日本建築学会環境系論文集 第81巻 第729号，
901-908，2016年11月
J. Environ. Eng., AIJ, Vol. 81 No. 729, 901-908, Nov., 2016
DOI http://doi.org/10.3130/aije.81.901【カテゴリーⅠ】

住宅内温熱環境と居住者の介護予防に関するイベントヒストリー分析
ఫᏯෆ －冬季の住宅内温熱環境が要介護状態に及ぼす影響の実態調査－⇕⎔ቃ࡜ᒃఫ⪅ࡢ௓ㆤண㜵࡟㛵ࡍࡿ࢖࣋ࣥࢺࣄࢫࢺ࣮ࣜศᯒEVENT 㸫෤ᏘࡢఫᏯෆHISTORY ANALYSISOF INDOOR THERMAL ENVIRONMENT⇕⎔ቃࡀせ௓ㆤ≧ែ࡟ཬࡰࡍᙳ㡪ࡢᐇែㄪᰝ㸫AND CARE PREVENTION OF RESIDENTS
EVENT HISTORY ANALYSIS OF INDOOR THERMAL ENVIRONMENT
A field survey on the effect of winter indoor thermal environment on care requirements
AND CARE PREVENTION OF RESIDENTS
A field survey on＊the effect of winter＊＊indoor thermal environment
on care requirements
＊＊＊
＊＊＊＊

林

侑 江 ，伊香賀 俊治

ᯘ

，星

旦二

，安藤 真太朗**㸪ᫍ IKAGA,
Yukie
HAYASHI,ಇ἞
Toshiharu
HOSHI᪦ ஧***Tanji㸪Ᏻ⸨┿ኴᮁ****
ౡ
Ụ*㸪ఀ㤶㈡andShintaro
ANDO
Yukie HAYASHI, Toshiharu
IKAGA, Tanji
HOSHI and Shintaro ANDO
The aim of this paper is to clarify the relationship between the indoor thermal environment and care prevention. A field study comprisingactual measurements, questionnaire surveys, and data collection from face sheets was conducted in 2014. Participants were classified into twogroups based on frequency of feeling cold in their rooms. Age at certification of needing long-term care was compared between the groups byusing survival analysis. The result was significant when the classification condition was frequency of feeling cold in their dressing rooms. Theage at which half of the group acquired their certification was 76 years in the high-frequency group and 80 years in the low-frequency group.

Keywords : Care prevention, Healthy life expectancy, Indoor thermal environment, Elderly people, Field survey, Event history analysis    ௓ㆤண㜵㸪೺ᗣᑑ࿨㸪ఫᏯෆ ⇕⎔ቃ㸪㧗㱋⪅㸪 ෭ឤ⏦࿌㸪࢝ࣉ࣭࣐ࣛࣥ࢖࣮ࣖἲ
㸯. ᗎㄽࡽ 10)࡟ࡼࡗ࡚࡞ࡉࢀ࡚࠸ࡿࠋᕝஂಖࡽ 11)ࡣᡞᘓఫᏯࡢᒃఫ⪅ࢆᑐ㇟1)ࠋᡃ

࡜ࡋࡓ኱つᶍ࡞ WEB ㄪᰝ࡟ࡼࡗ࡚ఫᏯࡢ⎔ቃᛶ⬟ὀ 3)ࡀ㧗࠸࡯࡝⥲ࡀᅜ࡟࠾࠸࡚௓ㆤண㜵࡜ࡣࠕせ௓ㆤ≧ែࡢⓎ⏕ࢆ࡛ࡁࡿ㝈ࡾ㜵ࡄ㸦㐜ࡌ࡚ྛ✀⑌⑓ࡢ᭷⑓๭ྜࡀపࡃࠊ⑌⑓ࢆ᭷ࡉ࡞࠸೺ᗣ࡞⪅ࡢ๭ྜࡀࡽࡏࡿ㸧ࡇ࡜ࠊࡑࡋ࡚せ௓ㆤ≧ែ࡟࠶ࡗ࡚ࡶࡑࡢᝏ໬ࢆ࡛ࡁࡿ㝈ࡾከ࠸ࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋࡉࡽ࡟ࠊせ௓ㆤㄆᐃࡢཎᅉ࡜ࡋ࡚᭱ࡶከ

㜵ࡄࡇ࡜ࠊࡉࡽ࡟ࡣ㍍ῶࢆ┠ᣦࡍࡇ࡜ࠖ࡜ᐃ⩏ࡉࢀࠊ೺ᗣᑑ࿨ࢆ࡛

࠸ᚠ⎔ჾ⑌ᝈ 12)࡟㛵㐃ࡋ࡚ࠊ⾑ᅽ࡟╔┠ࡋࡓ◊✲࡜ࡋ࡚ࡣ Saeki ࡽࡁࡿ㝈ࡾࡢࡤࡍ࡜࡜ࡶ࡟┿࡟႐ࡪ࡟್ࡍࡿ㛗ᑑ♫఍ࢆ๰⏕ࡍࡿࡇ࡜13, 14)ࠊᾏሷࡽ 15, 16)ࡀ኱つᶍ࡞ᐇែㄪᰝ࡟ᇶ࡙ࡁ෤ᏘࡢఫᏯෆ

ࢆ┠ᣦࡍࡶࡢ࡛࠶ࡿ 2)ࠋࡲࡓࠊ೺ᗣ᪥ᮏ 21㸦➨஧ḟ㸧࡛ࡣ೺ᗣᑑ࿨

ቃ࡜⾑ᅽࡢ㛵ಀ࡟ࡘ࠸࡚ᐃ㔞ⓗ࡞ホ౯ࢆ⾜ࡗ࡚࠸ࡿࠋࡲࡓࠊせ௓ㆤὀ 1)ㄆᐃࡢཎᅉࡢ⣙ 2 ๭ࢆ༨ࡵࡿ㛵⠇⑌ᝈࡸ㌿ಽ࣭㦵ᢡ 12)࡟㛵㐃ࡋ࡚ࡣ⌧ᅾࠊ㧗㱋໬࡟క࠸せ௓ㆤㄆᐃ⪅ᩘࡀᛴ㏿࡟ቑຍࡋ࡚࠸ࡿ

ࡢᘏఙࢆᅜẸࡢ೺ᗣቑ㐍࡟ྥࡅࡓᇶᮏⓗ᪉㔪࡟఩⨨࡙ࡅ࡚࠾ࡾ 3)ࠊ

⇕⎔2013 ᖺ᫬Ⅼ࡛ࡢ೺ᗣᑑ࿨ࡣ⏨ᛶࡀ 71.2 ᖺࠊዪᛶࡀ 74.2 ᖺ࡜ࠊࡑࢀ

ᰗ⃝ࡽ 17)ࡀఫᏯᛶ⬟࣭ఫᏯෆࡒࢀ 2001 ᖺ࡜ẚ㍑ࡋ࡚ఙࡧ࡚࠸ࡿ 4)ࠋࡋ࠿ࡋࠊ2001 ᖺ࠿ࡽ 2013࡚࠸ࡿࠋࡑࡢ௚ࠊ㌟యᶵ⬟࡟㛵ࡍࡿ◊✲࡜ࡋ࡚ࡣ Lindemann18)ࡽࡀ

ᖺࡲ࡛ࡢ೺ᗣᑑ࿨ࡢᘏࡧ㸦⏨ᛶ 1.8 ᖺࠊዪᛶ 1.6 ᖺ㸧ࡣࠊྠᮇ㛫࡟ዪᛶ㧗㱋⪅ࢆᑐ㇟࡜ࡋࡓᐇ㦂࡛ 15Υ⛬ᗘࡢᐮ෭࡞ᐊෆ

⇕⎔ቃ࡜㌟యάື㔞ࡢ㛵ಀࢆ᳨ドࡋ⇕⎔ቃ࡟࠾ࡅࡿᖹᆒᑑ࿨ࡢᘏࡧ㸦⏨ᛶ 2.1 ᖺࠊዪᛶ 1.7 ᖺ㸧࡜ẚ㍑ࡋ࡚ᑠࡉ᭚㟢ࡉࢀࡓ࠶࡜ࡢ➽ຊࡣ 25Υ⛬ᗘࡢࢣ࣮ࢫ࡜ẚ㍑ࡋ࡚ప࠸ࡇ࡜ࢆ

ࡃࠊ೺ᗣᑑ࿨࡜ᖹᆒᑑ࿨ࡢᕪࡣ௒ᚋࡼࡾᣑ኱ࡍࡿࡇ࡜ࡀᠱᛕࡉࢀ࡚

᫂ࡽ࠿࡟ࡋࡓࠋࡲࡓࠊ᳃ࡽ 19)ࡣ㧗㱋⪅ࡢṌ⾜㏿ᗘࡸ㌟యάື㔞ࡢ⥔࠸ࡿࠋࡲࡓࠊ⛅ᒣࡽ 5)ࡣ↓సⅭ࡟ᢳฟࡋࡓ᪥ᮏ඲ᅜࡢ 60 ṓ௨ୖࡢఫᣢ࣭ྥୖ࡟ᑐࡋ࡚❆ࡢ᩿⇕ᨵಟࡀຠᯝⓗ࡛࠶ࡿྍ⬟ᛶࢆ♧ࡋ࡚࠸ࡿࠋ

Ẹ 5,715 ேࢆᑐ㇟࡜ࡋࡓ㏣㊧ㄪᰝ࡟࠾࠸࡚ࠊ70 ṓࡲ࡛ࡣ⣙ 80%ࡢ௨ୖࡼࡾࠊ෤ᏘࡢఫᏯෆ

⇕⎔ቃࡢᨵၿࡀ㧗㱋⪅ࡢ೺ᗣ⥔ᣢቑ㐍㧗㱋⪅ࡀ⮬❧ࡋࡓ⏕άࢆႠࡴࡇ࡜ࡀฟ᮶ࡿ୍᪉࡛ࠊ70 ṓ௨㝆ࡣ᪥ᖖࢆᐇ⌧ࡋࠊࡦ࠸࡚ࡣ೺ᗣᑑ࿨ࢆᘏఙ࡛ࡁࡿࡇ࡜ࡀ♧၀ࡉࢀ࡚࠸ࡿࠋ

⏕ά⮬❧ᗘὀ 2)࡟ಶேᕪࡀ⏕ࡌࡿࡇ࡜ࢆぢฟࡋࡓࠋࡇࡢศᒱⅬࢆᑡࡋࡋ࠿ࡋࠊఫᏯෆ

࡛ࡶඛ㏦ࡾࡋࠊ㧗㱋⪅ࡀྍ⬟࡞㝈ࡾせ௓ㆤ≧ែ࡟࡞ࡽࡎ࡟⮬❧ࡋࡓࡣഹᑡ࡛࠶ࡾࠊ⛉Ꮫⓗ࢚ࣅࢹࣥࢫࡀ୙㊊ࡋ࡚࠸ࡿࡢࡀ⌧≧࡛࠶ࡿࠋ᪥ᖖ⏕άࢆႠࡴࡇ࡜ࡀ࡛ࡁࡿࡼ࠺ࠊ೺ᗣᑑ࿨ࢆᘏఙࡍࡿࡇ࡜ࡀႚ⥭ࡑࡇ࡛ᮏ◊✲࡛ࡣࠊࢹ࢖ࢧ࣮ࣅࢫ᪋タ฼⏝⪅ࢆᑐ㇟࡜ࡋࡓᐇែㄪᰝ

ࡢㄢ㢟࡛࠶ࡿ࡜ゝ࠼ࡿࠋࢆᐇ᪋ࡋࠊఫᏯෆ

ࡇࡢࡼ࠺࡞⫼ᬒࢆ㚷ࡳ࡚ࠊఫᏯᛶ⬟࣭ఫᏯෆ⇕⎔ቃ࡜೺ᗣࡢ㛵ಀ࡟ࡘ࠸࡚ᵝࠎ࡞◊✲ࡀࠊྜྷ㔝ࡽ 6, 7)ࠊ㛗㇂ᕝ 8)ࠊ⩚ᒣࡽ 9)ࠊఀ㤶㈡⇕⎔ቃ࡜௓ㆤண㜵ࡢ㛵㐃ࢆᐃ㔞ⓗ࡟᫂♧ࡋࡓ◊✲⇕⎔ቃ࡜ᒃఫ⪅ࡢ௓ㆤண㜵ࡢ㛵㐃ࢆ࢖࣋ࣥࢺࣄ

