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. 2023 Aug 25;102(34):e34818. doi: 10.1097/MD.0000000000034818

Table 5.

Multiple logistic regression analysis for the associations of variables with the prescription of PIMs.

Variables OR* (95% CI) P value
Age** 65–69 Ref
70–74 0.96 (0.94–0.99) <.001
75–79 1.00 (0.98–1.03) .855
≥80 1.04 (1.02–1.07) <.001
Gender Female Ref <.001
Male 1.27 (1.25–1.29)
Type of insurance*** Health insurance Ref <.001
Medical Aid 1.71 (1.67–1.74)
Chronic disease**** Hypertension (Yes) 1.03 (1.01–1.05) <.001
Diabetes Mellitus (Yes) 1.14 (1.12–1.16)
Heart disease (Yes) 1.33 (1.31–1.69)
Cerebrovascular disease (Yes) 1.37 (1.34–1.39)
Neoplasm (Yes) 1.43 (1.40–1.46)
Liver disease (Yes) 1.11 (1.09–1.13)
Mental and behavior disorder (Yes) 5.59 (5.82–6.16)
Respiratory Tuberculosis (Yes) 1.10 (1.04–1.17)
Nervous Disease (Yes) 2.63 (2.57–2.70)
Thyroid gland Disease (Yes) 1.09 (1.07–1.11)
Chronic Renal Disease (Yes) 1.16 (1.13–1.10)
Arthropathy (Yes) 0.92 (0.90–0.94)
*

The dependent variable was divided into 2 groups: ≥5 PIMs vs <5 PIMs in 1 claim.

**

As the patients’ age increased during the study period, it was defined as the age at which the last claim data was processed.

***

The type of insurance was classified as medical aid if patients received medical aid at least once.

***

*Patients who had been diagnosed with a chronic disease at least once were categorized as those with chronic diseases

PIMs = potentially inappropriate medications.