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. 2023 Mar 17;23:266. doi: 10.1186/s12913-023-09273-2

Table 5.

Stratified analysis of the relationship between changes in EBSMRs and PHNs (n = 1601)

Variables of change (2015–2010) Stratified analysis by baseline population Stratified analysis by baseline EBSMRs
Population < 10,000 Population ≥ 10,000 EBSMR < 100 EBSMR ≥ 100
(n = 470) (n = 1131)
Coefb P-value Coefb P-value (n) Coefb P-value (n) Coefb P-value
EBSMRs in malesa
 All causes of death -1.81 0.009 -1.00 0.026 (780) 0.20 0.638 (821) -1.90 0.001
 Malignant neoplasms -2.41 0.005 0.02 0.966 (960) -0.23 0.668 (641) -1.59 0.015
 Heart disease in males 1.61 0.371 -0.38 0.676 (745) 1.16 0.188 (856) -0.88 0.541
 Cerebrovascular disease -2.18 0.321 -2.21 0.065 (755) 1.09 0.335 (846) -2.43 0.128
EBSMRs in femalesa
 All causes of death -0.96 0.309 -0.31 0.536 (844) -0.95 0.084 (757) -0.36 0.624
 Malignant neoplasms -0.13 0.906 0.88 0.126 (1120) 0.47 0.442 (481) -0.30 0.715
 Heart disease -1.83 0.341 -0.91 0.352 (800) -2.09 0.040 (801) -0.18 0.909
 Cerebrovascular disease -2.57 0.283 -1.53 0.203 (808) -0.86 0.443 (793) -0.52 0.780

Coef Coefficient, EBSMR Empirical Bayes estimate of standardized mortality ratio, PHN Public health nurse

a Dependent variables

b Coefficients of PHNs per 100,000 population (logarithmic transformed) which are adjusted for random effects by prefecture and fixed effects by change of the number of population (logarithmic transformed) and healthcare resources per 100,000 population (2015–2010): physicians, medical clinics, general hospitals in a secondary healthcare area, and welfare facilities for the elderly requiring long-term care