Modeling the spectrum and determinants of multimorbidity risk among older adults in India.
<h4>Background</h4>India is passing through a parallel phase of demographic and epidemiological transition coupled with the shifting burden of multimorbidity. Unhealthy ageing and escalating morbidity burden have been identified as key drivers of this shifting multimorbidity risk among o...
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0323744 |
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| author | Ajay Kumar Bharti Singh |
| author_facet | Ajay Kumar Bharti Singh |
| author_sort | Ajay Kumar |
| collection | DOAJ |
| description | <h4>Background</h4>India is passing through a parallel phase of demographic and epidemiological transition coupled with the shifting burden of multimorbidity. Unhealthy ageing and escalating morbidity burden have been identified as key drivers of this shifting multimorbidity risk among older adults in India. This study aims to assess the distribution of morbidities and multimorbidity, provide new estimates of multimorbidity risk by socio-economic and demographic factors and further evaluate the multimorbidity count risk conditioned on leading factors.<h4>Methods</h4>This study used the nationally representative Longitudinal Ageing Study in India (LASI), Wave - 1, 2017-18, data of individuals aged 45 years and above. First, we assessed the relative proportional share of morbidities and compositions of multimorbidity counts over age. Second, we applied the Random Forest (RF) model to estimate the age-specific risk of multimorbidity susceptibility associated with socio-economic and demographic factors over age. Finally, conditional plots were constructed to assess the distributional composition of the leading factors affecting multimorbidity counts.<h4>Results</h4>The prevalence of multimorbidity was 43.20%. Eye disorders, followed by cardiovascular disease (CVDs), had the highest proportional share over age. Endocrine diseases, Gastrointestinal Conditions, and Infectious diseases showed a concordant decreasing proportional share in later age. The relative share of five or more multimorbidity counts increased significantly with age. The median expected risk of multimorbidity was significantly higher in females (66 years) than in males (71 years). The study also provides empirical evidence that individuals with higher levels of education, obesity, currently working, and poor childhood health were more prone to higher risk of multimorbidity at an early age. Furthermore, obesity was significantly associated with early multimorbidity onset and led to a pronounced escalation of complex multimorbidity progression, particularly in females.<h4>Conclusions</h4>Collective public health interventions are crucial to address early multimorbidity onset and burden disparities, to promote healthier ageing, and to address etiological factors. |
| format | Article |
| id | doaj-art-25d5228038ad4e3f95ed18c2cf7f5275 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
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| spelling | doaj-art-25d5228038ad4e3f95ed18c2cf7f52752025-08-20T03:13:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032374410.1371/journal.pone.0323744Modeling the spectrum and determinants of multimorbidity risk among older adults in India.Ajay KumarBharti Singh<h4>Background</h4>India is passing through a parallel phase of demographic and epidemiological transition coupled with the shifting burden of multimorbidity. Unhealthy ageing and escalating morbidity burden have been identified as key drivers of this shifting multimorbidity risk among older adults in India. This study aims to assess the distribution of morbidities and multimorbidity, provide new estimates of multimorbidity risk by socio-economic and demographic factors and further evaluate the multimorbidity count risk conditioned on leading factors.<h4>Methods</h4>This study used the nationally representative Longitudinal Ageing Study in India (LASI), Wave - 1, 2017-18, data of individuals aged 45 years and above. First, we assessed the relative proportional share of morbidities and compositions of multimorbidity counts over age. Second, we applied the Random Forest (RF) model to estimate the age-specific risk of multimorbidity susceptibility associated with socio-economic and demographic factors over age. Finally, conditional plots were constructed to assess the distributional composition of the leading factors affecting multimorbidity counts.<h4>Results</h4>The prevalence of multimorbidity was 43.20%. Eye disorders, followed by cardiovascular disease (CVDs), had the highest proportional share over age. Endocrine diseases, Gastrointestinal Conditions, and Infectious diseases showed a concordant decreasing proportional share in later age. The relative share of five or more multimorbidity counts increased significantly with age. The median expected risk of multimorbidity was significantly higher in females (66 years) than in males (71 years). The study also provides empirical evidence that individuals with higher levels of education, obesity, currently working, and poor childhood health were more prone to higher risk of multimorbidity at an early age. Furthermore, obesity was significantly associated with early multimorbidity onset and led to a pronounced escalation of complex multimorbidity progression, particularly in females.<h4>Conclusions</h4>Collective public health interventions are crucial to address early multimorbidity onset and burden disparities, to promote healthier ageing, and to address etiological factors.https://doi.org/10.1371/journal.pone.0323744 |
| spellingShingle | Ajay Kumar Bharti Singh Modeling the spectrum and determinants of multimorbidity risk among older adults in India. PLoS ONE |
| title | Modeling the spectrum and determinants of multimorbidity risk among older adults in India. |
| title_full | Modeling the spectrum and determinants of multimorbidity risk among older adults in India. |
| title_fullStr | Modeling the spectrum and determinants of multimorbidity risk among older adults in India. |
| title_full_unstemmed | Modeling the spectrum and determinants of multimorbidity risk among older adults in India. |
| title_short | Modeling the spectrum and determinants of multimorbidity risk among older adults in India. |
| title_sort | modeling the spectrum and determinants of multimorbidity risk among older adults in india |
| url | https://doi.org/10.1371/journal.pone.0323744 |
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