(2024) 24:37
Asano et al. BMC Emergency Medicine
https://doi.org/10.1186/s12873-024-00953-8

BMC Emergency Medicine

Open Access

RESEARCH

Association between social support
and ambulance use among older people
in Japan: an empirical cross‑sectional study
Yotaro Asano1, Tomo Takasugi1,2, Keiko Ueno3, Naoki Kondo3, Atsuto Yoshino4 and Toshiyuki Ojima1*

Abstract
Background Ambulance service demand and utilization are increasing worldwide. To address this issue, the factorsthat affect ambulance use must be identified. Few studies have examined factors that can intervene and thus reduce
the frequency of ambulance use. This study aimed to examine the association between social support and ambulance use among older adults in Japan. We hypothesize that social support is associated with reduced ambulance use.
Methods This cross-sectional study was conducted as part of the Japan Gerontological Evaluation Study. In December 2019 and January 2020, we collaborated with individuals aged 65 years or above with no long-term care needs.
A total of 24,581 participants were included in the analysis. The objective and explanatory variables were ambulance
use and social support, respectively. Binomial regression analysis was used to calculate the odds ratios (ORs) and 95%
confidence intervals (CIs).
Results Social support was associated with ambulance use. People who had no one to listen to their complaints
or worries were significantly more likely to use ambulance services than those who did (OR [95% CI] = 1.26 [1.03–
1.53]). People with no one to take care of them when they were ill were also significantly more likely to use ambulance services than those who had someone to provide care (1.15 [1.01–1.31]). Moreover, the results of binomial logistic regression analysis indicated that individuals who called an ambulance but were not hospitalized had significantly
lower social support compared to those who did not call an ambulance.
Conclusions The results suggest that the presence and quality of social support play a significant role in ambulance
use among older adults in Japan. Our findings can help policymakers to plan and implement strategies for reducing
the burden on emergency medical care.
Keywords Social support, Ambulance, Emergency department, Japan Gerontological Evaluation Study, Family
support, Social prescribing*Correspondence:
Toshiyuki Ojima
ojima@hama-med.ac.jp
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Asano et al. BMC Emergency Medicine(2024) 24:37

BackgroundIn emergency medicine, a worldwide increase in the
demand for ambulances and ambulance utilization has
become a critical issue [1–7]. For example, the demand
for ambulances in the United Kingdom increased byapproximately 4% per year for almost a decade from2010 [1]. Ambulance utilization is particularly highamong older adults who use the service for relatively
non-urgent problems because they have multiple healthproblems [8]. Currently, there is no effective solution
for this issue [3], which carries individual and societal costs. For example, in the United States, the costsof ambulance services are charged to the patients orinsurance companies; while in Japan, anyone can use
ambulance services at no financial charge by dialing
119. In other words, local governments defray the fulloperational costs in Japan and provide ambulance use
as a public service. Therefore, as the demand for ambulance services increases, the cost to local governments
also increases [9]. Therefore, it is important to identify the factors related to ambulance utilization amongolder adults.
Situations in which patients use the ambulance but are
not admitted to the hospital include mild medical conditions in which the patients think an ambulance is needed,
but medical staff consider the call for an ambulance
inappropriate; these situations indicate that patients
often have difficulty determining what circumstances
require calling an ambulance. For example, some studies have reported that non-urgent medical visits may
cause crowding in emergency departments [10]. Therefore, clarifying the factors of ambulance use that do not
require medical intervention may help reduce the overall
demand and, thereby, reduce congestion at emergency
departments.
Older adults, males, and people who have a lower
annual income have been associated with a high frequency of ambulance use [2, 5, 11–15]. For example,
older adults are associated with frequent ambulance use
because they are more likely to have serious diseases,
such as cerebral or cardiovascular diseases [13]. However,we think that designing interventions to address factors
other than annual income is challenging and the welfare
system may impact income. Further, the impact of welfare system takes time and is limited.
To the best of our knowledge, few studies have examined factors that can intervene and thus reduce the frequency of ambulance use among older adults. In thiscontext, the relationship between social support andambulance use is important. In one study, people whoarrived at the hospital by ambulance had significantly
lower social support than those who arrived by theirown means of transport [16]; however, as that study

Page 2 of 11

was conducted at a single institution, the sample size
was limited [16].
Therefore, this study aimed to examine the association between social support and ambulance use amongolder adults in Japan. We hypothesize that social support is associated with reduced ambulance use amongolder people in Japan.

