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: Globally, there has been an increase in the trend of sugar-sweetened beverages (SSB) consumption among adolescents and this has been implicated in the increased prevalence of diet-related NonCommunicable Diseases.
Objectives: This study compared the pattern of sweetened beverage consumption and factors associated with consumption among adolescents in rural and urban areas of Ogun State, Nigeria.
Methods: A comparative cross-sectional study was conducted among in-school adolescents in rural and urban areas of Ogun State. Respondents were selected via a multistage sampling method using a semi-structured questionnaire. Sugar-sweetened Beverage consumption was based on the estimated volume and frequency of SSB consumed daily. The quantity of SSB consumed in the previous day was summed up to the nearest ml to create three categories of SSB consumption: low - less than 350mls/day; moderate - 350-700mls/day; and high - more than 700mls/day. Data were analysed with the aid of SPSS 23.0. Descriptive and inferential statistics were calculated, and the significance level was set at a 95% confidence interval with a P value≤0.05.
Results: A total of 1796 adolescents participated in this study. The lifetime prevalence of SSB consumption was higher in rural (96%) than in urban areas (85.9%). The difference was statistically significant with the location of respondents (χ2=55.875; p =0.001). The current prevalence of SSB consumption was higher in rural (77.6%) than in urban areas (74.6%), however this was not found to be statistically significant (χ2=2.061; p =0.151). Age (AOR=0.47, 95%CI=0.23-0.99) and mother's education (AOR=8.80, 95%CI=1.35-57.41) were predictors of SSB consumption among adolescents in the rural area, while ethnicity was the only predictor of SSB consumption among adolescents in the urban area (AOR=0.12, 95%CI=0.02-0.95).
Conclusion: The prevalence of SSB consumption was high among adolescents in the rural and urban groups. While carbonated drinks were the most consumed SSB across both groups, caffeinated drinks were the least consumed. Age, mother's education and ethnicity were predictors of SSB consumption among adolescents in this study. Efforts should be made to institute strategies that influence adolescents to make healthier food choices.
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