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Lagergen M, Kurube N and Saito Y

means that you get overall agreement with the chosen target distribution, but you still
assume that all other relations between variables remain the same as in the original
dataset. Of course it is easy to use any target distribution in both cases. The target
distribution is just one model assumption that can be varied.
The strength of the individual-oriented approach applied in this study is the
different perspective it provides on aging, risk of death, and the progress of functional
dependency and need for LTC. This perspective is more relevant from an individual
point of view.

5 Conclusions

An important result of the study is that the initial state makes a great difference to the
future. This initial state is in many ways the result of how life has been lived up to the
age of 78. If this information is available at a younger age, the chances of influencing
coming developments are greater, and the incentive to change lifestyle and habits is
more powerful. It is well known that the health and dependency of the older persons
is a major determinant of future LTC costs. Health promotion and disease prevention
are major public tools for achieving a positive result. However, most of that must be
achieved by the middle-aged and by the old persons themselves.
Another result of these calculations is that an old person gets a realistic view of what
to expect. Many old people try to deny what is waiting for them and refuse to act—
by changing a living situation, for example, or seeking assistance. Health promotion
sometimes gives the impression that simply living a healthy life, running, and eating
a healthy diet will grant near immortality with no functional dependency until death.
Unfortunately, this is far from reality, and realizing this could make it easier to accept
the unacceptable: that we all age and die, and that there is no escape.
This model is a first attempt to come to grips with these issues from an individual
perspective. The model can be further developed by introducing more levels of
disability and LTC provision and using more complete datasets. However, introducing
more variables would appear to require the use of microsimulation. This could be well
worth the effort. The basic approach would be the same.
Authors’ Contribution

Mårten Lagergren developed the simulation model and performed the calculations.
Also, as national coordinator of the SNAC study, he supervised the data collection in
that study, which provided the Swedish data. Yasuhiko Saito initiated and managed
the NUJLSOA study, which provided the Japanese data for the study. He also took a
very active part in discussing and presenting the modelling results. Noriko Kurube has
participated together with Lagergren in a long series of different Japanese-Swedish
LTC comparisons, and in this study—besides taking part in discussing and presenting
the results—she provided expertise in Japanese old age and care.
Conflict of Interest

The authors declare that there is no conflict of interest.
Funding and Acknowledgements

The Swedish Ministry of Health and Social Affairs funded the study’s analysis through
the Swedish National Study on Aging and Care (Regeringsbeslut (Government
Decision 1999-11-11 and onwards)). Japanese funding for the analysis was by JSPS
KAKENHI Grant Number 26285137. The wave 3 of NUJLSOA was funded by
Nihon University and the wave 4 of NUJLSOA was funded by a grant obtained by the
Nihon University Population Research Institute from the Academic Frontier Project
for Private Universities and matching fund subsidy from MEXT (Japanese Ministry
of Education, Culture, Sports, Science and Technology) 2006–2010. The authors are
grateful for the support from the Swedish and Japanese governments.

International Journal of Population Studies 2017, Volume 3, Issue 1 89