Methods
Study settingThis study was designed as a cross-sectional study. This
research was conducted as a part of the Japan Gerontological Evaluation Study (JAGES). The main objectivesof JAGES are to clarify health disparities, directions forcare prevention strategies and the social determinantsof health among people over 65 years old. The survey
was conducted in cooperation with local governmentsthat identified with the JAGES objectives and offered
to cooperate. The JAGES questionnaire is based on thenational daily living area needs assessment data. Whileusing the data, experts in each field consulted with eachother. They added scales whose reliability and validity
were confirmed or added items if they were yet to be
developed. The survey items were set from multiple
perspectives, including physical, psychological, andsocial items. The JAGES questionnaire is continuously
being revised based on the JAGES’s knowledge from theprevious studies [17, 18].
The JAGES collaborated with municipal governments
and mailed questionnaires to 345,356 communitydwelling people aged 65 years or older without longterm care needs. The selection of the respondents was
randomized. The participants were selected from 64
municipalities, including metropolitan, urban, semiurban, and rural areas in 24 prefectures in Japan, from
Hokkaido (the northernmost prefecture in Japan) to
Kyushu (the southernmost region in Japan) (Supplemental Fig. 1). The sampling of participants for the
JAGES survey was done at the municipal level and was
randomized. The sampling frame was based on a list ofolder people (65 years or older), obtained from either
long-term care insurance or the basic resident register,whichever was easier for the municipality to use. The
JAGES questionnaire was developed from June 2018 to
October 2019. Questionnaire distribution, follow-up,
and data collection were conducted from November
2019 to January 2020.
To increase the response rate, JAGES used techniquessuch as call center placement and distribution of thankyou reminder letters. As an incentive, the researchers
shared the results of data analysis with the municipality
and residents.

Asano et al. BMC Emergency Medicine(2024) 24:37

Participants

Figure 1 shows the process of participant selection in this study. A total of 240,889 individuals from64 municipalities responded to the questionnaire(response rate: 69.8%, range: 54.4–89.8%). One-eighthof the participants (n = 45,974) were randomly selected,
and a questionnaire containing items about the frequency of ambulance use was administered. A totalof 31,771 people subsequently responded, and 24,581
were included in the analysis; 7190 were excluded due
to failing to provide informed consent, requiring longterm care for daily living, and omitting basic information such as sex and age. This study was approved by
the Ethics Committee at the National Center for Geriatrics and Gerontology in Japan (approval number:
1274–2; date: December 18, 2020), at Chiba University(approval number: 3442; date: December 11, 2019),
and at Japan Gerontological Evaluation and ResearchInstitute (approval number: 2019–01; date: October 10,

Fig. 1 Flow of participants during the study

Page 3 of 112020) and was performed in accordance with the Declaration of Helsinki.
All participants were informed that participation in thisstudy was voluntary and that completing the questionnaire, selecting the checkbox for approval, and returning
it by mail would indicate their consent to participate.
Measures
Objective variable

Two outcomes were used in the binomial logistic regression analyses. The first outcome was “whether or not
the participant used an ambulance “ [19]. The second
outcome was “whether or not” the participant was hospitalized after using an ambulance. “ As noted in the
introduction to this study, we developed the outcomethat participants who used ambulances but were nothospitalized are those considered “unnecessary use“
from view of medical staff. The following questions wereused to determine participants’ ambulance use and theAsano et al. BMC Emergency Medicine(2024) 24:37

number of hospitalizations: “Have you called an ambulance for yourself or had someone call one for you in thepast year? “and “How many times have you been hospitalized after visiting a medical facility by ambulance? ““Participants answered each of these questions by selecting
one of the five categories that apply to them (1–3 times,
4–6 times, 7–9 times, ≥ 10 times, or never). We dichotomized their response of ambulance call and hospitalization after ambulance transport into binary variables thatexhibited never (zero times), or one or more times.
Explanatory variable

