Gender and social mobility modify the effect of birth weight on total and central obesity

Analyzing the Sociodemographic Factors Impacting the Use of Virtual Reality for Controlling Obesity

Obesity is one of the most pressing issues in society today. Virtual reality has been used in the design of tools that promotes obesity control. However, the design of current VR tools lacks the involvement of prospective users and health practitioners. Such engagement is crucial in gathering semantic information that identifies stakeholders’ needs and ensures that all aspects of health are considered. Therefore, this paper aims to study the sociodemographic factors and individual-level characteristics and preferences that make the design of any obesity-control VR tool effective and satisfactory for a wide range of users. The paper also aims to solicit opinions of health practitioners to identify best health aspects that should be available in the design of any VR tool for obesity control. Organizations, businesses, and people will be able to readily augment such VR technologies on the semantic web, as well as on personal and mobile devices.

Environmental mismatch and obesity in humans: The Jerusalem Perinatal Family Follow-Up Study

BACKGROUND

According to the hypothesis of Gluckman and Hanson, mismatch between the developmental and postdevelopmental environments may lead to detrimental health impacts such as obesity. While several animal studies support the mismatch theory, there is a scarcity of evidence from human-based studies.

OBJECTIVES

Our study aims to examine whether a mismatch between the developmental and young-adult environments affect obesity in young adults of the Jerusalem Perinatal Family Follow-Up Study.

METHODS

Data from The Jerusalem Perinatal Family Follow-Up Study birth cohort was used to characterize early and late environments using offspring and parental sociodemographic and lifestyle information at birth, age 32 (n = 1140) and 42 (n = 404). Scores characterizing the early and late environments were constructed using factor analysis. To assess associations of mismatch with obesity, regression models were fitted using the first factor of each environment and adiposity measures at age 32 and 42.

RESULTS

Having a stable non-beneficial environment at birth and young-adulthood was most strongly associated with increased adiposity, while a stable beneficial environment was most favorable. The transition from a beneficial environment at birth to a less beneficial environment at young-adulthood was associated with higher obesity measures, including higher BMI (β = 0.979; 95% CI: 0.029, 1.929), waist circumference (β = 2.729; 95% CI: 0.317, 5.140) and waist-hip ratio (β = 0.017; 95% CI: 0.004, 0.029) compared with those experiencing a beneficial environment at both time points. Transition from a less beneficial environment at birth to a beneficial environment at adulthood was also associated with higher obesity measurements (BMI -β = 1.116; 95% CI: 0.085, 2.148; waist circumference -β = 2.736; 95% CI: 0.215, 5.256).

CONCLUSIONS

This study provides some support for the mismatch hypothesis. While there is indication that an accumulation of the effects of the non-beneficial environment has the strongest detrimental impact on obesity outcomes, our results also indicate that a mismatch between the developmental and later environments may result in maladaptation of the individual leading to obesity.

BIRTH WEIGHT AND OVERWEIGHT IN ADOLESCENTS: THE ERICA PROJECT IN THE CITY OF RECIFE, PERNAMBUCO

Objective:

To verify the association of anthropometric parameters at birth, socioeconomic and biological variables, physical activity, and parental nutritional status with overweight and abdominal obesity in adolescents.

Methods:

A cross-sectional study was carried out on 39 public and private schools in Recife (state of Pernambuco, Brazil). The sample consisted of 1,081 teenagers aged from 12 to 17 years. Data were collected from the Study of Cardiovascular Risks in Adolescents (ERICA). Body mass index according to age (BMI-for-age), waist circumference (WC), and waist-to-height ratio (WtHR) were considered as outcome variables, whereas the explanatory variables were birth weight, Röhrer’s Ponderal Index (RPI), biological and socioeconomic variables, physical activity, and parental nutritional status. The crude and adjusted prevalence ratios (PR) for the studied association were estimated by Poisson Regression.

Results:

The multivariate Poisson regression showed that the variable that remained significantly associated with overweight in adolescence was maternal overweight, PR=1.86 (95% confidence interval [95%CI] 1.09-3.17). High birth weight also remained significantly associated with abdominal obesity assessed by WC, PR=3.25 (95%CI 1.0-9.74).

Conclusions:

High birth weight may be a marker for abdominal obesity in adolescence; and high maternal BMI, for overweight.

Socioeconomic status throughout life and body mass index: a systematic review and meta-analysis

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.

Birth weight and type 2 diabetes: A meta-analysis

The prevalence of T2DM is increasing around the world on a yearly basis. A meta-analysis was conducted to analyze the association between birth weight and incidence of type 2 diabetes mellitus (T2DM). A literature search was performed from January 1990 to June 2016 in PubMed, ScienceDirect, SpringerLink, China National Knowledge Infrastructure and Chinese Biomedical Literature Database. After reviewing characteristics of all the included studies systematically, a meta-analytical method was employed to calculate the pooled odds ratios (ORs) and associated 95% confidence intervals (CI) from random-effects models. Heterogeneity was assessed by Q-statistic test. Funnel plot, Begg's and Egger's linear regression tests were applied to evaluate publication bias. A sensitivity analysis was also performed to assess the robustness of results. According to inclusion and exclusion criteria, 8 studies were selected to be included in the meta-analysis. Compared with normal birth weight (2,500–4,000 g), low birth weight (<2,500 g) was associated with an increased risk of T2DM (OR, 1.55; 95% CI, 1.39–1.73; P<0.001). No significant difference was observed between high birth weight (>4,000 g) and normal birth weight in terms of the risk of T2DM (OR, 0.98; 95% CI, 0.79–1.22). Compared with high birth weight, low birth weight was associated with an increased risk of diabetes mellitus (OR, 1.58; 95% CI, 1.30–1.93; P<0.001). These findings indicated that there may be an inverse linear association between birth weight and T2DM.