Sociodemographic characteristics determine dietary pattern adherence during pregnancy

Abstract

Objective: Sociodemographic factors may affect adherence to specific dietary patterns during pregnancy. The present study aimed to identify dietary patterns during pregnancy and associated factors among Brazilian pregnant women. Design: A cross-sectional analysis. Dietary intake was evaluated with a semiquantitative FFQ during the first postpartum week; the time frame included the second and third gestational trimesters. Principal component analysis was used to identify dietary patterns during pregnancy. Sociodemographic data were obtained using a structured questionnaire. Multiple linear regressions were applied to test the associations between the sociodemographic factors and dietary patterns. Setting: Mesquita, Rio de Janeiro, Brazil, 2011. Subjects: Postpartum women (n 327) who were 18-45 years of age and Mesquita residents. Results: Three different dietary patterns were identified: 'healthy' (mainly comprising legumes, vegetables and fruits), 'mixed' (mainly comprising candy, butter and margarine, and snacks) and 'traditional' (mainly comprising beans and rice). Women with a higher monthly per capita family income (β = 0·0006; 95 % CI 0·0001, 0·001; P = 0·011) and women of older age (β = 0·021; 95 % CI −0·001, 0·042; P = 0·058) were more likely to adhere to the 'healthy' dietary pattern. Women with higher parity were less likely to adhere to the 'healthy' pattern (β = − 0·097; 95 % CI −0·184, −0·009; P = 0·030) and were more likely to adhere to the 'traditional' pattern (β = 0·098; 95 % CI 0·021, 0·175; P = 0·012). Although not statistically significant, older women were less likely to adhere to the 'mixed' (β = − 0·017; 95 % CI −0·037, 0·003; P = 0·075) and 'traditional' (β = − 0·018; 95 % CI −0·037, 0·001; P = 0·061) dietary patterns. Conclusions: Monthly per capita family income, parity and maternal age were factors associated with adherence to a healthy diet during pregnancy.

Maternal nutrition practices in Uttar Pradesh, India: Role of key influential demand and supply factors

“…Additional nonmodifiable factors associated with dietary diversity included caste, education, and economic status. Our results are consistent with previous literature wherein maternal knowledge and socio‐economic status were found to be associated with dietary diversity (de Castro et al, ; Doyle, Borrmann, Grosser, Razum, & Spallek, ; Rosen et al, ; Shamim et al, ). Women belonging to higher caste and income groups were more likely to have a diverse diet, suggesting a resource constraint in adoption of diet recommendations beyond improved knowledge and counselling services.…”

Efeito de uma intervenção educativa na gravidez: ensaio clínico randomizado em cluster

“…(14) Some authors declared that family income is a factor that directly interferes with the quality of the diet of the examined pregnant women, and that the higher the family income, the higher the adherence to a healthy eating plan. (15) In this scenario, the consumption of regional foods is important to pregnant women because, in addition to their bioavailability and low cost, they are nutritious and enrich diet with fibers, Regarding the effect of the intervention caused by the use of the educational booklet, the results indicate an adequate KAP level on the IG in the seventh and thirtieth days after the intervention in comparison with the level shown in the CG. The IG had p<0.001, with increased chances of adequate knowledge on the seventh (OR = 68.01 and CI = 24.48 -188.97) and thirtieth days (OR = 83.57 and CI = 26.18 -266.72).…”

Socioeconomic predictors of dietary patterns among Guatemalan adults

“…We used the same criteria as described by others (Fernandez-Alvira et al 2014; Kesse-Guyot et al 2009) to retain dietary patterns, namely 1) eigenvalues greater than one, and 2) interpretability of the dietary patterns. As there is no established agreement for selecting the factor loading threshold of a pattern, food items with absolute factor loading >0.24 were considered to characterize the dietary pattern, which is similar or even higher than the ones used in other studies (de Castro et al 2016; Luger et al 2016). Dietary patterns were interpreted based on the foods with highest absolute loadings; food items with positive loadings were positively associated with the patterns and vice-versa.…”