Prevalence and predictors of multimorbidity among immigrant Asian Indian women residing in Sydney Australia: A cross-sectional study

Abstract

Background: There has been a rise in multimorbidity as people age and technology advances which is challenging for health systems. Multimorbidity prevalence varies globally due to various biological and social risk factors which can be accentuated or mitigated for populations in migration. This study investigated the prevalence and predictors of multimorbidity amongst a group of migrant Asian Indian women living in Australia. Methods: A cross-sectional descriptive study design using convenience sampling investigated the multimorbidity risk factors among first generation migrant Asian Indian women in Australia. This study was part of a larger study titled “Measuring Acculturation and Psychological Health of Senior Indian Women Living in Australia” that was conducted in Sydney, Australia. Data were collected using validated instruments as well as investigator developed questions. Women completed questionnaire surveys either by themselves or through the assistance of bilingual coordinators as English was not their first language. Results: 26% of the participants had one chronic condition and 74% had multimorbidities. The prevalence of individual conditions included cardiovascular disease 67.0%, osteoarthritis 57.6%, depression 37.4%, diabetes 31.5%, chronic respiratory conditions 10.8%, cancer 4.9% and nephrological problems 1.47%. In the unadjusted model, factors such as increasing age, education level, employment status, living arrangements, low physical activity, and elements of acculturative stress were significantly associated with multimorbidity. Multi-variable analysis identified the acculturative stress factor of threat to ethnic identity as a predictor of multimorbidity. Conclusion: Identifying the key determinants of multimorbidity in older adults from a migrant community with pre-existing risk factors can assist with the development of culturally appropriate strategies to identify people at risk of health conditions and to mitigate the health effects of acculturative stress.

Impact of a digital health literacy intervention and risk predictors for multimorbidity among poor women of reproductive years: Results of a randomized-controlled trial

“…In addition, living in rented houses and living in houses made of non-permanent material are also predictors of multimorbidity. Other research confirms that joblessness and low pay 27 as well as unfavorable household characteristics 28 contribute to multimorbidity. Women who have more than six children and are taking care of one or more physically dependent family members are also at higher risk.…”