The association between vitamin C dietary intake and its serum levels with anthropometric indices: A systematic review and meta-analysis

Mazaheri‐Tehrani, Sadegh; Yazdi, Maryam; Heidari‐Beni, Motahar; Yazdani, Zahra; Kelishadi, Roya

doi:10.1016/j.ctcp.2023.101733

Cited by 1 publication

(2 citation statements)

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“…Research studies have demonstrated that both dietary and serum vitamin C levels have an inverse relationship with BMI and waist circumference. 60 In contrast, obesity has been associated with lower levels of ketone bodies in circulation, indicating a reduced ability to produce and utilize ketones. 61 The study identifies 30 pathways specific to 1 & 3.…”

Section: F I G U R Ementioning

confidence: 99%

“…In terms of unique pathways for each differential network, seven pathways were found exclusively in 1 & 2, including degradation, ketogenesis and vitamin C pathways. Research studies have demonstrated that both dietary and serum vitamin C levels have an inverse relationship with BMI and waist circumference 60 . In contrast, obesity has been associated with lower levels of ketone bodies in circulation, indicating a reduced ability to produce and utilize ketones 61 …”

Section: Case Studymentioning

confidence: 99%

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Joint modeling of association networks and longitudinal biomarkers: An application to childhood obesity

Cremaschi,

De Iorio,

Kothandaraman

et al. 2024

Statistics in Medicine

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The prevalence of chronic non‐communicable diseases such as obesity has noticeably increased in the last decade. The study of these diseases in early life is of paramount importance in determining their course in adult life and in supporting clinical interventions. Recently, attention has been drawn to approaches that study the alteration of metabolic pathways in obese children. In this work, we propose a novel joint modeling approach for the analysis of growth biomarkers and metabolite associations, to unveil metabolic pathways related to childhood obesity. Within a Bayesian framework, we flexibly model the temporal evolution of growth trajectories and metabolic associations through the specification of a joint nonparametric random effect distribution, with the main goal of clustering subjects, thus identifying risk sub‐groups. Growth profiles as well as patterns of metabolic associations determine the clustering structure. Inclusion of risk factors is straightforward through the specification of a regression term. We demonstrate the proposed approach on data from the Growing Up in Singapore Towards healthy Outcomes cohort study, based in Singapore. Posterior inference is obtained via a tailored MCMC algorithm, involving a nonparametric prior with mixed support. Our analysis has identified potential key pathways in obese children that allow for the exploration of possible molecular mechanisms associated with childhood obesity.

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Section: F I G U R Ementioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%