Urban-suburban differences in the demographics and clinical profiles of type 2 diabetic patients attending primary healthcare centres in Malta.

INTRODUCTION: Social factors might bring about health inequities. Vulnerable population groups, including those suffering from non-communicable diseases such as type 2 diabetes and depression, might be more prone to suffering the effects of such inequities. This study aimed to identify patients with type 2 diabetes with depression in a primary care setting, with the objective of describing health inequities among urban and suburban dwellers. METHODS: A quantitative, retrospective and descriptive study was carried out among patients with diabetes attending public primary healthcare centres in different regions of Malta. Participants completed a self-administered questionnaire to identify patient and disease characteristics. Convenience sampling was used. RESULTS: The logistic regression model predicting the likelihood of different factors occurring with suburban patients with diabetes as opposed to those residing in urban areas contained five independent variables (severity of depression, monthly income, blood capillary glucose readings, weight and nationality). The full model containing all predictors was statistically significant, c2 (5, n=400), p<0.001, indicating that the model was able to distinguish between urban and suburban areas. The model as a whole explained between 10% (Cox and Snell R2) and 20% (Nagelkerke R2) of the variance in urban and suburban areas, and correctly classified 73.8% of cases. All five of the independent variables made a unique, statistically significant contribution to the model. Elevated blood glucose and obesity tended to be more prevalent in suburban respondents than in urban participants. Conversely, participants with diabetes living in urban areas were more likely to be depressed, non-Maltese and have a higher income. CONCLUSION: Despite the small size of the Maltese islands and the expected social homogeneity, health inequities still exist, highlighting the importance of social factors in the epidemiology of disease. This study provides information for healthcare professionals and policy-makers to mitigate the effects of social inequities on vulnerable population groups.

Urban-suburban differences in GP requests for lumbosacral spine radiographs in a primary healthcare centre in Malta.

INTRODUCTION: Due to demographic changes, growing demands, technological developments and rising healthcare costs, analysis of resources in rural and urban primary care clinics is crucial. However, data on primary care provision in rural and suburban areas are lacking. Moreover, health inequities in small island communities tend to be reduced by social homogeneity and an almost indiscernible urban-rural difference. The aim of the study was to examine the urban-suburban differences in the indications for lumbosacral spine radiographs in a public primary healthcare centre in Malta. METHODS: A list of all patients who underwent lumbosacral spine radiography in a public primary healthcare centre between January and June 2014 was obtained. The indications for lumbosacral spine radiographs were compared against the evidence-based indications posited by the America College of Radiology, the American Society of Spine Radiology, the Society for Pediatric Radiology and the Society of Skeletal Radiology in 2014. Differences between suburban and urban areas were analysed using the χ² test. Direct logistic regression was used to estimate the influences of different patients' characteristics and imaging indications in urban and suburban areas. RESULTS: The logistic regression model predicting the likelihood of different factors occurring with suburban patients as opposed to those residing in urban areas contained four independent variables (private/public sector, examination findings, osteoporosis, infection). The full model containing all predictors was statistically significant, c2 (4, N=1112) = 26.57, p≤0.001, indicating that the model was able to distinguish between patients residing in rural and urban areas. All four of the independent variables made a unique, statistically significant contribution to the model. The model as a whole explained between 2.4% (Cox and Snell R2) and 3.6% (Nagelkerke R2) of the variance in suburban/urban areas, and correctly classified 78.5% of cases. All four of the independent variables made a unique statistically significant contribution to the model. General practitioner (GP) requests for patients residing in suburban areas were more likely to be submitted from the private sector whereas urban GPs tended to include more examination findings. Requests by GPs for lumbosacral spine radiographs due to osteoporosis and infection tended to be more prevalent for urban patients. CONCLUSIONS: Such findings provide information for policymakers to improve equity in health care and resource allocations within the settings of urbanity and rurality.

Comparison of patients' experiences in public and private primary care clinics in Malta.

Demographic changes, technological developments and rising expectations require the analysis of public-private primary care (PC) service provision to inform policy makers. We conducted a descriptive, cross-sectional study using the dataset of the Maltese arm of the QUALICOPC Project to compare the PC patients' experiences provided by public-funded and private (independent) general practitioners in Malta. Seven hundred patients from 70 clinics completed a self-administered questionnaire. Direct logistic regression showed that patients visiting the private sector experienced better continuity of care with more difficulty in accessing out-of-hours care. Such findings help to improve (primary) healthcare service provision and resource allocation.