ࢫࢺ࣮ࣜศᯒ࡟ࡼࡗ᳨࡚ドࡋࡓࠋᑦࠊ⤫ィゎᯒ࡟ࡣ IBM SPSS
Statics ver.22 ࢆ౑⏝ࡋࡓࠋ

本論文は著者らが既に報告した文献 28 を加筆・修正したものである。

　　　＊
ᮏㄽᩥࡣⴭ⪅ࡽࡀ᪤࡟ሗ࿌ࡋࡓᩥ⊩　慶應義塾大学大学院理工学研究科
大学院生
Grad. Stud., Graduate School of Science and Technology, Keio Univ.
28 ࢆຍ➹࣭ಟṇࡋࡓࡶࡢ࡛࠶ࡿࠋ
　　＊＊　慶應義塾大学理工学部 教授・博士（工学）Prof., Facultyof Science
andSchool
Technology,
KeioandUniv.,
Dr.Eng. Keio Univ.
Graduate
Student,
Graduateof Science
Technology,៞᠕⩏ሿ኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉
኱Ꮫ㝔⏕
*
＊＊＊
　首都大学東京都市環境学部 名誉教授・医博Emeritus Prof., Faculty of Urban Environmental Sciences, Tokyo Metropolitan Univ., M.D.
Prof.,
Facultyof
ScienceandTechnology,
KeioUniv.,
Dr.
Eng.
៞᠕⩏ሿ኱Ꮫ⌮ᕤᏛ㒊ᩍᤵ࣭༤ኈ㸦ᕤᏛ㸧＊＊＊＊** 　北九州市立大学国際環境工学部 講師・博士（工学）Lect., Faculty of Environmental Engineering, The Univ. of Kitakyushu, Dr.Eng.
Emeritus Prof., Faculty of Urban Environmental Sciences, Tokyo Metropolitan Univ., M.D.
*** 㤳㒔኱Ꮫᮾி㒔ᕷ⎔ቃᏛ㒊 ྡ㄃ᩍᤵ࣭་༤
Lecturer, Faculty of Environmental Engineering, The Univ. of Kitakyushu, Dr. Eng.
**** ໭஑ᕞᕷ❧኱Ꮫᅜ㝿⎔ቃᕤᏛ㒊 ㅮᖌ ࣭༤ኈ㸦ᕤᏛ㸧

─ 901 ─㉁ၥ⣬ㄪᰝᑐ㇟ n=86 (79)㸰. ㄪᰝ᪉ἲ• ㄪᰝ⚊↓ᅇ⟅ n=3 (3)ㄪᰝᴫせᮏ◊✲࡛ࡣࠊ෤ᏘࡢఫᏯෆ

⇕⎔ቃ࡜ᒃఫ⪅ࡢ೺ᗣᑑ࿨ࡢ㛵ಀࢆ

FSㄪᰝᑐ㇟ࢧࣥࣉࣝ n=83 (79)
• せ௓ㆤࢹ࣮ࢱ࡞ࡋ n=2 (2)• ඛኳᛶ⑌ᝈ࠶ࡾ n=1 (1)᫂ࡽ࠿࡟ࡍࡿࡓࡵࠊ኱㜰ᗓ༓㔛ࢽ࣮ࣗࢱ࢘ࣥ࡟ᡤᅾࡍࡿࢹ࢖ࢧ࣮ࣅࢫ᪋タࢆ฼⏝ࡍࡿ⏨ዪࢆᑐ㇟࡟㉁ၥ⣬ㄪᰝཬࡧ⮬Ꮿࡢᐇㄪᰝࢆᐇ᪋ࡋࡓࠋࡲࡓࠊྠᑐ㇟⪅࡟㛵ࡋ࡚ࢹ࢖ࢧ࣮ࣅࢫ᪋タࡀಖ᭷ࡍࡿࣇ࢙㉁ၥ⣬ㄪᰝ᭷ຠࢧࣥࣉࣝ n=80 (78)• ᐇ ㄪᰝ୙ཧຍ n=40 (39)• ᐷᐊᐊ Ḟᦆ n=1 (1)• ⬺⾰ᡤᐊ Ḟᦆ n=2 (2)࢖ࢫࢩ࣮ࢺ ὀ 3)࡜௓ㆤಖ㝤⿕ಖ㝤⪅ド࠿ࡽ᪤ Ṕࡸせ௓ㆤ≧ែࡢࢹ࣮ࢱࢆ཰㞟ࡋࡓ㸦௨ୗ FS ㄪᰝ㸧ࠋᐇၥ⣬ㄪᰝᑐ㇟⪅ࡢ࠺ࡕᐇ
࡚ࠊ

‵ᗘཬࡧ

ㄪᰝࡢᐇ᪋࡟࠶ࡓࡗ࡚ࡣࠊ㉁ᐇ ㄪᰝ᭷ຠࢧࣥࣉࣝ n=37 (36)

ᅗ 1 ᭷ຠࢧࣥࣉࣝ㑅ᢥࡢࣇ࣮ࣟࢳ࣮ࣕࢺ

ᗘࢹ࣮ࢱ࣮ࣟ࢞ࡢタ⨨᪉ἲࢆಶู࡟ㄝ᫂ࡋࡓࠋ㉁ၥ⣬ㄪᰝࡣࠊFS ㄪᰝ࡜㉁ၥ⣬ㄪᰝ཮᪉ࡢࢹ࣮ࢱࡀᥞࡗࡓ⪅ࡢෆࠊ⾲ 1 ㉁ၥ⣬ㄪᰝ࣭ࢹ࣮ࢱ཰㞟ᴫせඛኳᛶ⑌ᝈࢆ᭷ࡍࡿࢧࣥࣉࣝࢆ㝖እࡋࡓ 80 ྡ㸦79 ୡᖏ㸧ࢆ᭷ຠࢧࣥࣉࣝ࡜ࡋࡓࠋࡲࡓࠊᐇͤ ࢝ࢵࢥෆࡣୡᖏᩘ

ㄪᰝ࡬ࡢཧຍࡢྠពࡀᚓࡽࢀࡓ⪅࡟ᑐࡋㄪᰝࡣ඲㒊ᒇࡢ

ᑐ㇟኱㜰ᗓ༓㔛ࢽ࣮ࣗࢱ࢘ࣥ࡟ᡤᅾࡍࡿ
ࢹ࢖ࢧ࣮ࣅࢫ᪋タࢆ฼⏝ࡍࡿ⏨ዪㄪᰝᮇ㛫

2014 ᖺ 7 ᭶ 25 ᪥㹼7 ᭶ 29 ᪥ཬࡧ2014 ᖺ 8 ᭶ 28 ᪥㹼8 ᭶ 30 ᪥ᐃࢹ࣮ࢱࡀᥞࡗࡓ 37

ྡ㸦36 ୡᖏ㸧ࢆ᭷ຠࢧࣥࣉࣝ࡜ࡋࡓ㸦ᅗ 1㸧ࠋㄪᰝ㡯┠ㄪᰝ᪉ἲ(1) ㉁ၥ⣬ㄪᰝᴫせ㸦⾲ 1㸧ᮏ◊✲࡛ࡣࢹ࢖ࢣ࢔ࢧ࣮ࣅࢫ᪋タ฼⏝⪅࡟ᑐࡋ࡚ᑐ㠃ᘧࡢ㉁ၥ⣬ㄪᰝࢆᐇ᪋ࡋࡓࠋㄪᰝ⚊ࡣᑐ㇟⪅ࡢᒓᛶ࣭⹫ᙅᗘࡸᑐ㇟ఫᏯࡢᛶ⬟࣭⎔ቃࢆᢕᥱࡍࡿࡇ࡜ࢆ୺ࡓࡿ┠ⓗ࡜ࡋࠊ඲ 26 ၥ࡛ᵓᡂࡋࡓࠋಶே
ᒓᛶ࡜ࡋ࡚ࡣᖺ㱋ࠊᛶูࠊ㌟㛗ࠊయ㔜➼ࡢᇶᮏⓗ࡞ᒓᛶࡸാࡁጞࡵㄪᰝෆᐜ(㉁ၥ⣬ㄪᰝ)ㄪᰝෆᐜ(FS ㄪᰝ)࢔ࣥࢣ࣮ࢺࢹ࢖ࢧ࣮ࣅࢫ᪋タಖ᭷ࡢࢹ࣮ࢱࢆ཰㞟ಶேᒓᛶᖺ㱋, ᛶู, ㌟㛗, య㔜, ാࡁጞࡵࡓᖺ㱋,୺ほⓗ⤒῭‶㊊ᗘࠊྠᒃ⪅ᩘ, ᅾᏯ᫬㛫 ➼ఫᏯ⠏ᖺᩘ, ᒃఫᖺᩘ, ❆࢞ࣛࢫࡢᯛᩘ, ❆ࢧࢵࢩࡢ✀㢮, CASBEE ೺ᗣࢳ࢙ࢵࢡࣜࢫࢺ

せ௓ㆤ≧ែ
᪤ Ṕ

ࡓᖺ㱋ὀ 4)ࠊ୺ほⓗ⤒῭‶㊊ᗘࢆ♫఍⤒῭ⓗỈ‽࡜ࡋ࡚ၥ࠺ࡓࠋᑐ㇟
⪅ࡢఫᏯ࡟㛵ࡋ࡚ࡣࠕᇶᮏ᝟ሗࠖ࡜ࡋ࡚⠏ᖺᩘཬࡧᒃఫᖺᩘࠊ
ࠕᛶ⬟ࠖ࡜ࡋ࡚❆࢞ࣛࢫࡢᯛᩘࠊ❆ࢧࢵࢩࡢ✀㢮ࢆၥ࠺ࡓࠋ᭦࡟ࠊCASBEE࠺ࡓࠋྠࢳ࢙ࢵࢡࣜࢫࢺ࡟࠾ࡅࡿ

ᐃ᪉ἲ
ᗘ
ᐃᶵჾ

(2) FS ㄪᰝᴫせ㸦⾲ 1㸧ᮏ◊✲࡛ࡣࢹ࢖ࢧ࣮ࣅࢫ᪋タࡀಖ᭷ࡍࡿ฼⏝⪅᝟ሗ࠿ࡽᑐ㇟⪅ࡢࢹ࢖ࢧ࣮ࣅࢫ᪋タ฼⏝㛤ጞࡲ࡛ࡢ᪤ Ṕㄪᰝᴫせ㉁ၥ⣬ㄪᰝᑐ㇟⪅ࡢ୍㒊
2014 ᖺ 12 ᭶ 8 ᪥㹼26 ᪥(࠺ࡕ⣙ 2 㐌㛫)‵ᗘ⇕⎔ቃࡣࠊྛ㒊ᒇ࡛ᐮ࠸࡜ឤࡌ

ࡿ㢖ᗘࡀప࠸࡯࡝㧗ᚓⅬࠊ㢖ᗘࡀ㧗࠸࡯࡝పᚓⅬ࡜ࡉࢀࡿࠋ

せ௓ㆤᗘ, ᭷ຠᮇ㛫⾲ 2 ᐇ
ᑐ㇟ㄪᰝᮇ㛫೺ᗣࢳ࢙ࢵࢡࣜࢫࢺ 20),ὀ 5)ࢆཧ⪃࡟ࠊྛ㒊ᒇ࡛⏕ࡌࡿ೺ᗣ࡟㛵ࡍࡿၥ㢟ࡢⓎ⏕㢖ᗘࢆࠕࡼࡃ࠶ࡿࠖ࠿ࡽࠕ඲ࡃ࡞࠸ࠖࡲ࡛ࡢ 4 ௳ἲ࡛ၥ⣬㠃፹య࡟ࡼࡿᑐ㠃ᘧཪࡣ㓄ᕸᘧ㉁ၥ⣬ㄪᰝ

ࢹ࣮ࢱ཰㞟

‵ᗘ

ᒃ㛫, ᐷᐊࡢᗋୖ 1.1m ࡢ㧗ࡉ࡟タ⨨
5 ศ㛫㝸ࡢ㐃⥆ ᐃᗯୗ, ⬺⾰ᡤࡢᗋୖ 1.1m ࡢ㧗ࡉ࡟タ⨨
5 ศ㛫㝸ࡢ㐃⥆ ᐃ‵ᗘࢹ࣮ࢱ࣮ࣟ࢞

ᗘᗘࢹ࣮ࢱ࣮ࣟ࢞RTR-501, TR-51i(T&D ♫)s3.1kg/m2 ࡛࠶ࡾࠊከࡃࡢᑐ㇟⪅ࡀᶆ‽ⓗ࡞యᆺ ὀ 7)࡛࠶ࡗࡓࠋᛶ

せ௓ㆤ≧ែཬࡧ᪤ Ṕࡢࢹ࣮ࢱࢆ཰㞟ࡋࡓࠋᑦࠊᮏ◊✲࡟࠾ࡅࡿࠗせู࡟㛵ࡋ࡚ࡣ⏨ዪ࡯ࡰྠᩘ࡛࠶ࡗࡓࠋ୍᪉ࠊാࡁጞࡵࡓᖺ㱋ࡣࠕ20௓ㆤㄆᐃ࠘ࡣཌ⏕ປാ┬௧࡛ᐃࡵࡽࢀࡓせ௓ㆤ≧ែ༊ศ 21)ࢆཧ⪃࡟ṓ௨ୖࠖࠊ୺ほⓗ⤒῭‶㊊ᗘࡣࠕࡲ࠶ࡲ࠶‶㊊ࠖࡀ኱ࡁ࡞ᅇ⟅๭ྜࢆせᨭ᥼ 1㹼せ௓ㆤ 5 ࡬ࡢㄆᐃ࡜ࡋࡓࠋせ௓ㆤ≧ែࡣࠊ௓ㆤಖ㝤⿕ಖ༨ࡵࠊࡸࡸ♫఍⤒῭ⓗỈ‽ࡢ㧗࠸ࢧࣥࣉ࡛ࣝ࠶ࡿࡇ࡜ࡀ☜ㄆࡉࢀࡓࠋ