Participants ‘social support was examined using the following four questions: “Is there someone who listens toyour worries and complaints? ““Do you have someone
whose worries and complaints you listen to? ““Is there
someone who takes care of you when you fall ill for a few
days? “and “Do you have someone who you take care ofwhen they fall ill for a few days? “ [20].
Participants responded to these questions with multiple answers: spouse, children living together, children
living separately, siblings/relatives/parents/grandchildren, neighbors, friends, and none. For the data analysis, we categorized the responses into three categories:“family” (spouse, children living together, children living
separately, and siblings /relatives/parents/grandchildren);“neighbors/friends” (neighborhood and friends); “none”.
Covariates

Participants were categorized by age (65–69, 70–74,
75–79, 80–84, ≥ 85 years), sex (men, women), years ofeducation (< 6, 6–9, 10–12, ≥ 13 years), marital status(yes: currently married, no: not currently married) andself-rated health status (good, bad). Annual equivalent
income was calculated by dividing household income by
the square root of the number of household members
and was divided into three groups (≥ 4 million yen, 2–4
million yen, or < 2 million yen per year; 1 dollar = 110 yen
in 2019) [21].
Data analysis

We described the characteristics of all the study participants for three groups. Group 1: people who never called
an ambulance. Group 2: people who called an ambulance
at least once but were not hospitalized after ambulancetransport. Group 3: people who called an ambulance atleast once and were hospitalized at least once after ambulance transport [19]. We described the characteristics offrequent ambulance users (e.g. ≥ 10 times, 4–6 times,
7–9 times) of this study.
We conducted a binomial logistic regression analysis to examine the relationship between social support
and ambulance use. First, odds ratios (ORs) and 95%

Page 4 of 11

confidence intervals (CIs) were calculated for people who
had never called an ambulance (Group 1), as opposed tothose who had called an ambulance at least once (Groups
2 and 3), to determine the characteristics of peopleusing ambulances. Second, ORs and 95% CIs were also
calculated for people who had never called an ambulance (Group 1), as opposed to people who had called
an ambulance but were not hospitalized after ambulancetransport (Group 2). The aim of this analysis was to clarify the use of ambulances for mild conditions or cases inwhich patients thought ambulance service was necessary
but seemed unnecessary from the medical personnels’
perspective.
For both analyses, the following three models wereapplied: Model 1 included social support as a covariate;
Model 2 included Model 1 and sex and age; and Model
3 included Model 2 plus health status, marital status,
equivalent annual income, and years of education. In themultivariate analyses reported in Tables 2 and 3, multicollinearity was checked using variance inflation factors.
Similarly, the model goodness of fit and discriminantability was checked with the Hosmer-Lemeshow test andc-statistic, respectively.
For annual income, a missing-value category was created. For all the other variables, data with missing values were excluded from the analysis. p-value < 0.05 wasinterpreted as statistically significant for all analyses. The
analyses were conducted using IBM SPSS Statistics for
Windows, version 26.0 (IBM Corp., Tokyo, Japan).

Results
Table 1 summarizes the descriptive data on ambulanceuse. Being male, being older, having poorer self-rated
health, and having lower income were associated withhospitalization after ambulance use. Having fewer yearsof education and having no spouse were also associated with frequent ambulance use. Being older, having alower income, and lacking social support were associatedwith hospitalization after ambulance use (Supplemental
Table 1).
In the analysis comparing Group 1 with Groups 2 and3, people who had no one who could attend to them forcomplaints or worries were more likely to make more
ambulance calls (in Model 3: OR [95% CI]: 1.26 [1.03–
1.53]) (Table 2). People who had no one who could takecare of them during an illness were significantly associated with more ambulance use than those who had aperson who could take care of them (1.15 [1.01–1.31]).
Overall, people whose family members listened to theircomplaints were less likely to call an ambulance thanthose whose family members did not (0.83 [0.71–0.96]).
Additionally, individuals who listened to their family members’ complaints or worries also tended to beAsano et al. BMC Emergency Medicine(2024) 24:37

Page 5 of 11

Table 1 Characteristics of study participants
Totaln
Gender%People who
did not call an
ambulance

