Sociodemographic, behavioural and cardiometabolic correlates of severe locomotive syndrome among older adults attending an urban health training centre in Maharashtra: a facility based cross-sectional study

Ajith Ramalingam; Rashmi Urkude; Ranjit Mankeshwar; Aishwarya Balakrishnan

doi:10.18203/2394-6040.ijcmph20263612

Authors

Ajith Ramalingam Department of Community Medicine, Grant Government Medical College & Sir J. J. Group of Hospitals, Mumbai, Maharashtra, India https://orcid.org/0009-0003-4212-1898
Rashmi Urkude Department of General Medicine, Urban Health Training Centre, Bandra East, Mumbai, Maharashtra, India
Ranjit Mankeshwar Department of Community Medicine, Grant Government Medical College & Sir J. J. Group of Hospitals, Mumbai, Maharashtra, India
Aishwarya Balakrishnan Department of Community Medicine, Grant Government Medical College & Sir J. J. Group of Hospitals, Mumbai, Maharashtra, India https://orcid.org/0009-0008-2919-1070

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20263612

Keywords:

Analytical cross-sectional, Anthropometric assessment, Cardiometabolic health, Geriatrics, Healthy ageing, Locomotor system

Abstract

Background: Severe Locomotive Syndrome (severe LS) is an emerging public health concern that affects functional independence among older adults. Evidence on its sociodemographic, behavioural, and cardiometabolic correlates in India remains limited. This study aimed to identify correlates of severe LS among older adults attending an urban health training centre in Maharashtra.

Methods: A facility-based cross-sectional study was conducted among 264 adults aged ≥60 years. Sociodemographic, behavioural, and cardiometabolic data were collected using a structured questionnaire. LS was assessed using the Stand-Up Test, Two-Step Test, and the 25-item Geriatric Locomotive Function Scale (GLFS-25). Participants were categorised as non-severe LS (LS-1/LS-2) or severe LS (LS-3). Associations were examined using Pearson's chi-square test and the Mann–Whitney U test. Multivariable logistic regression and dose–response trend analyses were performed, and model performance was evaluated.

Results: The median age of participants was 70 years (IQR: 66–74), and 57.6% were female. Severe LS was observed in 55.3% of participants. Independent correlates of severe LS included age ≥70 years, female gender, non-graduate educational status, history of falls, smoking, central obesity, and hyperlipidaemia. The odds of severe LS increased significantly with the number of cardiometabolic disorders (score test for trend, p<0.001). The model demonstrated good fit (Hosmer–Lemeshow p=0.238) and good discriminatory ability (AUC=0.89).

Conclusions: Severe LS affected more than half of the study participants and was significantly associated with advancing age and several modifiable risk factors. These findings highlight the need for early screening and targeted interventions to promote healthy ageing among urban older adults.

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