㝤⪅ド࡟グ㍕ࡉࢀࡓ௓ㆤಖ㝤ࢧ࣮ࣅࢫࡢࠕせ௓ㆤᗘࠖཬࡧࠕ᭷ຠᮇ

ྠᒃ⪅࡟㛵ࡋ࡚ࡣࠕ࠶ࡾࠖ࡜ᅇ⟅ࡋࡓ⪅ࡀ 8 ๭௨ୖ࡛࠶ࡗࡓࠋ㉁ၥ

㛫ࠖࡢࢹ࣮ࢱࢆඖ࡟ᢕᥱࡋࡓࠋࡲࡓࠊ᪤ Ṕࡣࢹ࢖ࢧ࣮ࣅࢫ᪋タ฼⣬ㄪᰝᑐ㇟⪅ࡀึࡵ࡚せ௓ㆤㄆᐃࡉࢀࡓ㝿ࡢせ௓ㆤᗘࡣせᨭ᥼ 1 ࠿⏝㛤ጞ᫬࡟ᐇ᪋ࡉࢀࡿ⪺ࡁྲྀࡾᘧࡢࣇ࢙࢖ࢫࢩ࣮ࢺ࠿ࡽ᪤ Ṕ࡟㛵ࡽせ௓ㆤ 3 ࡲ࡛ࡢ㛫࡛ศᕸࡋ࡚࠾ࡾࠊせ௓ㆤᗘࡢ㍍࠸ࢧࣥࣉࣝࡀ୺

ࡍࡿグ㏙ࢆᢳฟࡋࡓࠋᑦࠊࣇ࢙࢖ࢫࢩ࣮ࢺࡣࢣ࢔࣐ࢿ࣮ࢪ࣮ࣕ࡟ࡼ

࡛࠶ࡗࡓࠋࡇࢀࡣᮏㄪᰝࡢᑐ㇟⪅ࡀ฼⏝ࡍࡿࢹ࢖ࢧ࣮ࣅࢫࡀࠊ㏻ᡤ

ࡗ࡚⮬⏤グ㏙ࡉࢀࡓࡶࡢ࡛࠶ࡾࠊ᪋タ฼⏝㛤ጞࡲ࡛ࡢ᪤ Ṕ࡟㝈ᐃࢆ๓ᥦ࡜ࡋࡓ௓ㆤࢧ࣮ࣅࢫ 22)࡛࠶ࡾࠊẚ㍑ⓗ⏕άᶵ⬟ࡢ⮬❧ࡋࡓ⪅ࡉࢀࡓ᝟ሗ࡛࠶ࡿ
(3) ᐇ

ὀ 6)

ࠋ                      ࡀከ࠸ࡇ࡜ࡀᙳ㡪ࡋࡓࡶࡢ࡜⪃ᐹࡉࢀࡿࠋࡲࡓࠊึࡵ࡚せ௓ㆤㄆᐃ                                  ࡉࢀࡓᖺ㱋ࡣᖹᆒ 77.7s6.7 ṓ࡛࠶ࡗࡓࠋㄪᰝᴫせ㸦⾲ 2㸧ᮏ◊✲࡛ࡣ㉁ၥ⣬ㄪᰝཬࡧ FS ㄪᰝᑐ㇟⪅ࡢ୍㒊࡟ᑐࡋ࡚
ᗘࡢᐇ

‵ᗘࠊ

ㄪᰝࢆᐇ᪋ࡋࡓࠋ ‵ᗘィࡣᒃ㛫࣭ᐷᐊࠊ ᗘィࡣᗯୗ࣭⬺⾰ᡤࡢᗋୖ 1.1m ࡢ㧗ࡉ࡟タ⨨ࡋࠊ5 ศ㛫㝸࡛ 2014 ᖺ 12 ᭶ 8 ᪥
㹼26 ᪥ࡢ࠺ࡕ⣙ 2 㐌㛫㐃⥆ᐃࡋࡓࠋ ᐃ㛤ጞ᪥ࡣᑐ㇟⪅࡟ࡼࡾ␗࡞ࡾࠊ᭱኱࡛ 1 㐌㛫ࡢ㛤ࡁࡀ࠶ࡿࠋ

ࡉࡽ࡟ࠊ㉁ၥ⣬ㄪᰝᑐ㇟⪅ࡢ୍㒊࡛࠶ࡿᐇㄪᰝᑐ㇟⪅࡟㛵ࡋ࡚

ࡶྠᵝ࡟ಶேᒓᛶࡢ㞟ィࢆ⾜ࡗࡓࠋࡑࡢୖ࡛㉁ၥ⣬ㄪᰝᑐ㇟⪅࡜ᐇㄪᰝᑐ㇟⪅ࡢಶேᒓᛶࡢᕪࢆࠊ㔞ⓗኚᩘࡣ t ᳨ᐃࠊ㉁ⓗኚᩘࡣ࢝࢖஧஌᳨ᐃ᳨࡛ᐃࡋࡓࠋࡑࡢ⤖ᯝࠊ୧⩌࡟ಶேᒓᛶࡢ᭷ព࡞ᕪࡣ☜ㄆࡉࢀ࡞࠿ࡗࡓࠋ
ఫᏯ࡟㛵ࡍࡿ㞟ィ⤖ᯝ

㸱. ㉁ၥ⣬ㄪᰝཬࡧ )6 ㄪᰝ㞟ィ⤖ᯝ㸦⾲ 㸧ᮏ⠇࡛ࡣࠊఫᏯ࡟㛵ࡋ࡚㉁ၥ⣬ㄪᰝࡢ㞟ィ⤖ᯝࢆ♧ࡍࠋ⠏ᖺᩘࡣಶேᒓᛶཬࡧせ௓ㆤ≧ែ࡟㛵ࡍࡿ㞟ィ⤖ᯝ

21 ᖺ௨ୖࡢྂ࠸ఫᏯࡀ༙ᩘ௨ୖࢆ༨ࡵࡓࠋ」ᒙ࢞ࣛࢫࢆ᥇⏝ࡋ࡚࠸ᮏ⠇࡛ࡣࠊಶேᒓᛶ࡟㛵ࡍࡿ㉁ၥ⣬ㄪᰝࡢ㞟ィ⤖ᯝࢆ♧ࡍࠋ㉁ၥ

ࡿఫᏯࡣ⣙ 2 ๭࡟࡜࡝ࡲࡾࠊ❆ࢧࢵࢩࡣ 7 ๭௨ୖࡀ࢔࣑ࣝࢧࢵࢩ࡛

⣬ㄪᰝᑐ㇟⪅ࡢᖹᆒᖺ㱋ࡣ 78.6s6.7 ṓ㸦ᖹᆒ್sᶆ‽೫ᕪ㸧ࠊ࡛࠶࠶ࡗࡓࠋ௨ୖࡢ㞟ィ⤖ᯝ࠿ࡽ᪤ ◊✲ 23)ࡢ᥎ᐃ᪉ἲ࡟ᚑ࠸᩿⇕ᛶ⬟ࡾࠊᚋᮇ㧗㱋⪅ࡀ୺ࡓࡿࢧࣥࣉ࡛ࣝ࠶ࡗࡓࠋࡲࡓࠊBMI ࡣᖹᆒ 22.4

ࡢศ㢮ࢆ⾜ࡗࡓ⤖ᯝࠊ↓᩿⇕ࡢఫᏯࡀ 6 ๭௨ୖࢆ༨ࡵࠊ᩿⇕ᛶ⬟ࡢ

─ 902 ─

ᒃ㛫
ᐷᐊ
ᗯୗ
ᾎᐊ

ᐇ

16.3%

48.8%

12.5%

22.5%

ᐇ

16.2%

45.9%

16.2%

21.6%

㉁ၥ⣬ 7.5%
2.7%

ᐇ

26.3%
27.0%

24.3%

45.9%

㉁ၥ⣬ 11.3%

26.3%

22.5%

8.1%

32.4%

13.5%

0%

20%

ᐇ

ᐇ

15.0%

37.5%

10.8%

37.8%

13.5%

37.8%

40%

40.0%
45.9%
60%

80%

ᅗ 2 ྛ㒊ᒇ࡛ᐮ࠸࡜ឤࡌࡿ㢖ᗘ㸦࢝࢖஧஌᳨ᐃ㸧
100
90
80
70
60
50
40
30
20
10
0

(n=36)y = 㸫2.32x + 87.3
R2 = 0.56, p<0.01
7

9

11

13

15 17
ᒃ㛫ᐊ

ᅗ 3 ᒃ㛫ࡢᐊ
100
90
80
70
60
50
40
30
20
10
0

100%

㧗㱋⪅࡟㓄៖ࡋࡓ
ఫᏯ⇕⎔ቃᇶ‽್ (ᒃ㛫࣭㣗ᇽ)

19 21
[Υ]

23

25

27

࡜‵ᗘࡢ㛵ಀ

(n=36)

㧗㱋⪅࡟㓄៖ࡋࡓ
ఫᏯ⇕⎔ቃᇶ‽್ (ᐷᐊ)

y = 㸫2.27x + 85.6
R2 = 0.50, p<0.01
7

9

11

13

15 17 19 21 23 25
ᐷᐊᐊ [Υ]ᅗ 4 ᐷᐊࡢᐊ ࡜‵ᗘࡢ㛵ಀ

27





ᒃ㛫ཬࡧᐷᐊࡢ

⇕⎔ቃ࡟㛵ࡋ࡚ၥ࠺ࡓ CASBEE ೺ᗣࢳ࢙ࢵࢡࣜࢫࢺࡢ

46.3%

36.3%

㸲. ఫᏯෆ

ఫᏯෆ

20.0%

㉁ၥ⣬ 11.3%

ࡑࡢ⤖ᯝࠊఫᏯᒓᛶ࡟㛵ࡋ࡚ࡶ୧⩌࡟᭷ព࡞ᕪࡣ☜ㄆࡉࢀ࡞࠿ࡗࡓࠋ
෭ឤ࡟㛵ࡍࡿ㞟ィ⤖ᯝ

56.8%

n.s.

ㄪᰝᑐ㇟⪅ࡢ㛫࡛࢝࢖஧஌᳨ᐃࢆ⾜ࡗࡓࠋ

27.0%
60.0%

㉁ၥ⣬

ప࠸ఫᏯࡢࢧࣥࣉࣝࡀ୰ᚰ࡛࠶ࡗࡓࠋఫᏯᒓᛶ࡟㛵ࡋ࡚ࡶ๓⠇ྠᵝ࡟㉁ၥ⣬ㄪᰝᑐ㇟⪅࡜ᐇ

40.5%

n.s.