People whocalled ambulance,
but were nothospitalized

People whocalled an
ambulance
and were
hospitalized

n

n

n

%

%

%

21,471

Female11,19152.1

10,499

52.6

341

50.0

350

41.5

Male

10,280

47.9

9446

47.4

342

50.0

493

58.5

Age (years)

21,47165 ~ 69

5155

24.0

4922

24.7

117

17.1

116

13.8

70 ~ 74

6383

29.7

6016

30.1

164

24.0

203

24.1

75 ~ 79

5162

24.0

4768

23.9

175

25.6

219

26.0

80 ~ 84

3135

14.6

2820

14.1

131

19.1

184

21.8

1636

7.6

1419

7.1

96

14.1

121

14.4

≧85
Years of education

21,068

≧13

6486

30.8

6113

31.2

176

26.1

197

24.3

10 ~ 12

9035

42.9

8423

43.0

271

40.2

341

42.1

6~9

5233

24.8

4765

24.3

214

31.8

254

31.4

<6

143

0.7

126

0.6

7

1.0

10

1.2

171

0.8

157

0.8

6

0.9

8

1.0

OthersSelf-rated health status

21,149Good

18,26886.4

172,233

98.6

499

74.3

546

66.7

Poor

2881

13.6

2435

1.4

173

25.7

273

33.4

Marital status (currently married)

21,150Yes

15,502

73.3

14,441

73.5

463

68.7

598

73.3

No

5483

26.0

5073

25.8

201

29.8

209

25.6

165

0.8

146

0.7

10

1.5

9

1.1

OthersAnnual equivalent income

21,471≧4 million

2200

10.2

2111

10.6

52

76.1

57

6.8

2 million~ < 4 million

7464

34.8

7006

35.1

228

33.4

230

27.3

< 2 million

9158

42.7

8416

42.2

314

46.0

428

50.8

non-responsive

2629

12.2

2412

12.1

89

13.0

128

15.2

About people around you who listen to your complaints
Family members listen to your complaints

21,122

Yes

18,02685.3

16,812

85.6

539

81.4

675

82.4

No

3096

14.7

2829

14.4

123

18.6

144

17.6

Neighbors or friends listen to your complaints

21,122

Yes

10,67050.5

10,007

51.0

319

48.2

344

42.0

No

10,452

49.5

9634

49.0

343

51.8

475

58.0

There is no one to listen to your complaints

21,122

Yes

1028

4.9

931

4.7

54

8.2

43

5.3

No

20,09495.1

18,710

95.3

608

91.8

776

94.7

About people around you whose complaints you listen to
You listen to your family’s complaints

20,987

Yes

16,99181.0

15,874

81.2

500

75.6

617

77.2

No

3996

19.0

3653

18.8

161

24.4

182

22.8

You listen to neighboors’ or friends’ complaints

20,987

Yes

10,825

51.6

10,180

52.1

316

47.8

329

41.1

No

10,162

48.4

9347

47.9

345

52.2

470

58.9

You have no one to listen to his or her complaints

20,987

Asano et al. BMC Emergency Medicine(2024) 24:37

Page 6 of 11

Table 1 (continued)
Total

n

%

People who
did not call an
ambulance

People whocalled ambulance,
but were nothospitalized

People whocalled an
ambulance
and were
hospitalized

n

n

n

%

%

%

Yes

1326

6.3

1183

6.1

71

10.7

72

9.0

No

19,661

93.7

18,334

93.9

590

89.3

727

91.0

About pople who take care of you when you fall ill
Family members take care of you

