ArticleAnnals of translational medicine2020
Risk factors for cardiovascular disease from a population-based screening study in Tianjin, China: a cohort study of 36,215 residents.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Prevalence and Associated Factors of Self-Reported Coronary Heart Disease: A Population-Based Cross-Sectional Survey in Tianjin.Risk management and healthcare policy · 2024Article
- Late response to rosuvastatin and statin-related myalgia due toAnnals of translational medicine · 2021Article
- Estimating Risk of Cardiovascular Disease Among Long-Term Colorectal Cancer Survivors: A Nationwide Cohort Study.Frontiers in cardiovascular medicine · 2021Article
- A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial.Frontiers in cardiovascular medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiovascular disease (CVD) is a harmful disease that poses a serious threat to human life. By effectively controlling its risk factors, the occurrence and development of CVD can be reduced, and people's health status and quality of life can be improved.
methodsA total of 36,215 participants were collected from participants of the Early Screening and Comprehensive Intervention Program for High Risk Population of Cardiovascular Disease in Tianjin on July 31, 2017. We analyzed the relationship between CVD risk and personal information, personal and family medical history, biochemical index, and physical fitness index using Pearson's chi-squared test with and without Yates's correction for continuity, and Fisher's exact test. CVD risk-related factors were examined through logistic regression and decision tree analysis.
resultsA personal history of hypertension and apoplexy had a contingency coefficient with CVD risk of more than 0.3. A higher risk of CVD was also found to be associated with biochemical markers of cholesterol, low-density lipoprotein cholesterol, and blood sugar. Logistic regression analysis revealed 12 indicators to be influencing factors of CVD, including age, systolic blood pressure (SBP), diastolic blood pressure (DBP), and the number of people aged >90 in the family. Hypertension, SBP, BMI, cholesterol, and blood glucose were associated with five or more other indicators.
conclusionsThe prevalence of CVD risk factors in Tianjin residents is relatively high. Family disease history and individual physical fitness indicators need to be taken into account during CVD screening and intervention, to reduce the risk of CVD.
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.