Repository logo
  • English
  • 中文
Log In
Have you forgotten your password?
  1. Home
  2. College of Public Health / 公共衛生學院
  3. Epidemiology and Preventive Medicine / 流行病學與預防醫學研究所
  4. A Multi-level Model for Familial Aggregation of Obesity
 
  • Details

A Multi-level Model for Familial Aggregation of Obesity

Date Issued
2008
Date
2008
Author(s)
Tsai, Ping-Yun
URI
http://ntur.lib.ntu.edu.tw//handle/246246/184803
Abstract
Background and Study PurposeObesity is increasing in prevalence worldwide and is known to be associated with morbidity and mortality in relation to cardiovascular disease. The etiology of obesity is complex and is not completely understood. A large portion of epidemiologic research put emphasis on individual-level risk factors. However, group-level or macro-level variables, so-called contextual factors, also play an important role through interaction with individual factors. There are also limited studies taking both familial aggregation and contextual factors of obesity into accounts. Therefore, the aim of the present study is to explore the association between obesity and familial aggregation and risk factors at individual-level and area-level by conducting a community-based study with multi-level model analysis.aterials and methodsA total of 74,833 subjects with aged 20-69 years old are identified from Keelung community-based integrated screening program (KCIS) between 1999 and 2005. By dint of KCIS study, the study design is based on a case-control proband family sampling. A total of 4,499 cases and 16,932 controls were identified. Data of household registration, demographics including education and marital status, lifestyle, and diet were collected. Anthropometric measurements were taking and the criteria of obesity was defined as body mass index≧27 kg/m2. Area-level contextual factors including high educational rate, divorce or widowed rate, and population density separated with tertile were collected from seven administrative districts of Keelung City. We applied nonlinear mixed model and Bayesian analysis for multi-level analysis to investigate the odds ratios and 95% confidence interval of familial aggregation and different level factors for obesity. esultsThe prevalence rate of overweight and obesity were higher in aged, male, low educated, divorced or widowed subjects, the least tertile of high education rate, and the most tertile of population density among areas. The relative risk of familial aggregation in association with obesity among relatives in case proband families compared with control proband families was 1.29 (95% CI: 1.29-1.30). The relative risk of familial aggregation with obesity in the least tertile of high education rate, the most tertile of divorce rate, and the most tertile of population density were 1.39 (95% CI: 1.36-1.41), 1.36 (95%CI: 1.35-1.38), and 1.34 (95% CI: 1.32-1.35), respectively. The risk for obesity among relatives in case versus control proband families was 2.31 (95%CI: 1.67-3.20) after controlling for significant environmental factors, and it was modified by individual marital status and high education rate of area. The odds ratio was 1.52 (95%CI:1.10-2.11) in married subjects, 1.44 (95%CI:1.04-2.00) in divorced or widowed subjects, and 2.68 (95%CI:1.94-3.71) in the least tertile of high education rate, respectively. When Bayesian analysis for multi-level model is applied, the random effects considering unexplained heterogeneity among different families, different areas, and different area effect on familial aggregation are taken into account with better goodness of fit than others.onclusionhe present study confirmed a strong tendency to familial aggregation for obesity by using the case-control proband family study with a multi-level model approach. The risk of obesity was heterogeneous among families and areas by using multi-level analysis, and familial aggregation of obesity was also affected by contextual factors. The selection of more contextual factors from different levels and the selection of the appropriate contextual factors are needed in the future.
Subjects
obesity
familial aggregation
case-control proband family study
contextual factors
multi-level analysis
SDGs

[SDGs]SDG3

Type
thesis
File(s)
Loading...
Thumbnail Image
Name

ntu-97-R95846006-1.pdf

Size

23.32 KB

Format

Adobe PDF

Checksum

(MD5):2b05c0538486e90ad642dccf2b941c84

臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

總館學科館員 (Main Library)
醫學圖書館學科館員 (Medical Library)
社會科學院辜振甫紀念圖書館學科館員 (Social Sciences Library)

開放取用是從使用者角度提升資訊取用性的社會運動,應用在學術研究上是透過將研究著作公開供使用者自由取閱,以促進學術傳播及因應期刊訂購費用逐年攀升。同時可加速研究發展、提升研究影響力,NTU Scholars即為本校的開放取用典藏(OA Archive)平台。(點選深入了解OA)

  • 請確認所上傳的全文是原創的內容,若該文件包含部分內容的版權非匯入者所有,或由第三方贊助與合作完成,請確認該版權所有者及第三方同意提供此授權。
    Please represent that the submission is your original work, and that you have the right to grant the rights to upload.
  • 若欲上傳已出版的全文電子檔,可使用Open policy finder網站查詢,以確認出版單位之版權政策。
    Please use Open policy finder to find a summary of permissions that are normally given as part of each publisher's copyright transfer agreement.
  • 網站簡介 (Quickstart Guide)
  • 使用手冊 (Instruction Manual)
  • 線上預約服務 (Booking Service)
  • 方案一:臺灣大學計算機中心帳號登入
    (With C&INC Email Account)
  • 方案二:ORCID帳號登入 (With ORCID)
  • 方案一:定期更新ORCID者,以ID匯入 (Search for identifier (ORCID))
  • 方案二:自行建檔 (Default mode Submission)
  • 方案三:學科館員協助匯入 (Email worklist to subject librarians)

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science