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
Background: Obesity is associated with the rise of noncommunicable diseases worldwide. The pathophysiology behind this disease involves the increase of adipose tissue, being inversely related to adiponectin, but directly related to insulin resistance and metabolic syndrome (MetS). Therefore, this study aimed to determine the relationship between adiponectin levels with each component of MetS in eutrophic and obese Mexican children.
Methods: A cross sectional study was conducted in 190 school-age children classified as obese and 196 classified as eutrophic. Adiponectin, glucose, insulin, high density lipoprotein cholesterol (HDL-C) and triglycerides were determined from a fasting blood sample. Height, weight, waist circumference, systolic and diastolic blood pressures (BP) were measured; MetS was evaluated with the IDF definition. The study groups were divided according to tertiles of adiponectin, using the higher concentration as a reference. Linear regression analysis was used to assess the association between adiponectin and components of the MetS. Finally, stepwise forward multiple logistic regression analysis controlling for age, gender, basal HOMA-IR values and BMI was performed to determine the odds ratio of developing MetS according to adiponectin tertiles.
Results: Anthropometric and metabolic measurements were statistically different between eutrophic and obese children with and without MetS (P <0.001). The prevalence of MetS in obese populations was 13%. Adiponectin concentrations were 15.5 ± 6.1, 12.0 ± 4.8, 12.4 ± 4.9 and 9.4 ± 2.8 μg/mL for eutrophic and obese subjects, obese without MetS, and obese with MetS, respectively (P <0.001). Obese children with low values of adiponectin exhibited a higher frequency of MetS components: abdominal obesity, 49%; high systolic BP, 3%; high diastolic BP, 2%; impaired fasting glucose, 17%; hypertriglyceridemia, 31%; and low HDL-C values, 42%. Adjusted odds ratio of presenting MetS according to adiponectin categories was 10.9 (95% CI 2.05; 48.16) when the first tertile was compared with the third.
Conclusion: In this sample of eutrophic and obese Mexican children we found that adiponectin concentrations and MetS components have an inversely proportional relationship, which supports the idea that this hormone could be a biomarker for identifying individuals with risk of developing MetS.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570482 | PMC |
http://dx.doi.org/10.1186/1471-2458-13-88 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!