Objectives: The present study aimed to assess the attitude of Saudi and Pakistani individuals with diabetes regarding Eid-al-Fitr festivities, exploring diabetes care during the month of Ramadan and these individuals' dietary patterns on Eid day.
Design: Cross-sectional study.
Setting: Jeddah (Saudi Arabia) and Karachi (Pakistan).
Participants: Of the total 405 subjects, 204 individuals with diabetes from Saudi Arabia (SA) and 201 from Pakistan (Pak) were enrolled.
Data Collection And Analysis: This survey-based study was carried out in SA and Pak after Eid-al-Fitr 2020. An online questionnaire was circulated via various social media platforms. The data analyses were performed using SPSS V.26.
Results: There were 80 subjects with type 1 diabetes mellitus (DM) and 325 subjects with type 2 DM. Among our study subjects, 73 were on insulin, 260 were on oral antidiabetics (OADs) and 72 were taking both OADs and insulin. Two-thirds of the participants, 276 (68%) visited their physicians before Ramadan. Many participants (175, 43.2%) broke their fast a day or more because of diabetes. Many participants consumed sugary food on Eid day. The use of chocolates, sugary foods and fresh juices on Eid-al-Fitr was higher in Saudi subjects than in Pakistani ones (p<0.001). Saudi subjects with diabetes adhered more strictly to medications during Ramadan than Pakistani subjects (p=0.01). Saudi participants were more compliant with monitoring DM during Eid-al-Fitr compared with Pakistani subjects. Many participants in both groups felt stressed or depressed and stated that their Eid celebrations were restrictive because of their DM conditions.
Conclusions: Most Saudi and Pakistani participants enjoyed Eid celebrations by abstaining from dietary restrictions. The sugar consumption attitude during Eid day was not up to the mark. Many subjects broke their fasts for a day or more because of diabetes. Saudis were more vigilant in monitoring DM than Pakistanis during Eid-al-Fitr. Individuals with diabetes should consult their physicians before Ramadan for checkups and counselling.
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http://dx.doi.org/10.1136/bmjopen-2021-054902 | DOI Listing |
Cardiovasc Diabetol
January 2025
Department of Cardiology, Zhongda Hospital, Southeast University, No. 87 Dingjiaqiao, Nanjing, 210009, Jiangsu, China.
Background: Atherosclerotic dyslipidemia is associated with an increased risk of type 2 diabetes (T2D). Although previous studies have demonstrated an association between the atherogenic index of plasma (AIP) and insulin resistance, there remains a scarcity of large cohort studies investigating the association between AIP and the long-term risk of T2D in the general population. This study aims to investigate the potential association between AIP and the long-term risk of T2D in individuals with normal fasting plasma glucose levels.
View Article and Find Full Text PDFBMC Public Health
January 2025
Faculty of Health Sciences, Department of Internal Medicine Nursing, Sakarya University, Sakarya, 54050, Turkey.
Background: Adults with diabetes encounter various challenges related to managing their condition. In this study, we explored the experiences of adults with type 2 diabetes mellitus with low socioeconomic status in Türkiye.
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BMC Pediatr
January 2025
Nutrition & Health Innovation Research Institute, Edith Cowan University, Perth, WA, Australia.
Background: Growing evidence shows that dysregulated metabolic intrauterine environments can affect offspring's neurodevelopment and behaviour. However, the results of individual cohort studies have been inconsistent. We aimed to investigate the association between maternal diabetes before pregnancy and gestational diabetes mellitus (GDM) with neurodevelopmental, cognitive and behavioural outcomes in children.
View Article and Find Full Text PDFAnn Pharmacother
January 2025
Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel.
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Data Source: A literature review was performed in PubMed and Embase for cohort studies published up to August 2024 using PICO-consistent terms.
The classification of chronic diseases has long been a prominent research focus in the field of public health, with widespread application of machine learning algorithms. Diabetes is one of the chronic diseases with a high prevalence worldwide and is considered a disease in its own right. Given the widespread nature of this chronic condition, numerous researchers are striving to develop robust machine learning algorithms for accurate classification.
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