Linking Evidence to Health Policy for the Ageing:

IFA 11th Global Conference on Ageing | 28 May – 1 June, 2012 Prague, Czech Republic1 |

Linking Evidence to Health Policy for the Ageing:

A Social Health Atlas of Older Adults in a Major Japanese City

Megumi Kano,1 Jimpei Misawa,2 Kayo Suzuki,3 Masataka Nakagawa,3 Katsunori Kondo3

1WHO Centre for Health Development, Kobe, Japan; 2Rikkyo University, Tokyo, Japan;

3 Center for Well-being and Society, Nihon Fukushi University, Nagoya, Japan


Japan’s achievements in longevity

Life expectancy at birth– 86 yrs for women, 80 yrs for men

Healthy life expectancy at age 60– 21.7 yrs for women, 17.5 yrs for men

Key contributing factors: – Health system and health services– Social and physical environment– Health behaviour– Genetics


The demographics of ageing in Japan


RAPID ageing


Key Challenges

Ageing of the urban population

Dwindling resource base

Growing income inequalities health inequalities?

“Ageing in Place”

Lack of data to enable evidence-based policy and practice, especially at the local government level


Project Objectives

To establish a mechanism for integrating research into policy and programme development to promote elderly health and wellbeing in a major metropolitan area of Japan

To build the epidemiological evidence base on the broader determinants of health and wellbeing among elderly residents in rapidly ageing urban areas

To empower local stakeholders to create healthy conditions in which people live, work, and age


Main Project Partners

City of Kobe: Public Health and Welfare Bureau, Health Division, Long Term Care Insurance Unit (Kobe, Japan)

Centre for Well-being and Society, Nihon Fukushi University (Nagoya, Japan) and the JAGES Research Group

WHO Centre for Health Development (Kobe, Japan)

Common interests in urban health, health equity assessment, social determinants of health, and evidence-based policy/programme development


Japan Gerontological Evaluation Study (JAGES)

One of the few population-based social epidemiological gerontological surveys in Japan

Conducted in 1999, 2003/4, 2006/7, 2010/11

2010/11 included 112,123 individuals across 31 municipalities in 12 prefectures

Kobe City was among the first few major metropolitan areas to join this study in 2010/11


Survey Items

Health status indicators: self-rated health, chronic conditions, health behavior, oral health, nutrition/diet, tobacco, alcohol, ADL/IADL, etc

Psychological indicators: depression, subjective well-being, etc

Social indicators: social support, social capital, social participation

Socioeconomic status indicators: income, education, relative deprivation, pension, etc

Environmental indicators: road safety, parks and recreation, accessibility, etc


JAGES Survey: Kobe

Kobe City has the sixth largest population in Japan and a significant proportion of elderly residents (20% in 2005)

It is a “government-decreed city”

Representative sample of 15,000 independent, community-dwelling elderly residents aged 65 years or older

– 9,873 responses (66% response rate)– 9,328 valid responses

Self-administered mail survey conducted between December 2011 and February 2012


Kobe sample characteristics

Age (years)65-7475-8485-9495-99

56.3%37.7%5.8%0.2%

SexMale

Female45.2%54.8%

Equivalent household income groupLow (<2 million JPY)

Middle (2-4 million JPY)High (>4 million JPY)

43.6%33.9%8.4%

Household compositionLone elderly

Elderly coupleOther

23.3%44.8%31.9%

IFA 11th Global Conference on Ageing | 28 May – 1 June, 2012 Prague, Czech Republic12 |柏市名古屋

市知多市東浦町大府市半田市西尾市碧南市神戸市吉良町美瑛町東海市度会町武豊町一色町幡豆町高梁市十和田市

阿久比町常滑市美浜町岩沼市中央市東神楽

町十津川

村松浦市南知多町東川町南城市今帰仁

村全体60%

65%

70%

75%

80%

85%

90%

87.2

%

83.5

%

82.8

%

82.7

%

82.1

%

81.4

%

80.8

%

80.5

%

80.3

%

80.2

%

79.7

%

79.5

%

79.4

%

78.8

%

78.2

%

78.2

%

78.2

%

78.0

%

78.0

%

77.9

%

77.6

%

77.2

%

77.1

%

76.7

%

76.1

%

75.9

%

75.2

%

74.0

%

72.8

%

67.6

%

79.2

%

Prop

ortio

n re

porti

ng "

very

goo

d" o

r "so

mew

hat g

ood"

hea

lth

Self-rated health: “Very/Somewhat good”

