Association between frailty, chronic conditions and socioeconomic status in community-dwelling older adults attending primary care: a cross-sectional study using practice-based research network data.

Objectives: Frailty is a multidimensional syndrome of loss of reserves in energy, physical ability, cognition and general health. Primary care is key in preventing and managing frailty, mindful of the social dimensions that contribute to its risk, prognosis and appropriate patient support. We studied associations between frailty levels and both chronic conditions and socioeconomic status (SES).

Design: Cross-sectional cohort study SETTING: A practice-based research network (PBRN) in Ontario, Canada, providing primary care to 38 000 patients. The PBRN hosts a regularly updated database containing deidentified, longitudinal, primary care practice data.

Participants: Patients aged 65 years or older, with a recent encounter, rostered to family physicians at the PBRN.

Intervention: Physicians assigned a frailty score to patients using the 9-point Clinical Frailty Scale. We linked frailty scores to chronic conditions and neighbourhood-level SES to examine associations between these three domains.

Results: Among 2043 patients assessed, the prevalence of low (scoring 1-3), medium (scoring 4-6) and high (scoring 7-9) frailty was 55.8%, 40.3%, and 3.8%, respectively. The prevalence of five or more chronic diseases was 11% among low-frailty, 26% among medium-frailty and 44% among high-frailty groups (χ=137.92, df 2, p<0.001). More disabling conditions appeared in the top 50% of conditions in the highest-frailty group compared with the low and medium groups. Increasing frailty was significantly associated with lower neighbourhood income (χ=61.42, df 8, p<0.001) and higher neighbourhood material deprivation (χ=55.24, df 8, p<0.001).

Conclusion: This study demonstrates the triple disadvantage of frailty, disease burden and socioeconomic disadvantage. Frailty care needs a health equity approach: we demonstrate the utility and feasibility of collecting patient-level data within primary care. Such data can relate social risk factors, frailty and chronic disease towards flagging patients with the greatest need and creating targeted interventions.