![The mental health recovery patterns: the trajectory models of resilience, recovery, remitting, and delayed/chronic dysfunction presented by Norris et al. (2009) [31] was utilized as the measurement scale for our questionnaire. Participants were asked the subjective question of which of the seven patterns most appropriately described their mental health status changes from pre-disaster to its current state and they selected the most appropriate choice from six mental health recovery patterns.](https://www.researchgate.net/publication/328591110/figure/fig2/AS:11431281210652718@1702058231971/The-mental-health-recovery-patterns-the-trajectory-models-of-resilience-recovery_Q320.jpg)
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International Journal of
Environmental Research
and Public Health
Article
Mental Health Recovery of Evacuees and Residents
from the Fukushima Daiichi Nuclear Power Plant
Accident after Seven Years—Contribution of Social
Network and a Desirable Lifestyle
Masatsugu Orui 1, * , Satomi Nakajima 2,3, Yui Takebayashi 3,4, Akiko Ito 3,4, Maho Momoi 3,4,
Masaharu Maeda 3,4, Seiji Yasumura 1,3 and Hitoshi Ohto 3
1Department of Public Health, Fukushima Medical University School of Medicine, Fukushima 960-1295,
Japan; yasumura@fmu.ac.jp
2Faculty of Human Studies, Musashino University, Tokyo 135-8181, Japan; satonaka@musashino-u.ac.jp
3Radiation Medical Science Center for the Fukushima Health Management Survey,
Fukushima Medical University, Fukushima 960-1295, Japan; takeb-ky@fmu.ac.jp (Y.T.);
itoaki@fmu.ac.jp (A.I.); maho-m@fmu.ac.jp (M.M.); masagen@fmu.ac.jp (M.M.); hit-ohto@fmu.ac.jp (H.O.)
4Department of Disaster Psychiatry, Fukushima Medical University School of Medicine,
Fukushima 960-1295, Japan
*Correspondence: oruima@fmu.ac.jp; Tel.: +81-24-547-1180
Received: 21 September 2018; Accepted: 25 October 2018; Published: 27 October 2018
Abstract:
The 2011 Fukushima nuclear accident resulted in the exposure to radiation and evacuation,
which has created psychological distress among the Fukushima residents. With the provision of
multi-faceted support and the progress of the reconstruction, their mental health has appeared to
show signs of recovery. However, there have been few studies investigating their recovery. To clarify
the related factors associated with mental health recovery, a cross-sectional questionnaire survey
was conducted. Subjects whose answers were associated with Resilience, Recovery, and Remitting
patterns of mental health status were categorized in the Recovery group, while those associated
with Delayed/Chronic dysfunction were placed in the Non-recovered group. In a multivariable
logistic regression analysis, disaster-related unemployment (odds ratio (OR): 0.80, 95% CI (confidence
interval): 0.65–0.99) and economic hardship (OR: 0.80, 95% CI: 0.65–0.98) were associated with the
hindrance of recovery. In contrast, overall good health (OR: 1.47, 95% CI: 1.20–1.80), regular physical
activity (OR: 1.23, 95% CI: 1.01–1.50), social interaction with friends (OR: 1.25, 95% CI: 1.00–1.55),
and established social roles (OR: 1.44, 95% CI: 1.14–1.82) were associated with the promotion of
recovery. In conclusion, our study showed a positive association between mental health recovery and
a desirable lifestyle and social network, particularly with social roles. Thus, the provision of active
social roles can promote recovery related to a disaster as with multi-faceted support.
Keywords:
mental health; nuclear disaster; great East Japan earthquake; recovery; social network;
social role; desirable lifestyle
1. Introduction
The Great East Japan Earthquake, which occurred on 11 March 2011, was the largest earthquake ever
recorded in Japan’s history. The earthquake (magnitude 9.0) generated a massive tsunami that caused
enormous damage to the Pacific Coast. This was followed by a separate tsunami, which hit the Fukushima
Daiichi Nuclear Power Plant operated by the Tokyo Electric Power Company, and caused a radiation disaster
in the Fukushima Prefecture that required the long-term evacuation of residents from many surrounding
Int. J. Environ. Res. Public Health 2018,15, 2381; doi:10.3390/ijerph15112381 www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2018,15, 2381 2 of 16
municipalities. As of May 2016, more than 92,000 residents who lived near the nuclear power plant had
been forced to leave their homes at the directive of the Japanese government due to this triple disaster [1].
The earthquake and nuclear accident caused multiple psychological reactions among the
evacuees and residents of Fukushima which included traumatic responses [
2
–
4
], loss of family,
relatives,
and friends [5]
, and the perceived health risk due to radiation exposure [
6
,
7
]. Under these
circumstances, the suicide rate in Fukushima increased after 2–3 years of the disaster occurrence [
8
,
9
].
In addition to other mental health problems, in particular, the perceived radiation exposure risk,
may have resulted in a prejudiced attitude among the public, or chronic anxiety among the evacuees.
These effects could cause sociopsychological issues such as public or self-stigma [
9
,
10
]. Their mental
health status had also been affected by loss of employment and/or community ties due to the nuclear
disaster and residential relocation with consequent drastic changes in their living circumstances [11].
Despite this harsh situation, there has been gradual progress in the reconstruction of Fukushima
after the nuclear disaster in the past seven years since the accident [
12
]. Although the mental
health status among some evacuees and residents appeared to be recovering due to frequent
opportunities for support or aid in the post-disaster period [
13
–
18
] and reconstruction progress [
19
,
20
],
there have been few studies investigating mental health recovery from the Fukushima nuclear disaster.
We hypothesized that desirable lifestyle or adequate social networks could promote mental health
recovery. Therefore, the present study aimed to clarify the related factors associated with the recovery
of mental health status such as desirable lifestyle or adequate social networks among the evacuees
and residents by conducting a cross-sectional questionnaire survey in Fukushima. These findings will
most likely be useful for future disaster risk reduction and management of mental health problems.
