DOI: https://dx.doi.org/10.18203/2394-6040.ijcmph20222572
Published: 2022-09-28

A multinomial regression model to determine the factors related to morbidity pattern among the geriatric population of Jammu district, Jammu and Kashmir

V. K. Shivgotra, Himani Nanda, Manjeet Kumar

Abstract


Background: Ageing is progressive phenomenon beginning with conception and ends with death. It is a universal reality characterized by increase in morbidity, multimorbidity, increased health care and social demands. The purpose of this study was to examine patterns in morbidities existing among geriatric population and to identify effect of various socio-demographic variables on number of morbidities prevailing among them.

Methods: A cross-sectional study was conducted among geriatric population of Jammu district, Jammu and Kashmir, India by using multi-stage procedure. Descriptive analysis was done by using software IBM SPSS version 25.0. Multinomial regression model was used to examine effect of various socio-demographic variables on number of chronic morbidities prevailing among them.

Results: A total of 750 geriatric persons included 392 (52.3%) males and 352 (48.7%) females. Majority of them were suffering from vision problems (51.5%), followed by arthritis (40.7%), hypertension (39.3%), and so on. It was observed that Nagalkerke’s R square was 0.331 which showed that there exists weak relationship (33.1%) between the predictors and predicted variable. Our findings reported that gender, marital status, dependency status, socio-economic factors and increasing age were mainly responsible for predicting number of morbidities at various levels among the geriatric population with reference category one morbidity.

Conclusions: The findings of this study are important to support policy makers and health care professionals in recognizing individuals at risk that could be integrated into current programs of social, economic and health security of older persons.


Keywords


Ageing, Geriatric, Morbidity, Maximum likelihood estimate, Multinomial regression

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