Table 3.
Bivariate association between changes in EBSMRs and PHNs by no-intercept simple regression analysis
Variables of change (2015–2010) | All municipalities | Population < 10,000 | Population ≥ 10,000 | |||
---|---|---|---|---|---|---|
(n = 1601) | (n = 470) | (n = 1131) | ||||
Coefb | P-value | Coefb | P-value | Coefb | P-value | |
EBSMRs in malesa | ||||||
All causes of death | -4.42 | < 0.001 | -3.39 | 0.001 | -5.30 | < 0.001 |
Malignant neoplasms | -4.02 | < 0.001 | -3.86 | < 0.001 | -4.16 | < 0.001 |
Heart disease in males | -3.65 | 0.002 | -1.02 | 0.630 | -5.88 | < 0.001 |
Cerebrovascular disease | -11.60 | < 0.001 | -8.20 | 0.009 | -14.49 | < 0.001 |
EBSMRs in femalesa | ||||||
All causes of death | -2.08 | < 0.001 | -1.61 | 0.111 | -2.48 | < 0.001 |
Malignant neoplasms | -0.49 | 0.405 | -0.39 | 0.739 | -0.57 | 0.375 |
Heart disease | -5.06 | < 0.001 | -3.49 | 0.089 | -6.40 | < 0.001 |
Cerebrovascular disease | -10.99 | < 0.001 | -7.62 | 0.014 | -13.87 | < 0.001 |
Coef Coefficient, EBSMR Empirical Bayes estimate of standardized mortality ratio, PHN Public health nurse
a Dependent variables
b Coefficients of PHNs (2015–2010) per 100,000 population (logarithmic transformed)