Document Type
Article
Disciplines
3. MEDICAL AND HEALTH SCIENCES, Public and environmental health
Abstract
Dietary patterns and body mass index (BMI) play a significant role in the development of noncommunicable diseases (NCDs), which are the leading cause of mortality worldwide, including Ireland. A cross-sectional survey was conducted across Ireland to collate respondents’ socioeconomic profiles, health status, and dietary patterns with a representative sample size of 957 adult respondents. Principal component analysis (PCA) and statistical analyses were subsequently employed. To the author’s knowledge, this is the first study to use recent (2021) nationally representative data to characterise dietary patterns in Ireland via dimensionality reduction. Five distinct dietary patterns (“meat-focused”, “dairy/ovo-focused”, “vegetable-focused”, “seafood-focused”, and “potatofocused”) were identified and statistically characterised. The “potato-focused” group exhibited the highest mean BMI (26.88 kg/m2), while the “vegetable-focused” group had the lowest (24.68 kg/m2). “Vegetable-focused” respondents were more likely to be associated with a categorically healthy BMI (OR = 1.90) and urban residency (OR = 2.03). Conversely, “meat-focused” respondents were more likely to have obesity (OR = 1.46) and rural residency (OR = 1.72) along with the “potato-focused” group (OR = 2.15). Results show that data-derived dietary patterns may better predict health outcomes than self-reported dietary patterns, and transitioning to diets focusing on vegetables, seafood, and lower meat consumption may improve health.
DOI
https://doi.org/10.3390/nu15143256
Recommended Citation
Burke, Daniel; Bennett, Annemarie E.; Hynds, Paul; and Priyadarshini, Anushree, "Identifying Novel Data-Driven Dietary Patterns via Dimensionality Reduction and Associations with Socioeconomic Profile and Health Outcomes in Ireland" (2023). Articles. 69.
https://arrow.tudublin.ie/ehsiart/69
Funder
This work was financially supported by the Irish Research Council (IRC COALESCE Award); Project ID: COALESCE/2022/804.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.
Publication Details
https://www.mdpi.com/2072-6643/15/14/3256
Burke, D.T.; Bennett, A.E.; Hynds, P.; Priyadarshini, A. Identifying Novel Data-Driven Dietary Patterns via Dimensionality Reduction and Associations with Socioeconomic Profile and Health Outcomes in Ireland. Nutrients 2023, 15, 3256.
https://doi.org/10.3390/nu15143256