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Multimorbidity and Complex Multimorbidity in India: Findings from the 2017–2018 Longitudinal Ageing Study in India (LASI)

Author

Listed:
  • Abhinav Sinha

    (ICMR-Regional Medical Research Centre, Bhubaneswar 751023, India)

  • Sushmita Kerketta

    (ICMR-Regional Medical Research Centre, Bhubaneswar 751023, India)

  • Shishirendu Ghosal

    (ICMR-Regional Medical Research Centre, Bhubaneswar 751023, India)

  • Srikanta Kanungo

    (ICMR-Regional Medical Research Centre, Bhubaneswar 751023, India)

  • John Tayu Lee

    (The Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
    Public Health Policy Evaluation Unit, Department of Primary Care and Public Health, School of Public Health, Imperial College London, London SW7 2AZ, UK)

  • Sanghamitra Pati

    (ICMR-Regional Medical Research Centre, Bhubaneswar 751023, India)

Abstract

Complex multimorbidity refers to the co-occurrence of three or more chronic illnesses across >2 body systems, which may identify persons in need of additional medical support and treatment. There is a scarcity of evidence on the differences in patient outcomes between non-complex (≥2 conditions) and complex multimorbidity groups. We evaluated the prevalence and patient outcomes of complex multimorbidity and compared them to non-complex multimorbidity. We included 30,489 multimorbid individuals aged ≥45 years from the Longitudinal Ageing Study in India (LASI) from wave-1 conducted in 2017–2018. We employed a log link in generalised linear models (GLM) to identify possible risk factors presenting the adjusted prevalence–risk ratio (APRR) and adjusted prevalence–risk difference (APRD) with 95% confidence interval. The prevalence of complex multimorbidity was 34.5% among multimorbid individuals. Participants residing in urban areas [APRR: 1.10 (1.02, 1.20)], [APRD: 0.04 (0.006, 0.07)] were more likely to report complex multimorbidity. Participants with complex multimorbidity availed significantly higher inpatient department services and had higher expenditure as compared to the non-complex multimorbidity group. Our findings have major implications for healthcare systems in terms of meeting the requirements of people with complicated multimorbidity, as they have significantly higher inpatient health service utilisation, higher medical costs, and poorer self-rated health.

Suggested Citation

  • Abhinav Sinha & Sushmita Kerketta & Shishirendu Ghosal & Srikanta Kanungo & John Tayu Lee & Sanghamitra Pati, 2022. "Multimorbidity and Complex Multimorbidity in India: Findings from the 2017–2018 Longitudinal Ageing Study in India (LASI)," IJERPH, MDPI, vol. 19(15), pages 1-13, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9091-:d:871887
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    References listed on IDEAS

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    1. Christopher J. M. Whitty & Fiona M. Watt, 2020. "Map clusters of diseases to tackle multimorbidity," Nature, Nature, vol. 579(7800), pages 494-496, March.
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    1. Preeti Pushpalata Zanwar & Robyn Taylor & Tanisha G. Hill-Jarrett & Elena Tsoy & Jason D. Flatt & Zunera Mirza & Carl V. Hill & Arokiasamy Perianayagam, 2024. "Characterizing Multimorbidity Prevalence and Adverse Outcomes in Ethnically and Culturally Diverse Sub-Populations in India: Gaps, Opportunities, and Future Directions," IJERPH, MDPI, vol. 21(3), pages 1-14, March.

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