Background: This manuscript aimed to map the spatial distributions of health clinics for public and private sectors in Malaysia. It would assist the stakeholders and responsible authorities in the planning for health ...Background: This manuscript aimed to map the spatial distributions of health clinics for public and private sectors in Malaysia. It would assist the stakeholders and responsible authorities in the planning for health service delivery. Methods: Data related to health clinic were gathered from stakeholders. The location of health facilities was geo-coded using a Global Positioning System (GPS) handheld. The average nearest neighbour was used to identify whether health clinics were spatially clustered or dispersed. Hot spot analysis was used to assess high density of health clinics to population ratio and average distance of health clinics distribution. A Geographically Weighted Regression (GWR) was used to analyse the requirement of health clinic in a sub-district based on population density and number of health clinics with significant level展开更多
Background: This study aims to determine the hazard ratio of having any complication from diabetes mellitus, and the associations between comorbidities and risk of having any complications from diabetes mellitus among...Background: This study aims to determine the hazard ratio of having any complication from diabetes mellitus, and the associations between comorbidities and risk of having any complications from diabetes mellitus among diabetic patients who have attended government primary care clinics. Methods: Secondary data were retrieved from the Malaysian National Diabetic Registry which included all patients who received care. The data from the study on the socio-demographic, diabetes complications, clinical and treatment characteristics were analyzed using descriptive statistics. Cox regression was performed to estimate the hazard ratio for comorbidities, tobacco use, duration of diabetes and socio-demography characteristics upon time to diabetic complications. Results: Adjusted for other covariates, increase number of comorbidities contributed the highest hazard ratio risk: 1 comorbid (aHR: 2.47, 95% CI: 2.39, 2.55), 2 comorbidities (aHR: 4.34, 95% CI: 4.22, 4.47), 3 comorbidities (aHR: 6.56, 95% CI: 6.31, 6.81) and 4 comorbidities (aHR: 9.13, 95% CI: 8.20, 10.17). Other factors: age > 40 years (8%) Malays (27%) and smokers (10%) have hazard risks to develop diabetic complications. Conclusions: Increase in number of comorbidities will increase the risk of getting diabetes complications. Other factors such as age, gender, race, smoking status and duration of diabetes are also noted to contribute to increase risk for diabetes complications.展开更多
文摘Background: This manuscript aimed to map the spatial distributions of health clinics for public and private sectors in Malaysia. It would assist the stakeholders and responsible authorities in the planning for health service delivery. Methods: Data related to health clinic were gathered from stakeholders. The location of health facilities was geo-coded using a Global Positioning System (GPS) handheld. The average nearest neighbour was used to identify whether health clinics were spatially clustered or dispersed. Hot spot analysis was used to assess high density of health clinics to population ratio and average distance of health clinics distribution. A Geographically Weighted Regression (GWR) was used to analyse the requirement of health clinic in a sub-district based on population density and number of health clinics with significant level
文摘Background: This study aims to determine the hazard ratio of having any complication from diabetes mellitus, and the associations between comorbidities and risk of having any complications from diabetes mellitus among diabetic patients who have attended government primary care clinics. Methods: Secondary data were retrieved from the Malaysian National Diabetic Registry which included all patients who received care. The data from the study on the socio-demographic, diabetes complications, clinical and treatment characteristics were analyzed using descriptive statistics. Cox regression was performed to estimate the hazard ratio for comorbidities, tobacco use, duration of diabetes and socio-demography characteristics upon time to diabetic complications. Results: Adjusted for other covariates, increase number of comorbidities contributed the highest hazard ratio risk: 1 comorbid (aHR: 2.47, 95% CI: 2.39, 2.55), 2 comorbidities (aHR: 4.34, 95% CI: 4.22, 4.47), 3 comorbidities (aHR: 6.56, 95% CI: 6.31, 6.81) and 4 comorbidities (aHR: 9.13, 95% CI: 8.20, 10.17). Other factors: age > 40 years (8%) Malays (27%) and smokers (10%) have hazard risks to develop diabetic complications. Conclusions: Increase in number of comorbidities will increase the risk of getting diabetes complications. Other factors such as age, gender, race, smoking status and duration of diabetes are also noted to contribute to increase risk for diabetes complications.
