Cross-sectional association between soda consumption and body mass index in a community-based sample of twins

The impact of adverse childhood events on service support and educational outcomes of children who are autistic: A theory-guided analysis using structural equation modeling

Autistic children who have experienced adverse childhood experiences (ACEs) may have barriers to receiving special education or other developmental services-thus, impacting educational outcomes. Our objective was to model such a pathway using the 2016-2021 National Survey of Children's Health datasets. We extracted data for school outcomes, use of special education and autism-related specialty services and sociodemographic characteristics among autistic children within the data. Associations between sociodemographics and ACEs (categorized as 0, 1-3, and 4+) were tested using design-based X2 tests. We then used structural equation modeling to map the quasi-causal pathways. The sample for our analysis included 4717 autistic children-38.94% were aged 6-10 years, 35.73% of children aged 11-14 years, and 25.32% were between 15 and 17 years-with 88.70% living in metropolitan areas. The X2 showed significant relationships between ACEs and age, ethnoracial groups, and urbanicity among others. The SEM showed ACEs were directly associated with poorer school outcomes (β = -0.14 (0.04), p = 0.002) and through their inverse relationship with support services (β = -0.08 (0.04), p = 0.023)- when support services were increased, school outcomes improved (β = 0.62, p < 0.001). Findings suggested ACEs have a significant direct and indirect impact on school outcomes of autistic children, and 10.76% of children who are autistic have experienced four or more ACEs-which were more likely to occur with severe autism symptomatology and in rural areas. Results highlight the need for communities to recognize the potential long-term impact of ACEs on the academic outcomes of autistic children.

Epigenome-wide association study of systemic effects of obesity susceptibility in human twins

The current study was designed to use an epigenome-wide association approach (EWAS) to identify potential systemic DNA methylation alterations that are associated with obesity using 22 discordant twin pairs. Buccal cells (from a cheek swab) were used as a non-obesity relevant purified marker cell for the epigenetic analysis. Analysis of differential DNA methylation regions (DMRs) was used to identify epigenetic associations with metabolic and dietary measures related to obesity with discordant twins. An edgeR analysis provided a DMR signature with p < 1e-04, but statistical significance was reduced due to low sample size and known multiple origins of obesity. A weighted gene coexpression network analysis (WGCNA) was performed and identified modules (p < 0.005) of epigenetic sites that correlated with different metabolic and dietary measures. The DMR and WGCNA epigenetic sites were near genes (e.g., CIDEC, SPP1, ZFPG9, and POMC) with previously identified obesity associated pathways (e.g., metabolism, cholesterol, and fat digestion). Observations demonstrate the feasibility of identifying systemic epigenetic biomarkers for obesity, which can be further investigated for clinical relevance in future research with larger sample sizes. The availability of a systemic epigenetic biomarker for obesity susceptibility may facilitate preventative medicine and clinical management of the disease early in life.

Dietary Mediators of the Genetic Susceptibility to Obesity-Results from the Quebec Family Study

BACKGROUND

Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity.

OBJECTIVE

This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity.

METHODS

This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach.

RESULTS

The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC.

CONCLUSIONS

The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.

The genetic architecture of the association between eating behaviors and obesity: combining genetic twin modeling and polygenic risk scores

BACKGROUND

Obesity susceptibility genes are highly expressed in the brain suggesting that they might exert their influence on body weight through eating-related behaviors.

OBJECTIVES

To examine whether the genetic susceptibility to obesity is mediated by eating behavior patterns.

METHODS

Participants were 3977 twins (33% monozygotic, 56% females), aged 31-37 y, from wave 5 of the FinnTwin16 study. They self-reported their height and weight, eating behaviors (15 items), diet quality, and self-measured their waist circumference (WC). For 1055 twins with genome-wide data, we constructed a polygenic risk score for BMI (PRSBMI) using almost 1 million single nucleotide polymorphisms. We used principal component analyses to identify eating behavior patterns, twin modeling to decompose correlations into genetic and environmental components, and structural equation modeling to test mediation models between the PRSBMI, eating behavior patterns, and obesity measures.

RESULTS

We identified 4 moderately heritable (h2 = 36-48%) eating behavior patterns labeled "snacking," "infrequent and unhealthy eating," "avoidant eating," and "emotional and external eating." The highest phenotypic correlation with obesity measures was found for the snacking behavior pattern (r = 0.35 for BMI and r = 0.32 for WC; P < 0.001 for both), largely due to genetic factors in common (bivariate h2 > 70%). The snacking behavior pattern partially mediated the association between the PRSBMI and obesity measures (βindirect = 0.06; 95% CI: 0.02, 0.09; P = 0.002 for BMI; and βindirect = 0.05; 95% CI: 0.02, 0.08; P = 0.003 for WC).

CONCLUSIONS

Eating behavior patterns share a common genetic liability with obesity measures and are moderately heritable. Genetic susceptibility to obesity can be partly mediated by an eating pattern characterized by frequent snacking. Obesity prevention efforts might therefore benefit from focusing on eating behavior change, particularly in genetically susceptible individuals.

Decomposition of Gender Differences in Body Mass Index in Saudi Arabia using Unconditional Quantile Regression: Analysis of National-Level Survey Data

Understanding gender differences in body mass index (BMI) between males and females has been much debated and received considerable attention. This study aims to decompose gender differentials in the BMI of people of the Kingdom of Saudi Arabia. The study decomposed the BMI gender gap into its associated factors across the entire BMI distribution by using counterfactual regression methods. The main method of analysis was newly developed unconditional quantile regression-based decomposition, which applied Blinder-Oaxaca decomposition using data from the Saudi Health Interview Survey. Gender differentials were found in the BMI, with females showing a higher BMI than males. The aggregate decomposition showed that both the covariate effect and the structural effect were significant at the 25th and 50th quantiles. Detailed decomposition indicated that income level and employment status as well as soda consumption and the consumption of red meat were significantly correlated in explaining gender differentials in BMI across various quantiles, but the magnitude varied by quantile. Our study suggests the government should consider introducing programs that specifically target women to help them reduce BMI. These programs could include organizing sporting events at the workplace and at the national level. Furthermore, the effect of soda consumption could be reduced by levying a tax on beverages, which might reduce the demand for soda due to the increased price.