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Updated: Aug 9, 2025

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
Published on: January 5, 2024
Cross-sectional study examining the epidemiology of chronic pain in Nepal
Cassie Higgins1, Saurab Sharma2,3, Inosha Bimali4
1Division of Population Health and Genomics, School of Medicine, Ninewells Hospital, University of Dundee, Dundee, Scotland.
Introduction:
The World Health Organization recognizes chronic pain as a global public health concern; however, there is a bias towards research conducted in relatively affluent nations. There is a dearth of large-scale epidemiological studies in Nepal using rigorously validated, cross-culturally adapted instruments.
Objectives:
The aim of this study was to examine the prevalence of both chronic pain and chronic pain of predominantly neuropathic origin and their associations with a range of sociodemographic and psychosocial characteristics.
Methods:
We conducted a cross-sectional study of adults (≥18 years) in all households in Ranipani, Baluwa Village Development Committee, Nepal. All adults (n = 887) were approached, and those consenting, who met the inclusion criteria (n = 520, 58.6%), participated. Questionnaires validated in Nepali were used to examine several constructs: demographics; chronic pain; neuropathic pain; pain catastrophizing; resilience, pain intensity; pain interference; sleep disturbance; and depression.
Results:
The point prevalence of chronic pain was 53.3% (n = 277). The point prevalence of chronic pain of predominantly neuropathic origin was 12.7% (n = 66). Chronic pain was associated with female gender, older age, and manual labour occupations. Using standardized scoring techniques, compared with available population estimates from other countries, those with chronic pain were associated with lower pain intensity and resilience scores and higher pain catastrophizing, pain interference, and depression scores.
Conclusion:
These findings are broadly comparable to epidemiological studies from other countries, and these indicate areas for targeting interventions (eg, occupational and mental health). For comparison, more data are needed, from larger population samples in this region.
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