Assessing hypertension and diabetes knowledge, attitudes and practices among residents in Akatsi South District, Ghana using the KAP questionnaire.

Objective: Low awareness of hypertension and diabetes is a public health concern in Ghana. Assessing the general population's behaviour via knowledge, attitude, and practice (KAP) will be invaluable in these diseases, where prevention and control need a lifelong commitment to a healthy lifestyle. Hence, our goal was to assess the behaviour of Akatsi South residents towards the diseases to assist health providers in implementing tailored intervention programs. Methods: This was a population-based cross-sectional study with 150 adults (18-70 years) from November to December 2021. A semi-structured questionnaire with face-to-face interviews was used to obtain data. All variables in the model had descriptive statistics. The Chi-square (χ2) test was used to examine correlations between variables, and a value of p < 0.05 was considered statistically significant. The factors associated with checking blood sugar levels and blood pressure were determined using binary logistic regression. Results: The respondents' mean age and BMI were 32.40 years (± 12.07) and 24.98 kg/m2 (± 2.36), respectively. Only 46.67% of the respondents frequently monitor their blood pressure and 17.33% their blood glucose (at least once a year). Less than half of those surveyed had a good knowledge of hypertension (42.7%) and diabetes (32.0%), whereas nearly 3/4 had poor attitudes regarding both conditions. A binary logistic regression analysis revealed that having a good attitude toward hypertension (exp B = 2.479, p = 0.036) and diabetes (exp B = 4.547, p = 0.009) were the participants' strongest predictor of blood pressure and sugar level checks. However, being overweight (exp B = 0.046, p = 0.002,) or obese (exp B = 0.144, p = 0.034) negatively influenced the frequency with which our respondents checked their blood glucose levels. Conclusion: In the study, we found that the population generally has poor knowledge, which affects their behaviour (attitudes and practices) towards the diseases. To enable healthcare practitioners to reduce disease-associated mortality and morbidity in the future, frequent public health education and promotion about the conditions is critical to closing the knowledge gap.

Hypertension and Diabetes in Akatsi South District, Ghana: Modeling and Forecasting.

BACKGROUND: The rising incidence of hypertension and diabetes calls for a global response. Hypertension and diabetes will rise in Ghana as the population ages, urbanization increases, and people lead unhealthy lives. Our goal was to create a time series algorithm that effectively predicts future increases to help preventative medicine and health care intervention strategies by preparing health care practitioners to control health problems. METHODS: Data on hypertension and diabetes from January 2016 to December 2020 were obtained from three health facilities. To detect patterns and predict data from a particular time series, three forecasting algorithms (SARIMAX (seasonal autoregressive integrated moving average with exogenous components), ARIMA (autoregressive integrated moving average), and LSTM (long short-term memory networks)) were implemented. We assessed the model's ability to perform by calculating the root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), and mean absolute percentage error (MAPE). RESULTS: The RMSE, MSE, MAE, and MAPE for ARIMA (5, 2, 4), SARIMAX (1, 1, 1) × (1, 1, 1, 7), and LSTM was 28, 769.02, 22, and 7%, 67, 4473, 56, and 14%, and 36, 1307, 27, and 8.6%, respectively. We chose ARIMA (5, 2, 4) as a more suitable model due to its lower error metrics when compared to the others. CONCLUSION: All models had promising predictability and predicted a rise in the number of cases in the future, and this was essential for administrative and management planning. For appropriate and efficient strategic planning and control, the prognosis was useful enough than would have been possible without it.