KobeMean

Nagoya


Income inequality

柏市東浦町知多市武豊町大府市東海市阿久比町神戸市名古屋

市常滑市岩沼市東神楽町美瑛町半田市西尾市吉良町美浜町中央市東川町松浦市碧南市度会町幡豆町十和田

市一色町南城市十津川村高梁市南知多

町今帰仁

村全体0.0

0.1

0.2

0.3

0.4

0.5

0.32

9

0.34

2

0.34

9

0.35

2

0.35

6

0.35

6

0.35

9

0.36

3

0.36

5

0.37

5

0.37

5

0.38

1

0.38

3

0.38

5

0.38

8

0.39

8

0.39

8

0.40

1

0.40

5

0.40

5

0.40

5

0.40

9

0.41

1

0.41

5

0.41

7

0.41

8

0.42

1

0.42

20.43

8

0.47

6

0.39

4

Gin

i coe

ffici

ent

Kobe

Gini coefficient for total population = 0.329


Physical environment: Parks and pedestrian paths

名古屋市神戸市柏市美瑛町東海市知多市大府市東川町東浦町碧南市半田市東神楽

町中央市幡豆町阿久比町武豊町吉良町十和田

市度会町美浜町岩沼市南城市松浦市南知多町

今帰仁村西尾市常滑市高梁市一色町十津川

村全体20%

30%

40%

50%

60%

70%

80%

90%

100%

85.2

%

85.1

%

82.5

%

81.7

%

81.2

%

79.8

%

79.7

%

78.4

%

78.3

%

77.9

%

75.3

%

72.7

%

72.6

%

71.9

%

71.1

%

69.3

%

69.1

%

68.4

%

67.9

%

67.4

%

66.8

%

66.6

%

65.6

%

65.5

%

64.1

%

63.6

%

63.6

%

53.3

%

50.8

%

38.7

%

71.9

%

Ther

e ar

e pa

rks

and

pede

stria

n pa

ths

good

for w

alki

ng a

nd e

xerc

isin

g

Kobe


Social-physical environment: Places to visit for a casual drop in

今帰仁村南城市東川町度会町東神楽

町十津川

村美瑛町幡豆町碧南市高梁市南知多町松浦市吉良町東浦町中央市大府市半田市柏市十和田

市西尾市一色町岩沼市美浜町東海市知多市武豊町神戸市阿久比町常滑市名古屋

市全体0%

10%

20%

30%

40%

50%

60%

70%

62.3

%

58.5

%

56.8

%

55.5

%

55.3

%

51.2

%

51.0

%

50.0

%

49.3

%

48.5

%

46.9

%

46.8

%

46.4

%

45.5

%

45.2

%

43.4

%

43.2

%

42.2

%

42.0

%

41.8

%

40.7

%

40.6

%

40.6

%

39.6

%

39.0

%

37.7

%

37.4

%

36.9

%

36.6

%

35.6

%

42.9

%

Ther

e ar

e ho

mes

or f

acili

ties

whe

re I

can

casu

ally

dro

p in

Kobe


Social capital: Trust in the community

今帰仁村南城市十津川

村松浦市幡豆町吉良町一色町西尾市高梁市南知多町碧南市柏市東川町美瑛町知多市常滑市阿久比

町度会町大府市東浦町美浜町東神楽町中央市武豊町十和田

市名古屋

市東海市岩沼市神戸市全体40%

50%

60%

70%

80%

90%

100%

88.3

%

78.9

%

78.8

%

78.6

%

78.4

%

78.2

%

77.5

%

76.1

%

76.1

%

75.5

%

74.6

%

73.8

%

73.7

%

73.4

%

73.3

%

72.5

%

72.2

%

72.2

%

72.1

%

71.9

%

71.7

%

71.1

%

70.9

%

69.3

%

69.0

%

68.0

%

67.9

%

67.7

%

67.4

%

72.4

%

Perc

eptio

n th

at p

eopl

e in

the

com

mun

ity c

an b

e tru

sted

(%)

Kobe


Determinants of health*Ages 65-74 only

Prevalence of low BM

I <18.5

Trust in the community Coefficient of correlation=-.539

Ecological analysis at the municipality level

0%

20%

40%

60%

80%

0% 20% 40% 60%

r=.568

この３年間で地域住民の活動や交流が衰退したと感じた人の割合

閉じこもり者の割合

Prevalence of social isolation

Multilevel analysis at the sub-municipality level

Sense of decline in community activities and relationships in past 3 years

Coefficient of correlation=.568


Small-area data mappingHas not received health

check-up in the past year (%)

Goes out less than once a week(%)

Geriatric Depression Scale score

*)Only among >=75(

Had a fall in the past year(%)


Interactive data mappinghttp://www.doctoral.sakura.ne.jp/WebAtlas/Kihonchecklist/Single/kinki/atlas.html

http://www.doctoral.sakura.ne.jp/WebAtlas/Kihonchecklist/Single/kinki/atlas.html


Conclusions

Older adults in large urban areas may feel healthier and benefit from better infrastructure and economy, but may experience poorer social well-being compared to smaller, more rural municipalities

Multilevel analysis confirmed some of the correlations between neighbourhood-level social factors and health indicators

Systematic collection, mapping, and analysis of social and health data by small geographic units are crucial to develop policies and programmes that are responsive to the geographically non-uniform needs of the local elderly population

Technological innovations have made interactive data mapping a feasible and effective tool for both researchers and policy-makers

Linking Evidence to Health Policy for the Ageing:

Documents

urban health

health policy

elderly health

health division

health servicessocial

public health

health system

health development kobe