Cheng et al. BMC Public Health 2011, 11:380 http://www.biomedcentral.com/1471-2458/11/380 strongly indicated that there exists a discrepancy in drug use between the north and the south of Taiwan, and the southern areas exhibited spatial clustering of unusual utilization in cardiovascular drugs. There are two possi- ble explanations for this finding. First, the disease preva- lence may be different between the north and south in Taiwan as a result of urbanization levels. The prevalence of cardiovascular disease, such as hypertension and cor- onary heart disease, varies between the urban and rural areas. Some countries reported the prevalence was higher for people living in the urban than rural areas [31,32], while others, including Taiwan, presented evi- dence to the contrary [33,34]. Second, there were urban-rural differences in the appropriateness of disease treatment and the inclination of patients to receive med- ical care. Previous studies have documented regional variation in quality of care in cardiovascular disease [22,35]. Patients hospitalized for acute myocardial infarction (AMI) in rural hospitals were less likely to receive recommended intervention than in urban hospi- tals. In addition, inappropriate or lower utilization of health care could be associated with lower socioeco- nomic status of patients in rural areas [36,37]. Utilization of cardiovascular drugs appeared to be associated with different classes of pharmacological drugs among geographic regions. We found that under- utilization of all classes of drugs was more likely to be observed than overutilization, and the former was scat- tered mainly in the southern, rural, and aboriginal town- ships. (Figure 2) It seemed to suggest a wide variation in prescribing behavior. Drug Group A, Group B, and Group C were generally the most widely used drugs for the treatment of cardiovascular diseases [38]; however, there were large variations across townships with regard to the use of drugs. A study conducted in France reported the socio-economic status at the area level influenced the utilization of specialty care [39]. Differ- ences between general practitioners and other specialties have been described in relation to the use of cardiovas- cular medicines [40-42]. For example, compared with cardiologists, family practitioners and general internists probably underutilize ACE inhibitors due to less knowl- edge about heart failure and poor adherence to guide- lines [42]. Among seventeen townships where ACE inhibitors were underutilized, we found that a clinic for primary care is the major medical resource in these areas [43]. In addition, there are three aboriginal town- ships have the High-High hotspot. They tend to over- utilize Group B, C, D and O but not ACEI inhibitors. This might be attributable to the fact that the aboriginal residents only have access to general practitioners and medical treatment by specialists is lacking. Accordingly, the spatial patterns of drug use observed in this study suggested that there was a wide variation in physicians’ Page 6 of 9 prescribing behavior across Taiwan, to the extent that medical resources were not consistently utilized among 352 townships. Utilization of cardiovascular drugs also associated with the disease patterns appeared to be different between townships. Some studies showed that rural residents are at higher risk for the burden of major diseases such as cardiovascular disorder and the severity of their compli- cations [33,44]. In contrast, other studies showed that higher prevalence rates of cardiovascular risk factors were found in urban than rural areas due to diet and stressful life styles [31,45]. Drug choice should be based on clinical features of patients. For instance, rennin- angiotensin system agents have greatly improved clinical outcomes in patients with renal complications, [46] or diuretics are first-line agents for elderly hypertensive patients without other complications [47]. Spatial analytical methods recognize that spatial con- cordance between two proximal entities is closely con- nected by intrinsic causal relationship or hidden confounders. Although the geographical variations in drug use were widely documented, the concept of spatial dependence has received little attention in pharmacoepi- demiology. It was our intention in this study to establish that “spatial perspectives in pharmacoepidemiology” would be an effective method in detecting the variation of drug utilization. That is, unusual drug prescriptions are not randomly located across locations but tend to be concentrated within certain areas. LISAs are simply local derivations or disaggregation of global measures of spatial autocorrelation, and allow one to detail the information of local variations in spa- tial autocorrelation (e.g., hot spots and cold spots) for further study consideration[48]. This method is useful to indicate spatial correlation of similar values at loca- tion i and its neighborhood. This means that location i and its neighborhood can both have values above the average value (hot spots), or both can have values below the average (cold spots). Such local variations in spatial autocorrelation are statistically significant. Departure from the classical assumption of statistical indepen- dence, the spatial clusters represent that data are not randomly distributed over the global region and can occur because there is a contagious factor to the under- lying process that is commonly shared by the clustered region. Lack of the factor that triggers spatial depen- dence does not give rise to spatial clustering. The primary strength of this study was that we incor- porated GIS and tools for spatial analysis to explore the role of geography in drug utilization. In so doing, we were able to divert our examination from the traditional framework, which only considers individual decision- making, into the spatial realm. Epidemiologic investiga- tions are commonly involved with data from contiguous