Skip to main content

How you live is how you feel? Positive associations between different lifestyle factors, cognitive functioning, and health-related quality of life across adulthood

Abstract

Purpose

Self-reported health-related quality of life (HRQoL) represents one central indicator for the need of prevention or intervention with gaining importance for public health monitoring. As part of this framework, the present study aims to identify potentially supportive factors of HRQoL and to determine age-related differences.

Methods

In a sample of young to older adults (18–79 years; M = 52.71, SD = 16.06) from the German Health Interview and Examination Survey for Adults (DEGS1 subsample, n = 3667, 52% female), we investigated interrelations between individual (e.g., chronic condition), social (e.g., social support), and lifestyle factors (e.g., healthy eating) and executive functioning with the physical composite scale (PCS) and the mental composite scale (MCS) of HRQoL with the help of path analyses. Secondly, we performed multiple regression analyses to determine age interactions.

Results

Results suggest direct and indirect paths on PCS, respectively, MCS from various lifestyle factors and executive functioning in addition to individual and social factors with a good model fit (PCS: CD = .63, SRMR = .001; MCS: CD = .64, SRMR = .003). Furthermore, results suggest physical activity and healthy eating to become particularly relevant with advancing age (age group  ×  physical activity on PCS, β = .09, p < .05; age group × healthy eating on MCS, β > .50, p < .01).

Conclusions

Several lifestyle factors and executive functioning offer the potential to promote HRQoL in the everyday life of individuals at various ages, independent of individual or social determinants. Public health action might want to foster behavioral multicomponent approaches supporting healthy aging.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Notes

  1. We tested multicollinearity by taking the correlation between indicators and the variance inflation factor (VIF) of all indicators of the regression model into account. All values were below the conventional limits of r < .70 and VIF < 10 (e.g., [56]).

  2. We furthermore tested for HRQoL differences between the three physical activity (none, < 2 h, > 2 h) and healthy eating categories (low, medium, high) for each age group, separately. PCS scores differed significantly regarding physical activity for young (none vs. < 2 h B = − 0.14, SE = 0.75, p = .85; none vs. > 2 h B = 1.67, SE = 0.70, p = .02), middle-aged (none vs. < 2 h B = 0.41, SE = 0.73, p = .58; none vs. > 2 h B = 2.71, SE = 0.72, p < .01) as well as older adults (none vs. < 2 h B = 2.85, SE = 0.83, p < .01; none vs. > 2 h B = 5.21, SE = 0.94, p < .01), while MCS scores did not differ significantly regarding physical activity for young (none vs. < 2 h B = 1.47, SE = 1.24, p = .24; none vs. > 2 h B = 1.96, SE = 1.30, p = .14), middle-aged (none vs. < 2 h B = 0.31, SE = 0.82, p = .71; none vs. > 2 h B = 1.49, SE = 0.85, p = .08) , and older adults (none vs. < 2 h B = − 0.36, SE = 0.85, p = .67; none vs. > 2 h B = − 0.08, SE = 0.98, p = .94). MCS scores differed significantly regarding healthy eating for older (low vs. medium B = 4.04, SE = 1.86, p = .03; low vs. high B = 6.43, SE = 1.96, p < .01) but not for young (low vs. medium B = − 0.49, SE = 1.14, p = .67; low vs. high B = − 2.61, SE = 2.21, p = .24) or middle-aged adults (low vs. medium B = − 0.46, SE = 1.34, p = .73; low vs. high B = − 0.73, SE = 1.88, p = .64)

References

  1. Fagerström, C., & Borglin, G. (2013). Mobility, functional ability and health-related quality of life among people of 60 years or older. Aging Clinical and Experimental Research, 22(5–6), 387–394. https://doi.org/10.1007/bf03324941.

    Article  Google Scholar 

  2. Mulasso, A., Roppolo, M., & Rabaglietti, E. (2014). The role of individual characteristics and physical frailty on health related quality of life (HRQOL): A cross sectional study of Italian community-dwelling older adults. Archives of Gerontology and Geriatrics, 59(3), 542–548. https://doi.org/10.1016/j.archger.2014.08.012.