せ௓ㆤㄆᐃ
ᐇ್
77.7 (6.7) 77.2 (6.4) n.s.
ࡉࢀࡓᖺ㱋 [ṓ]1) 16 ṓᮍ‶
1 [1.3]2 [5.4]2) 16㹼19 ṓ
25 [31.3]
14 [37.8]
ാࡁጞࡵࡓ3) 20 ṓ௨ୖ46 [57.5]
18 [48.6] n.s.
ᖺ㱋4) ⟅࠼ࡓࡃ࡞࠸
1 [1.3]3 [8.1]↓ᅇ⟅
7 [8.8]0 [0.0]1) ࡜࡚ࡶ‶㊊
6 [7.5]2 [5.4]2) ࡲ࠶ࡲ࠶‶㊊
50 [62.5]
25 [67.6]
3) ࠶ࡲࡾ୺ほⓗ
11 [13.8]
7 [18.9]
‶㊊࡛࡞࠸
n.s.
⤒῭‶㊊ᗘ
4) ඲ࡃ‶㊊
10 [12.5]
3 [8.1]ࡋ࡚࠸࡞࠸↓ᅇ⟅
3 [3.8]0 [0.0]1) ࡞ࡋ(⊂ᒃ)
13 [16.3]
6 [16.2]
ྠᒃ⪅ࡢ
n.s.
᭷↓
2) ࠶ࡾ
67 [83.8]
31 [83.8]
1) 10 ᖺᮍ‶7 [8.8]2 [5.5]2) 11~20 ᖺ
13 [16.3]
4 [11.1]
3) 21~30 ᖺ
13 [81.3]
5 [13.9]⠏ᖺᩘn.s.
4) 31~40 ᖺ
20 [25.0]
13 [36.1]
5) 41 ᖺ௨ୖ24 [30.0]
11 [30.6]↓ᅇ⟅
2 [2.5]
1 [2.8]1) 10 ᖺᮍ‶18 [22.5]
9 [25.0]
2) 11~20 ᖺ
17 [21.3]
5 [13.9]
3) 21~30 ᖺ
10 [12.5]
6 [16.7]ᒃఫᮇ㛫n.s.
4) 31~40 ᖺ
16 [20.0]
11 [30.6]
5) 41 ᖺ௨ୖ18 [22.5]5 [13.9]ఫᏯ↓ᅇ⟅
0 [0.0]0 [0.0]࡟1) 1 ᯛ
65 [81.3]
30 [83.3]
㛵 ❆࢞ࣛࢫࡢ
2) 2 ᯛ
14 [17.5]
6 [16.6] n.s.
ࡍ ᯛᩘ↓ᅇ⟅
0 [0.0]0 [0.0]ࡿ1) ࢔࣑ࣝ
62 [77.5]
26 [72.2]
㡯┠2) 2 㔜࢔࣑ࣝ
7 [8.8]4 [11.1]
3) ᩿⇕
4 [5.0]2 [5.6]❆ࢧࢵࢩࡢ4) ྂ࠸ᮌ〇3 [3.8]2 [5.6] n.s.
✀㢮5) ᪂ࡋ࠸ᮌ〇2 [2.5]
1 [2.8]6) ᶞ⬡
0 [0.0]0 [0.0]↓ᅇ⟅
1 [1.3]1 [2.8]1) ↓᩿⇕
50 [62.5]
23 [63.9]
2) S55 ᖺᇶ‽
19 [23.8]
9 [25.0]᩿⇕ᛶ⬟3) H4 ᖺᇶ‽6 [7.5]3 [8.3] n.s.
4) H11 ᖺᇶ‽
3 [3.8]1 [2.8]ศ㢮୙ྍ
1 [1.3]0 [0.0]㔞ⓗኚᩘ(ᖺ㱋, BMI, せ௓ㆤㄆᐃࡉࢀࡓᖺ㱋)ࡣᖹᆒ್(ᶆ‽೫ᕪ)࡜ t ᳨ᐃ⤖
ᯝࠊ㉁ⓗኚᩘ(ୖグ௨እ)ࡣᗘᩘ[┦ᑐᗘᩘ%]࡜࢝࢖஧஌᳨ᐃ⤖ᯝࢆグ㍕

㉁ၥ⣬

඲ࡃ࡞࠸
36.3%

n.s.

ಶ
ே
࡟
㛵
ࡍ
ࡿ
㡯
┠

10.8% 21.6%
2.5%
7.5%
30.0%
2.7%
10.8%
29.7%

ᐇ

⬺⾰ᡤ

n.s.

ࡵࡗࡓ࡟࡞࠸

32.5%

ࢺ࢖ࣞ

n.s.
n.s.

21.3%

n.s.

せ௓ㆤᗘ

n.s.

ࡵࡗࡓ࡟࡞࠸

㉁ၥ⣬ 10.0%n.s.

ᖺ㱋 [ṓ]BMI [kg/m 2]᭷ព☜⋡ᒃ㛫‵ᗘ [%]

ᛶู

㑅ᢥ⫥
1) ⏨ᛶ
2) ዪᛶ
ᐇ್
ᐇ್
1) せᨭ᥼ 12) せᨭ᥼ 23) せ௓ㆤ 14) せ௓ㆤ 25) せ௓ㆤ 3

ᐇ ㄪᰝ
ᑐ㇟⪅20 [54.1]
17 [45.9]
78.5 (5.9)
22.6 (2.7)
20 [54.1]
8 [21.6]
4 [10.8]
4 [10.8]
1 [2.7]ᐷᐊ‵ᗘ [%]

タၥ

㉁ၥ⣬ㄪᰝ
ᑐ㇟⪅
38 [47.5]
42 [52.5]
78.6 (6.7)
22.4 (3.1)
30 [37.5]
25 [31.3]
11 [13.8]
11 [13.8]
3 [3.8]

n.s.



ࡓࡲ࡟࠶ࡿ

⾲ 3 ㉁ၥ⣬ㄪᰝࡢ㞟ィ⤖ᯝ

ᐇ

⇕⎔ቃࡢ

ᐃ⤖ᯝὀ ‵ᗘᐃ⤖ᯝ࡜‵ᗘࡢ㛵ಀࢆᅗ 3, 4ㄪᰝᮇ㛫୰ࡢᒃ㛫ཬࡧᐷᐊࡢᖹᆒᐊ

ᅇ⟅⤖ᯝࡣࠊᒃ㛫ࡸᐷᐊ࡜࠸ࡗࡓᒃᐊ࡜ẚ㍑ࡋ࡚ࠊᗯୗࡸ⬺⾰ᡤ࡜࡟♧ࡍࠋᅗ୰࡟⥙᥃ࡅ࡛♧ࡋࡓ㧗㱋⪅࡟㓄៖ࡋࡓఫᏯ⇕⎔ቃᇶ‽್࠸ࡗࡓ㠀ᒃᐊ࡛ᐮ࠸࡜ឤࡌࡿ㢖ᗘࡀ㧗ࡃࠊ෤Ꮨࡢ

24)ࡢ⠊ᅖ࡟ᖹᆒᐊ

⇕⎔ቃ࡟ᑐࡍࡿ

ࠊ‵ᗘࡀ཰ࡲࡿᑐ㇟ఫᏯࡣ 4 ࢧࣥࣉࣝࡢࡳ࡛࠶୺ほホ౯ࡀప࠸ഴྥࡀ♧ࡉࢀࡓ㸦ᅗ 2㸧ࠋࡇࡢഴྥࡣ㉁ၥ⣬ㄪᰝᑐ㇟

ࡾࠊ≉࡟ᐊ

⪅࡜ᐇ

ࡓࠋᅗ 2 ࡢ୺ほホ౯࡛ࡣᐮ࠸࡜ឤࡌࡿ㢖ᗘࡀప࠸࡜ᅇ⟅ࡋࡓ⪅ࡀከㄪᰝᑐ㇟⪅࡛ඹ㏻ࡋ࡚ぢࡽࢀࡿࡶࡢ࡛࠶ࡾࠊ࢝࢖஧஌᳨ᐃ

࡛ࡶ᭷ព࡞ᕪࡣ☜ㄆࡉࢀ࡞࠿ࡗࡓࠋ

࠿ࡗࡓࡀࠊᐇ㝿࡟௨ୖࡼࡾࠊᐇ

ㄪᰝ᭷ຠࢧࣥࣉࣝ㸦n=37㸧ࡀ㉁ၥ⣬ㄪᰝ᭷ຠࢧࣥ

㱋⪅ࡢࣉࣝ㸦n=80㸧ࡢ෭ឤࢆ௦⾲ࡍࡿ࡟㊊ࡿࡶࡢ࡛࠶ࡾࠊಶேᒓᛶࡸఫ

Ꮿᒓᛶ࡟ࡶ⤫ィᏛⓗ࡟᭷ព࡞ᕪࡀ࡞࠸ࡇ࡜ࢆ☜ㄆࡋࡓࠋࡇࢀࢆཷࡅ
࡚ࠊḟ❶࡛ࡣఫᏯෆ

⇕⎔ቃࡢᐃ⤖ᯝ࡟ࡘ࠸࡚㆟ㄽࢆ㐍ࡵࡿࠋࡀᇶ‽್ࢆୗᅇࡿᐮ෭࡞ࢧࣥࣉࣝࡀከࡃࡢ๭ྜࢆ༨ࡵ
ᐃࡉࢀࡓᐊࡀప࠸ఫᏯࡀከ࠿ࡗࡓࠋࡇࢀࡣ㧗෭ឤࡢ㕌໬ 25)ࡀᙳ㡪ࡋࡓࡶࡢ࡜⪃ᐹࡉࢀࡿࠋ
⇕⎔ቃࡢ୺ほホ౯࡜ᐊ๓⠇࡛ࡢᑐᛂ㛵ಀ

⇕⎔ቃࡢ୺ほホ౯࡜ᐊࡢᐇ್ࡢ஋㞳ࡀ♧၀ࡉࢀࡓࠋ

ࡑࡇ࡛ࠊ୺ほホ౯ࡢᣦᶆ࡜ࡋ࡚⏝࠸ࡓ CASBEE ೺ᗣࢳ࢙ࢵࢡࣜࢫ

─ 903 ─

㹼8㸧ࠋࡑࡢ⤖ᯝࠊᐇ

ㄪᰝ࡛ᐊ

ࢆ

ᐃࡋࡓ 4 㒊ᒇࡢෆ 2 ⩌㛫࡟᭷ព࡞ᕪࡀ☜ㄆࡉࢀࡓࡢࡣᒃ㛫࡜⬺⾰ᡤࡢࡳ࡛࠶ࡗࡓ㸦 p<0.01㸧ࠋ2ࡢ㐪࠸ࡀ☜ㄆࡉࢀ࡞࠿ࡗࡓ 2 ᐊࡢෆࠊᐷᐊࡣᐷලࡢᙳ㡪

⩌㛫࡟ᐊ

ᒃ㛫ᐊ

࡜ࡢ㛵㐃ᛶ࡟ࡘ࠸࡚ࠊt ᳨ᐃࢆᐇ᪋ࡋࡓ㸦ᅗ 5Ⅼ⩌࡟ศ㢮ࡋࠊᐊ

16
13
10**p<0.01
పᚓⅬ⩌(n=12)

ᗘᕪࡀ୺

22

19
16
13
10

7
㧗ᚓⅬ⩌
(n=25)ほホ౯࡟ᙳ㡪ࢆཬࡰࡋࡓྍ⬟ᛶࡀ⪃࠼ࡽࢀࡿࠋࡑࡇ࡛ࠊᒃ㛫࡜ᗯୗ

ᅗ 5 ୺ほホ౯ูᒃ㛫ᐊ

ࡢᐊ㛫

25

25

22

22

16

㸦ᅗ 9㸧ࠋࡑࡢ⤖ᯝࠊపᚓⅬ⩌ࡣ㧗ᚓⅬ⩌࡜ẚ㍑ࡋ࡚ᐊ㛫ᗘᕪࡀ኱ࡁࡃࠊᗯୗࡢ

ࡼࡾࡶᒃ⇕⎔ቃࡢ୺ほホ౯࡟ࡣᗯୗࡢ⤯ᑐⓗ࡞ᐊᗘᕪࡀ኱ࡁࡃᙳ㡪ࡋࡓࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡓࡔࡋࠊ

⌧᫬Ⅼࡢศᯒ⤖ᯝ࡛ࡣࠕᒃ㛫ࡶᗯୗࡶᬮ࠿ࡃᐊ㛫ࢧࣥࣉࣝ࡜ࠕᒃ㛫ࡶᗯୗࡶᐮࡃᐊ㛫ᗘᕪࡀᑠࡉ࠸ࠖ

ᗘᕪࡀᑠࡉ࠸ࠖࢧࣥࣉࣝࡀศ

19
16
13
10
7

ᬮ࡞ࢧࣥࣉࣝࢆ୰ᚰ࡟ࢧࣥࣉࣝᩘࢆᣑ඘ࡍࡿࡇ࡜

**p<0.01
㧗ᚓⅬ⩌(n=19)

ᅗ 8 ୺ほホ౯ู⬺⾰ᡤᐊ᩿⇕ᛶ⬟ࡀ㧗࠸࡯࡝ᐊࡀ㧗࠸ഴྥ࡟࠶ࡾࠊ≉࡟㠀ᒃᐊ࡛࠶ࡿᗯୗ

࡛ࡑࡢഴྥࡀᙉ࠸ࡇ࡜ࡀ☜ㄆࡉࢀࡓ㸦 p<0.05㸧ࠋᒃᐊ࡛࠶ࡿᒃ㛫ཬࡧᐷᐊ࡛᩿⇕ᛶ⬟ࡀ㧗࠸࡯࡝ᐊపᚓⅬ⩌(n=14)(n=14)
㧗ᚓⅬ⩌(n=23)(n=23)
5䠉5ࡀ㧗ࡃ࡞ࡿഴྥࡀஈࡋ࠿ࡗࡓࡢࡣࠊ

ᅾᏯ᫬ࡸᑵᐷ๓ࡢᬮᡣࡢ౑⏝᭷↓ࡢᙳ㡪ࡀ᩿⇕ᛶ⬟ࡢᙳ㡪ࡼࡾࡶ኱࢖࣋ࣥࢺࣄࢫࢺ࣮ࣜศᯒࡢ 1 ࡘ࡛࠶ࡿ࢝ࣉ࣭࣐ࣛࣥ࢖࣮ࣖἲ㸦௨ୗ
KM ἲ㸧ࢆ⏝࠸ࡓࠋ࢖࣋ࣥࢺࣄࢫࢺ࣮ࣜศᯒ࡛ࡣࠊ᫬Ⅼ t ࡼࡾ๓࡟

