BACKGROUND: Low socioeconomic status (SES) has been associated with increased risk of disability in later life. The purpose of this study was to determine if SES has an impact on mobility functioning and to explore which physiological impairments are also associated with SES and may explain its relationship with mobility. METHODS: The study sample consisted of 1025 individuals aged 65 years or older residing in the Chianti area (Italy). Number of years of education was used as an indicator of SES. Mobility functioning was assessed using gait speed (400 m) and the Short Physical Performance Battery (SPPB). Mobility-related physiological impairments were assessed with tests of executive functioning, nerve conduction velocity, muscle power, hip-ankle range of motion, Ankle-Brachial Index, and visual acuity. Linear regression models were used to study the association between number of years of education and mobility and to estimate the contribution of each of the selected physiological impairments to this association. RESULTS: Adjusting for age and sex, slower gait speed (1.16 vs 1.26 m/s, p <.0001) and lower SPPB scores (9.55 vs 10.11, p =.006) were seen in persons with < or =5 years of total education compared with those persons with >5 years of total education. Leg power and executive function decreased the strength of the association between educational level and gait speed by more than 15%. Controlling for all selected impairments (full model) decreased the education-gait speed association by 49%. Low education continued to be significantly associated with gait speed (p <.01). Adjusting for all physiological impairments substantially reduced the low education-SPPB score association by 100%, and this association was no longer significant. CONCLUSIONS: Low SES is related to multiple physiological impairments, which explain a large amount of the association between education and gait limitations. Further work must be done to understand the mechanisms whereby low SES translates into the impairments that play an important role in mobility.
BACKGROUND: Low socioeconomic status (SES) has been associated with increased risk of disability in later life. The purpose of this study was to determine if SES has an impact on mobility functioning and to explore which physiological impairments are also associated with SES and may explain its relationship with mobility. METHODS: The study sample consisted of 1025 individuals aged 65 years or older residing in the Chianti area (Italy). Number of years of education was used as an indicator of SES. Mobility functioning was assessed using gait speed (400 m) and the Short Physical Performance Battery (SPPB). Mobility-related physiological impairments were assessed with tests of executive functioning, nerve conduction velocity, muscle power, hip-ankle range of motion, Ankle-Brachial Index, and visual acuity. Linear regression models were used to study the association between number of years of education and mobility and to estimate the contribution of each of the selected physiological impairments to this association. RESULTS: Adjusting for age and sex, slower gait speed (1.16 vs 1.26 m/s, p <.0001) and lower SPPB scores (9.55 vs 10.11, p =.006) were seen in persons with < or =5 years of total education compared with those persons with >5 years of total education. Leg power and executive function decreased the strength of the association between educational level and gait speed by more than 15%. Controlling for all selected impairments (full model) decreased the education-gait speed association by 49%. Low education continued to be significantly associated with gait speed (p <.01). Adjusting for all physiological impairments substantially reduced the low education-SPPB score association by 100%, and this association was no longer significant. CONCLUSIONS: Low SES is related to multiple physiological impairments, which explain a large amount of the association between education and gait limitations. Further work must be done to understand the mechanisms whereby low SES translates into the impairments that play an important role in mobility.
Authors: Kate Birnie; Richard M Martin; John Gallacher; Antony Bayer; David Gunnell; Shah Ebrahim; Yoav Ben-Shlomo Journal: J Epidemiol Community Health Date: 2010-07-19 Impact factor: 3.710
Authors: Joshua Z Willey; Yeseon P Moon; Mandip S Dhamoon; Erin R Kulick; Ahmet Bagci; Noam Alperin; Ying Kuen Cheung; Clinton B Wright; Ralph L Sacco; Mitchell S V Elkind Journal: Neuroepidemiology Date: 2018-06-28 Impact factor: 3.282
Authors: John E Morley; Angela Marie Abbatecola; Josep M Argiles; Vickie Baracos; Juergen Bauer; Shalender Bhasin; Tommy Cederholm; Andrew J Stewart Coats; Steven R Cummings; William J Evans; Kenneth Fearon; Luigi Ferrucci; Roger A Fielding; Jack M Guralnik; Tamara B Harris; Akio Inui; Kamyar Kalantar-Zadeh; Bridget-Anne Kirwan; Giovanni Mantovani; Maurizio Muscaritoli; Anne B Newman; Filippo Rossi-Fanelli; Giuseppe M C Rosano; Ronenn Roubenoff; Morris Schambelan; Gerald H Sokol; Thomas W Storer; Bruno Vellas; Stephan von Haehling; Shing-Shing Yeh; Stefan D Anker Journal: J Am Med Dir Assoc Date: 2011-07 Impact factor: 4.669
Authors: Aron S Buchman; Patricia A Boyle; Sue E Leurgans; Lisa L Barnes; David A Bennett Journal: Am J Geriatr Psychiatry Date: 2011-06 Impact factor: 4.105
Authors: Roland James Thorpe; Judith D Kasper; Sarah L Szanton; Kevin D Frick; Linda P Fried; Eleanor M Simonsick Journal: Soc Sci Med Date: 2007-12-27 Impact factor: 4.634