    Article  PubMed  Google Scholar 

  3. Saarni, S. I., Suvisaari, J., Sintonen, H., Pirkola, S., Koskinen, S., Aromaa, A., et al. (2007). Impact of psychiatric disorders on health-related quality of life: General population survey. British Journal of Psychiatry, 190(4), 326–332. https://doi.org/10.1192/bjp.bp.106.025106.

    Article  PubMed  Google Scholar 

  4. Hennessy, C. H., Moriarty, D. G., Zack, M. M., Scherr, P. A., & Brackbill, R. (1994). Measuring health-related quality of life for public health surveillance. Public Health Reports, 109(5), 665–672.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. WHO. (1995). The World Health Organization quality of life assessment (WHOQOL): Position paper from the World Health Organization. Social Science & Medicine, 41(10), 1403–1409. https://doi.org/10.1016/0277-9536(95)00112-k.

    Article  Google Scholar 

  6. US Department of Health and Human Services. (2010). Healthy people 2020. Washington, DC: Office of the Assistant Secretary for Health. Retrieved from http://www.healthypeople.gov/2020/about/DOHAbout.aspx.

  7. Parekh, A. K., Goodman, R. A., Gordon, C., Koh, H. K., & HHS Interagency Workgroup on Multiple Chronic Conditions (2011). Managing multiple chronic conditions: A strategic framework for improving health outcomes and quality of life. Public Health Reports 126(4), 460–471, https://doi.org/10.1177/003335491112600403.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Saarni, S. I., Härkänen, T., Sintonen, H., Suvisaari, J., Koskinen, S., Aromaa, A., et al. (2006). The impact of 29 chronic conditions on health-related quality of life: A general population survey in Finland using 15D and EQ-5D. Quality of Life Research, 15(8), 1403–1414. https://doi.org/10.1007/s11136-006-0020-1.

    Article  PubMed  Google Scholar 

  9. Lubetkin, E. I., Jia, H., Franks, P., & Gold, M. R. (2005). Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the US general population. Quality of Life Research, 14(10), 2187–2196. https://doi.org/10.1007/s11136-005-8028-5.

    Article  PubMed  Google Scholar 

  10. Sun, S., Chen, J., Johannesson, M., Kind, P., Xu, L., Zhang, Y., et al. (2011). Population health status in China: EQ-5D results, by age, sex and socio-economic status, from the National Health Services Survey 2008. Quality of Life Research, 20(3), 309–320. https://doi.org/10.1007/s11136-010-9762-x.

    Article  PubMed  Google Scholar 

  11. Gana, K., Bailly, N., Saada, Y., Joulain, M., & Alaphilippe, D. (2013). Does life satisfaction change in old age: Results from an 8-year longitudinal study. Journal of Gerontology B Psychological Science and Social Science, 68(4), 540–552. https://doi.org/10.1093/geronb/gbs093.

    Article  Google Scholar 

  12. Gunzelmann, T., Albani, C., Beutel, M., & Brahler, E. (2006). Subjective health of older people in view of the SF-36: Values from a large community-based sample. Zeitschrift Gerontologie Geriatrie, 39(2), 109–119. https://doi.org/10.1007/s00391-006-0352-z.

    CAS  Article  Google Scholar 

  13. Costa, P. T. Jr., McCrae, R. R., & Zonderman, A. B. (1987). Environmental and dispositional influences on well-being: Longitudinal follow-up of an American national sample. British Journal of Psychology, 78(3), 299–306. https://doi.org/10.1111/j.2044-8295.1987.tb02248.x.