[Υ]
ᒃ㛫ᐊ

⇕⎔ቃ࡜೺ᗣᑑ࿨ࡢ㛵㐃⇕⎔ቃ࡜ᒃఫ⪅ࡢ௓ㆤண㜵ࡢ㛵㐃ࢆ᳨ドࡍࡿࡓࡵࠊ

ࡣ࢖࣋ࣥࢺࡀⓎ⏕ࡋ࡞࠸☜⋡㸦⏕Ꮡ☜⋡㸧ࢆࠊt ࡢ㛵ᩘ࡜ࡋ࡚⾲ࡋ

25

20

20

15
10
5
0

࡜࡞ࡃồࡵࡓୖ࡛ࠊ」ᩘ࠶ࡿᑐ㇟⩌㛫ࡢ⏕Ꮡ㛵ᩘࡢᕪ␗ࡢ⤫ィᏛⓗ26)ࠋ

ㄆࡉࢀࡓᒃ㛫ཬࡧ⬺⾰ᡤࡢ୺ほホ౯ࢆ᥇⏝ࡋࠊࢧࣥࣉࣝࢆ 2 ⩌࡟ศ[Υ]㢮ࡋࡓࠋࡲࡓࠊᮏศᯒ࡟࠾ࡅࡿ࢖࣋ࣥࢺࡣࠗせ௓ㆤㄆᐃ࠘ࡢⓎ⏕࡜ᗯୗᐊ࡜ࡢᑐᛂ㛵ಀࡀ☜ࡋࠊせ௓ㆤㄆᐃࡉࢀࡓ᫬Ⅼࡢᖺ㱋ࡀ㧗࠸࡯࡝௓ㆤண㜵ࡉࢀ࡚࠸ࡿ࡜
ゎ㔘ࡍࡿࡶࡢ࡜ࡋࡓࠋせ௓ㆤㄆᐃ᫬Ⅼࡢᖺ㱋ࡣࠊㄪᰝ᫬Ⅼࡢᖺ㱋࡜せ௓ㆤㄆᐃ᪥ࡢ᝟ሗࢆ⏝࠸࡚ィ⟬ࡋࡓࠋᑦࠊᮏศᯒ࡟࠾ࡅࡿࢫࢱ࣮
ࢺ᫬Ⅼ㸦0 ᖺ┠㸧ࡣࠊᑐ㇟ࢧࣥࣉࣝࡑࢀࡒࢀࡢ 60 ṓ᫬Ⅼ࡜ࡋࡓࠋࡇ
ࢀࡣ඲ࢧࣥࣉࣝࡀᮍࡔせ௓ㆤㄆᐃࢆཷࡅ࡚࠸࡞࠸ᖺ㱋࡛࠶ࡿࠋᒃ㛫ཬࡧ⬺⾰ᡤࡢ⇕⎔ቃࡢ୺ほホ౯࡟ᇶ࡙ࡁ KM ἲࢆᐇ᪋ࡋࡓ

n.s.

25
15

ᗘᕪ

15
10
5
0

H4ᖺ
S55ᖺ
ᇶ‽ ᇶ‽௨ୖ
(n=4)
(n=9)

↓᩿⇕
(n=23)

᭷ពᛶࢆ᳨ᐃࡍࡿࡇ࡜ࡀ࡛ࡁࡿࣀࣥࣃ࣓ࣛࢺࣜࢵࢡ࡞ᡭἲ࡛࠶ࡿ

⇕⎔ቃࡢ୺ほホ౯ูᐊ㛫25ࡓ⏕Ꮡ㛵ᩘࢆồࡵࡿࠋKM ἲࡣᑐ㇟⩌ࡢ⏕Ꮡ㛵ᩘࢆࠊ௬ᐃࢆ⨨ࡃࡇ⇕⎔ቃࡢᣦᶆ࡜ࡋ࡚ࡣࠊ4.2 ⠇࡛ᐊ

10
15
20
0
5
10
ᐊ㛫 ᗘᕪ㸦ᒃ㛫ᐊ 㸫ᗯୗᐊ 㸧[Υ]ᅗ 9 ᗯୗࡢ

ࡁ࠿ࡗࡓࡶࡢ࡜⪃ᐹࡉࢀࡿࠋ
㸳. ෤ᏘࡢఫᏯෆ

n.s.

[Υ]

࡜ࡢ㛵㐃ࢆ᳨ドࡍࡿࡓࡵ࡟୍ඖ㓄⨨ศᩓศᯒࢆᐇ᪋ࡋࡓ㸦ᅗ 10㹼13㸧ࠋࡑࡢ⤖ᯝࠊᒃ㛫ࠊᗯୗࠊ⬺⾰ᡤ࡛ࡣ

ఫᏯෆ

10

ࡢ㛵㐃

⥆࠸࡚ࠊ᩿⇕ᛶ⬟࡜ᐊ෤ᏘࡢఫᏯෆ

13

పᚓⅬ⩌(n=18)

ᐷᐊᐊ᩿⇕ᛶ⬟࡜ᐊ

19

㧗ᚓⅬ⩌
(n=14)

ᅗ 7 ୺ほホ౯ูᗯୗᐊ᳨࡛ドࡋࡓ࠸ࠋ

**

7

n.s.
↓᩿⇕

S55ᖺ
ᇶ‽

H4ᖺ
ᇶ‽௨ୖ

ᅗ 10 ᩿⇕ᛶ⬟ูᒃ㛫ᐊ

ᅗ 11 ᩿⇕ᛶ⬟ูᐷᐊᐊ

25

25

*

20

*

[Υ]

ᚋఫᏯෆ඲యࡀ

n.s.
పᚓⅬ⩌(n=23)

㞳࡛ࡁ࡚࠸࡞࠸ࡇ࡜࡟␃ពࡍ࡭ࡁ࡛࠶ࡿࠋࡇࡢㄢ㢟Ⅼ࡟ࡘ࠸࡚ࡣ௒

㧗ᚓⅬ⩌(n=32)

ᅗ 6 ୺ほホ౯ูᐷᐊᐊ

15

⬺⾰ᡤᐊ

㛫࡜ᗯୗࡢᐊ㛫[Υ]⇕⎔ቃࡢ୺ほホ౯ู࡟ẚ㍑᳨ᐃࡋࡓᗯୗᐊᗘᕪ࡟ࡘ࠸࡚ᗯୗࡢ

n.s.
పᚓⅬ⩌
(n=5)

[Υ]

ࡀపࡃศᩓࡀᑠࡉ࠸୰࡛ࠊᒃ㛫࡜ࡢMax.
Ave.+S.D.
Ave.
Ave.㻙S.D.
Min.

⬺⾰ᡤᐊ

඲య࡜ࡋ࡚ᗯୗᐊ

25

19

7

ࡀ኱ࡁ࠿ࡗࡓࡶࡢ࡜⪃࠼ࡽࢀࡿࠋᗯୗ࡟㛵ࡋ࡚ࡣࡑࡶࡑࡶᑐ㇟ఫᏯ

**
[Υ]

22

ᐷᐊᐊ

25

పᚓⅬ⩌ࠊࠕ3) ࡵࡗࡓ࡟࡞࠸ࠖࠕ4) ඲ࡃ࡞࠸ࠖ࡜ᅇ⟅ࡋࡓ⪅ࢆ㧗ᚓ[Υ]ࢺࡢᅇ⟅ࡢ࠺ࡕࠊࠕ1) ࡼࡃ࠶ࡿࠖࠕ2) ࡓࡲ࡟࠶ࡿࠖ࡜ᅇ⟅ࡋࡓ⪅ࢆ

10
50*p<0.05
↓᩿⇕

S55ᖺ
ᇶ‽

20
15
10
5
0

H4ᖺ
ᇶ‽௨ୖ

n.s.
↓᩿⇕

ᅗ 12 ᩿⇕ᛶ⬟ูᗯୗᐊ

S55ᖺ
ᇶ‽

H4ᖺ
ᇶ‽௨ୖ

ᅗ 13 ᩿⇕ᛶ⬟ู⬺⾰ᡤᐊⅬ⩌ࡣせ௓ㆤㄆᐃ࡟⮳ࡿᖺ㱋ࡀ 4 ṓⱝ࠸ࠋᚑࡗ࡚ࠊ⬺⾰ᡤࡢᐊ࡟࡜ࡇࢁࠊᒃ㛫ࡢ୺ほホ౯ู࡟᭷ព࡞⤖ᯝࡣᚓࡽࢀ࡞࠿ࡗࡓ㸦ᅗ 14㸧㛵ࡍࡿᚓⅬࡀ㧗࠸࡯࡝せ௓ㆤ≧ែ࡟⮳ࡿ᫬Ⅼࡀ㧗㱋᫬࡜࡞ࡿࡇ࡜ࡀ

୍᪉࡛ࠊ⬺⾰ᡤ࡟㛵ࡋ࡚ࡣ㧗ᚓⅬ⩌ࡀపᚓⅬ⩌࡜ẚ㍑ࡋ࡚㧗㱋࡟࡞♧ࡉࢀࡓࠋࡇࢀࡣ⬺⾰ᡤࡢࡗ࡚ࡶ㠀せ௓ㆤ⪅ࡢ๭ྜࡀ㧗ࡃಖࡓࢀࡿഴྥ࡟࠶ࡿࡇ࡜ࡀ☜ㄆࡉࢀᐤ୚ࡋ࡚࠸ࡿ࡜ゎ㔘ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ௨ୖࡢ⤖ᯝ࠿ࡽᒃఫ⪅ࡢ௓ࡓ㸦p<0.05, ᅗ 15㸧ࠋ౛࠼ࡤ㠀せ௓ㆤㄆᐃ⪅ࡢ๭ྜࡀ 50%࡟࡞ࡿ᫬ㆤண㜵࡟ࡣ≉࡟෤Ꮨࡢ⬺⾰ᡤᐊⅬ࡛ẚ㍑ࡍࡿ࡜ࠊపᚓⅬ⩌ࡣ 76 ṓࠊ㧗ᚓⅬ⩌ࡣ 80 ṓ࡛࠶ࡾࠊపᚓ

࡜ࡀ♧၀ࡉࢀࡓࠋ⬺⾰ᡤᐊ

─ 904 ─⇕⎔ቃࡀ௓ㆤண㜵࣭೺ᗣᑑ࿨ࡢᘏఙ࡟
ࢆᬮ࡟ಖࡘࡇ࡜ࡀ᭷ຠ࡛࠶ࡿࡇ

ࡣ⾑ᅽୖ᪼ 27)ࡸάື㔞పୗ 17)࡜࠸ࡗࡓ

100
1೺ᗣ࡬ࡢᙳ㡪ࡀ᪤ ◊✲࡛ᣦ᦬ࡉࢀ࡚࠸ࡿࡇ࡜࠿ࡽࠊ௒ᅇࡢศᯒ⤖n.s.

