Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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: 3122
Function: getPubMedXML
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
While smoking prevalence in the U.S. and other industrialized countries has decreased substantially, this change has been unevenly distributed, with dramatic decreases in certain subpopulations but little change or even increases in others. Accordingly, considerable attention has been fruitfully devoted to identifying important risk factors for smoking (e.g., mental illness, other substance use disorders). However, there has been little research on the intersection of these risk factors. As risk factors rarely occur in isolation, it is important to examine risk-factor profiles as is commonly done in studying other chronic conditions (e.g., cardiovascular disease). The purpose of this Commentary is to encourage greater interest in the intersection of multiple risk factors using cigarette smoking as an exemplar. We focus on the intersection of eight well-established risk factors for smoking (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness). Studying the intersection of risk factors is likely to require use of innovative data-analytic methods. We illustrate, using years 2011-2016 of the US National Household Survey on Drug Use and Health, how Classification and Regression Tree (CART) analysis can be an effective tool for identifying risk profiles for smoking. Examination of the intersection of these risk factors elucidates a series of risk profiles with associated, orderly gradations in vulnerability to current smoking, including the striking and reliable strength of a college education as a stand-alone profile predicting low risk for current smoking, and illustrating the potentially increasing importance of drug abuse/dependence as a risk factor.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234036 | PMC |
http://dx.doi.org/10.1016/j.ypmed.2018.09.006 | DOI Listing |
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