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
The prevalence of metabolic syndrome and its components continue to increase among patients with serious mental illness. This cross-sectional study investigated whether metabolic syndrome prevalence and risk factors differ between male and female patients with serious mental illness. In total, 260 eligible patients were recruited from two hospitals. The data on demographic characteristics, lifestyle behaviour factors, biochemistry, and anthropometry were collected. Analyses were performed using multivariate logistic regression. Metabolic syndrome prevalence was 40.8% (35.1% in men and 46.8% in women). Among patients aged 40-49 years, metabolic syndrome prevalence was higher in men; however, the trend was reversed among patients aged 50 years or older. Notably, gender-specific metabolic syndrome risk factors were observed. In men, they included low education level, high body mass index (BMI), prolonged illness, comorbid physical illness, and diagnosis of bipolar disorder, whereas they included being married, old age, and high BMI in women. Our findings suggest that mental health professionals should consider the gender- and age-based metabolic syndrome prevalence trend in patients with serious mental illness when designing interventions for the study population to minimize metabolic syndrome prevalence.
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Source |
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http://dx.doi.org/10.1111/inm.12670 | DOI Listing |
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