ᯝࡀጇᙜ࡞ࡶࡢ࡛࠶ࡗࡓ࡜⪃ᐹࡉࢀࡿࠋ
ࡓࡔࡋࠊKM ἲࡢࡳ࡛ࡣㄪᩚኚᩘࢆྠ᫬࡟ᢞධ࡛ࡁ࡞࠸ࡓࡵࠊせ⇕⎔ቃ࡛ࡣ࡞ࡃಶேᒓᛶࡸ♫఍⤒῭ⓗỈ‽ࡢᕪ࡟ࡼࡗ࡚ࡶࡓࡉࢀࡓࡶࡢ࡛࠶ࡿྍ⬟ᛶࡀྰᐃฟ᮶
࡞࠸ࠋࡑࡇ࡛ 2 ⩌㛫ࡢಶேᒓᛶཬࡧ♫఍⤒῭ⓗỈ‽ࡢᕪࢆ࢝࢖஧஌᳨ᐃ᳨࡛ドࡋࡓ㸦⾲ 4㸧ࠋࡑࡢ⤖ᯝࠊ඲࡚ࡢ㡯┠࡛᭷ព࡞ᕪࡣ☜ㄆࡉࢀࡎࠊ೺ᗣᑑ࿨ࡢᕪࡀ⬺⾰ᡤࡢ⇕⎔ቃࡢ୺ほホ౯ࡢᕪ࡟ࡼࡿࡶࡢ

࡛࠶ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ

0.75
75

㠀せ௓ㆤ⪅ࡢ๭ྜ [%]௓ㆤㄆᐃࡉࢀࡓᖺ㱋ࡢᕪࡀ⬺⾰ᡤࡢᒃ㛫 ⇕⎔ቃ
㧗ᚓⅬ⩌ (n=25)50
0.5ᒃ㛫 ⇕⎔ቃ
పᚓⅬ⩌ (n=55)

25
0.25


㸴. ࡲ࡜ࡵ
⤖ㄽ

0ᮏሗ࡛ࡣࠊ2014 ᖺ࡟ᐇ᪋ࡋࡓ㉁ၥ⣬ㄪᰝࠊFS ㄪᰝཬࡧ෤Ꮨࡢᐇ
ㄪᰝ⤖ᯝࢆ⏝࠸ࠊఫᏯෆ

⇕⎔ቃ࡜ᒃఫ⪅ࡢ௓ㆤண㜵ࡢ㛵㐃࡟ࡘ

70

75
80
85
90
ᖺ㱋 [ṓ]⇕⎔ቃࡢ୺ほホ౯ู㠀せ௓ㆤㄆᐃ⪅๭ྜ

100㸯㸧ఫᏯෆࡢྛ㒊ᒇ࡛ᐮ࠸࡜ឤࡌࡿ㢖ᗘࡢ⏦࿌ࡣࠊᒃᐊ࡜ẚ㍑ࡋ࡚
ࡋࡓᐊ

65

ᅗ 14 ᒃ㛫࠸᳨࡚ドࡋࡓࠋࡑࡢ⤖ᯝࠊ௨ୗࡢ 4 Ⅼࡢ▱ぢࡀᚓࡽࢀࡓࠋ
㠀ᒃᐊ࡛ᅇ⟅ࡍࡿ⪅ࡀከ࠿ࡗࡓࠋᐇ

60

95

Generalized Wilcoxon test: p<0.05࡟╔┠ࡍࡿ࡜ࠊ㧗⇕⎔ቃ࡟ᑐࡍࡿ୺ほホ౯࡜ᐊ࡟ࡎࢀࡀᏑᅾࡍࡿྍ⬟ᛶࡀ♧ࡉࢀࡓࠋ㸰㸧ᒃ㛫ࠊᐷᐊࠊᗯୗࠊ⬺⾰ᡤࡢ⇕⎔ቃ࡟ᑐࡍࡿ୺ほホ౯࡜ᐊࡢᑐᛂࢆ᳨ドࡋࡓ࡜ࡇࢁࠊᒃ㛫࡜⬺⾰ᡤࡢࡳ㧗ᚓⅬ⩌ࡢᐊࡀ᭷ព࡟㧗࠸࡜࠸࠺┦㛵㛵ಀࡀ☜ㄆࡉࢀࡓࠋᗯୗ࡟㛵ࡋ࡚ࡣࠊᗯୗࡢ
ᐊࡼࡾࡶᒃ㛫࡜ᗯୗࡢᐊ㛫ᗘᕪࡀ୺ほホ౯࡟ᙳ㡪ࢆཬࡰࡋ࡚㠀せ௓ㆤ⪅ࡢ๭ྜ [%]㱋⪅࡟㓄៖ࡋࡓఫᏯ⇕⎔ቃᇶ‽್ࢆୗᅇࡿࢧࣥࣉࣝࡀ኱༙ࢆ༨ࡵࠊ

࠸ࡿྍ⬟ᛶࡀ♧ࡉࢀࡓࠋ㸱㸧᩿⇕ᛶ⬟ࡢ㧗࠸ఫᏯࡣࠊ㠀ᒃᐊ࡛࠶ࡿᗯୗࡢᐊ

50⬺⾰ᡤ ⇕⎔ቃ
పᚓⅬ⩌ (n=38)250⇕⎔ቃ࡜ᒃఫ⪅ࡢ௓ㆤண㜵ࡢ㛵㐃࡟ࡘ࠸࡚ KM

ἲ࡟ᇶ࡙ࡁ᳨ドࡋࡓࠋࡑࡢ⤖ᯝࠊ⬺⾰ᡤࡢ⬺⾰ᡤ ⇕⎔ቃ㧗ᚓⅬ⩌ (n=42)ࡀ㧗࠸ഴྥ࡟

࠶ࡗࡓࠋ㸲㸧෤ᏘࡢఫᏯෆ

75

60

ホ౯ࡀ㧗࠸㧗ᚓⅬ⩌ࡣࠊపᚓⅬ⩌࡜ẚ㍑ࡋ࡚せ௓ㆤ≧ែ࡟⮳ࡿ᫬
Ⅼࡀ㧗㱋࡟࡞ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡉࡽ࡟ࠊ㧗ᚓⅬ⩌࡜పᚓⅬ⩌ᅗ 15 ⬺⾰ᡤᛶูᬮ࡞ఫᏯࡢᒃఫ⪅ࡣせ௓ㆤ≧ែ࡟⮳ࡿ᫬Ⅼࡀ㧗㱋࡟࡞ࡿࠖ࡜࠸࠺௬ㄝࡢୗ࡛ఫᏯෆ

⇕⎔ቃ࡜௓ㆤண㜵ࡢ㛵㐃࡟ࡘ࠸࡚ศᯒࢆᐇ᪋ࡋࠊ≉࡟⬺⾰ᡤࡢ⇕⎔ቃࡀせ௓ㆤㄆᐃࡉࢀࡿᖺ

㱋࡟㛵㐃ࡍࡿྍ⬟ᛶࢆ♧ࡋࡓࠋࡋ࠿ࡋ࡞ࡀࡽᮏሗ࡟࠾ࡅࡿ᭱⤊⤖ᯝࡣ࠶ࡃࡲ࡛⇕⎔ቃࡢ୺ほホ౯࡟ᇶ࡙࠸ࡓศᯒ࡛࠶ࡾࠊ㧗㱋⪅ࡢ෭ឤࡢ㕌໬࡟ࡼࡿᐊ

ㄪᰝࡢࢧࣥࣉࣝࢆᣑ඘ࡋࠊᐈほⓗ࡞ᣦᶆ࡟ᇶ࡙ࡁ෤Ꮨࡢఫ

Ꮿෆ⇕⎔ቃ࡜೺ᗣᑑ࿨ࡢ㛵㐃ࢆ᳨ドࡍࡿᚲせࡀ࠶ࡿࠋࡑࡢ㝿ࠊఫᏯෆ⇕⎔ቃ࡟ᙳ㡪ࢆཬࡰࡋ࠺ࡿᅉᏊ࡜ࡋ࡚ᮏሗ࡛ࡣ᳨ドࡋࡁࢀ࡚࠸࡞࠸ᬮᡣࡢ౑⏝࡟ࡼࡿ⇕⎔ቃไᚚࡸࠊ╔⾰㔞࡟ࡘ࠸࡚ࡶ⪃៖ࡍࡿᚲせࡀ࠶ࡿࠋࡲࡓࠊ⤯ᑐⓗ࡞ᐊ
㛫

BMI

ാࡁጞࡵࡓ
ᖺ㱋

࡜୺ほホ౯ࡢࡎࢀࢆ⪃៖࡛ࡁࡓࡶࡢ࡛ࡣ࡞࠸ࠋ

௒ᚋᐇࡢࡳ࡞ࡽࡎᒃᐊ࡜㠀ᒃᐊ㛫ࡢᐊᗘᕪࡀ௓ㆤண㜵࡟ᙳ㡪ࢆཬࡰࡋ࡚࠸ࡿࡇ࡜ࡶ⪃࠼ࡽࢀࡿࡓࡵࠊ

75
80
85
90
ᖺ㱋 [ṓ]⇕⎔ቃࡢ୺ほホ౯ู㠀せ௓ㆤㄆᐃ⪅๭ྜ

పᚓⅬ⩌
ᐇᩘ
[%]

ᒓᛶ

ㄆࡋࡓࠋ
௒ᚋࡢㄢ㢟

70

95



⾲ 4 ⬺⾰ᡤࡢ୺ほホ౯ูࡢᒓᛶ㞟ィ⤖ᯝ㸦࢝࢖஧஌᳨ᐃ㸧ࡢ㛫࡟ࡣಶேᒓᛶཬࡧ♫఍⤒῭ⓗỈ‽ࡢ᭷ព࡞ᕪࡀ↓࠸ࡇ࡜ࢆ☜

ᮏሗ࡛ࡣࠊ
ࠕ෤Ꮨ࡟

65

⇕⎔ቃ࡟ᑐࡍࡿ୺ほ

୺ほⓗ
⤒῭‶㊊ᗘ

ྠᒃேࡢ
᭷↓

㧗ᚓⅬ⩌
ᐇᩘ
[%]

⏨ᛶ
ዪᛶ

19
19

50.0
50.0

21
21

50.0
50.0

పయ㔜(<18.5)
ᶆ‽

5
29

13.2
76.3

7
23

16.7
54.8

⫧‶(Ӎ25)16 ṓᮍ‶

4

10.5

12

28.6

16㹼19 ṓ20 ṓ௨ୖ

13
22

34.2
57.9

12
24

28.6
57.1

⟅࠼ࡓࡃ࡞࠸࣭↓ᅇ⟅
࡜࡚ࡶ‶㊊

2
4

5.3
10.5

6
2

14.3
4.8

ࡲ࠶ࡲ࠶‶㊊࠶ࡲࡾ‶㊊࡛࡞࠸

6
20

15.8
52.6

5
30

11.9
71.4

඲ࡃ‶㊊ࡋ࡚࠸࡞࠸
↓ᅇ⟅

6
2

15.8
5.3

4
1

9.5
2.4

࡞ࡋ(⊂ᒃ)
࠶ࡾ

4
34

10.5
89.5

9
33

21.4
78.6

1

2.6

0

᭷ព
☜⋡
n.s.
n.s.

0.0

n.s.

n.s.

n.s.

1 ࡘ࡛࠶ࡿ KM ἲࡣㄪᩚኚᩘࢆ⪃៖࡛ࡁ࡞࠸࡜࠸࠺ㄢ㢟ࡀ࠶ࡿࠋ௒

௒ᚋࡢㄢ㢟࡜ࡋ࡚ศᯒࢆ㐍ࡵࡿᚲせࡀ࠶ࡿࠋࡉࡽ࡟ࠊᮏሗࡢᑐ㇟ࢧ

ᚋࡣ᩿⇕ᛶ⬟ࡀ㧗ࡃᬮ࡞ఫᏯࡢࢧࣥࣉࣝࢆᣑ඘ࡍࡿ࡜࡜ࡶ࡟ࠊ࢖

ࣥࣉࣝࡣఫᏯࡢ᩿⇕ᛶ⬟ࡀపࡃ෤Ꮨ࡟ᐮ෭࡞ࢧࣥࣉࣝࡀ኱༙ࢆ༨ࡵࠊ

࣋ࣥࢺࣄࢫࢺ࣮ࣜศᯒࡢ୰࡛ࡶㄪᩚኚᩘࢆྠ᫬࡟ᢞධࡍࡿࡇ࡜ࡀ࡛

ఫᏯෆࡀᬮ࡟ಖࡓࢀࡿࡇ࡜࡟ࡼࡿຠᯝ࡟㛵ࡋ࡚༑ศ࡟ゝཬ࡛ࡁࡓࡁࡿ Cox ẚ౛ࣁࢨ࣮ࢻศᯒ࡜࠸ࡗࡓከኚ㔞ゎᯒࢆᑟධࡋࠊせ௓ㆤㄆ࡜ࡣゝ࠸㞴࠸ࠋຍ࠼࡚ࠊᮏሗ࡛᥇⏝ࡋࡓ࢖࣋ࣥࢺࣄࢫࢺ࣮ࣜศᯒࡢ