    Article  PubMed  Google Scholar 

  14. Cherepanov, D., Palta, M., Fryback, D. G., & Robert, S. A. (2010). Gender differences in health-related quality-of-life are partly explained by sociodemographic and socioeconomic variation between adult men and women in the US: Evidence from four US nationally representative data sets. Quality of Life Research, 19(8), 1115–1124. https://doi.org/10.1007/s11136-010-9673-x.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Bukman, A. J., Teuscher, D., Feskens, E. J., van Baak, M. A., Meershoek, A., & Renes, R. J. (2014). Perceptions on healthy eating, physical activity and lifestyle advice: Opportunities for adapting lifestyle interventions to individuals with low socioeconomic status. BMC Public Health. https://doi.org/10.1186/1471-2458-14-1036.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Stringhini, S., Sabia, S., Shipley, M., Brunner, E., Nabi, H., Kivimaki, M., et al. (2010). Association of socioeconomic position with health behaviors and mortality. JAMA, 303(12), 1159–1166. https://doi.org/10.1001/jama.2010.297.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. Lallukka, T., Laaksonen, M., Rahkonen, O., Roos, E., & Lahelma, E. (2007). Multiple socio-economic circumstances and healthy food habits. European Journal of Clinical Nutrition, 61(6), 701–710. https://doi.org/10.1038/sj.ejcn.1602583.

    CAS  Article  PubMed  Google Scholar 

  18. Pinquart, M., & Sörensen, S. (2001). How effective are psychotherapeutic and other psychosocial interventions with older adults? A meta-analysis. Journal of Mental Health and Aging, 7(2), 207–243.

    Google Scholar 

  19. Enkvist, A., Ekstrom, H., & Elmstahl, S. (2012). Associations between functional ability and life satisfaction in the oldest old: Results from the longitudinal population study good aging in Skane. Clinical Interventions in Aging, 7, 313–320. https://doi.org/10.2147/CIA.S33610.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Fone, D., Dunstan, F., Lloyd, K., Williams, G., Watkins, J., & Palmer, S. (2007). Does social cohesion modify the association between area income deprivation and mental health? A multilevel analysis. International Journal of Epidemiology, 36(2), 338–345. https://doi.org/10.1093/ije/dym004.

    Article  PubMed  Google Scholar 

  21. Kawachi, I., & Berkman, L. F. (2001). Social ties and mental health. Journal of Urban Health, 78(3), 458–467. https://doi.org/10.1093/jurban/78.3.458.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. Kahana, E., Kahana, B., & Lee, J. E. (2014). Proactive approaches to successful aging: One clear path through the forest. Gerontology, 60(5), 466–474. https://doi.org/10.1159/000360222.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bize, R., Johnson, J. A., & Plotnikoff, R. C. (2007). Physical activity level and health-related quality of life in the general adult population: A systematic review. Preventive Medicine, 45(6), 401–415. https://doi.org/10.1016/j.ypmed.2007.07.017.

    Article  PubMed  Google Scholar 

  24. Fontaine, K. R., Barofsky, I., Andersen, R. E., Bartlett, S. J., Wiersema, L., Cheskin, L. J., et al. (1999). Impact of weight loss on health-related quality of life. Quality of Life Research, 8(3), 275–277. https://doi.org/10.1023/A:1008835602894.

    CAS  Article  PubMed  Google Scholar 

  25. Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychology Science, 14(2), 125–130. https://doi.org/10.1111/1467-9280.t01-1-01430.

    Article  Google Scholar 

  26. Penedo, F. J., & Dahn, J. R. (2005). Exercise and well-being: A review of mental and physical health benefits associated with physical activity. Current Opinion in Psychiatry, 18(2), 189–193.

    Article  Google Scholar 

  27. Drewnowski, A., & Evans, W. J. (2001). Nutrition, physical activity, and quality of life in older adults: Summary. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56(Supplement 2), 89–94. https://doi.org/10.1093/gerona/56.suppl_2.89.

    Article  Google Scholar 

  28. Smith, P. J., Blumenthal, J. A., Hoffman, B. M., Cooper, H., Strauman, T. A., Welsh-Bohmer, K., et al. (2010). Aerobic exercise and neurocognitive performance: A meta-analytic review of randomized controlled trials. Psychosomatic Medicine, 72(3), 239–252. https://doi.org/10.1097/PSY.0b013e3181d14633.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Josefsson, T., Lindwall, M., & Archer, T. (2014). Physical exercise intervention in depressive disorders: Meta-analysis and systematic review. Scandinavian Journal of Medicine Science in Sports, 24(2), 259–272. https://doi.org/10.1111/sms.12050.

    CAS  Article  PubMed  Google Scholar 

  30. Kennedy, E., Ohls, J., Carlson, S., & Fleming, K. (1995). The healthy eating index: Design and applications. Journal of the Academy of Nutrition and Dietetics, 95(10), 1103–1108. https://doi.org/10.1016/S0002-8223(95)00300-2.

