Socioeconomic status throughout life and body mass index: a systematic review and meta-analysis.
Luna Strieder VieiraIsabel Oliveira BierhalsJuliana Dos Santos VazFernanda de Oliveira MellerFernando César WehrmeisterMaria Cecilia Formoso AssunçãoPublished in: Cadernos de saude publica (2019)
This article aimed to systematically review the association between socioeconomic status according to the life course models and the body mass index (BMI) in adults. A review was performed following the guidelines of the PRISMA. The studies were identified in the MEDLINE/PubMed, LILACS and Web of Science databases. The eligible articles investigated the association between at least one life course model (risk accumulation, critical period or social mobility) and BMI. In order to assess the quality of the selected articles, the NOS checklist was applied to each study. Eleven articles were selected for the systematic review, and seven articles were selected for the meta-analysis. The average score and the median in the NOS checklist were 6.4, within a maximum possible score of 8 points. The most used model was social mobility. Regarding meta-analysis, there was association between lower life course socioeconomic status and BMI among women. BMI mean difference (MD) was higher among those who remained with low socioeconomic status throughout life when compared with those who maintained a high socioeconomic status (MD: 2.17, 95%CI: 1.48; 2.86). Before that, the BMI MD was higher among those with upward mobility, compared with those who maintained a high socioeconomic status throughout life (MD: 1.20, 95%CI: 0.73; 1.68). The risk of overweight was also higher among women who maintained low socioeconomic status (summary RR: 1.70, 95%CI: 1.05; 2.74); however, according to the GRADE, the studies presented very low quality evidence. For men, no association was observed. Having low socioeconomic status sometime during life is associated with higher BMI in adulthood.
Keyphrases
- body mass index
- systematic review
- weight gain
- meta analyses
- molecular dynamics
- physical activity
- healthcare
- public health
- metabolic syndrome
- pregnant women
- high resolution
- depressive symptoms
- type diabetes
- adipose tissue
- insulin resistance
- machine learning
- deep learning
- nitric oxide synthase
- single molecule
- atomic force microscopy
- middle aged