Year: 2026
Type: article
Study design: Observational Study
Abstract: ABSTRACT Introduction While bipolar disorder is associated with significant comorbidity, little is known about the musculoskeletal health of individuals with bipolar disorder. Thus, we aimed to investigate the association between bipolar disorder and muscle strength, mass, quality and sarcopenia. Methods Women with bipolar disorder ( n = 106) were recruited from healthcare settings and age‐matched to controls ( n = 300), without bipolar disorder, from the Geelong Osteoporosis Study. Both groups, aged ≥ 20 years. were drawn from South‐Eastern Australia. Bipolar disorder was identified using a clinical interview (SCID‐I/NP). Maximum handgrip strength (HGS) was measured using a Jamar dynamometer, appendicular lean mass (ALM) using a Lunar densitometer and body mass index (BMI, kg/m 2 ) was calculated. Foundation for the National Institute of Health (FNIH) and European Working Group on Sarcopenia in Older People (EWGSOP2) algorithms were used to determine low HGS, ALM, probable and confirmed sarcopenia. Socioeconomic status (SES) was determined and information on lifestyle obtained via questionnaire. Results Higher proportion of women with bipolar disorder met criteria for low HGS and ALM compared to those without bipolar disorder. Using FNIH and EWGSOP2 criteria, 36 (8.9%; 34 probable and 2 confirmed) and 46 (11.4%; 43 probable and 3 confirmed) women met criteria for sarcopenia, respectively. Women with bipolar disorder were twice as likely to have sarcopenia (FNIH; OR 2.24, 95% CI: 1.11–4.55 and EWGSOP2; OR 2.78, 95% CI: 1.47–5.20), independent of age, smoking, activity, alcohol, diet and SES. Conclusion These data suggest women with bipolar disorder have an increased likelihood of sarcopenia. Replication and research into underlying mechanisms are next necessary steps.
Source: Bipolar Disorders
DOI: 10.1111/bdi.70192
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,730
OpenAlex ID: W7223065701
