» Articles » PMID: 15548339

Dietary Patterns in Middle-aged Irish Men and Women Defined by Cluster Analysis

Overview
Date 2004 Nov 19
PMID 15548339
Citations 30
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: To identify and characterise dietary patterns in a middle-aged Irish population sample and study associations between these patterns, sociodemographic and anthropometric variables and major risk factors for cardiovascular disease.

Design: A cross-sectional study.

Subjects And Methods: A group of 1473 men and women were sampled from 17 general practice lists in the South of Ireland. A total of 1018 attended for screening, with a response rate of 69%. Participants completed a detailed health and lifestyle questionnaire and provided a fasting blood sample for glucose, lipids and homocysteine. Dietary intake was assessed using a standard food-frequency questionnaire adapted for use in the Irish population. The food-frequency questionnaire was a modification of that used in the UK arm of the European Prospective Investigation into Cancer study, which was based on that used in the US Nurses' Health Study. Dietary patterns were assessed primarily by K-means cluster analysis, following initial principal components analysis to identify the seeds.

Results: Three dietary patterns were identified. These clusters corresponded to a traditional Irish diet, a prudent diet and a diet characterised by high consumption of alcoholic drinks and convenience foods. Cluster 1 (Traditional Diet) had the highest intakes of saturated fat (SFA), monounsaturated fat (MUFA) and percentage of total energy from fat, and the lowest polyunsaturated fat (PUFA) intake and ratio of polyunsaturated to saturated fat (P:S). Cluster 2 (Prudent Diet) was characterised by significantly higher intakes of fibre, PUFA, P:S ratio and antioxidant vitamins (vitamins C and E), and lower intakes of total fat, MUFA, SFA and cholesterol. Cluster 3 (Alcohol & Convenience Foods) had the highest intakes of alcohol, protein, cholesterol, vitamin B(12), vitamin B(6), folate, iron, phosphorus, selenium and zinc, and the lowest intakes of PUFA, vitamin A and antioxidant vitamins (vitamins C and E). There were significant differences between clusters in gender distribution, smoking status, physical activity, body mass index, waist circumference and serum homocysteine concentrations.

Conclusion: In this general population sample, cluster analysis methods yielded two major dietary patterns: prudent and traditional. The prudent dietary pattern is associated with other health-seeking behaviours. Study of dietary patterns will help elucidate links between diet and disease and contribute to the development of healthy eating guidelines for health promotion.

Citing Articles

Optimally Controlled Diabetes and Its Influence on Neonatal Outcomes at a Level II Center: A Study on Infants Born to Diabetic Mothers.

Muntean M, Prelipcean I, Racean M, Cucerea M, Fagarasan A, David C Medicina (Kaunas). 2023; 59(10).

PMID: 37893486 PMC: 10607977. DOI: 10.3390/medicina59101768.


How is healthy eating index-2015 related to risk factors for cardiovascular disease in patients with type 2 diabetes.

Zeinalabedini M, Nasli-Esfahani E, Esmaillzadeh A, Azadbakht L Front Nutr. 2023; 10:1201010.

PMID: 37305085 PMC: 10248502. DOI: 10.3389/fnut.2023.1201010.


Dietary diversity and association with non-communicable diseases (NCDs) among adult men (15-54 years): A cross-sectional study using National Family and Health Survey, India.

Dolui M, Sarkar S, Ghosh P, Hossain M PLOS Glob Public Health. 2023; 3(4):e0001775.

PMID: 37185617 PMC: 10132668. DOI: 10.1371/journal.pgph.0001775.


Regional Differences in the Association between Dietary Patterns and Muscle Strength in Korean Older Adults: Data from the Korea National Health and Nutrition Examination Survey 2014-2016.

Seo A, Kim M, Park K Nutrients. 2020; 12(5).

PMID: 32408472 PMC: 7284570. DOI: 10.3390/nu12051377.


Multidimensional Analysis of Food Consumption Reveals a Unique Dietary Profile Associated with Overweight and Obesity in Adolescents.

Andrade V, Santana M, Fukutani K, Queiroz A, Arriaga M, Conceicao-Machado M Nutrients. 2019; 11(8).

PMID: 31430906 PMC: 6723851. DOI: 10.3390/nu11081946.