Dataset Information

An application of partial least squares for identifying dietary patterns in bone health.

ABSTRACT: In a large cohort of older women, a mechanism-driven statistical technique for assessing dietary patterns that considers a potential nutrient pathway found two dietary patterns associated with lumbar spine and femoral neck bone mineral density. A "healthy" dietary pattern was observed to be beneficial for bone mineral density.

Introduction

Dietary patterns represent a broader, more realistic representation of how foods are consumed, compared to individual food or nutrient analyses. Partial least-squares (PLS) is a data-reduction technique for identifying dietary patterns that maximizes correlation between foods and nutrients hypothesized to be on the path to disease, is more hypothesis-driven than previous methods, and has not been applied to the study of dietary patterns in relation to bone health.

Methods

Women from the Aberdeen Prospective Osteoporosis Screening Study (2007-2011, n = 2129, age = 66 years (2.2)) provided dietary intake using a food frequency questionnaire; 37 food groups were created. We applied PLS to the 37 food groups and 9 chosen response variables (calcium, potassium, vitamin C, vitamin D, protein, alcohol, magnesium, phosphorus, zinc) to identify dietary patterns associated with bone mineral density (BMD) cross-sectionally. Multivariable regression was used to assess the relationship between the retained dietary patterns and BMD at the lumbar spine and femoral neck, adjusting for age, body mass index, physical activity level, smoking, and national deprivation category.

Results

Five dietary patterns were identified, explaining 25% of the variation in food groups and 77% in the response variables. Two dietary patterns were positively associated with lumbar spine (per unit increase in factor 2: 0.012 g/cm² [95% CI: 0.006, 0.01]; factor 4: 0.007 g/cm² [95% CI: 0.00001, 0.01]) and femoral neck (factor 2: 0.006 g/cm² [95% CI: 0.002, 0.01]; factor 4: 0.008 g/cm² [95% CI: 0.003, 0.01)]) BMD. Dietary pattern 2 was characterized by high intakes of milk, vegetables, fruit and vegetable juices, and wine, and low intakes of processed meats, cheese, biscuits, cakes, puddings, confectionary, sweetened fizzy drinks and spirits while dietary pattern 4 was characterized by high intakes of fruits, red and white meats, and wine, and low intakes of vegetables and sweet spreads.

Conclusion

Our findings using a robust statistical technique provided important support to initiatives focusing on what constitutes a healthy diet and its implications.

SUBMITTER: Yang TC

PROVIDER: S-EPMC5506508 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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An application of partial least squares for identifying dietary patterns in bone health.

Yang Tiffany C TC Aucott Lorna S LS Duthie Garry G GG Macdonald Helen M HM

Archives of osteoporosis 20170712 1

In a large cohort of older women, a mechanism-driven statistical technique for assessing dietary patterns that considers a potential nutrient pathway found two dietary patterns associated with lumbar spine and femoral neck bone mineral density. A "healthy" dietary pattern was observed to be beneficial for bone mineral density.<h4>Introduction</h4>Dietary patterns represent a broader, more realistic representation of how foods are consumed, compared to individual food or nutrient analyses. Partia ...[more]

PMID: 28702941

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Project description:In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Project description:Nutrition affects bone health status. However, analysis of the dietary patterns gives insights into which particular combination of foods may influence nutritional status and bone health. The aim of this study was to explore the associations between dietary patterns, bone mineral density (BMD) and T-scores, and body composition in New Zealand postmenopausal women. This cross-sectional study examined 125 postmenopausal women aged between 54 and 81 years. Body composition, BMD and T-scores were determined using dual-energy X-ray a bsorptiometry (DXA). Diet composition was assessed using a validated food frequency questionnaire (FFQ) composed of 108 food items, from which 34 food groups were created. Dietary patterns were identified by principal component analysis. The bone and body composition data including skeletal sites T-scores, waist circumference, BMI and body fat percentage were regressed onto the dietary patterns. Four dietary patterns were identified; the milk and milk-rich beverages dietary pattern, the dessert, cheese and red meat dietary pattern, the fruit-rich, biscuit and crackers dietary pattern and the oily fish, sports drink and seafood-rich dietary pattern. The milk and milk-rich beverages dietary pattern was significantly positively associated with spine T-score (r = 0.247, P = 0.008), and not whole-body BMD (r = 0.182, P = 0.051). The oily fish, sports drink and seafood-rich dietary pattern was marginally negatively associated with waist circumference (r = -0.157, P = 0.094) and body mass index (r = -0.163, P = 0.081) and significantly associated with body fat percentage (r = -0.247, P = 0.008). Binary logistic regression indicated that intake of the milk and milk-rich beverages dietary pattern reduced the occurrence of osteoporosis [adjusted odds ratio OR (95% CI): 0.589 (0.353, 0.982)]. A dietary pattern characterized by a high factor loading of milk and milk-rich beverages was positively associated with whole-body BMD and spine T-score, while the oily fish, sports drink, seafood-rich dietary pattern was inversely associated with total body fat percentage. Consumption of milk, even with coffee showed a positive association with bone health among postmenopausal women. Further longitudinal intervention studies is warranted to confirm effects of dietary patterns on skeletal body sites such as hip and femoral neck T-scores.

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Dataset Information

An application of partial least squares for identifying dietary patterns in bone health.

Introduction

Methods

Results

Conclusion

Publications

An application of partial least squares for identifying dietary patterns in bone health.

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