Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Up to date, the sufficient-component cause model seems to be a theoretical framework for disease causation in epidemiology, and its implications in epidemiological research methods is currently still limited. Recently, pitfalls in current epidemiological research methods were addressed based on the sufficient-component cause model; hence, new research approaches are needed as alternatives. Therefore, this paper aims to review and suggest new epidemiological methods used to assess disease causation. A new approach was discussed to identify potential mechanisms of disease occurrence which may be useful for risk prediction and disease prevention. In addition, a novel "exposed case-control" design was introduced to identify potential component causes. Furthermore, this paper suggested a new approach of conducting a systematic review/meta-analysis related to causation studies.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482181 | PMC |
http://dx.doi.org/10.4081/jphr.2020.1726 | DOI Listing |
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