    CAS  Article  Google Scholar 

  31. Bowling, A., & Grundy, E. (1997). Activities of daily living: Changes in functional ability in three samples of elderly and very elderly people. Age and Ageing, 26(2), 107–114. https://doi.org/10.1093/ageing/26.2.107.

    CAS  Article  PubMed  Google Scholar 

  32. Borg, C., Fagerstrom, C., Balducci, C., Burholt, V., Ferring, D., Weber, G., et al. (2008). Life satisfaction in 6 European countries: The relationship to health, self-esteem, and social and financial resources among people (aged 65–89) with reduced functional capacity. Geriatric Nursing, 29(1), 48–57. https://doi.org/10.1016/j.gerinurse.2007.05.002.

    Article  PubMed  Google Scholar 

  33. Jonker, A. A., Comijs, H. C., Knipscheer, K. C., & Deeg, D. J. (2009). The role of coping resources on change in well-being during persistent health decline. Journal of Aging Health, 21(8), 1063–1082. https://doi.org/10.1177/0898264309344682.

    Article  PubMed  Google Scholar 

  34. Weuve, J., Kang, J. H., Manson, J. E., Breteler, M. M., Ware, J. H., & Grodstein, F. (2004). Physical activity, including walking, and cognitive function in older women. JAMA, 292(12), 1454–1461. https://doi.org/10.1001/jama.292.12.1454.

    CAS  Article  PubMed  Google Scholar 

  35. Ford, D. E., & Kamerow, D. B. (1989). Epidemiologic study of sleep disturbances and psychiatric disorders. An opportunity for prevention? JAMA, 262(11), 1479–1484.

    CAS  Article  Google Scholar 

  36. Alhola, P., & Polo-Kantola, P. (2007). Sleep deprivation: Impact on cognitive performance. Neuropsychiatric Disease Treatment, 3(5), 553–567.

    PubMed  Google Scholar 

  37. Lo, J. C., Loh, K. K., Zheng, H., Sim, S. K., & Chee, M. W. (2014). Sleep duration and age-related changes in brain structure and cognitive performance. Sleep, 37(7), 1171–1178. https://doi.org/10.5665/sleep.3832.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Kim, S., DeRoo, L. A., & Sandler, D. P. (2011). Eating patterns and nutritional characteristics associated with sleep duration. Public Health Nutrition, 14(5), 889–895. https://doi.org/10.1017/S136898001000296X.

    Article  PubMed  Google Scholar 

  39. Jacobi, F., Mack, S., Gerschler, A., Scholl, L., Hofler, M., Siegert, J., et al. (2013). The design and methods of the mental health module in the German Health Interview and Examination Survey for Adults (DEGS1-MH). International Journal of Methods in Psychiatric Research, 22(2), 83–99. https://doi.org/10.1002/mpr.1387.

    Article  PubMed  Google Scholar 

  40. Scheidt-Nave, C., Kamtsiuris, P., Gosswald, A., Holling, H., Lange, M., Busch, M. A., et al. (2012). German health interview and examination survey for adults (DEGS)—design, objectives and implementation of the first data collection wave. BMC Public Health, 12, 730. https://doi.org/10.1186/1471-2458-12-730.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ware, J. E., Kosinski, M., Bjorner, J. B., Turner-Bowker, D. M., Gandek, B., & Maruish, M. E. (2008). User’s manual for the SF-36v2 health survey. Lincoln: Quality Metric Incorporated.

    Google Scholar 

  42. Bullinger, M. (1995). German translation and psychometric testing of the SF-36 Health Survey: Preliminary results from the IQOLA project. Social Science & Medicine, 41(10), 1359–1366. https://doi.org/10.1016/0277-9536(95)00115-N.

    CAS  Article  Google Scholar 

  43. Ware, J. E., & Gandek, B. (1998). Overview of the SF-36 health survey and the International Quality of Life Assessment (IQOLA) Project. Journal of Clinical Epidemiology, 51(11), 903–912. https://doi.org/10.1016/S0895-4356(98)00081-X.