ᐃࡉࢀࡿᖺ㱋࡟ᙳ㡪ࢆཬࡰࡋ࠺ࡿ௚ᅉᏊࢆ⥲ྜⓗ࡟⪃៖ࡋࡓୖ࡛ࠊ

─ 905 ─௓ㆤண㜵࡟᭷ຠ࡞ఫᏯᛶ⬟ࠊఫࡲ࠸᪉ࢆ᫂ࡽ࠿࡟ࡍࡿ┠ᣦࡍணᐃ࡛
࠶ࡿࠋࡓࡔࡋࠊᮏศᯒࡢ᮲௳タᐃ࡟ࡣㄢ㢟ࢆ᭷ࡍࡿࠋࡇࢀࡣࠊ࢖࣋
ࣥࢺࣄࢫࢺ࣮ࣜศᯒ࡟࠾ࡅࡿࢫࢱ࣮ࢺ᫬ⅬࡢఫᏯ➼ࡢ᝟ሗࡀ༑ศ࡟
཰㞟࡛ࡁ࡚࠸࡞࠸Ⅼ࡟࠶ࡿࠋࡇࡢㄢ㢟ࡢゎỴ࡟ࡣせ௓ㆤㄆᐃࡉࢀ࡚
࠸࡞࠸⪅ࢆᑐ㇟࡜ࡋࡓ㛗ᖺ࡟ࢃࡓࡿ๓ྥࡁࡢ㏣㊧ㄪᰝࡢᐇ᪋ࡀ᭷ຠ
࡛࠶ࡿ࡜⪃࠼ࡽࢀࠊࡑࡢ㝿࡟ࡣ⇕⎔ቃࡢᨵၿ࡟ಀࡿ௓ධ࣭㠀௓ධ࡟ࡼࡿ᳨ドࡶ࠶ࡾᚓࡿࠋࡇࢀࡽࡢ௒ᚋࡢⓎᒎ◊✲࡟ᮇᚅࡉࢀࡓ࠸ࠋ
ㅰ㎡ᮏ◊✲ࡢᐇ᪋࡟㝿ࡋከ኱࡞ࡈᨭ᥼ࢆ㡬࠸ࡓ⣽஭᫛ᏹᵝࠊᐇ࣭㉁ၥ⣬ㄪᰝ࡟ᚚ༠ຊ㡬࠸ࡓⓙࡉࡲ࡟῝⏒ࡢㅰពࢆ⾲ࡍࡿࠋࡲࡓࠊᾏሷ΅ᵝࠊ㧗ᒣ┤ேᵝࠊ኱ᶫ▱ెᵝࠊᮏከⱥ㔛ᵝ㸦ᙜ᫬៞᠕⩏ሿ኱Ꮫ኱Ꮫ㝔㸧࡟ࡣㄪᰝᐇ᪋࡟࠶ࡓࡾࡈຓゝ࣭ࡈᣦᑟࢆ㡬࠸ࡓࠋࡇࡇ࡟ឤㅰ
ࡢពࢆ⾲ࡍࡿࠋᑦࠊᮏ◊✲ࡣࠊཌ⏕ປാ┬⪁ேಖ೺஦ᴗ᥎㐍㈝➼⿵ຓ㔠ཷク◊✲㸦◊✲௦⾲⪅㸸ᫍ᪦஧㸧ࠊᩥ㒊⛉Ꮫ┬◊✲ᣐⅬᙧᡂ㈝➼⿵ຓ㔠㸦༤ኈㄢ⛬ᩍ⫱࣮ࣜࢹ࢕ࣥࢢࣉࣟࢢ࣒ࣛ㸧୪ࡧ࡟⛉Ꮫ◊✲㈝⿵ຓ㔠࣭ᇶ┙◊✲㸦A㸧㸦◊✲௦⾲⪅㸸ఀ㤶㈡ಇ἞ࠊㄢ㢟␒ྕ㸸
26249083㸧ࡢຓᡂࢆཷࡅᐇ᪋ࡋࡓࡶࡢ࡛࠶ࡿࠋ

Hypertension, Vol.28, pp.482-488, 2014.2
14) K Saeki, K Obayashi, J Iwamoto et al.㸸Stronger association of indoor

temperature than outdoor temperature with blood pressure in colder

months, Journal of Hypertension, Vol. 32, No. 8, pp.1582-1589, 2014.8
15) ᾏሷ΅, ఀ㤶㈡ಇ἞, ኱ሯ㑥᫂, Ᏻ⸨┿ኴᮁ㸸ಶேᅉᏊูࡢᐙᗞ⾑ᅽୖ᪼㔞࡟㛵ࡍࡿศᯒ㸫෤Ꮨࡢᐊෆ ⇕⎔ቃࡀ⾑ᅽ࡟ཬࡰࡍᙳ㡪ࡢᐇែㄪᰝ㸫,᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟, Vol.79, No.701, pp.571-577, 2014.7
16) ᾏሷ΅, ఀ㤶㈡ಇ἞, ኱ሯ㑥᫂, Ᏻ⸨┿ኴᮁ㸸࣐ࣝࢳࣞ࣋ࣝࣔࢹࣝ࡟ᇶ࡙
ࡃᐊ࡟ࡼࡿᐙᗞ⾑ᅽ࡬ࡢᙳ㡪㸫෤Ꮨࡢᐊෆ

⇕⎔ቃࡀ⾑ᅽ࡟ཬࡰࡍᙳ㡪ࡢ ᐇ ែ ㄪ ᰝ ࡑ ࡢ 2 㸫 , ᪥ ᮏ ᘓ ⠏ Ꮫ ఍ ⎔ ቃ ⣔ ㄽ ᩥ 㞟 , Vol.80, No.715,
pp.703-710, 2015.9
17) ᰗ⃝ᜨ, ఀ㤶㈡ಇ἞, Ᏻ⸨┿ኴᮁ ௚ 2 ྡ㸸ఫᏯࡢ ⇕⎔ቃཬࡧ᩿⇕ᛶ⬟
࡟ࡼࡿ㌟యάື࡬ࡢᙳ㡪, ᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟, Vol.80, No.716,
pp.985-992, 2015.10

18) Lindemann U, Oksa J, Skelton DA et al 㸸 Effect of cold indoor
environment on physical performance of older women living in thecommunity, Age and Ageing, Vol.43, No.4, pp.571-575, 2014.5
19) ᳃㑳ᜨ, 㒔⠏࿴௦, Ᏻᒸ⤢Ꮚ ௚ 2 ྡ㸸❆ࡢ᩿⇕ᨵಟࡀఫᏯࡢ

⇕⎔ቃ࡜㧗㱋⪅ࡢ⏕ά࠾ࡼࡧ೺ᗣ࡟ཬࡰࡍᙳ㡪࡟㛵ࡍࡿ◊✲, ᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟, Vol.79, No.706, pp.1061-1069, 2014.12

20) ୍⯡♫ᅋἲே ᪥ᮏࢧࢫࢸࢼࣈࣝᘓ⠏༠఍㸸CASBEE ೺ᗣࢳ࢙ࢵࢡࣜࢫ
ࢺ, 2011.7 [WEB ࢧ࢖ࢺ]http://www.ibec.or.jp/CASBEE/casbee_health/files/pamphlet.pdf
㸦2016.3.11 ཧ↷㸧21) ཌ⏕ປാ┬㸸せ௓ㆤㄆᐃ࡟ಀࡿἲ௧ [WEB ࢧ࢖ࢺ]ཧ⪃ᩥ⊩1) ෆ㛶ᗓ㸸ᖹᡂ 27 ᖺ∧㧗㱋♫఍ⓑ᭩㸦඲య∧㸧, pp.24-29, 2015.6 [WEB ࢧ࢖ࢺ]
http://www8.cao.go.jp/kourei/whitepaper/w-2015/zenbun/pdf/1s2s_3_2.pdf㸦2016.2.19 ཧ↷㸧2) ཌ⏕ປാ┬㸸௓ㆤண㜵࣐ࢽࣗ࢔ࣝ㸦ᨵゞ∧㸧, pp.1, 2012.3 [WEB ࢧ࢖ࢺ]http://www.mhlw.go.jp/topics/2009/05/dl/tp0501-1_01.pdf㸦2016.3.12 ཧ↷㸧3) ཌ⏕ປാ┬㸸ࠕ೺ᗣ᪥ᮏ 21ࠖᅜẸࡢ೺ᗣࡢቑ㐍ࡢ⥲ྜⓗ࡞᥎㐍ࢆᅗࡿࡓࡵ
ࡢᇶᮏⓗ࡞᪉㔪, pp.1, 2012.7 [WEB ࢧ࢖ࢺ]http://www.mhlw.go.jp/bunya/kenkou/dl/kenkounippon21_01.pdf
㸦2016.3.12 ཧ↷㸧4) ෆ㛶ᗓ㸸ᖹᡂ 27 ᖺ∧㧗㱋♫఍ⓑ᭩㸦඲య∧㸧, pp.19-23, 2015.6 [WEB ࢧ࢖ࢺ]
http://www8.cao.go.jp/kourei/whitepaper/w-2015/zenbun/pdf/1s2s_3_1.pdf㸦2015.3.12 ཧ↷㸧5) ⛅ᒣᘯᏊ㸸㛗ᑑ᫬௦ࡢ⛉Ꮫ࡜♫఍ࡢᵓ᝿, ⛉Ꮫ, Vol.81, No.1, ᒾἼ᭩ᗑ,20106) ྜྷ㔝༤, 㛗㇂ᕝව୍㸸㧗᩿⇕㧗ẼᐦఫᏯ࡟࠾ࡅࡿ⇕⎔ቃ≉ᛶ࡜ᒃఫ⪅ࡢ೺ᗣ࡟㛵ࡍࡿㄪᰝ, ᪥ᮏᘓ⠏Ꮫ఍ィ⏬⣔ㄽᩥ㞟, No.507, pp.13-19, 1998.5
7) ྜྷ㔝༤㸸ᐮ෭ᆅ࡟࠾ࡅࡿᒃఫ⎔ቃ, ᪥ᮏ⏕Ẽ㇟Ꮫ఍㞧ㄅ, Vol.34, No.1,
pp.23-30, 1997.4
8) 㛗㇂ᕝව୍㸸㧗᩿⇕㧗ẼᐦఫᏯࡢ೺ᗣᛶ, ᪥ᮏ㞷ᕤᏛ఍ㄅ, Vol.13, No.1,
pp.47-49, 19979) ⩚ᒣᗈᩥ, 㔩⃝⏤⣖, ᯇᮧு඾, ⳥⏣ᘯ㍤㸸Ẽ㇟᮲௳࣭ṚஸሙᡤࡀṚஸཎᅉ࡟୚࠼ࡿᙳ㡪, ཌ⏕ປാ⤫ィ༠఍ཌ⏕ࡢᣦᶆ, Vol.58, No.13, pp.1-6,
2011.1110) ఀ㤶㈡ಇ἞, Ụཱྀ㔛ె, ᮧୖ࿘୕ ௚ 5 ྡ㸸೺ᗣ⥔ᣢࡀࡶࡓࡽࡍ㛫᥋ⓗ౽┈㸦NEB㸧ࢆ⪃៖ࡋࡓఫᏯ᩿⇕ࡢᢞ㈨ホ౯, ᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟,
Vol.76, No.666, pp.735-740, 2011.8
11) ᕝஂಖಇ, ఀ㤶㈡ಇ἞, ᮧୖ࿘୕ ௚ 2 ྡ㸸ఫ⎔ቃࡀᒃఫ⪅ࡢ೺ᗣ⥔ᣢቑ㐍࡟୚࠼ࡿᙳ㡪࡟㛵ࡍࡿ◊✲㸫඲ᅜࡢᡞᘓఫᏯࡢ⎔ቃᛶ⬟࡜ᒃఫ⪅ࡢ೺ᗣ≧ែ࡟㛵ࡍࡿᐇែㄪᰝ㸫, ᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟, Vol.79, No.700,
pp.555-561, 2014.6
12) ෆ㛶ᗓ㸸ᖹᡂ 27 ᖺ∧㧗㱋♫఍ⓑ᭩㸦඲య∧㸧, p.26, 2015.6 [WEB ࢧ࢖ࢺ]
http://www8.cao.go.jp/kourei/whitepaper/w-2015/zenbun/pdf/1s2s_3_2.pdf㸦2016.2.19 ཧ↷㸧13) K Saeki, K Obayashi, J Iwamoto et al㸸The relationship between indoor,
outdoor and ambient temperatures and morning BP surges frominter-seasonally repeated measurements, Journal of Human─ 906 ─http://www.mhlw.go.jp/topics/kaigo/nintei/gaiyo4.html㸦2016.5.4 ཧ↷㸧22) ཌ⏕ປാ┬㸸බⓗ௓ㆤಖ㝤ไᗘࡢ⌧≧࡜௒ᚋࡢᙺ๭, p.19, 2016.2 [WEBࢧ࢖ࢺ]
http://www.mhlw.go.jp/file/06-Seisakujouhou-12300000-Roukenkyoku/2
20160kaigohokenntoha.pdf㸦2016.3.13 ཧ↷㸧23) 㧗ᰗ⤮㔛, ఀ㤶㈡ಇ἞, ᮧୖ࿘୕ ௚ 2 ྡ㸸೺ᗣ⥔ᣢቑ㐍࡟ྥࡅࡓఫ⎔ቃホ౯ࢶ࣮ࣝࡢ᭷ຠᛶࡢ᳨ド, ᪥ᮏᘓ⠏Ꮫ఍⎔ቃ⣔ㄽᩥ㞟, Vol.70, No.670,
pp.1101-1108, 2011.12

24) ᪥ᮏᘓ⠏Ꮫ఍⦅㸸㧗㱋⪅ࡢࡓࡵࡢᘓ⠏⎔ቃ, ᙲᅜ♫, p.58, 1994.1
25) ጧ⇩, 㱟᭷஧, 㤶ᕝ἞⨾㸸㧗㱋⪅⚟♴᪋タ࡟࠾ࡅࡿ ⇕⎔ቃ࡜฼⏝⪅ࡢᚰ⌮ ཯ ᛂ ࡟ 㛵 ࡍ ࡿ ◊ ✲ , ᪥ ᮏ ᘓ ⠏ Ꮫ ఍ ⎔ ቃ ⣔ ㄽ ᩥ 㞟 , Vol.73, No.624,
pp191-197, 2008.2

