Feeling older, walking slower—but only if someone’s watching. Subjective age is associated with walking speed in the laboratory, but not in real life
The huge inter-individual differences in how people age have prompted researchers to examine whether people’s own perception of how old they are—their subjective age—could be a better predictor of relevant outcomes than their actual chronological age. Indeed, how old people feel does predict mortality hazards, and health-related measures such as walking speed may account for this association. In the present study, we extended this line of work by investigating whether subjective age also predicts walking speed and running speed in daily life or whether the predictive effects of subjective age for behavior manifest only within a controlled performance situation. We used data from 80 older participants (age range 62–82 years; M = 69.50, SD = 4.47) from the Berlin Aging Study II (BASE-II). Subjective age was assessed by self-report. Walking speed in the laboratory was measured with the Timed Up and Go test, and walking speed and running speed in real life were measured with an accelerometer. Results showed that compared to participants who felt older, those who felt younger than they actually were indeed walked faster in the laboratory, but they did not walk or run faster in real life. These patterns of results held when age, gender, education, BMI, comorbidity, depression, physical activity, and cognition were covaried. We discuss the role of stereotype threat in accounting for these results.
KeywordsWalking speed Subjective age Age stereotypes Health Running speed
This manuscript reports data from the Berlin Aging Study II (BASE-II). The BASE-II research project (Co-PIs are Lars Bertram, Denis Gerstorf, Ulman Lindenberger, Graham Pawelec, Elisabeth Steinhagen-Thiessen, and Gert G. Wagner) is supported by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) under grant numbers #16SV5536 K, #16SV5537, #16SV5538, and #16SV5837, and #01UW0808). Another source of funding is the Max Planck Institute for Human Development, Berlin, Germany. Additional contributions (e.g., equipment, logistics, personnel) are made from each of the other participating sites. Further details about the study can be obtained at https://www.base2.mpg.de/en. We thank Martin Daumer from the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR), e.V., Munich, Germany for his input regarding the use of the actibelt accelerometer. The SLCMSR co-developed the device. N. N. was supported by a Horizon 2020 Marie Sklodowska-Curie Individual Fellowship (grant number H2020-MSCA-IF-2014 661555).
- Baltes, PB, Lindenberger, U, Staudinger, UM (2006). Lifespan theory in developmental psychology. In R. M. Lerner (Ed.), Handbook of child psychology Vol. 1: Theoretical models of human development (6th ed., pp. 569–664). New York, NY: Wiley. doi: 10.1002/9780470147658.chpsy0111Google Scholar
- Caspersen CJ, Powell KE, Christenson GM (1985) Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep 100:126–131Google Scholar
- Cesari M, Kritchevsky SB, Penninx BW, Nicklas BJ, Simonsick EM, Newman AB, Visser M (2005) Prognostic value of usual gait speed in well-functioning older people—results from the health, aging and body composition study. J Am Geriatr Soc 53:1675–1680. https://doi.org/10.1111/j.1532-5415.2005.53501.x CrossRefGoogle Scholar
- Düzel S, Völkle M, Düzel E, Gerstorf D, Drewelies J, Steinhagen-Thiessen E, Demuth I, Lindenberger U (2016) The subjective health horizon questionnaire (SHH-Q): assessing future time perspectives for facets of an active lifestyle. Gerontology 62:345–353. https://doi.org/10.1159/000441493 CrossRefGoogle Scholar
- Gerstorf D, Hülür G, Drewelies J, Eibich P, Düzel S, Demuth I, Ghisletta P, Steinhagen-Thiessen E, Wagner GG, Lindenberger U (2015) Secular changes in late-life cognition and well-being: towards a long bright future with a short brisk ending? Psychol Aging 30:301–310. https://doi.org/10.1037/pag0000016 CrossRefGoogle Scholar
- Gouveia ÉR, Gouveia BR, Ihle A, Kliegel M, Maia JA, Badia SB, Freitas DL (2017) Correlates of lifestyle and functional fitness status influencing health-related quality of life in community-dwelling older people. Qual Life Res 26:1561–1569. https://doi.org/10.1007/s11136-017-1502-z CrossRefGoogle Scholar
- Ihira H, Furuna T, Mizumoto A, Makino K, Saitoh S, Ohnishi H, Makizako H (2015) Subjective physical and cognitive age among community-dwelling older people aged 75 years and older: differences with chronological age and its associated factors. Aging Ment Health 19:756–761. https://doi.org/10.1080/13607863.2014.967169 CrossRefGoogle Scholar
- Motl RW, Weikert M, Suh Y, Sosnoff JJ, Pula J, Soaz C, Daumer M (2012) Accuracy of the actibelt ® accelerometer for measuring walking speed in a controlled environment among persons with multiple sclerosis. Gait Posture 35:192–196. https://doi.org/10.1016/j.gaitpost.2011.09.005 CrossRefGoogle Scholar
- Mueller S, Wagner J, Drewelies J, Duezel S, Eibich P, Specht J, Demuth I, Steinhagen-Thiessen E, Wagner GG, Gerstorf D (2016) Personality development in old age relates to physical health and cognitive performance: evidence from the Berlin aging study II. J Res Pers 65:94–108. https://doi.org/10.1016/j.jrp.2016.08.007 CrossRefGoogle Scholar
- Podsiadlo D, Richardson S (1991) The Timed “Up & Go”: A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39:142–148. https://doi.org/10.1111/j.1532-5415.1991.tb01616.x CrossRefGoogle Scholar
- Simonsick EM, Montgomery PS, Newman AB, Bauer DC, Harris T (2001) Measuring fitness in healthy older adults: the health ABC long distance corridor walk. J Am Geriatr Soc 49:1544–1548. https://doi.org/10.1046/j.1532-5415.2001.4911247.x CrossRefGoogle Scholar