Dietary intake, Nutritional status, and Health outcomes among Vegan, Vegetarian and Omnivore families: results from the observational study

Reports hub

All reports use an initialization file and custom R functions file. The initialization file includes basic data preprocessing and wrangling, loading packages, etc. The custom R functions contains definition and description of each custom function used for this project in Roxygen format.

A report, 368_G_Methods, describes the statistical methodology for the entire study.

The report 368_A_Wrangling_Summary provides basic data exploration.

Section 2 explores clinical characteristics across diet groups.
- Section 2.2 presents medians and quartiles of clinical characteristics for each age (sub)group.
- Section 2.3 shows the distribution of numerical variables (the clinical characteristics).
- Section 2.4 visualizes the differences in clinical characteristics across diet groups.
Section 3 details food and nutrition intake across diet groups.

Reports 368_D_[…] present mixed-effects models across different clinical characteristics and adjusting the effect of diet for confounders as sex, age, breastfeeding status (children) and relevant supplementation.
368_D1_MixedEff_all_child provides robust mixed-effects models for children.

368_D4_MixedEff_adult presents mixed-effects models for adults.

The report 368_E_MixedEff_Summary reports results from mixed-effects models across age groups, in summary tables, volcano plots (adjusted diet effect), and heatmaps (importance of diet, confounders and magnitude of family clustering, estimated via AIC).

The report 368_F_ElasticNet shows elastic net logistic regression, i.e., models learning to discriminate between diet groups based on clinical characteristics.

--- title: "Dietary intake, Nutritional status, and Health outcomes among Vegan, Vegetarian and Omnivore families: results from the observational study" subtitle: "Reports hub" format: html: embed-resources: true keep-md: false toc: false toc-expand: 3 toc-depth: 4 toc-location: left number-sections: false number-depth: 4 code-fold: show code-tools: true code-summary: "Open code" grid: body-width: 1000px sidebar-width: 600px margin-width: 100px editor: source project: type: default output-dir: output theme: darkly highlight-style: github-dark fontsize: 12 px code-block-bg: '#2D2D31' fontcolor: '#C4C4C4' monobackgroundcolor: '#3B3B3B' bibliography: ../references.bib --- ---------------------------------------------------------------------------------------------------- # Reports hub All reports use an initialization file and custom R functions file. The [initialization](https://github.com/filip-tichanek/kompas_clinical/blob/main/368_initiation.R) file includes basic data preprocessing and wrangling, loading packages, etc. The custom [R functions](https://github.com/filip-tichanek/kompas_clinical/blob/main/368_functions.R) contains definition and description of each custom function used for this project in Roxygen format. A report, [368_G_Methods](html/368_G_Methods.html), describes the statistical methodology for the entire study. The report [368_A_Wrangling_Summary](html/368_A_Wrangling_Summary.html) provides basic data exploration. - **Section 2** explores clinical characteristics across diet groups. - **Section 2.2** presents medians and quartiles of clinical characteristics for each age (sub)group. - **Section 2.3** shows the distribution of numerical variables (the clinical characteristics). - **Section 2.4** visualizes the differences in clinical characteristics across diet groups. - **Section 3** details food and nutrition intake across diet groups. Reports 368_D_[...] present mixed-effects models across different clinical characteristics and **adjusting the effect of diet for confounders as sex, age, breastfeeding status (children) and relevant supplementation**. [368_D1_MixedEff_all_child](html/368_D1_MixedEff_all_child.html) provides robust mixed-effects models for children. [368_D4_MixedEff_adult](html/368_D4_MixedEff_adult.html) presents mixed-effects models for adults. The report [368_E_MixedEff_Summary](html/368_E_MixedEff_Summary.html) reports results from mixed-effects models across age groups, in summary tables, volcano plots (adjusted diet effect), and heatmaps (importance of diet, confounders and magnitude of family clustering, estimated via AIC). The report [368_F_ElasticNet](html/368_F_ElasticNet.html) shows elastic net logistic regression, i.e., models learning to discriminate between diet groups based on clinical characteristics.