2. Materials and Methods
2.1. Participants
This cross-sectional questionnaire survey targeted 1000 residents of the Fukushima Prefecture
aged 20 and above. We selected 500 people from the evacuation area comprising Tamura City,
Minami-Soma City, Kawamata Town, Hirono Town, Naraha Town, Tomioka Town, Okuma Town,
Futaba Town, Namie Town, Kawauchi Village, Katsurao Village, and Iitate Village. The Japanese
government has designated evacuation areas according to the spatial radiation dose rates as follows:
(1) difficult-to-return areas with a radiation dose rate
≥
50 millisieverts (mSv) per year; (2) residence
restricted areas with a radiation dose rate
≥
20 and <50 mSv per year; and (3) areas where evacuation
orders were ready to be lifted as of 22 April 2011. Those living in the evacuation area were forced
to leave their homes at the direction of the Japanese government. Five hundred people in the
non-evacuation area were selected (Figure 1) using a two-stage stratified random sampling (stage
one comprising a regional survey, and stage two comprising an individual survey) method. Thirty to
35 individuals per area were randomly selected from municipal resident registration files to obtain
1000 representative participants. We sent an anonymous, self-reporting postal questionnaire to
participants from January to February 2018. The survey was approved by the ethics review committee
of Fukushima Medical University on 10 October 2017 (No. 29206).
2.2. Survey Variables
For related factors to mental health recovery, (1) disaster-related experiences; (2) economic status;
(3) general health status and lifestyle, and (4) social network (social interacting with friends from
pre-disaster, places to communicate about the disaster, and social roles through daily activities) were
set as dependent variables.
2.2.1. Disaster-Related Experiences
Needless to say, disaster-related experiences such as evacuation, separation from family members,
housing damage, and loss of family, relatives or friends are associated with mental health
status [5,21]
.
Int. J. Environ. Res. Public Health 2018,15, 2381 3 of 16
The effects of the disaster on socioeconomic statuses such as the loss of employment was also
hypothesized as a risk factor for mental health recovery [
22
]. Disaster-related experiences including
evacuation, separation from family members, housing damage (severe/partial collapse), loss of family,
relatives or friends, and disaster-related loss of employment were evaluated on a two-point scale
defined as “Experienced” or “Never”.
Int.J.Environ.Res.PublicHealth2018,15,x3of19
Figure1.LocationoftheFukushimaDaiichiNuclearPowerPlantandtheevacuation/non‐evacuation
areas.Thegraycolorshowstheevacuationareaandthewhitecolorshowsthenon‐evacuationarea
(asofDecember2015).
2.2.SurveyVariables
Forrelatedfactorstomentalhealthrecovery,(1)disaster‐relatedexperiences;(2)economic
status;(3)generalhealthstatusandlifestyle,and(4)socialnetwork(socialinteractingwithfriends
frompre‐disaster,placestocommunicateaboutthedisaster,andsocialrolesthroughdailyactivities)
weresetasdependentvariables.
2.2.1.Disaster‐RelatedExperiences
Needlesstosay,disaster‐relatedexperiencessuchasevacuation,separationfromfamily
members,housingdamage,andlossoffamily,relativesorfriendsareassociatedwithmentalhealth
status[5,21].Theeffectsofthedisasteronsocioeconomicstatusessuchasthelossofemploymentwas
alsohypothesizedasariskfactorformentalhealthrecovery[22].Disaster‐relatedexperiences
includingevacuation,separationfromfamilymembers,housingdamage(severe/partialcollapse),
lossoffamily,relativesorfriends,anddisaster‐relatedlossofemploymentwereevaluatedonatwo‐
pointscaledefinedas“Experienced”or“Never”.
2.2.2.EconomicStatus
Ithasbeenreportedthatsocioeconomiccircumstancesmayaffectevacuees’psychological
status[23].Thus,inordertoevaluatetherelationshipwiththementalhealthrecovery,economic
statuswasassessedbythefollowingquestion“Doyoufeelthatyoucanaffordyourcurrenteconomic
status?”andansweredonthefive‐pointscale“Difficult”,“Somewhatdifficult”,“Average”,
“Somewhatenough”,and“Enough”.
2.2.3.SubjectiveHealthStatusandLifestyle
Subjectivehealthstatusingeneralhealthstatusandlifestylewerescoredbasedonafive‐point
scalerangingfrom“Verywell”,“Well”,“Unremarkable”,“Poor”,and“Verypoor”.Toevaluate
lifestylethatmightberelatedtomentalhealthrecovery,weinvestigatedsleepsatisfactionand
changesinphysicalactivityafterthedisaster[24,25].Sleepsatisfactionwasassessedonafour‐point
scalerangingfrom“Reallysatisfied”,”Satisfied”,“Dissatisfied”,and“Reallydissatisfied”.Change
inphysicalactivitylevelwasrecordedas“Increase”,“Nochange”,and“Decrease”whencompared
tothepre‐disasterlevel.Somedisasterstudieshavereportedthatalcoholconsumptionincreased
followingadisaster,duetopsychologicaldistressintheaffectedindividuals[26,27],therefore,a
Figure 1.
Location of the Fukushima Daiichi Nuclear Power Plant and the evacuation/non-evacuation
areas. The gray color shows the evacuation area and the white color shows the non-evacuation area (as
of December 2015).
2.2.2. Economic Status
It has been reported that socioeconomic circumstances may affect evacuees’ psychological status [
23
].
Thus, in order to evaluate the relationship with the mental health recovery, economic status was assessed
by the following question “Do you feel that you can afford your current economic status?” and answered
on the five-point scale “Difficult”, “Somewhat difficult”, “Average”, “Somewhat enough”, and “Enough”.