21,141

Yes

19,69393.1

18,350

93.4

601

90.0

742

90.1

No

1448

6.9

1303

6.6

68

10.0

77

9.9

Neighbors or friends take care of you

21,141

Yes

1594

7.5

1461

7.4

54

8.1

79

9.6

No

19,54792.5

18,192

92.6

615

91.9

740

90.4

There is no one who takes care of you

21,141

Yes

1078

5.1

977

5.0

50

7.5

51

6.2

No

20,063

94.9

18,676

95.0

619

91.5

368

93.8

About people who you take care of when they fall ill
You take care of family

21,141

Yes

15,68774.2

14,675

74.7

459

68.6

553

65.1

No

5080

25.8

4656

25.3

187

31.4

237

34.9

You take care of neighbors or friends

21,141

Yes

1773

8.4

1648

8.4

51

76.2

74

9.0

No

18,994

91.6

17,683

91.6

595

23.8

716

91.0

There is no one who you take care of

21,141

Yes

4600

21.8

4216

21.5

169

25.3

215

26.3

No

16,16788.2

15,115

78.5

477

74.7

575

73.7

less likely to call an ambulance than those who did not(0.85 [0.75–0.93]). Moreover, people who have family
members to care of them when they are ill called ambulances less frequently compared to those who did not(0.73 [0.60–0.90]). However, people who were cared forby neighbors/friends were considerably more likely toavail themselves of ambulance services than those who
were not (1.34 [1.10–1.63]). People who took care of their
ill family members were significantly less likely to callambulances than those who did not (0.81 [0.72–0.91]).
In the analysis comparing Group 1 with Group 2, social
support was significantly lower among those who called
an ambulance but who were not hospitalized after ambulance transport than those who did not call an ambulance(Table 3). In Model 3, the most frequent ambulance use
was observed among individuals who did not attend toanyone’s’ complaints (OR [95% CI]: 1.46 [1.11–1.91]),
those who had no one who listened to their complaints(1.58 [1.16–2.14], and those who had no one to take careof them when ill (1.39 [1.01–1.92]). These results wereconfirmed after adjusting for sex, age, health status, yearsof education, marital status, and income level.

In the multivariate analyses reported in Tables 2 and 3,
the results of the multicollinearity check using the variance inflation factor show that no multicollinearity wasobserved because all variables in models 2 and 3 had a
VIF less than 10 (Supplemental Table 2). The results ofthe Hosmer-Lemeshow test show that most of the variables in Models 2 and 3 had p-values greater than 0.05,
and in addition, the model fit was good, considering thepositive discrimination rate. The c-statistic shows that
fit rates of most of the models were poor (Supplemental
Tables 3 and 4).

Discussion
Older people who had never called an ambulance weremore likely to receive family and social support, suchas listening to someone’s’ complaints or taking care ofsomeone when they get ill, than those who had called
an ambulance at least once. Older people who had
never called an ambulance were more likely to receive
family support (except for taking care of family) andsocial support, having their complaints listened to,listening to someone’s’ complaints, or being cared forCategories

There is no one who you take care of

3
1.30

1.01

0.67 to 0.88

1.16 to 1.47

0.84 to 1.22

0.68 to 0.86

1.13 to 1.72

1.04 to 1.49

0.54 to 0.77

1.41 to 2.02

0.64 to 0.80

0.70 to 0.86

1.13 to 1.73

0.70 to 0.86

Bold P figure: p < 0.05

*Model 3: Model 2+ adjusted for health status, marital status, annual equivalent income and years of education*Model 2: Model 1 + adjusted for age and sex*Model 1: adjusted for social support

OR odds ratio: CI confidence interval

You take care of your family

You take care of neighbors or friends

1

2

0.76

1.39

There is no one who takes care of you

3

About people who you take care of when they fall ill

1.24

Family members take care of you

Neighbors or friends take care of you

1

2

0.64

1.69

You have no one whose complaints you listen to3

About pople who take care of you when you fall ill

0.72

You listen to your family’s complaints

You listen to neighbors’ or friends’ complaints

1

2

0.76

1.40

There is no one to listen to your complaints

3

About people around you whose complaints you listen to

0.78

Family members listen to your complaints

Neigbors or friends listen to your complaints

1
0.77

0.00

0.92

0.00

1.22

1.10

0.81

1.44

0.00

0.63
1.34

0.02

0.00

1.48

0.00

0.78
0.82

0.00

0.00

1.27

0.00

0.77
0.89

0.00

0.00

OR

P

OR

(95%CI)

Model 2Model 1

2

About people around you who to listen to your complaints

Variables

Table 2 Binomial logistic regression analysis of the relationship between social support and ambulance call1.08 to 1.38

