The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
Dyslipidemia and cardiovascular disease risk among the MASHAD study population
Open accessAbstract
Introduction: Dyslipidemia may be defined as increased levels of serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), or a decreased serum high-density lipoprotein cholesterol (HDL-C) concentration. Dyslipidemia is an established risk factor for cardiovascular disease (CVD). We aimed to investigate the association of dyslipidemia and CVD events among a population sample from Mashhad, in northeastern Iran. Material and methods: This prospective cohort study comprised a population of 8698 men and women aged 35–65 years who were recruited from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. Socioeconomic and demographic status, anthropometric parameters, laboratory evaluations, lifestyle factors, and medical history were gathered through a comprehensive questionnaire and laboratory and clinical assessment for all participants. Cox regression model and 95% confidence interval (CI) were used to evaluate the association of dyslipidemia and its components with CVD incidence. Results: After 6 years of follow-up, 233 cases of CVD (including 119 cases of unstable angina [US], 74 cases of stable angina [SA], and 40 cases of myocardial infarction [MI]) were identified in the study population. Unadjusted baseline serum LDL-C, TC, and TG levels were positively associated with the risk of total CVD events among the entire population (HR: 1.54, 95% CI: 1.19–2; P-value< 0.01; HR: 1.53; 95% CI: 1.18–1.98; P < 0.01; HR: 1.57; 95% CI: 1.27–2.03; P < 0.01, respectively). However, after adjusting for confounding factors (age, body mass index [BMI], family history of CVD, smoking status [non-smoker, ex-smoker and current smoker], lipid lowering drug treatment, anti-hypertensive drug treatment, hypertension, healthy eating index [HEI], total energy intake, and presence of diabetes mellitus), a significant direct association only remained between TC and MI risk in men (HR: 2.71; 95%CI: 1.12–6.57; P-value< 0.05). Conclusion: In the present study, TC baseline level was significantly associated with the risk of MI among men.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Toprak, O., Kurt, H., Sarı, Y., Şarkış, C., Us, H., & Kırık, A. (2017) · Kidney and Blood Pressure Research · doi:10.1159/000468530 · Cited by 29,627
Grundy, S. M., Bilheimer, D. W., Chait, A., Clark, L. T., Denke, M. A., Havel, R. J., Hazzard, W. R., Hulley, S. B., Hunninghake, D. B., Kreisberg, R. A., et al. (1993) · JAMA · doi:10.1001/jama.269.23.3015 · Cited by 27,947
Expert Panel on Detection, E. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.285.19.2486 · Cited by 26,011
Zhang, Q., Wang, C., Zheng, M., Li, Y., Li, J., Zhang, L., Shang, X., & Yan, C. (2015) · Cerebrovascular Diseases · doi:10.1159/000369778 · Cited by 11,533
Projections of Global Mortality and Burden of Disease from 2002 to 2030
Mathers, C. D., & Loncar, D. (2006) · PLoS Medicine · doi:10.1371/journal.pmed.0030442 · Cited by 11,386
Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000625 · Cited by 6,185
Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease
Sabatine, M. S., Giugliano, R. P., Keech, A. C., Honarpour, N., Wiviott, S. D., Murphy, S. A., Kuder, J. F., Wang, H., Liu, T., Wasserman, S. M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1615664 · Cited by 6,138
Abdominal obesity and metabolic syndrome
Després, J.-P., & Lemieux, I. (2006) · Nature · doi:10.1038/nature05488 · Cited by 4,354
Prevalence and Trends in Overweight Among US Children and Adolescents, 1999-2000
Ogden, C. L. (2002) · JAMA · doi:10.1001/jama.288.14.1728 · Cited by 4,060
Cited by
Trends in insulin resistance: insights into mechanisms and therapeutic strategy
Li, M., Chi, X., Wang, Y., Setrerrahmane, S., Xie, W., & Xu, H. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01073-0 · Cited by 939
Ghavami, A., Ziaei, R., Talebi, S., Barghchi, H., Nattagh-Eshtivani, E., Moradi, S., Rahbarinejad, P., Mohammadi, H., Ghasemi-Tehrani, H., Marx, W., et al. (2023) · Advances in Nutrition · doi:10.1016/j.advnut.2023.01.005 · Cited by 86
Li, L., Yao, H., Zhang, L., Garcia‐Argibay, M., Du Rietz, E., Brikell, I., Solmi, M., Cortese, S., Ramos‐Quiroga, J. A., Ribasés, M., et al. (2023) · JCPP Advances · doi:10.1002/jcv2.12158 · Cited by 55
Song, Y., Choi, J.-E., Kwon, Y.-J., Chang, H.-J., Kim, J. O., Park, D.-H., Park, J.-M., Kim, S.-J., Lee, J. W., & Hong, K.-W. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-021-02751-3 · Cited by 41
Sarapis, K., George, E. S., Marx, W., Mayr, H. L., Willcox, J., Powell, K. L., Folasire, O. S., Lohning, A. E., Prendergast, L. A., Itsiopoulos, C., et al. (2023) · British Journal Of Nutrition · doi:10.1017/s0007114522003634 · Cited by 20
Metadata
- Authors
- Hedayatnia, M., Asadi, Z., Zare-Feyzabadi, R., Yaghooti-Khorasani, M., Ghazizadeh, H., Ghaffarian-Zirak, R., Nosrati-Tirkani, A., Mohammadi-Bajgiran, M., Rohban, M., Sadabadi, F., Rahimi, H.-R., Ghalandari, M., Ghaffari, M.-S., Yousefi, A., Pouresmaeili, E., Besharatlou, M.-R., Moohebati, M., Ferns, G. A., Esmaily, H., & Ghayour-Mobarhan, M.
- Venue
- Lipids in Health and Disease
- Published
- 2020-03-16
- Volume
- 19
- Issue
- 1
- Pages
- 42-42
- ISSN
- 1476-511X (ISSN-L)
- OpenAlex
- W3012162348
- Cited by
- 367
- References
- 76
- FWCI
- 36.35
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dyslipidemia and cardiovascular disease risk among the MASHAD study population. https://app.cochat.ai/papers/10.1186/s12944-020-01204-y
- The paper
- Hedayatnia, M., Asadi, Z., Zare-Feyzabadi, R., Yaghooti-Khorasani, M., Ghazizadeh, H., Ghaffarian-Zirak, R., Nosrati-Tirkani, A., Mohammadi-Bajgiran, M., Rohban, M., Sadabadi, F., Rahimi, H.-R., Ghalandari, M., Ghaffari, M.-S., Yousefi, A., Pouresmaeili, E., Besharatlou, M.-R., Moohebati, M., Ferns, G. A., Esmaily, H., & Ghayour-Mobarhan, M. (2020). Dyslipidemia and cardiovascular disease risk among the MASHAD study population. Lipids in Health and Disease. https://doi.org/10.1186/s12944-020-01204-y
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.