Dietary patterns in internal migrants in a continental country: A population-based study

Dietary patterns and adiposity over time - analysis of the ELSA-Brasil

PURPOSE

Combining different statistical methods to identify dietary patterns (DP) may provide new insights on how diet is associated with adiposity. This study investigated the association of DP derived from three data-driven methods and adiposity indicators over time.

METHODS

This study used data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). DP were identified at baseline applying three statistical methods: Factor Analysis (FA), Treelet Transform (TT), and Reduced Rank Regression (RRR). The association between DP and adiposity indicators (weight, body mass index, waist circumference, body fat percentage and fat mass index) over the period of 8.2 years of follow-up was assessed by linear mixed-models.

RESULTS

Convenience DP, marked by unhealthy food groups, was associated with higher adiposity over the follow-up period, regardless of the method applied. The DP identified by TT and marked by high consumption of rice and beans was associated with lower adiposity, whereas the similar DP identified by FA, but additionally characterised by consumption of poultry and red meat was associated with higher adiposity. Prudent DP, marked by plant-based food groups and fish, identified by FA was associated with lower adiposity across the median follow-up time.

CONCLUSION

Applying different methods to identify DP showed that a convenience DP was associated with higher adiposity independent of the method applied. We also identified the nuances within adherence to a Brazilian traditional dietary pattern characterised by the consumption of rice and beans, that only when combined with reduced consumption of animal protein and unhealthy foods was associated with lower adiposity over time.

Different statistical methods identify similar population-specific dietary patterns: an analysis of Longitudinal Study of Adult Health (ELSA-Brasil)

In recent decades, different data-driven approaches have emerged to identify dietary patterns (DP) and little is discussed about how these methods are able to capture diet complexity within the same population. This study aimed to apply three statistical methods to identify the DP of the Longitudinal Study of Adult Health (ELSA-Brasil) population and evaluate the similarities and differences between them. Dietary data were assessed at baseline in the ELSA-Brasil study using a FFQ. DP were identified by applying three statistical methods: (1) factor analysis (FA), (2) treelet transform (TT) and (3) reduced rank regression (RRR). The characteristics of individuals classified in the last tertile of each DP were compared. Cross-classification and Pearson's correlation coefficients were assessed to evaluate the agreement between individuals' adherence to DP of the three methods. A similar convenience DP was identified for all three methods. FA and TT also identified a similar prudent DP and a DP highly loaded for the food groups rice and beans. Individuals classified in the third tertile of similar DP of each method presented similar socio-demographic and nutrient intake characteristics. Regarding the cross-classification, prudent DP from FA and TT presented a higher level of agreement (75 %), while convenience DP from TT and RRR presented the lowest agreement (44·8 %). The different statistical methods were able to capture the populations' DP in a similar way while highlighting the particularities of each method.

Dietary patterns of Chinese women of childbearing age during pregnancy and their relationship to the neonatal birth weight

OBJECTIVE

To examine the type of maternal dietary patterns during pregnancy and the distribution characteristics of children's birth weight and the association between dietary patterns and neonatal birth weight in China.

METHODS

Data were derived from a cross-sectional program named "The prevalence and risk factors of birth defects in Shaanxi Province" in July to November in 2013. A stratified multistage random sampling method was used to select women and their children. The mother's diet during pregnancy was investigated using semi-quantitative food frequency questionnaire (FFQ) to collect the frequency and amount of food consumption, and the newborn birth weight as well as related social demographic information was collected at the same time. In our study, 0-1 year old children and their mothers with complete dietary survey data were selected as research objects. The main dietary patterns were identified according to factor analysis, and latent class analysis (LCA) was used to investigate the social demographic factors affecting dietary patterns. The logistic regression model was used to assess the association between birth weight and maternal dietary patterns during pregnancy by establishing three adjusting models and the data were stratified for further analysis by urban-rural and regions.

RESULTS

A total of 15,980 participants were involved in this study. Four dietary patterns were identified: "vegetarian pattern", "balance pattern", "traditional pattern" and "processing pattern". Compared with moderate tertile, women in the highest tertile of adherence to vegetarian pattern increased the risk of low birth weight in offspring in rural areas (OR = 1.61, 95%CI:1.06-2.93) and middle region (OR = 1.75, 95%CI:1.18-2.62), and the traditional pattern had greater odds of lower birth weight in the middle region (OR = 1.55, 95%CI:1.05-3.75). The processing pattern was found a protective factor for the occurrence of low birth weight in rural areas (OR = 0.98, 95%CI:0.43-0.99) but was a risk factor for low birth weight in the southern region (OR = 8.83, 95%CI:1.22-15.16). The balance pattern was a protective factor for the occurrence of low birth weight in the northern region(OR = 0.35, 95%CI:0.14-0.83).

CONCLUSION

The vegetarian and traditional pattern may be positively related to a higher risk of low birth weight while the balanced pattern may keep birth weight of offspring within the appropriate range. Health education of balanced diet and individual nutrition guidance during pregnancy should be strengthened, to make the dietary structure during pregnancy are more reasonable, reduce the occurrence of adverse birth weight of newborns.

Influence of internal migration on body mass index: Results of the ELSA-Brasil study

OBJECTIVES

To investigate the association between internal migration and body mass index (BMI) in the adult population with data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) and to determine whether the association differs by the urban hierarchical levels (or influence regions) of Brazilian municipalities.

METHODS

Baseline data from 13 084 participants aged 35 to 74 (2008-2010) in the ELSA-Brasil were analyzed. A migrant was defined as an individual whose municipality of residence at the beginning of schooling (origin) was different from the municipality of residence at the study baseline (destination). The origin and destination municipalities were classified by urban hierarchical levels, or influence regions, and migration was categorized as nonmigrant, stable migrant, downward migrant, or upward migrant.

RESULTS

Of the ELSA-Brasil participants, 51% were migrants. Using gamma regression models, it was observed that for women and men, upward migration was associated with lower mean BMI after adjusting for age, mother's education level, participant's education level, and income. Downward migration, on the other hand, was associated with the highest mean BMI, but this result was statistically significant only for women.

CONCLUSION

These findings highlight the role of environmental factors on nutritional status, noting that the effects on BMI may be positive or negative, depending on the trajectory of displacements between origin and destination.