Comparing two methods for deriving dietary patterns associated with risk of metabolic syndrome among middle-aged and elderly Taiwanese adults with impaired kidney function

Abstract

Background Dietary patterns were associated with the risk of chronic disease development and outcome-related diseases. In this study, we aimed to compare the correlation between dietary patterns and metabolic syndrome (MetS) using two methods for identifying dietary patterns. Methods The participants (n = 25,569) aged ≥40 years with impaired kidney function were retrieved from Mei Jau (MJ) Health Screening database from 2008 to 2010. Dietary patterns were identified by principal component analysis (PCA) and reduced rank regression (RRR) from twenty-two food groups using PROC FACTOR and PROC PLS functions. Results We identified two similar dietary pattern characteristics (high intakes of deep fried foods, preserved or processed foods, dipping sauce, meat, sugary drinks, organ meats, jam/honey, fried rice/flour products, instant noodles and eggs) derived by PCA and RRR. Logistic regression analysis revealed that RRR-derived dietary pattern scores were positively associated with an odds ratio (OR = 1.70, 95% CI: 1.56, 1.86) of having MetS than PCA-derived dietary pattern scores (OR = 1.38, 95% CI: 1.27, 1.51). The correlations between RRR-derived dietary pattern scores and elevated systolic and diastolic blood pressure (OR = 1.30 for both) or low high density lipoprotein cholesterol in women (OR = 1.32) were statistically significant but not significant in PCA-derived dietary pattern scores. Conclusions Our findings suggest that RRR gives better results when studying behavior related dietary patterns in association with MetS. RRR may be more preferable to provide dietary information for developing dietary guidelines among people with MetS. Further studies with prospective measurements are needed to verify whether RRR is a useful analytic tool for the association between dietary patterns and other chronic diseases.

Healthy Taiwanese Eating Approach (TEA) toward Total Wellbeing and Healthy Longevity

“…In order to include only dietary factors highly associated with disease or health conditions of interest, we excluded dietary factors discovered by PCA or EFA that focused purely on dimension reduction of the multivariate dietary frequency variables. A total number of 19 articles were included in this review [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. The flow chart of searching literatures is shown in Figure 1.…”

“…No matter what similarities or differences are discovered, they may provide insight into components of diet that work toward better or worse health. In this endeavor, we reviewed data mining-related literature [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] pertaining to Taiwanese dietary patterns and multiple health or disease outcomes and also described the recent Taiwanese dietary content using data collected in the Nutrition and Health Survey in Taiwan from 2017 to 2020 in order to shed light on healthy eating patterns and options in Asians.…”

Association between Dietary Pattern, Lifestyle, Anthropometric Status, and Anemia-Related Biomarkers among Adults: A Population-Based Study from 2001 to 2015

“…A dietary pattern is a new approach for evaluating eating patterns in the general population [13]. The use of an RRR to derive the dietary pattern provides a better explanation for diet-disease associations [24]. Additionally, our study highlighted the correlation of several variables, including dietary pattern, lifestyle, and anthropometric data, with anemia.…”

“…We included Hb, Hct, RBC, WBC, and CRP for the response variables (Figure 2). According to previous investigations, we retained all food groups which had the absolute value of factor loading ≥0.20 to derive the dietary patterns associated with anemia [24,25]. Then, we calculated dietary factor scores for each food group by summing food frequency intake weighed by their factor loadings.…”

Synergistic Interaction of Dietary Pattern and Concordance Lifestyle with Abnormal Liver Function among Young Adults in Taiwan: A Population-Based Longitudinal Study

“…For generating the dietary pattern associated with liver function, 7 response variables, including ALT, AST, γ-GT, alkaline phosphatase (ALP), lactate dehydrogenase (LDH), albumin, and total bilirubin, were applied, and 22 food items were used as the predictors. We only retracted food items with absolute factor loadings ≥0.20 to obtain the most representative dietary habits of study participants [22,23]. The scores of the derived dietary patterns were classified into quartiles, and the higher quartile of the derived dietary pattern, the higher the risk for abnormal liver enzymes.…”