0.91 to 1.33

0.72 to 0.91

1.17 to 1.77

1.12 to 1.62

0.53 to 0.75

1.30 to 1.77

0.73 to 0.91

0.69 to 0.88

1.02 to 1.58

0.80 to 0.99

0.67 to 0.88

(95%CI)

0.00

0.33

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.03

0.04

0.00

P

1.15

1.13

0.81

1.22

1.34

0.73

1.26

0.90

0.85

1.11

0.97

0.83

OR

Model 31.01 to 1.31

0.93 to 1.38

0.72 to 0.91

0.97 to 1.54

1.10 to 1.63

0.60 to 0.90

1.03 to 1.53

0.80 to 1.01

0.75 to 0.98

0.88 to 1.39

0.86 to 1.08

0.71 to 0.96

(95%CI)

0.04

0.22

0.00

0.09

0.00

0.00

0.02

0.07

0.02

0.39

0.54

0.01

P

Asano et al. BMC Emergency Medicine(2024) 24:37
Page 7 of 11

Categories

There is no one who takes care of you

3

1.27

There is no one who you take care of

3

0.60 to 0.90

1.06 to 1.52

0.69 to 1.23

0.66 to 0.92

1.15 to 2.07

0.82 to 1.45

0.49 to 0.81

1.15 to 2.07

0.72 to 0.98

0.60 to 0.86

1.34 to 2.38

0.77 to 1.05

0.62

0.96
1.20

0.01

0.82

1.60

1.11

0.57

0.01

0.00

0.54

0.00

1.69

0.00

0.75
0.92

0.03

0.00

1.74

0.00

0.74
0.98

0.00
0.16

1.00 to 1.43

0.71 to 1.28

0.69 to 0.98

1.19 to 2.15

0.84 to 1.48

0.48 to 0.80

1.31 to 2.19

0.78 to 1.08

0.62 to 0.90

1.30 to 2.33

0.83 to 1.15

0.61 to 0.91

(95%CI)

Binomial logistic regression analysis for people who did not call an ambulance versus people who did but were not hospitalized after ambulance transport

Bold P figure: p < 0.05

*Model 3: Model 2+ adjusted for health status, marital status, annual equivalent income and years of education*Model 2: Model 1 + adjusted for age and sex*Model 1: adjusted for social support

OR odds ratio: CI confidence interval

0.92

You take care of your family

You take care of neighbors or friends

1
0.78

1.54

1.09

2

About people who you take care of when they fall ill

Family members take care of you

Neighbors or friends take care of you

1

2

0.63

1.54

You have no one whose complaints you listen to3

About pople who take care of you when you fall ill

0.84

You listen to your family’s complaints

You listen to neighbors’ or friends’ complaints

1

2

0.72

1.79

There is no one to listen to your complaints

3

About people around you whose complaints you listen to

0.90

Family members listen to your complaints

Neigbors or friends listen to your complaints

1
0.74

OR

P

OR

(95%CI)

Model 2Model 1

2

About people around you who to listen to your complaints

Variables

Table 3 People who did not call an ambulance versus people who did but were not hospitalized

0.05

0.77

0.03

0.00

0.47

0.00

0.00

0.28

0.00

0.00

0.78

0.00

P

1.10

0.96

0.91

1.39

1.11

0.70

1.46

0.99

0.79

1.58

1.05

0.76

OR

Model 30.91 to 1.34

0.71 to 1.31

0.75 to 1.10

1.01 to 1.92

0.82 to 1.50

0.52 to 0.92

1.11 to 1.91

0.84 to 1.18

0.65 to 0.96

1.16 to 2.14

0.90 to 1.24

0.62 to 0.94

(95%CI)