    Article  PubMed  Google Scholar 

  44. Ellert, U., & Kurth, B. M. (2004). Methodological views on the SF-36 summary scores based on the adult German population. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 47(11), 1027–1032. https://doi.org/10.1007/s00103-004-0933-1.

    CAS  Article  PubMed  Google Scholar 

  45. Cox, B., Oyen, H. V., Cambois, E., Jagger, C., Roy, S. l., Robine, J.-M., et al. (2009). The reliability of the Minimum European Health Module. International Journal of Public Health, 54(2), 55–60. https://doi.org/10.1007/s00038-009-7104-y.

    Article  PubMed  Google Scholar 

  46. Netz, Y., Wu, M. J., Becker, B. J., & Tenenbaum, G. (2005). Physical activity and psychological well-being in advanced age: A meta-analysis of intervention studies. Psychology and Aging, 20(2), 272–284. https://doi.org/10.1037/0882-7974.20.2.272.

    Article  PubMed  Google Scholar 

  47. Forte, R., Boreham, C. A., Leite, J. C., De Vito, G., Brennan, L., Gibney, E. R., et al. (2013). Enhancing cognitive functioning in the elderly: Multicomponent vs resistance training. Clinical Interventions in Aging, 8, 19–27. https://doi.org/10.2147/CIA.S36514.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Lampert, T., Kroll, L., Muters, S., & Stolzenberg, H. (2013). Measurement of socioeconomic status in the German Health Interview and Examination Survey for Adults (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 56(5–6), 631–636. https://doi.org/10.1007/s00103-012-1663-4.

    CAS  Article  PubMed  Google Scholar 

  49. Mensink, G. B., Truthmann, J., Rabenberg, M., Heidemann, C., Haftenberger, M., Schienkiewitz, A., et al. (2013). Fruit and vegetable intake in Germany: Results of the German Health Interview and Examination Survey for Adults (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz, 56(5–6), 779–785. https://doi.org/10.1007/s00103-012-1651-8.

    CAS  Article  PubMed  Google Scholar 

  50. Kuhn, D. A. (2017). Entwicklung eines Index zur Bewertung der Ernährungsqualität in der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1) [The development of a healthy eating index to assess the quality of nutrition in the German Health Examination and Interview for Adults (DEGS1)] (master’s thesis). Berlin and Potsdam, Germany: Robert Koch Institute and German Institute of Human Nutrition.

  51. Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., DonCarlos, L., et al. (2015). National Sleep Foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health, 1(1), 40–43. https://doi.org/10.1016/j.sleh.2014.12.010.

    Article  PubMed  Google Scholar 

  52. Chen, X., Wang, R., Zee, P., Lutsey, P. L., Javaheri, S., Alcántara, C., et al. (2015). Racial/ethnic differences in sleep disturbances: The multi-ethnic study of atherosclerosis (MESA). Sleep, 38(6), 877–888. https://doi.org/10.5665/sleep.4732.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Wagner, M., Wolfsgruber, S., Gaertner, B., Kleineidam, L., Buttery, A. K., Jacobi, F., et al. (2017). Cognitive functioning in the general population: Factor structure and association with mental disorders-the neuropsychological test battery of the mental health module of the German Health Interview and Examination Survey for Adults (DEGS1-MH). International Journal of Methods Psychiatric in Research, 27(1), e1594. https://doi.org/10.1002/mpr.1594.

    Article  Google Scholar 

  54. StataCorp LP (2015). STATA 14 [Computer software]. College Station: TX: StataCorp LP.

    Google Scholar 

  55. Ladwig, K. H., Marten-Mittag, B., Formanek, B., & Dammann, G. (2000). Gender differences of symptom reporting and medical health care utilization in the German population. European Journal of Epidemiology, 16(6), 511–518. https://doi.org/10.1023/A:1007629920752.

    CAS  Article  PubMed  Google Scholar 

  56. Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., et al. (2013). Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46. https://doi.org/10.1111/j.1600-0587.2012.07348.x. doi.

