loadings for preserved foods and beverages, snacks, and also included a small amount of vegetables, soy products and staple foods. Among the four dietary structures, the vegetarian pattern was a predominant pattern, which explained the 13.63% of the variability in the predictors, and the latter three patterns explained 9.28%, 7.62% and 5.96% of the variability in the predictors, respectively.(Table 3).
3.2.2 Dietary patterns during pregnancy were studied by LCA We chose 4 classes by LCA analysis because at which time the value of AIC (1307.28) and BIC (1311.01) were the smallest, the optimal model was obtained. This result was consistent with the classification of dietary patterns obtained by factor analysis. Figure 1 showed the intake of 14 foods in each dietary pattern (with the median intake as the limit, the group was divided into three groups: greater than, less than the median and no intake). The LCA-Traditional class had higher intake of cereals, potatoes, beans, vegetables, fruits, livestock and poultry, and eggs. The LCA-Balance class had higher intake of cereals, potatoes, beans, vegetables, fruits, fungus mushrooms, livestock and poultry meat, fish, shrimps, crabs, shellfish, milk, and nuts. The LCA-Vegetarian class had higher intake of cereals, beans, vegetables, fruits, livestock and poultry. The LCA-Processing class had higher intake of cereals, vegetables, snacks, instant food, and beverages.
3.2.3 Social demographic factors affecting the classification of dietary patterns In this study, 5,881 subjects were included in the vegetarian pattern, 4,778 in the balance pattern, 4,442 in the traditional pattern, and 879 in the processing pattern. The social demographic characteristics that had an impact on the classification of dietary patterns included family monthly expenditure (P=0.018), the higher the monthly household expenditure, the more inclined the balance pattern and processing pattern, while the lower ones were more likely to choose the vegetarian pattern. Urban women were more inclined to choose balanced pattern, rural women were more inclined to choose vegetarian pattern (P=0.020). The higher the education level of the mother, the more inclined to choose the balanced pattern, the lower the education level, the more inclined to vegetarian pattern and processing pattern(P=0.035). Women with gestational age of less than 37 weeks tended to choose the traditional model, while women with gestational age of more than 37 weeks tended to choose the balanced model (P=0.003). Women in southern region mostly relied on balanced pattern and processing pattern, women in northern region were mostly based on traditional pattern, while women in middle region were mostly vegetarian pattern (P<0.001). (Table 4).
3.2.4 Nutrient intake under different dietary patterns Processing pattern (average energy intake was 2789±853kcal) and balanced pattern (average energy intake was 2527±895kcal) compared to traditional pattern (average energy intake was 2395±824kcal) and vegetarian pattern (average energy intake was 2325±899kcal), more easy to intake more energy (P=0.005); balanced pattern (average protein intake of 78 ± 9 g) was more adequate than the other three groups of protein intake (P<0.001); processing pattern (average carbohydrate intake was 389±133g) and traditional pattern (average carbohydrate intake was 377±137g) compared to the balanced pattern (average carbohydrate intake was 349±132g) and the vegetarian pattern (average carbohydrate intake was 369±126g), were more likely to intake more carbohydrate (P=0.040); processing pattern (average cholesterol intake of 220±105g) was higher than the other three groups of cholesterol intake (P<0.001); balanced pattern (average vitamin A intake was 637±452μgRE) was more adequate than the other three groups of vitamin A intake (P=0.026); balanced pattern (average vitamin B12 intake was 2.5 ± 0.5 μg, average folic acid intake was 559 ± 227 μgDFE, average calcium intake was 906 ± 365 mg) was higher than the other three groups of vitamin B12, folic acid, calcium intake (P<0.001); the balanced pattern (average iron intake was 33 ± 12 mg) was more adequate than the other three groups of iron intake (P = 0.044). For other nutrients, there was no difference between the four dietary patterns. (Table 5).
3.3 The association between dietary patterns during pregnancy and neonatal birth weight Unstratified analysis, women in the lowest tertile of adherence to vegetarian pattern had lower risk of low birth weight in offspring compared with moderate tertile (OR=0.67, 95%CI: 0.46-0.98), women in the highest tertile increased the risk of low birth weight in offspring (OR=1.82, 95%CI: 1.36-3.77), and the results remained unchanged after adjusting for covariates. In rural areas, vegetarian pattern was positively associated with a higher risk of low birth weight (OR=1.61, 95%CI: 1.06-2.93), the processing pattern was found a protective factor for the occurrence of low birth weight (OR=0.98, 95%CI: 0.43-0.99). The same results were not shown in urban areas.
After stratification by region, compared with the moderate processing pattern, T1 and T3 groups in pregnant women could increase the risk of low birth weight in offspring in southern Shaanxi region, the T3 group was statistically significant (OR=8.83, 95%CI: 1.22-15.16). In northern Shaanxi region, the balanced pattern T1 group could increase the risk of low birth weight (OR=1.35, 95%CI: 1.14–3.85), the T3 group reduced the risk of low birth weight (OR=0.35, 95%CI: 0.14-0.83). In middle region, women in the highest tertile of adherence to vegetarian pattern had higher risk of low birth weight in offspring (OR=1.75, 95%CI: 1.18-2.62). The traditional pattern T1 group could reduce the risk of low birth weight in offspring (OR=0.80, 95%CI: 0.39-0.93), the T3 group increased the risk of low birth weight (OR=1.55, 95%CI: 1.05-3.75). (Table 6).