0.33

0.81

0.31

0.04

0.49

0.01

0.01

0.94

0.02

0.00

0.57

0.01

P

Asano et al. BMC Emergency Medicine(2024) 24:37
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Asano et al. BMC Emergency Medicine(2024) 24:37

when ill, than those who had called an ambulance butwere not hospitalized after ambulance transport.
The lack of social support was associated with a tendency to call an ambulance. Moreover, we found thatsocial support was significantly lower among those nothospitalized after calling an ambulance. This result is
consistent with that of a previous study [16]. In a study
that interviewed older patients who visited the emergency department with lower clinical urgency, 66% ofthem reported that they were dissatisfied with theirlevel of social interaction with others [22]. Therefore,
based on the results of this study, policies to reduce
unnecessary ambulance use, wherein physicians prescribe a greater provision of social support for older
people who use ambulances too frequently, shouldbe implemented to reduce the burden on emergency
departments. Social prescribing is also known as “community referral;” it provides a way of linking patientsin primary care to their nonmedical sources of support
within the community [23]. As a practical example, we
think that social prescriptions such as salons for older
people may reduce ambulance use among older people.
In this study, having family support was associatedwith ambulance use. A lack of family support has beenreported to be associated with emergency department
admissions [24]. We believe that the presence or absenceof family is a pertinent factor that determines ambulanceuse. For example, providing support for family members,
approaching an agency or organization that provides
support for family members, and family-like counselingfor people who live alone or are estranged from theirfamilies may reduce ambulance use, and thereby theburden on emergency medicine departments.
A notable finding of this study is that older people
are less likely to call an ambulance if they are takencare of by family members when they become ill; however, they are more likely to call an ambulance if neighbors or friends take care of them in the same situation.
Neighbors and friends are often less familiar with theirillness and symptoms than family members. This tendency can, therefore, also be expected in cases where
an ambulance is requested for non-emergency healthconditions. At the same time, older people who receive
care from family members may go to a medical institution by themselves. However, if older people are takencare of by neighbors or friends, they may call for an
ambulance. Older people whose neighbors and friends
call an ambulance may benefit from medical services
at home (e.g., home nursing, visiting physicians) andlegal systems consulting about sudden illnesses as thenumber of older people living alone is increasing.

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Limitations

This study had several limitations. First, due to the crosssectional design of the study, reverse causality exists.
Therefore, future studies should expand on this study byanalyzing data using a longitudinal design. Second, neither data about the diseases with which the older people
were diagnosed after ambulance use nor their medication history could be collected in this study. Additionally,
although “admission” vs “no admission” is a reasonable
category to separate mild from severe medical conditions, some major medical conditions can result in being
discharged from the emergency department, such as
fractures of the extremities, head injuries, lacerations,etc. It cannot be ruled out, therefore, that this clinicalinformation may be confounding. Hence, future studies should determine the relationship between ambulance use and social support by adjusting for disease
severity, diagnosis, and medication. Third, the findingsin this study may not be generalizable to all older people because of sampling bias resulting from only using
older people who did not need long-term care. However,
the effect of sampling bias on the result was minimal
because the participants were selected randomly. Finally,
external validity may be low when this study is implemented in contexts such as underdeveloped social environments. This is because the results of this study wereconducted in Japan, where healthcare systems are wellorganized with minimal variations in sociodemographic
conditions across regions.
The strength of this study is that we used large data sets
and identified the association between social support andambulance use in older people. We believe that futurestudies should analyze longitudinal data to identify causal
relationships and find the association between diseasetype and treatment intensity in emergency departments
after ambulance use and social support by using medical
claims databases.

Conclusion
This study revealed that the association between social
support and ambulance use among older adults. Our
results suggest that social support can be an importantfactor related to ambulance use. We suggest that policymakers should implement the interventions to enhance
the provision of social support to reduce ambulance use
among older people. We believe that this research can beused to make policies that improve the burden on emergency medical care. Based on the findings in this study,
these policies would be aimed at decreasing ambulance
use by increasing family support.

Asano et al. BMC Emergency Medicine(2024) 24:37

Page 10 of 11

Abbreviations
JAGES	Japan Gerontological Evaluation StudyCI	confidence intervalOR	odds ratios

the current study, and so are not publicly available. Data are however available
from the authors upon reasonable request and with permission of JAGES.

Supplementary Information

Ethics approval and consent to participate
This study was approved by the Ethics Committee of the National Center
for Geriatrics and Gerontology in Japan (approval number: 1274–2), Chiba
University (approval number: 3442), and Japan Gerontological Evaluation
and Research Insitute (approval number: 2019-01) and was performed inaccordance with the Declaration of Helsinki. We confirmed that consent toparticipate in this study was informed consent and informed consent was
obtained from all participants in this study.