    Article  Google Scholar 

  57. Kessler, E.-M., & Staudinger, U. M. (2010). Emotional resilience and beyond: A synthesis of findings from lifespan psychology and psychopathology. In P. S. Fry & C. L. M. Keyes (Eds.), New frontiers in resilient aging: Life-strengths and well-being in late life (pp. 258–282). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  58. Gidlow, C., Johnston, L. H., Crone, D., Ellis, N., & James, D. (2006). A systematic review of the relationship between socio-economic position and physical activity. Health Education Journal, 65(4), 338–367. https://doi.org/10.1177/0017896906069378.

    Article  Google Scholar 

  59. Oxman, T. E., Berkman, L. F., Kasl, S., Freeman, D. H. Jr., & Barrett, J. (1992). Social support and depressive symptoms in the elderly. American Journal of Epidemiology, 135(4), 356–368. https://doi.org/10.1093/oxfordjournals.aje.a116297.

    CAS  Article  PubMed  Google Scholar 

  60. Bassuk, S. S., Glass, T. A., & Berkman, L. F. (1999). Social disengagement and incident cognitive decline in community-dwelling elderly persons. Annals of Internal Medicine, 131(3), 165–173. https://doi.org/10.7326/0003-4819-131-3-199908030-00002.

    CAS  Article  PubMed  Google Scholar 

  61. Wolinsky, F. D., Unverzagt, F. W., Smith, D. M., Jones, R., Wright, E., & Tennstedt, S. L. (2006). The effects of the ACTIVE cognitive training trial on clinically relevant declines in health-related quality of life. Journal of Gerontology B Psychological Science and Social Science, 61(5), 281–287. https://doi.org/10.1093/geronb/61.5.S281.

    Article  Google Scholar 

  62. Singh, B., Parsaik, A. K., Mielke, M. M., Erwin, P. J., Knopman, D. S., Petersen, R. C., et al. (2014). Association of mediterranean diet with mild cognitive impairment and Alzheimer’s disease: A systematic review and meta-analysis. Journal of Alzheimer’s disease: JAD, 39(2), 271–282. https://doi.org/10.3233/JAD-130830.

    Article  PubMed  Google Scholar 

  63. Theodora, P., Psaltopoulou, T., Sergentanis, T. N., Panagiotakos, D. B., Sergentanis, I. N., Kosti, R., & Scarmeas, N. (2013). Mediterranean diet, stroke, cognitive impairment, and depression: A meta-analysis. Annals of Neurology, 74(4), 580–591. https://doi.org/10.1002/ana.23944.

    Article  Google Scholar 

  64. Bamidis, P. D., Vivas, A. B., Styliadis, C., Frantzidis, C., Klados, M., Schlee, W., et al. (2014). A review of physical and cognitive interventions in aging. Neuroscience Biobehavioral Reviews, 44, 206–220. https://doi.org/10.1016/j.neubiorev.2014.03.019.

    CAS  Article  PubMed  Google Scholar 

  65. Payette, H., & Shatenstein, B. (2005). Determinants of healthy eating in community-dwelling elderly people. Canadian Journal of Public Health, 96, 27–31.

    Google Scholar 

Download references

Acknowledgements

We are particularly grateful to all study participants and wish to acknowledge the assistance given by all collaborators in providing vigorous support and premises in the 180 study locations. Our grateful thanks are also extended to our colleagues from the Robert Koch Institute as well as from the Technische Universität Dresden for their excellent collaboration, high engagement, and valuable contribution to this project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Caroline Cohrdes.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The present research was approved by the Medical Ethics Review Committee of the Charité Berlin and by the Ethics Board of the Technische Universität Dresden, Germany. Informed consent was obtained from all individual participants included in this research. The present research (DEGS1) is primary funded by the German Ministry of Health (BMG) and additionally by the German Association of Psychotherapy and Psychiatry (DGPPN) for implementing the module on mental health (DEGS1-MH).

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 31 KB)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Cohrdes, C., Mensink, G.B.M. & Hölling, H. How you live is how you feel? Positive associations between different lifestyle factors, cognitive functioning, and health-related quality of life across adulthood. Qual Life Res 27, 3281–3292 (2018). https://doi.org/10.1007/s11136-018-1971-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-018-1971-8

Keywords

  • Health-related quality of life
  • Physical activity
  • Healthy eating
  • Sleep duration
  • Executive functioning
  • Age differences