This chapter discussed intrinsic capacity and functional ability in relation to the
new concept described in the World Report on Aging and Health by using trajectories of five health indexes; however, other health indexes warrant consideration in
future studies. Vascular condition (Taniguchi et al., 2018b), which is associated with
physical performance, nutritional biomarkers, and certain diseases are important
health indexes in later life. Moreover, body mass index may be useful for evaluating
a person’s health from early childhood to old age. Identifying key indexes during the
course of life is clearly an important research concern. Furthermore, the crucial topic
of how life stage and level of function, as assessed by a key index, are related to
intrinsic capacity and functional ability in later life should be studied in greater
detail.
8 Conclusion
Based on the empirical data sets, this chapter discussed trajectories of aging in five
health indexes among community-dwelling older Japanese. Because older adults
with higher function at age 65 maintain high function until late in life, healthy aging
interventions using a life course approach should target adults younger than
65 years. A new informatics for healthy ageing is needed in order to develop a
framework of policy that improves trajectory of ageing patterns at optimal time
points between young adulthood and middle age. Public health policy, and health
promotion policy in particular, should pay attention on data sets and discussions
provided by this chapter. A new informatics of healthy aging, as discussed earlier,
should be effectively utilized in addressing translational health systems focusing on
healthy aging.
References
Bohannon, R. W., & Williams Andrews, A. (2011). Normal walking speed: A descriptive metaanalysis. Physiotherapy, 97, 182–189. https://doi.org/10.1016/j.physio.2010.12.004
Cooper, R., et al. (2010). Objectively measured physical capability levels and mortality: Systematic
review and meta-analysis. BMJ, 341, c4467. https://doi.org/10.1136/bmj.c4467
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). "mini-mental state". A practical method
for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12,
189–198.
Gatta, A., Verardo, A., & Bolognesi, M. (2012). Hypoalbuminemia. Internal and Emergency
Medicine, 7, 193–199. https://doi.org/10.1007/s11739-012-0802-0
Higashiguchi, M., et al. (2008). Malnutrition and the risk of long-term care insurance certification or
mortality. A cohort study of the Tsurugaya project. [Nihon koshu eisei zasshi] Japanese Journal
of Public Health, 55, 433–439.
Hines, K. E., Middendorf, T. R., & Aldrich, R. W. (2014). Determination of parameter
identifiability in nonlinear biophysical models: A Bayesian approach. The Journal of General
Physiology, 143, 401–416. https://doi.org/10.1085/jgp.201311116
78
Y. Taniguchi and H. Matsushita
new concept described in the World Report on Aging and Health by using trajectories of five health indexes; however, other health indexes warrant consideration in
future studies. Vascular condition (Taniguchi et al., 2018b), which is associated with
physical performance, nutritional biomarkers, and certain diseases are important
health indexes in later life. Moreover, body mass index may be useful for evaluating
a person’s health from early childhood to old age. Identifying key indexes during the
course of life is clearly an important research concern. Furthermore, the crucial topic
of how life stage and level of function, as assessed by a key index, are related to
intrinsic capacity and functional ability in later life should be studied in greater
detail.
8 Conclusion
Based on the empirical data sets, this chapter discussed trajectories of aging in five
health indexes among community-dwelling older Japanese. Because older adults
with higher function at age 65 maintain high function until late in life, healthy aging
interventions using a life course approach should target adults younger than
65 years. A new informatics for healthy ageing is needed in order to develop a
framework of policy that improves trajectory of ageing patterns at optimal time
points between young adulthood and middle age. Public health policy, and health
promotion policy in particular, should pay attention on data sets and discussions
provided by this chapter. A new informatics of healthy aging, as discussed earlier,
should be effectively utilized in addressing translational health systems focusing on
healthy aging.
References
Bohannon, R. W., & Williams Andrews, A. (2011). Normal walking speed: A descriptive metaanalysis. Physiotherapy, 97, 182–189. https://doi.org/10.1016/j.physio.2010.12.004
Cooper, R., et al. (2010). Objectively measured physical capability levels and mortality: Systematic
review and meta-analysis. BMJ, 341, c4467. https://doi.org/10.1136/bmj.c4467
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). "mini-mental state". A practical method
for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12,
189–198.
Gatta, A., Verardo, A., & Bolognesi, M. (2012). Hypoalbuminemia. Internal and Emergency
Medicine, 7, 193–199. https://doi.org/10.1007/s11739-012-0802-0
Higashiguchi, M., et al. (2008). Malnutrition and the risk of long-term care insurance certification or
mortality. A cohort study of the Tsurugaya project. [Nihon koshu eisei zasshi] Japanese Journal
of Public Health, 55, 433–439.
Hines, K. E., Middendorf, T. R., & Aldrich, R. W. (2014). Determination of parameter
identifiability in nonlinear biophysical models: A Bayesian approach. The Journal of General
Physiology, 143, 401–416. https://doi.org/10.1085/jgp.201311116
78
Y. Taniguchi and H. Matsushita