2.2.3. Subjective Health Status and Lifestyle
Subjective health status in general health status and lifestyle were scored based on a five-point
scale ranging from “Very well”, “Well”, “Unremarkable”, “Poor”, and “Very poor”. To evaluate
lifestyle that might be related to mental health recovery, we investigated sleep satisfaction and changes
in physical activity after the disaster [
24
,
25
]. Sleep satisfaction was assessed on a four-point scale
ranging from “Really satisfied”,” Satisfied”, “Dissatisfied”, and “Really dissatisfied”. Change in
physical activity level was recorded as “Increase”, “No change”, and “Decrease” when compared to the
pre-disaster level. Some disaster studies have reported that alcohol consumption increased following a
disaster, due to psychological distress in the affected individuals [
26
,
27
], therefore, a change in alcohol
consumption was assessed as “Increase”, “No change”, “Decrease”, or “Non-drinker” when compared
with the pre-disaster level in order to assess the relationship with mental health recovery. As a previous
study reported that laughter may lower the risk of poor subjective health [
28
], laughing frequency was
asked on a four-point scale ranging from “Almost every day”, “1–5 times per week”, “1–3 times per
month”, and “Never or almost never” based on the previous study [29].
2.2.4. Social Network
Social networks were considered as an important factor influencing mental health outcomes, and
high social capital played an important role in protecting mental health [
30
]. Therefore, we assessed
the association between mental health recovery and social networks by utilizing the following three
questions: (1) Social interaction with friends from pre-disaster, “Have you been interacting with friends
from pre-disaster?”; (2) Places to communicate about the disaster, “Do you have places where you feel
free to talk about the disaster?”; and (3) Social roles through daily activities, “Do you feel that you are
Int. J. Environ. Res. Public Health 2018,15, 2381 4 of 16
helpful to others through your job(s), housework, or social activities?”. Participants answered these
social network questions on a five-point scale ranging from “Strongly agree”, “Agree”, “Neutral”,
“Disagree”, and “Strongly disagree”. These responses were categorized into two groups: “Agree” and
“Disagree/Neutral” while analyzing the related factors with mental health recovery.
2.2.5. Mental Health Recovery Patterns
We used the trajectory models of resistance, resilience, recovery and delayed/chronic dysfunction
presented by Norris et al. (2009) to assess the independent variables associated with the recovery
of mental health status [
31
]. Participants were asked the subjective question “Which of the seven
patterns most appropriately describe your mental health status changes from pre-disaster to its current
state? (1) Resistance; (2) Resilience; (3) Recovery; (4) Remitting; (5) Chronic dysfunction; (6) Delayed
dysfunction; and (7) none of the six patterns” and to select the most appropriate choice (Figure 2).
Int.J.Environ.Res.PublicHealth2018,15,x5of19
Figure2.Thementalhealthrecoverypatterns:thetrajectorymodelsofresilience,recovery,remitting,
anddelayed/chronicdysfunctionpresentedbyNorrisetal.(2009)[31]wasutilizedasthemeasurement
scaleforourquestionnaire.Participantswereaskedthesubjectivequestionofwhichoftheseven
patternsmostappropriatelydescribedtheirmentalhealthstatuschangesfrompre‐disastertoitscurrent
stateandtheyselectedthemostappropriatechoicefromsixmentalhealthrecoverypatterns.
2.3.StatisticalAnalysis
Thechi‐squaretestandmultivariablelogisticregressionmodelswereusedtoexaminethe
associationofmentalhealthrecoverywithdisaster‐relatedexperiences,generalhealthstatus,and
lifestyle,economicstatus,andsocialnetworkvariables.Inparticular,twomodelswereanalyzedin
multivariablelogisticregressionanalysis:Model1wasadjustedbyage,gender,disaster‐related
experiences,andcurrenteconomicstatus,whichwasobservedtoaffectdisaster‐associatedmental
healthrecovery[30,34,35];andModel2hadcurrenthealthstatusandlifestyle(generalsubjective
healthstatus,sleepquality,physicalactivitylevel,andlaughingfrequency)andsocialnetworkstatus
addedtothevariablesinModel1,whichcouldbeprotectivefortheirmentalhealth[24,25,28,36–39],
andevacueesreceivedhealthguidanceasapartofdisasterhealthactivities[40–42].Moreover,thet‐
testwasutilizedtoassesstheK6scaleinthe“Recovered”and“Non‐recovered”groups.
Statisticalsignificancewasevaluatedusingtwo‐sided,design‐basedtestswitha5%levelof
significance.AllstatisticalanalyseswereperformedusingSPSS24.0(IBMCorp.,Armonk,NY,USA).
Pattern 5. Delayed dysfunction Pattern 6. Chronic dysfuncti on
Pattern 7. None o f abov e six p atterns
Pattern 1. Resistance Pattern 2. Resilience
Pattern 3. Recovery Pattern 4. Remitting
‐8
‐6
‐4
‐2
0
2
‐8
‐6
‐4
‐2
0
2
‐8
‐6
‐4
‐2
0
2
‐8
‐6
‐4
‐2
0
2
‐8
‐6
‐4
‐2
0
2
‐8
‐6
‐4
‐2
0
2
Pre‐disaster Pre‐disaster
Pre‐disaster Pre‐disaster
Pre‐disaster Pre‐disaster
Post‐disaster
Post‐disaster
Post‐disaster Pos t‐disaster
Post‐disaster
Post‐disaster
Present Present
Present
Present
Present Present
Mental
health
status
Well
Poor
Mental
health
status
Well
Poor
Mental
health
status
Well
Poor
Figure 2. The mental health recovery patterns: the trajectory models of resilience, recovery, remitting,
and delayed/chronic dysfunction presented by Norris et al. (2009) [
31
] was utilized as the measurement
scale for our questionnaire. Participants were asked the subjective question of which of the seven
patterns most appropriately described their mental health status changes from pre-disaster to its current
state and they selected the most appropriate choice from six mental health recovery patterns.
To assess the mental health status in the “Recovered” and “Non-recovered” groups, we utilized
the K6 scale to screen for non-specific psychological distress [
32
]. Those scoring 0–12 points were
classified as having probable mild–moderate/probable no psychological distress and those scoring
13–24 points were classified as having probable severe psychological distress [
32
]. This study used
Int. J. Environ. Res. Public Health 2018,15, 2381 5 of 16
the Japanese version of the K6, which has been empirically validated as an independent means of
screening for psychological distress among evacuees [33].
2.3. Statistical Analysis
The chi-square test and multivariable logistic regression models were used to examine the
association of mental health recovery with disaster-related experiences, general health status,
and lifestyle, economic status, and social network variables. In particular, two models were analyzed
in multivariable logistic regression analysis: Model 1 was adjusted by age, gender, disaster-related
experiences, and current economic status, which was observed to affect disaster-associated mental
health recovery [
30
,
34
,
35
]; and Model 2 had current health status and lifestyle (general subjective
health status, sleep quality, physical activity level, and laughing frequency) and social network status
added to the variables in Model 1, which could be protective for their mental health [
24
,
25
,
28
,
36
–
39
],
and evacuees received health guidance as a part of disaster health activities [
40
–
42
]. Moreover, the t-test
was utilized to assess the K6 scale in the “Recovered” and “Non-recovered” groups.
Statistical significance was evaluated using two-sided, design-based tests with a 5% level of
significance. All statistical analyses were performed using SPSS 24.0 (IBM Corp., Armonk, NY, USA).
3. Results
3.1. Participants
We sent out 938 questionnaires (excluding 62 subjects that were returned to the sender as no
one was residing at the address), and received 445 responses (response rate, 47.4%). After excluding
10 respondents who failed to provide information regarding age or gender, and 102 respondents who
answered “Resistant” and “None of previous six patterns” of the mental health recovery pattern or
did not answer this question, the final study population was comprised of 233 respondents (Figure 3).
Int.J.Environ.Res.PublicHealth2018,15,x6of19
3.Results
3.1.Participants
Wesentout938questionnaires(excluding62subjectsthatwerereturnedtothesenderasnoone
wasresidingattheaddress),andreceived445responses(responserate,47.4%).Afterexcluding10
respondentswhofailedtoprovideinformationregardingageorgender,and102respondentswho
answered“Resistant”and“Noneofprevioussixpatterns”ofthementalhealthrecoverypatternordid
notanswerthisquestion,thefinalstudypopulationwascomprisedof233respondents(Figure3).
Figure3.Sampleselectionintheevacuationandnon‐evacuationarea:Amongthe1000subjects,191
evacueesintheevacuationareaand254residentsinthenon‐evacuationarearespondedtothe
questionnaire.Afterexcludingrespondentswhoweremissingageandgenderinformation,andwho
didnotchangetheirmentalhealthstatusornon‐respondents,weanalyzed160subjectsinthe
evacuationareaand173subjectsinthenon‐evacuationarea.
3.2.RespondentCharacteristics
Table1showsthecharacteristicofeachmentalhealthrecoverypattern.Inthosewitha
“Resistance”pattern,therewasthetendencyofahigherproportionofyoungersubjects,male,
employed,andlivinginthenon‐evacuationareaon11March2011.Whereas,inthosewitha“Chronic
dysfunction”pattern,therewasthetendencyofahigherproportionofoldersubjects,unemployed,and
livingintheevacuationareaasof11March2011.ThemeanK6scoreamongtotalcaseswas6.0while
thoseofDelayed/Chronicdysfunctionwerehigherthanotherpatterns(relatively11.8and12.3).
Basedontheresponseofthementalhealthrecoverypatterns,wedefinedthosewhoselectedthe
“Resilience”,“Recovery”,and“Remitting”patternsintothe“Recoveredgroup”andthosewhoselected
(n=58) (n=4)
(n=5) (n=5)
[Evacuation area] [Non-evacuation area]
Subjects :500eva cu ees Su bj ec ts :500residents
Respondents:
191eva cuees
Respondents:
254residents
Respondents:
186eva cuees
Respondents:
249residents
(n=26) (n=76)
Analysedsubject s:
n=160
Analysedsubject s:
n=173
Exclud edmailing
adressunknown
Exclud edmissingageorgende r
Exclud edrespo nden tswhodid
notcha ngementalhealthstatus
ornon‐resp ondents
Ana lysed there lat edfactorsfor
res i lience inFukushimaPref.
re s i dents
Figure 3.
Sample selection in the evacuation and non-evacuation area: Among the 1000 subjects,
191 evacuees in the evacuation area and 254 residents in the non-evacuation area responded to
the questionnaire. After excluding respondents who were missing age and gender information,
and who did not change their mental health status or non-respondents, we analyzed 160 subjects in the
evacuation area and 173 subjects in the non-evacuation area.
Int. J. Environ. Res. Public Health 2018,15, 2381 6 of 16
3.2. Respondent Characteristics
Table 1shows the characteristic of each mental health recovery pattern. In those with a “Resistance”
pattern, there was the tendency of a higher proportion of younger subjects, male, employed, and living
in the non-evacuation area on 11 March 2011. Whereas, in those with a “Chronic dysfunction” pattern,
there was the tendency of a higher proportion of older subjects, unemployed, and living in the
evacuation area as of 11 March 2011. The mean K6 score among total cases was 6.0 while those
of Delayed/Chronic dysfunction were higher than other patterns (relatively 11.8 and 12.3).
Based on the response of the mental health recovery patterns, we defined those who selected the
“Resilience”, “Recovery”, and “Remitting” patterns into the “Recovered group” and those who selected
the “Delayed dysfunction” and “Chronic dysfunction” pattern into the “Non-recovered group”. In this
study, those who selected “Resistance” or “None of six patterns” were excluded from analysis because
their mental health status between pre- and post-disaster was unchanged or unknown. There were
274 subjects in the “Recovered group” and 59 in the “Non-recovered group”. There were 80.0% in
the “Recovered group” in the evacuation area 80.0%, and 84.4% in the non-evacuation area, which
was not significantly different. There was a higher proportion of unemployed respondents in the
“Non-recovered group” compared to the “Recovered group”. The proportion of those with a K6
score
≥
13 was significantly higher in the “Non-recovered group” than in the “Recovered group”
(Recovered: 32.5%, Non-recovered: 67.5%), with a corresponding significantly higher mean K6 score
in the non-recovered group (Recovered: 4.81 point, Non-recovered: 12.1 point) (Table 2).
3.3. Disaster-Related Experiences and Current Economic Status
Table 3shows the distribution of disaster-related experiences and current economic status in the
recovered and non-recovered groups. Loss of family, relatives and friends, disaster-associated loss of
employment, and higher current psychological distress were significantly high in the “Non-recovered
group”. In contrast, experiences of evacuation, disaster-associated separation of family members, and
house damage were not significantly associated with mental health recovery in this study. Economic
hardship was significantly associated with non-recovered mental health.
Int. J. Environ. Res. Public Health 2018,15, 2381 7 of 16
Table 1. Basic characteristics of respondents (each mental health recovery patterns).
Basic Characteristics
Total
Pattern 1 Pattern 2 Pattern 3 Pattern 4 Pattern 5 Pattern 6 None of
These Patterns
Resistance Resilience Recovery Remitting Delayed
Dysfunction
Chronic
Dysfunction
(n= 410) (n= 42) (n= 100) (n= 127) (n= 47) (n= 19) (n= 40) (n= 35)
n(%) n(%) n(%) n(%) n(%) n(%) n(%) n(%)
Age (as of February 2018)
Less than 40 years old 56
(100.0)
9
(16.1)
9
(16.1)
15
(26.8)
12
(21.4)
6
(10.7)
1 (1.8) 4 (7.1)
40–64 years old 190
(100.0)
19
(10.0)
50
(26.3)
58
(30.5)
22
(11.6)
7 (3.7) 17 (8.9) 17 (8.9)
65 years old and more 164
(100.0)
14 (8.5) 41
(25.0)
54
(32.9)
13 (7.9) 6 (3.7) 22
(13.4)
14 (8.5)
Gender
Male 178
(100.0)
27
(15.2)
42
(23.6)
51
(28.7)
14 (7.9) 9 (5.1) 18
(10.1)
17 (9.6)
Female 232
(100.0)
15 (6.5) 58
(25.0)
76
(32.8)
33
(14.2)
10 (4.3) 22 (9.5) 18 (7.8)
Education
Junior/Senior high school 300
(100.0)
23 (7.7) 67
(22.3)
100
(33.3)
35
(11.7)
14 (4.7) 33
(11.0)
28 (9.3)
Vocational college, University 108
(100.0)
19
(17.6)
33
(30.6)
26
(24.1)
11
(10.2)
5 (4.6) 7 (6.5) 7 (6.5)
Occupational category
Employed, Owner 154
(100.0)
24
(15.6)
44
(28.6)
42
(27.3)
19
(12.3)
4 (2.6) 11 (7.1) 10 (6.5)
Part-time 49
(100.0)
1 (2.0) 13
(26.5)
16
(32.7)
8
(16.3)
2 (4.1) 3 (6.1) 6 (12.2)
Homemaker 77
(100.0)
8
(10.4)
19
(24.7)
26
(33.8)
12
(15.6)
1 (1.3) 6 (7.8) 5 (6.5)
Unemployed 122
(100.0)
9 (7.4) 20
(16.4)
41
(33.6)
7 (5.7) 11 (9.0) 20
(16.4)
14 (11.5)
Living area as of 11 March 2011
Evacuation area 177
(100.0)
8 (4.5) 30
(16.9)
72
(40.7)
26
(14.7)
8 (4.5) 24
(13.6)
9 (5.1)
Non-evacuation area 233
(100.0)
34
(14.6)
70
(30.0)
55
(23.6)
21 (9.0) 11 (4.7) 16 (6.9) 26 (11.2)
Living with family member
Living with family 362
(100.0)
40
(11.0)
93
(25.7)
111
(30.7)
39
(10.8)
14 (3.9) 35 (9.7) 30 (8.3)
Single life 38
(100.0)
1 (2.6) 7
(18.4)
14
(36.8)
7
(18.4)
3 (7.9) 3 (7.9) 3 (7.9)
Current psychological distress (K6: Kessler 6)
K6 score ≥13 50
(100.0)
5
(12.8)
4 (4.0) 3 (2.5) 6
(13.6)
7
(36.8)
20
(54.1)
5 (14.7)
K6 score (mean, SD) 6.0 (5.3) 5.2 (5.7) 3.1 (3.9) 5.5 (3.7) 6.8 (4.4) 11.8 (5.1) 12.3 (5.4) 6.4 (6.38)
Int. J. Environ. Res. Public Health 2018,15, 2381 8 of 16
Table 2. Basic characteristics of subjects (Recovered/Non-recovered group).
Basic Characteristics
Total Recovered Non-Recovered
p-Value (χ2/t)
(n= 333) (n= 274) (n= 59)
n(%) n(%) n(%)
Age (as of February 2018)
Less than 40 years old 43 (100.0) 36 (83.7) 7 (16.3)
40–64 years old 154 (100.0) 130 (84.4) 24 (15.6) 0.52 (χ2= 1.31)
65 years old and more 136 (100.0) 108 (79.4) 28 (20.6)
Gender
Male 134 (100.0) 107 (79.9) 27 (20.1) 0.34 (χ2= 0.91)
Female 199 (100.0) 167 (83.9) 32 (16.1)
Education
Junior/Senior high school 249 (100.0) 202 (81.1) 47 (18.9) 0.38 (χ2= 0.76)
Vocational college, University 82 (100.0) 70 (85.4) 12 (14.6)
Occupational category
Employed, Owner 120 (100.0) 105 (87.5) 15 (12.5)
Part-time 42 (100.0) 37 (88.1) 5 (11.9)
Homemaker 64 (100.0) 57 (89.1) 7 (10.9) <0.01 (χ2= 19.5)
Unemployed 99 (100.0) 68 (68.7) 31 (31.3)
Living area as of 11 March 2011
Evacuation area 160 (100.0) 128 (80.0) 32 (20.0) 0.29 (χ2= 1.10)
Non-evacuation area 173 (100.0) 146 (84.4) 27 (15.6)
Living with family member 0.90 (χ2= 0.02)
Living with family 292 (100.0) 243 (83.2) 49 (16.8)
Single life 34 (100.0) 28 (82.4) 6 (17.6)
Current psychological distress (K6: Kessler6)
K6 score ≥13 40 (100.0) 13 (32.5) 27 (67.5) <0.01 (χ2= 79.2)
K6 score ≤12 280 (100.0) 251 (89.6) 29 (10.4)
K6 score (mean, SD) 6.0 (5.3) 4.8 (4.1) 12.1 (5.2) <0.01 (t= 9.81)
K6 score was tested by the t-test. The others were tested by χ2test. SD: Standard Deviation.
Table 3. Disaster-related experience and current economic status.
Disaster-Related Experience and
Current Economic Status
Total Recovered Non-Recovered
p-Value (χ2)
(n= 333) (n= 274) (n= 59)
n(%) n(%) n(%)
Evacuation
Experienced 176
(100.0)
144 (81.8) 32 (18.2) 0.82 (χ2= 0.06)
Never 157
(100.0)
130 (82.8) 27 (17.2)
Separation from family members
Experienced 103
(100.0)
82 (79.6) 21 (20.4) 0.39 (χ2= 0.73)
Never 230
(100.0)
192 (83.5) 38 (16.5)
House damage (severe/partial collapse)
Experienced 117
(100.0)
93 (79.5) 24 (20.5) 0.33 (χ2= 0.97)
Never 216
(100.0)
181 (83.8) 35 (16.2)
Loss of family, relatives or friends
Experienced 59
(100.0)
41 (69.5) 18 (30.5) 0.01 (χ2= 8.05)
Never 274
(100.0)
233 (85.0) 41 (15.0)
Disaster-related loss of employment <0.01 (χ2= 17.9)
Experienced 81
(100.0)
54 (66.7) 27 (33.3)
Never 252
(100.0)
220 (87.3) 32 (12.7)
Economic status (Afford to live in current economic status)
Difficult 110
(100.0)
76 (69.1) 34 (30.9) <0.01 (χ2= 20.4)
Enough/Average 221
(100.0)
197 (89.1) 24 (10.9)
3.4. Current Health Status, Lifestyle, and Social Network
The current health status, lifestyle, and social network among the “Recovered” and
“Non-recovered group” are shown in Table 4. Poor general subjective health status, a dissatisfactory
sleep condition, decreased physical activity level, and lower laughing frequency were significantly
Int. J. Environ. Res. Public Health 2018,15, 2381 9 of 16
associated with non-recovered mental health. In contrast, social interacting with friends from
pre-disaster and social roles through daily activities were associated with mental health recovery.
Table 4. Current health status, lifestyle, and social status.
Current Health Status, Lifestyle
and Social Status
Total Recovered Non-Recovered
p-Value (χ2)
(n= 333) (n= 274) (n= 59)
n(%) n(%) n(%)
General subjective health status
Very well/Well/Unremarkable 249 (100.0) 228 (91.6) 21 (8.4) <0.01 (χ2= 61.6)
Poor/Very poor 81 (100.0) 43 (53.1) 38 (46.9)
Sleep condition
Satisfied with sleep condition 149 (100.0) 137 (91.9) 12 (8.1) <0.01 (χ2= 17.3)
Dissatisfied 184 (100.0) 137 (74.5) 47 (25.5)
Changes in physical activities
Increase/No change 203 (100.0) 182 (89.7) 21 (10.3) <0.01 (χ2= 19.7)
Decrease 125 (100.0) 88 (70.4) 37 (29.6)
Changes in alcohol consumption
Increase 42 (100.0) 33 (78.6) 9 (21.4)
No change 111 (100.0) 95 (85.6) 16 (14.4) 0.22 (χ2= 4.47)
Decrease 42 (100.0) 31 (73.8) 11 (26.2)
Non-drinker 109 (100.0) 94 (86.2) 15 (13.8)
Frequency of laughing
Almost everyday 80 (100.0) 76 (95.0) 4 (5.0) <0.01 (χ2= 11.7)
Less that 1–5 times/week 253 (100.0) 198 (78.3) 55 (21.7)
Social network status
Social interaction with friends from pre-disaster
Agree 190 (100.0) 173 (91.1) 17 (8.9) <0.01 (χ2= 16.1)
Disagree/Neither or not 132 (100.0) 94 (71.2) 38 (28.8)
Place to communicate about the disaster
Agree 119 (100.0) 104 (87.4) 15 (12.6) 0.06 (χ2= 3.59)
Disagree/Neither or not 205 (100.0) 162 (79.0) 43 (21.0)
Social roles through daily activities
Agree 138 (100.0) 129 (93.5) 9 (6.5) <0.01 (χ2= 21.4)
Disagree/Neither or not 189 (100.0) 139 (73.5) 50 (26.5)
3.5. Association between Mental Health Recovery and Disaster-Related Experience, Current Economic Status
and Health Status, and Lifestyle and Social Network
In the multivariable logistic regression analysis, Model 1 was adjusted for age, gender,
disaster-related experiences, and current economic status, which was observed to affect disaster-related
mental health recovery. As a result, disaster-related loss of employment (odds ratio (OR): 0.75, 95%
confidence interval: 0.63–0.89) and economic hardship (OR: 0.70, 95% CI: 0.59–0.82) were associated
with non-recovered mental health status. In Model 2, which had current health status, lifestyle, and
social network variables added on, good general subjective health status (OR: 1.47,
95% CI: 1.20–1.80
),
increased or unchanged physical activity level (OR: 1.23, 95% CI: 1.01–1.50), social interaction with
friends from pre-disaster (OR: 1.25, 95% CI: 1.00–1.55), and social roles through daily activities
(OR: 1.44, 95% CI: 1.14–1.82) were significantly associated with mental health recovery. However,
disaster-related loss of employment (OR: 0.80, 95% CI: 0.65–0.99) and economic hardship (OR: 0.80,
95% CI: 0.65–0.98) were still associated with non-recovered mental health status even when the positive
effects of good general subjective health status, regular physical activity, social interaction with friends
from pre-disaster, and social roles through daily activities on their mental health were considered
(Table 5).
Int. J. Environ. Res. Public Health 2018,15, 2381 10 of 16
Table 5. Multivariable logistic regression analysis between mental health recovery and related factors.
Relative Factors with Mental Health Recovery Model 1 (n= 331) Model 2 (n= 310)
OR (95% CI) p-Value OR (95% CI) p-Value
Basic characteristics
Age 1.02 (0.99–1.04) 0.15 1.00 (0.98–1.03) 0.78
Gender Male 0.72 (0.39–1.35) 0.31 0.72 (0.33–1.57) 0.41
Female (Ref.) 1.00 1.00
Living area as of 11 March 2011 Evacuation 0.97 (0.82–1.16) 0.77 0.97 (0.78–1.22) 0.82
non-evacuation (Ref.) 1.00 1.00
Disaster-related experience
Loss of family, relatives or friends Experienced 0.84 (0.70–1.02) 0.08 0.89 (0.71–1.13) 0.34
Never (Ref.) 1.00 1.00
Disaster-related loss of employment Experienced 0.75 (0.63–0.89) <0.01 0.80 (0.65–0.99) 0.04
Never (Ref.) 1.00 1.00
Economic status
Afford to live in current economic status Difficult 0.70 (0.59–0.82) <0.01 0.80 (0.65–0.98) 0.03
Enough/Average (Ref.) 1.00 1.00
Current health status and lifestyle
General subjective health status Well/Unremarkable 1.47 (1.20–1.80) <0.01
Poor/Very poor (Ref.) 1.00
Sleep condition Satisfied with sleep 1.09 (0.86–1.37) 0.49
Dissatisfied (Ref.) 1.00
Changes in physical activities Increase/No change 1.23 (1.01–1.50) 0.04
Decrease (Ref.) 1.00
Frequency of laughing Almost everyday 1.19 (0.85–1.67) 0.30
Less that 1–5 times/week (Ref.) 1.00
Social network status
Social interaction with friends Agree 1.25 (1.00–1.55) 0.05
Disagree/Neither or not (Ref.) 1.00
Place to communicate about the disaster Agree 0.81 (0.63–1.03) 0.08
Disagree/Neither or not (Ref.) 1.00
Social roles through daily activities Agree 1.44 (1.14–1.82) <0.01
Disagree/Neither or not (Ref.) 1.00
OR
: Odds Ratio,
CI
: Confidence Interval,
Bold
:p< 0.05.
Model 1
: Adjusted by age, gender, disaster-related experiences, and current economic status variables.
Model 2
: Adjusted current
health status and lifestyle, and social network status added on to the variables in Model 1.
Int. J. Environ. Res. Public Health 2018,15, 2381 11 of 16
4. Discussion
The present study aimed to clarify the related factors associated with mental health recovery
among the evacuees and residents. We consequently found that good general subjective health status,
regular physical activity, and social networking (interacting with friends from pre-disaster and social
roles through daily activities) were significantly associated with mental health recovery. In contrast,
disaster-related loss of employment and economic hardship negatively affected mental health recovery
in Fukushima evacuees and residents.
4.1. The Mental Health Recovery Patterns and Their Basic Characteristics
In this study, we utilized the mental health recovery pattern based on the trajectory models
of resilience, recovery, and delayed/chronic disfunction presented by Norris et al. While the
patterns in our study have not been validated yet, the mean K6 score in Resilience, Recovery,
and Remitting were much lower than those in Delayed/Chronic dysfunction. Moreover, the mean
K6 score in the “Recovered” group was significantly lower than that of the “Non-recovered” group.
Thus, our patterns of mental health status changes and categorization of mental health recovery
(Recovered/Non-recovered group) may be reliable to a certain extent.
Unemployed respondents were likely to be in the “Non-recovered group” in this study, suggesting
an effect of employment status on their mental health recovery. In contrast, age, gender, education,
and living with family members were not significantly different between the “Recovered” and
“Non-recovered” groups.
In this study, the proportion of “Recovered” mental health status between the evacuation (80.0%)
and non-evacuation area (84.4%) were similar. Importantly, our findings showed that even evacuees
who have been forced to relocate to the outside of the evacuation area could recover their mental health
status equally well when compared to the residents living in the non-evacuation area. In contrary,
even some of the residents in the non-evacuation area have yet to recover their mental health status.
In fact, a previous study reported that residents in the non-evacuation area had radiation anxiety
and psychological distress regardless of the environmental radiation levels [
43
]. Moreover, some
residents in the non-evacuation area had voluntarily evacuated outside of Fukushima Prefecture due
to anxiety of radiation exposure. Indeed, 15.6% of residents in the non-evacuation area in this study
had experienced evacuation due to a nuclear disaster (Voluntary evacuation, n= 27). Detailed analysis
among the residents in the non-evacuation area showed that they had disaster-related experiences or
economic hardship although it was lower than that of the evacuees in the evacuation area (Separated
from family members: 8.7%, Disaster-associated loss of employment: 11.6%, Economic hardship:
41.3%) (Data in Supplementary Table S1). These situations may affect why there was no significant
difference in the mental health recovery between evacuees in the evacuation area and the residents in
the non-evacuation area (Table 2). Thus, we analyzed the association between mental health recovery
and related factors in evacuees in the evacuation area and residents in the non-evacuation area as a
whole as some of the residents in the non-evacuation area had some disaster-related experiences or
economic hardship, and consequently could have psychological distress.
4.2. Association between Mental Health Recovery and Disaster-Related Experiences, Current Economic and
Health Status, and Lifestyle and Social Network
In analyzing related factors associated with mental health recovery, Model 1 was adjusted by
disaster-related experiences and current economic status consequent to the disaster that could cause a
negative psychological reaction. In contrast, Model 2 was adjusted by health status, lifestyle, and social
network, which have been provided as information or service as disaster health activities and could
have positive psychological effects. Our findings in Model 1 showed that disaster-related loss of
employment and economic hardship could hinder mental health recovery, and were more likely to
be risk factors compared to the residential area (evacuation/non-evacuation area), or loss of family,
relatives, or friends. Disaster-related loss of employment and economic hardship was an obviously
Int. J. Environ. Res. Public Health 2018,15, 2381 12 of 16
stressful event and could be considered the role of relative poverty, social isolation, and decreasing
opportunities for health-related behaviors [
44
]. This may affect the association with the hindrance of
mental health recovery.
In contrast, good general subjective health condition and steady physical activities may have
promoted mental health recovery among the evacuees and residents. A previous study reported that
employees in the evacuation area who had good general subjective health and regular physical activity
could maintain their mental health in the post-disaster period even if their work and life circumstances
had significantly changed [
39
]. In the post disaster period of the Great East Japan Earthquake and
Fukushima Daiichi nuclear power plant accident, numerous supports including maintaining the
general health and physical activity level among the evacuees and residents have been received health
guidance as a part of the disaster health activities [
41
,
42
]. Leisure activities including physical activities
could play a role in benefitting overall well-being coping to adequately deal with stress [
45
,
46
]. Similar
to the previous study, our findings showed that health habits that promoted a good general health
status and physical activity could have helped to promote mental health recovery while providing
health guidance at the disaster health activities.
Moreover, building a social network or social ties was also an important role of disaster health
activities as many evacuees had to relocate outside of their hometown, consequently leading to
separation from their original community. In fact, previous studies have reported that perceived
social network is associated with reduced psychological distress or has a positive effect on mental
health [47–49]
, and numerous events have been implemented in the Fukushima prefecture, particularly
in the evacuation area (e.g., exchange meetings, parties in temporary housing, active listening for
evacuees or residents) to help build social networks or social ties [
50
–
53
]. Our findings could
indicate that these measures may have enabled social interaction with friends from pre-disaster,
which consequently might promote mental health recovery.
Evacuees and residents in Fukushima were given numerous types of support from outside
supporters or volunteers in the short- to mid-term in the post-disaster period. However, for evacuees
and residents “to feel that they can be helpful to others through jobs, housework, or social activities”,
both passive support and playing any social roles through their daily activities could promote mental
health recovery during the past seven years since the disaster. A previous study reported that social
roles had a significant positive effect on mental health and their quality might help prevent depression
or anxiety disorders [
54
]. Indeed, the loss of employment was a risk factor for mental health recovery
in this study, with concomitant loss of opportunities for activities that could enable them to feel helpful
to others. In short, our findings suggest that any social role that enables one to feel helpful to others
might be related to mental health recovery in the long-term following a disaster.
Our findings showed that disaster-related loss of employment and economic hardship were
still associated with non-recovered mental health status even after adjusting for other health and
social network factors that positively affected mental health recovery. A previous study showed that
socio-economic issues were strongly and significantly associated with the needs of long-term disaster
mental health support [
55
]. Moreover, disaster-induced socioeconomic changes were associated with
poor subjective health even after adjusting for lifestyle-related factors such as sleep, community
participation, or regular exercise [
35
]. Thus, our findings provide insights for disaster mental health
service providers, where health and socio-economic support is essential for evacuees and residents to
recover their mental health status in the long-term following a disaster.
Meanwhile, the three variables that were significantly associated with mental health recovery in a
univariate analysis (loss of family, relatives or friends, sleep satisfaction, and frequency of laughing)
lost a significance in the multivariable analysis. The reason might be influenced by adjusting covariates
(i.e., age, gender or Evacuation/Non-evacuation area).
Int. J. Environ. Res. Public Health 2018,15, 2381 13 of 16
4.3. Limitations and Strengths
This study had several limitations. First, causality could not be established due to its
cross-sectional design. Second, the mental health recovery patterns that we utilized in this study
were not validated measurements. Moreover, there was no clear definition of the six-patterns
because participants selected the most appropriate mental health status changes subjectively. Third,
the response rate was less than 50%, and previous studies have reported its correlation with mental
health status, which suggests non-response as a consequence to poor mental health status [
56
]. Many
evacuees in poor condition may not have wanted to or been able to answer the survey, thus leading to
an underestimation in our analysis. Fourth, recall bias should be considered because we conducted
this survey after the disaster and by self-reporting. Finally, the measurements for disaster-related
experience, economic status, general subjective health condition, lifestyle, and social network in this
study were non-validated and subjective. Therefore, caution is necessary in interpreting the findings.
5. Conclusions
Despite these limitations, we were able to show a positive association between mental health
recovery and good general subjective health condition, regular physical activities, and social
networking. In particular, the provision of passive supports and any social roles enabling one to
feel helpful to others could promote mental health recovery. Despite these, disaster-related loss of
employment and economic hardship still hindered mental health recovery, indicating the necessity of
socio-economic support for evacuees and residents in addition to health support. Our findings could
potentially aid in preparing to support evacuees in future disasters.
Supplementary Materials:
The following are available online at http://www.mdpi.com/1660-4601/15/11/2381/
s1, Table S1: Disaster-related experience and current economic status (Evacuation/Non-evacuation area).
Author Contributions:
H.O. and S.Y. conceived and designed the framed study. M.M.(Masaharu Maeda), S.N.,
Y.T., A.I., and M.M. (Maho Momoi) contributed to designing the questionnaire. S.Y. contributed to discussing the
statistical method and the interpretation of our findings as an epidemiological study. M.M. (Masaharu Maeda)
and S.N. contributed to discussing the interpretation of our findings as a mental health specialist. M.O. conducted
the questionnaire survey, analyzed the data, and wrote the paper. All authors contributed to revisions of the
manuscript and critical discussion.
Acknowledgments:
This study was supported by a grant from KAKENHI, the Japan Society for the Promotion of
Science (JSPS), as a Grant-in-Aid for Scientific Research (C) research (JSPS KAKENHI Grant Number: 16K09136).
Conflicts of Interest: The authors declare no conflict of interest.
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