Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

Gholizadeh, Sepedeh;Moghimbeigi, Abbas;Poorolajal, Jalal;Khjeian, Mohammadali;Bahramian, Fatemeh;
iranian south medical journal 2016 Vol. 19 pp. 385-397
457
gholizadeh2016studyiranian

Abstract

Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or) diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5), 29.4% (0.95%CI; 26.6-32.1) respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05). Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05). Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

Citation

ID: 17763
Ref Key: gholizadeh2016studyiranian
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
17763
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet