The study included 289 of 290 Swedish municipalities. One municipality was excluded due to missing data. The study includes data from1998 to 2002. The Swedish population 40-79 years old in the year 2000 consisted of 1 926 113 men and 1 995 981 women.

The utilisation of statins, and antidiabetic drugs in 1998-2002 among outpatients, was based on the prescriptions served by The Corporation of Pharmacies in Sweden (Apoteket AB) and expressed in Defined Daily Doses (DDD) per 1000 Inhabitants and Day (TID) [7]. The DDD for simvastatin was 15 mg, atorvastatin 10 mg and pravastatin 20 mg. The DDD for antidiabetic drugs included both insulin and oral drugs.

The number of deaths with AMI (ICD-10 code I21 and I22) as the underlying cause was obtained from The Causes of Death Register at The Swedish Board of Health and Welfare. Data on the incidence, attack rate, of AMI was obtained from The AMI Statistics at The Swedish Board of Health and Welfare, and comprised fatal as well as non-fatal AMIs (ICD-10 code I21 and I22), as main or secondary diagnosis [3]. The cut off level of Cardiac troponin T, troponin I or creatine kinase (CK-MB) for AMI was changed in 2001 and therefore more AMIs were diagnosed [8]. Routine coronary revascularisation in unstable coronary artery disease has been shown to reduce mortality and non-fatal myocardial infarctions after one year [9]. The number of persons being subjected to coronary revascularisation i.e. coronary artery by pass grafting and/or percutan coronary intervention was obtained from the Centre of Epidemiology, Swedish Board of Health and Welfare and the Swedish Coronary Angiography and Angioplasty Registry (SCAAR). The yearly incidence and mortality of myocardial infarction and coronary revascularisation rates were calculated for each of the 289 Swedish municipalities for men and women and each of the age groups 40-49, 50-59, 60-69 and 70-79 years. The population sizes for the year 2000 were used.

A socio-economic municipality deprivation index consisting of standardised education level (A), salary (B) and unemployment (C) was calculated for men and women respectively for the year 2000.

For each municipality,

A = (X1 - mean1)/SD1, where X1 is percentage low educated (9 years) in the particular municipality, mean1 is mean percentage of low educated in all municipalities, SD1 is standard deviation of low educated in all municipalities,

B = (X2 - mean2)/SD2, where X2 is percentage having an income within the lowest quartile for Sweden in the particular municipality, mean2 is mean percentage of having an income within the lowest quartile for Sweden in all municipalities, SD2 is standard deviation for having an income within the lowest quartile for Sweden in all municipalities, and

C = (X3 - mean3)/SD3, where X3 is percentage unemployed, 40-59 years old, mean3 is mean percentage of unemployed 40-59 years old in all municipalities, SD3 is standard deviation for unemployed 40-59 years old in all municipalities.

Deprivation index is the sum of A, B and C for the particular municipality [10]. Data on low education and low salary was gathered from Statistics Sweden and on unemployment from The National Labour Market Board.

Data on the geographic x- and y- coordinates of each municipality was obtained from The National Land Survey of Sweden [11, 12].

An official grouping of Swedish municipalities into nine groups according to number of inhabitants and infrastructure was used, in order to form subgroups of similar and enough populated municipalities [13]. The groups were 1: Big city (n = 3). Municipalities with a population in excess of 200 000 inhabitants, 2: Suburban municipality (n = 36), 3: Larger town (n = 26). Municipalities with 50 000 to 200 000 inhabitants, 4: Medium-sized town (n = 40). Municipalities with 20 000 to 50 000 inhabitants, 5: Industrial municipality (n = 53), 6: Rural municipality (n = 30), 7: Sparsely populated municipality (n = 29). Municipalities with fewer than 20 000 inhabitants, 8: Other larger municipality (n = 31). Municipalities with 15 000 to 50 000 inhabitants, 9: Other smaller municipality (n = 42). Municipalities with fewer than 15 000 inhabitants.

### Statistical methods

A simple bivariate Pearson correlation coefficient for statin utilisation vs. AMI-incidence and AMI-mortality was calculated for each of the years 1998-2002 and for respective age-groups and gender. Linear regression analysis was used. AMI-incidence was used as the dependent variable and utilisation of statins and antidiabetic drugs, deprivation index, and geographic x- and y-coordinates for each of the 289 municipalities as independent variables. Separate analyses were made for each of the years 1998-2002, and for respective age-groups and gender. The independent variables were ranked in order of significant outcomes vs. incidence in a univariate analyse. According to the ranking, a multivariate statistical model was constructed including the independent variables in the following order, deprivation index, antidiabetic drugs, statin utilisation, x- and y-coordinates. The multivariate model was used in analysing AMI-incidence vs. statin utilisation.

In order to minimise the effect of unusual events and small populations, a multivariate analyses of statin utilisation vs. incidence and mortality, was performed in a group of 26 larger towns, i.e. municipality group 3, with 1857 to 4720 men aged 70-79 years. Considering the time delay for the preventive effect of statins the change in statin utilisation from 1998 to 2000 was estimated as the quotient between statin DDDs per TID in 2000 and in 1998. This quotient was calculated for men aged 70-79 years in each of 149 municipalities, municipality groups 3, 4, 5 and 6. Equivalently, the change in mortality from 2000 to 2002 was calculated in each of those 149 municipalities. A value > 1 implies an increase and < 1 a decrease in statin utilisation or mortality. Subsequently, the quotients representing the change in statin utilisation and the change in AMI mortality were plotted against each other.

The utilisation of statins, AMI-mortality, AMI-incidence and coronary revascularisation rates are shown as means (range) in tables. In the text standard deviations (± SD) also are given.