ArticlePublic health nutrition2018
Dietary patterns and the risk of metabolic syndrome in Chinese adults: a population-based cross-sectional study.
Article in Public health nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Exploring the traditional Chinese diet and its association with health status-a systematic review.Nutrition reviews · 2025Pooled it
- Dietary Patterns and Metabolic Syndrome in Adult Subjects: A Systematic Review and Meta-Analysis.Nutrients · 2019Pooled it
- Integrating dietary patterns and metabolomics with machine learning for metabolic syndrome risk assessment in a rural population.NPJ science of food · 2026Article
- Fruit and vegetable consumption and metabolic syndrome in Chinese adults: a cross-sectional study.Frontiers in nutrition · 2026Article
- Association between the Chinese diet balance index 2022 and the risk of metabolic syndrome: a cross-sectional analysis in middle-aged and older adults.Frontiers in nutrition · 2026Article
- Gender disparities in complex association of metabolic syndrome with dietary habits and lifestyle risk factors in Chinese population.Scientific reports · 2025Article
- The dose-response relationships between all-cause and cardiovascular mortality and the accrual of various dietary habits.American journal of preventive cardiology · 2025Article
- Dietary patterns derived by Gaussian graphical models and metabolic profiles among overweight and obese individuals.Scientific reports · 2025Article
- Uncovering a New Concept of Foodnality in Diet Recommendations for Chinese Aging Populations Based on Systematic and Bibliometric Review.Foods (Basel, Switzerland) · 2024Review
- Metabolic syndromes increase significantly with the accumulation of bad dietary habits.The journal of nutrition, health & aging · 2024Article
- Dietary insulin index, dietary insulin load and dietary patterns and the risk of metabolic syndrome in Hoveyzeh Cohort Study.Scientific reports · 2024Article
- Associations of dietary pattern, insulin resistance and risk of developing metabolic syndrome among Chinese population.PloS one · 2024Article
- A High-Quality Diet, as Measured by the DASH Score, Is Associated with a Lower Risk of Metabolic Syndrome and Visceral Obesity.Biomedicines · 2023Article
- Saturated fats network identified using Gaussian graphical models is associated with metabolic syndrome in a sample of Iranian adults.Diabetology & metabolic syndrome · 2022Article
- Cheese Intake Exhibits an Alteration of Glycolipid Profile and Impacts on Non-Alcoholic Fatty Liver in Bahraini Older Adults.Geriatrics (Basel, Switzerland) · 2022Article
- Dietary Patterns and Their Association with Sociodemographic and Lifestyle Factors in Filipino Adults.Nutrients · 2022Article
- A Lard and Soybean Oil Mixture Alleviates Low-Fat-High-Carbohydrate Diet-Induced Nonalcoholic Fatty Liver Disease in Mice.Nutrients · 2022Article
- Individual Diet Modification Reduces the Metabolic Syndrome in Patients Before Pharmacological Treatment.Nutrients · 2021Article
- Article
- Association between dietary patterns and prediabetes risk in a middle-aged Chinese population.Nutrition journal · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveData on dietary patterns in relation to the risk of metabolic syndrome (MetS) in a middle-aged Chinese population are sparse. The present study was performed to determine the major dietary patterns among a population aged 45-59 years and to evaluate their associations with MetS risk in China.
designCross-sectional examination of the association between dietary patterns and MetS. Face-to-face interviews were used to assess dietary intake using a validated semi-quantitative FFQ. OR and 95 % CI for MetS were calculated across quartiles of dietary pattern scores using multivariate logistic regression analysis models.
settingCity of Linyi, Shandong Province, China. SUBJECTS: Adults (n 1918) aged 45-59 years.
resultsThree major dietary patterns were identified: traditional Chinese, animal food and high-energy. After adjustment for potential confounders, individuals in the highest quartile of the traditional Chinese pattern had a reduced risk of MetS relative to the lowest quartile (OR=0·72, 95 % CI 0·596, 0·952; P<0·05). Compared with those in the lowest quartile, individuals in the highest quartile of the animal food pattern had a greater risk of MetS (OR=1·28; 95 % CI 1·103, 1·697; P<0·05). No significant association was observed between the high-energy pattern and risk of MetS.
conclusionsThese findings indicate that the traditional Chinese pattern was associated with a reduced risk, while the animal food pattern was associated with increased risk of MetS. Given the cross-sectional nature of our study, further prospective studies are warranted to confirm these findings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.