The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12873-​024-​00953-8.
Additional file 1: Supplemental figure 1. Participating Municipalities inJapan Gerontological Evaluation Study (JAGES) in 2019 (Japan Gerontological Evaluation Study (JAGES) repository (URL:https://​www.​jages.​net/)).
Municipalities that have participated in JAGES2019 are shown in red andthose that have participated in the past are shown in blue.
Additional file 2: Supplemental Table 1. Characteristics of frequentambulance users according to the frequency of ambulance call per year.
Additional file 3:. Supplemental Table 2. Variance inflation factor (VIF)
of Model 2 and 3 in Table 2s and 3.
Additional file 4: Supplemental Table 3. Hosmer-Lemeshow test andthe c statistic about Table 2. Supplemental Table 4 Hosmer-Lemeshow test
and the c statistic about Table 3.
Acknowledgments
The authors would like to thank the study participants and the Japan Gerontological Evaluation Study (JAGES) team for data collection. We would also
like to thank the members of the JAGES group for their advice regarding thisstudy.
Publication of identifying information/images in an online open‑accesspublication
Not applicable.
Authors’ contributions
YA: conception, design, analysis and interpretation of the data, and writing
the article. TT: conception, design, interpretation of the data, and critical revision of the article. KU: critical revision of the article. NK: critical revision of thearticle. AY: critical revision of the article. TO: conception, design, and criticalrevision of the article. All authors read and approved the final draftt.
Funding
This study used data from Japan Gerontological Evaluation Study (JAGES),
which was supported by MEXT (Ministry of Education, Culture, Sports, Scienceand Technology-Japan)-Supported Program for the Strategic Research Foundation at Private Universities (2009–2013), JSPS (Japan Society for the Promotionof Science) KAKENHI Grant Numbers (JP18390200, JP22330172, JP22390400,
JP23243070, JP23590786, JP23790710, JP24390469, JP24530698, JP24683018,
JP25253052, JP25870573, JP25870881, JP26285138, JP26882010, JP15H01972),
Health Labour Sciences Research Grants (H22-Choju-Shitei-008, H24-Junkanki[Seishu]- Ippan-007, H24-Chikyukibo-Ippan-009, H24-Choju-Wakate-009,
H25-Kenki-Wakate-015, H25-Choju-Ippan-003, H26-Irryo-Shitei-003 [Fukkou],
H26-Choju-Ippan-006, H27-Ninchisyou-Ippan-001, H28-choju-Ippan-002,
H28- Ninchisyou-Ippan-002, H30-Kenki-Ippan-006, H30-Junkankitou-Ippan-004,
JPMH22LA2003), Japan Agency for Medical Research and development (AMED)(JP17dk0110017, JP18dk0110027, JP18ls0110002, JP18le0110009), and the
Research Funding for Longevity Sciences from National Center for Geriatrics
and Gerontology (24–17, 24–23, 29–42, 30–22). The views and opinions
expressed in this article are those of the authors and do not necessarily reflect
the official policy or position of the respective funding organizations.
Availability of data and materials
The datasets generated and/or analyzed during the current study are available
in the Japan Gerontological Evaluation Study (JAGES) repository (https://www.
jages.net/). The datasets used and/or analyzed during the current study areavailable from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this published article. The
data that support the findings of this study are available from JAGES but restrictions apply to the availability of these data, which were used under license for

Declarations

Consent for publication
All participants were informed that participation in this study was voluntary
and that completing the questionnaire, selecting the checkbox for approval,
and returning it by mail would indicate their consent to participate andpublish the results.
Competing interests
The authors declare no competing interests.
Author details
1
Department of Community Health and Preventive Medicine, Hamamatsu
University School of Medicine, Shizuoka, Japan. 2 Center for Preventive Medical
Sciences, Chiba University, Chiba, Japan. 3 Department of Social Epidemiology,
Graduate School of Medicine and School of Public Health, Kyoto University,
Kyoto, Japan. 4 Department of Medicine Emergency & Disaster Medicine,
Hamamatsu University School of Medicine, Shizuoka, Japan.
Received: 6 November 2023 Accepted: 18 February 2024

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