Adherence to Carbohydrate Counting Improved Diet Quality of Adults with Type 1 Diabetes Mellitus during Social Distancing Due to COVID-19.
Gabriela Correia UlianaManuela Maria De Lima CarvalhalTalita Nogueira BerinoAline Leão ReisKarem Miléo FelícioJoão Soares FelícioDaniela Lopes GomesPublished in: International journal of environmental research and public health (2022)
To control glycemic variability in people with Type 1 diabetes mellitus (T1DM), it is essential to perform carbohydrate counting (CC), a strategy that ensures better quality of life for these patients. Thus, this study aims to analyze potential factors associated with adherence to CC in adults with T1DM during social distancing due to COVID-19 in Brazil. This was a single cross-sectional study carried out in July 2020. An online form was used to collect sociodemographic and economic data on the purchasing of supplies and food, as well as social distancing. The Chi-square test was performed with adjusted residuals analysis and a binomial logistic regression analysis ( p < 0.05). Of 472 adults, 37.71% reported performing CC in the same frequency as before social distancing. There was an association between performance of CC and the type of city ( p = 0.027), family income ( p = 0.000), use of financial emergency aid ( p = 0.045), type of insulin administration and glycemic monitoring ( p < 0.000), and cooking more ( p = 0.012). Participants who maintained or reduced consumption of ultra-processed foods were 0.62 times more likely to adhere to CC (OR 0.626, 95% IC: 0.419-0.935) and participants who cooked more were 1.67 times more likely to adhere to CC (OR 1.67, 95% CI: 1.146-2.447). There are still people with T1DM who did not know about and did not use CC method, which highlights the need for diabetes education.
Keyphrases
- glycemic control
- type diabetes
- healthcare
- mental health
- sars cov
- coronavirus disease
- end stage renal disease
- weight loss
- physical activity
- emergency department
- cardiovascular disease
- public health
- chronic kidney disease
- ejection fraction
- newly diagnosed
- high resolution
- prognostic factors
- metabolic syndrome
- risk assessment
- electronic health record
- peritoneal dialysis
- quality improvement
- respiratory syndrome coronavirus
- deep learning
- young adults
- mass spectrometry
- emergency medical