26) ୕㍯ဴ, ᯘ㞝ு㸸SPSS ࡟ࡼࡿᛂ⏝ከኚ㔞ゎᯒ, ࣮࣒࢜♫, pp.207-232,
2014.527) 㔜⮧᐀఑, బ⸨࣡࢝ࢼ, ෇ᒣၨྖ, ྜྷᒸᑦᩥ㸸㧗㱋⪅ࡢධᾎ୰✺↛Ṛ࡟㛵ࡍࡿㄪᰝ◊✲, ᪥ᮏᩆᛴ་Ꮫ఍㞧ㄅ, Vol.12, No.3, pp.109-120, 200128) ᯘౡỤ, ఀ㤶㈡ಇ἞, ᫍ᪦஧ ࡯࠿ 4 ྡ㸸⏕Ꮡศᯒ࡟ᇶ࡙ࡃఫᏯෆ

⇕⎔ቃ࡜⹫ᙅ㧗㱋⪅ࡢせ௓ㆤㄆᐃ࡜ࡢ㛵㐃, ᪥ᮏᘓ⠏Ꮫ఍኱఍Ꮫ⾡ㅮ₇᱾ᴫ㞟,⎔ቃᕤᏛϨ, pp.973-974, 2015.9
ὀὀ 1) ୍⯡࡟ࠊ࠶ࡿ೺ᗣ≧ែ࡛⏕άࡍࡿࡇ࡜ࡀᮇᚅࡉࢀࡿᖹᆒᮇ㛫ࡲࡓࡣࡑࡢ
ᣦᶆࡢ⥲⛠ࢆᣦࡍࠋ೺ᗣ᪥ᮏ 21㸦➨ 2 ḟ㸧࡛ࡣࠊࠕ೺ᗣୖࡢၥ㢟࡛᪥ᖖ⏕άࡀไ㝈ࡉࢀࡿࡇ࡜࡞ࡃ⏕ά࡛ࡁࡿᮇ㛫ࠖ࡜ᐃࡵࡽࢀ࡚࠸ࡿࠋᮏ◊✲࡛ࡣせᨭ᥼࣭せ௓ㆤㄆᐃࡉࢀࡓᖺ㱋ࢆ೺ᗣᑑ࿨࡜ࡋ࡚ᢅࡗࡓࠋ
ὀ 2) ⛅ᒣࡽࡣ㧗㱋⪅ࡢ᪥ᖖ⏕ά⮬❧ᗘࢆࠊ3=⮬❧ࠊ2㸻ࠕᡭẁⓗ᪥ᖖ⏕άືసࠖ࡟᥼ຓࡀᚲせࠊ1=ࠕᇶᮏⓗ᪥ᖖ⏕άືసࠖ࡟᥼ຓࡀᚲせࠊ0=Ṛஸ࡜ࡋ࡚ 4 ẁ㝵࡛ホ౯ࡋࡓࠋࠕᡭẁⓗ᪥ᖖືసࠖࡣࠊ᪥⏝ရࡢ㈙࠸≀ࢆࡍࡿࠊ㟁ヰࢆ࠿ࡅࡿࠊࣂࢫࡸ㟁㌴࡟஌ࡗ࡚እฟࡍࡿ࡞࡝ࡢືసࢆᣦࡍࠋ
ࠕᇶᮏⓗ᪥ᖖື
సࠖࡣ㢼࿅࡟ࡣ࠸ࡿࠊ▷࠸㊥㞳ࢆṌࡃࠊ㝵ẁࢆ 2㹼3 ẁୖࡀࡿ➼ࡢືసࢆᣦࡍࠋὀ 3) ་⒪࣭⚟♴ศ㔝࡛᥼ຓࢆ┠ⓗ࡜ࡋࡓ᝟ሗ཰㞟࡟࠾࠸࡚౑⏝ࡉࢀࡿࠊ฼⏝⪅ࡢᇶᮏࢹ࣮ࢱࢆࡲ࡜ࡵࡓ⏝⣬ࡢࡇ࡜ࠋὀ 4) ᮏ◊✲࡛ࡣᏛṔࢆ┤᥋ၥ࠺ࡇ࡜ࡣࡏࡎࠊാࡁጞࡵࡓᖺ㱋ࢆၥ࠺ࡇ࡜࡛ᑐ
㇟⪅ࡢᏛṔࢆ᥎ᐃࡋࡓࠋ
ࠕࠥ15 ṓࠖࡀ୰༞௨ୗࠊ
ࠕ16ࠥ19 ṓࠖࡀ㧗༞ࠊ
ࠕ20ṓࠥࠖࡀ኱༞௨ୖ࡟┦ᙜࡍࡿ࡜⪃࠼ࡽࢀࡿࠋὀ 5) ඲ 50 ၥ࡛ᵓᡂࡉࢀࠊ⮬Ꮿࡢ㒊ᒇ࣭ሙᡤࡈ࡜ࡢ೺ᗣ࡟㛵ࡍࡿ㡯┠࡟ࠊ㢖ᗘࢆࠕࡼࡃ࠶ࡿࠖ࠿ࡽࠕ඲ࡃ࡞࠸ࠖࡲ࡛ࡢ 4 ẁ㝵࡛ᅇ⟅ࡍࡿࡇ࡜࡛ࠊ⮬Ꮿࡢ೺ᗣ࡬ࡢᙳ㡪ࢆᚓⅬ໬ࡍࡿ㉁ၥ⚊ࠋὀ 6) ࣇ࢙࢖ࢫࢩ࣮ࢺࡢ᪤ Ṕࡣയ⑓ྡࡢグ㍕࡟㝈ࡽࢀ࡚࠾ࡾⓎ⑕ᖺ㱋࡟ࡘ࠸࡚ࡢࢹ࣮ࢱࡣ཰㞟࡛ࡁ࡞࠿ࡗࡓࠋࡼࡗ࡚ࠊ᪤ ࡢⓎ⏕ࡀせ௓ㆤ≧ែⓎ⏕ࡢ๓ᚋ࡝ࡕࡽ࡛࠶ࡿ࠿࡟ࡘ࠸࡚ࡣᢕᥱࡀᅔ㞴࡞≧ἣ࡛࠶ࡗࡓࠋࡑࡢࡓࡵࠊ
ᮏ◊✲࡛ࡣఫᏯෆ

⇕⎔ቃࡢᙳ㡪ࡀ☜ᐇ࡟Ꮡᅾࡋ࡞࠸ඛኳᛶࡢ⑌ᝈࢆ᭷ࡍ

ࡿࢧࣥࣉࣝࢆ㝖እࡍࡿ࡟࡜࡝ࡲࡗࡓࠋࡲࡓࠊࢹ࢖ࢧ࣮ࣅࢫ฼⏝㛤ጞ௨㝆ࡢ
യ⑓ࡢⓎ⏕࡟㛵ࡋ࡚ࡣ୍ᚊࡢグ㘓ࣇ࢛࣮࣐ࢵࢺࡀタࡅࡽࢀ࡚࠾ࡽࡎࠊࢹ࣮
ࢱࢆ୍ᚊ࡟ᢅ࠺ࡇ࡜ࡀ㞴ࡋ࠸≧ἣ࡛࠶ࡗࡓࠋ
ὀ 7) ᪥ᮏ⫧‶Ꮫ఍ࡢᐃࡵࡓᇶ‽࡟๎ࡾ BMI18.5 ᮍ‶ࢆࠕపయ㔜ࠖࠊ18.5 ௨ὀ 8) 2 ⩌ࡢẚ㍑ࡣ➼ศᩓࡢ᳨ᐃ㸦F ᳨ᐃ㸧ࢆᐇ᪋ࡋࠊ➼ศᩓࡀ௬ᐃࡉࢀࡓሙ
ྜ t ᳨ᐃࢆᐇ᪋ࡋࡓࠋከ㔜ẚ㍑ࡣ➼ศᩓࡀ௬ᐃࡉࢀࢀࡤ Shuffe ἲ࡟ࡼࡾࠊ

௬ᐃࡉࢀ࡞ࡅࢀࡤ Games-Howel ἲ࡟ࡼࡾẚ㍑ࡋࡓࠋ

ὀ 9) ᖹᆒᐊ ཬࡧᖹᆒ‵ᗘࡣᒃ㛫ࠊᗯୗࠊ⬺⾰ᡤ࡟㛵ࡋ࡚ࡣ㉁ၥ⣬ㄪᰝ࡟ࡼࡗ࡚ᢕᥱࡋࡓᅾᏯ࠿ࡘ㉳ᗋࡋ࡚࠸ࡿ᫬㛫ᖏࡢᖹᆒࠊᐷᐊࡣᑵᐷ᫬㛫ᖏࡢᖹᆒ࡜ࡋࡓࠋ

ୖ 25.0 ᮍ‶ࢆࠕᬑ㏻య㔜ࠖ
ࠊ25.0 ௨ୖࢆࠕ⫧‶ࠖ࡜ࡋࡓࠋ

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EVENT HISTORY ANALYSIS OF INDOOR THERMAL ENVIRONMENTEVENT HISTORYOF INDOORENVIRONMENT
AND ANALYSISCARE PREVENTIONOFTHERMALRESIDENTS
AND CARE PREVENTION OF RESIDENTS
A field survey on the effect of winter indoor thermal environment on care requirements

A field survey on the effect of winter indoor thermal environment on care requirements

Yukie HAYASHI*, Toshiharu IKAGA**, Tanji HOSHI*** and Shintaro ANDO****
Yukie HAYASHI ＊, Toshiharu IKAGA ＊＊, Tanji HOSHI ＊＊＊＊＊＊＊* Graduate Student, Graduate
School ofANDO
Science andTechnology, Keio Univ.
and Shintaro** Prof., Faculty of Science and Technology, Keio Univ., Dr. Eng.

Prof.
Emeritus,
Tokyo
Metropolitan
Univ., M.D.Keio Univ.
Grad. ***
Stud.,
Graduate
Schoolof Scienceand Technology,＊＊
Prof., Faculty of Science and Technology, Keio Univ., Dr.Eng.
**** Lecturer, Faculty of Environmental Engineering, The Univ. of Kitakyushu, Dr. Eng.
Emeritus Prof., Faculty of Urban Environmental Sciences, Tokyo Metropolitan Univ., M.D.
＊＊＊＊
Lect., Faculty of Environmental Engineering, The Univ. of Kitakyushu, Dr.Eng.
＊＊＊＊

As ageing of the population progresses, long-term care becomes a more pressing health issue. In Japan, the gap
between healthy life expectancy and average life span is expected to grow; therefore, it is necessary to extend healthy
life expectancy while minimising the need for long-term care. The effect of indoor air temperature on the health of theelderly has recently attracted attention. Thus, in this study, we clarify the relationship between the indoor thermal
environment and the care requirements of the elderly.
This research was conducted as a field study comprising actual measurements of indoor thermal environment,
questionnaire surveys, and data collection from face sheets in 2014. The study area was Senri New Town, Osaka
Prefecture, Japan. Participants were elderly residents (65–91 years) who were using a day service facility. The indoor
air temperature 1.1 m above the floor was measured over approximately 2 weeks in the living room, bedroom,
corridor, and dressing room at 5-min intervals. Relative humidity was also measured in the living room and bedroom
concurrently. Questionnaire surveys regarding personal factors and housing were distributed. Data about healthconditions and diseases requiring care were also collected. Data about care level, date of care certification, and carecertification period were collected from long-term care insurance cards.
Regarding the frequency of feeling cold in each of the rooms, participants who answered “1) Frequently” and “2)Sometimes” were assigned to the high-frequency group, whereas those who answered “3) Seldom” and “4) Never”
were assigned to the low-frequency group. Mean living room and dressing room temperatures were significantly
lower in the high-frequency group than in the low-frequency group (p < 0.01). Mean room temperatures were also
compared between houses with different insulation performance. The mean room temperatures in the corridors anddressing rooms were lowest for “Pre-1980 standards” households, and highest for “Over 1992 standards”.
The results describe the differences in room temperature between the frequency of feeling cold in dressing rooms,
which is affected by low insulation performance, and verifies the association between indoor thermal environment
and long-term care through subjective evaluation. The Kaplan-Meier (KM) method was used to analyse the speed ofcertification for the participants’ long-term care needs. The age at which half of the group was certificated was 76
years in the high-frequency group and 80 years in the low-frequency group (p < 0.05). The chi-square test showedthat there were no significant differences in personal factors between the two groups, confirming that the result in
KM method could be explained by the difference in the thermal environment in the dressing rooms.
Our results suggest that it is necessary to maintain an appropriate indoor thermal environment to prevent theneed for long-term care, especially the indoor thermal environment in rooms other than the living room, such as the
dressing room. The results of this study are expected to promote improvements in the indoor thermal environment,
thereby contributing to care prevention among frail elderly people.
（2016 年 5 月 5 日原稿受理，2016 年 8 月 10 日採用決定）

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