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The Great East Japan earthquake, subsequent tsunamis and the Fukushima nuclear incident had a tremendous impact on Japanese society. Although small-scale surveys have been conducted in highly affected areas, few have elucidated the disaster’s effect on health from national perspective, which is necessary to prepare national policy and response.
The aim of the present study was to describe prefecture-level health status and investigate associations with number of aftershocks, seismic intensity, a closer geographical location to the Fukushima Nuclear Power Plant, or higher reported radiation dose in each prefecture even after adjusting for individual socioeconomic factors, by utilizing individual-level data acquired from a national cross-sectional Internet survey as well as officially reported prefecture-level data.
A Japanese government research institute obtained 12,000 participants by quota sampling and 7335 participants were eligible for the analysis in an age range between 17 and 27 years old. We calculated the percentage of people with decreased subjective health in each prefecture after the earthquake. Variability introduced by a small sample size for some prefectures was smoothed using empirical Bayes estimation with a random-intercept logistic model, with and without demographic factors. Multilevel logistic regression was used to calculate adjusted odds ratios (ORs) for change of subjective health associated with prefecture-level and individual-level factors.
Adjusted empirical Bayes estimates were higher for respondents commuting in the northeast region (Iwate 14%, Miyagi 19%, and Fukushima 28%), which faces the Pacific Ocean, while the values for Akita (10%) and Yamagata (8%) prefectures, which do not face the Pacific Ocean, were lower than those of Tokyo (12%). The values from the central to the western region were clearly lower. The number of aftershocks was coherently associated with decreased health (OR 1.05 per 100 times, 95% CI 1.04-1.06;
We found nationwide differences that show decreased health status because of the Great East Japan disaster according to prefecture. The number of aftershocks, change in work conditions, being female, a higher age, and duration of the evacuation were risk factors for the population after the major earthquake, tsunamis, and nuclear incident.
The Great East Japan earthquake (Tohoku earthquake) on March 11, 2011 and the subsequent tsunami had a tremendous impact on Japanese society [
Unlike impromptu and unsystematic surveys on health, many younger persons tried to empower others in disaster-struck areas promptly through the use of Internet technologies. Physicians and hospital officials in affected areas reported their medical resource status utilizing email lists or social media such as Twitter, which made a definite difference in the disaster response compared with the Great Hanshin earthquake of 1995 [
Public health assessments as well as constructive advice via the Internet have unique advantages in terms of a more rapid and broader reach [
Although the elderly or children may be the most vulnerable, a previous study indicated disruption of work after natural disaster as being independently associated with decreases in general mental and physical health among university students [
We hypothesized that there are positive associations between the decreased subjective health of the young population nationwide and a larger number of aftershocks, a closer geographical location to the Fukushima NPP, or a higher reported radiation dose in the atmosphere in each region even after adjusting for individual socioeconomic factors. Therefore, the aim of the present study is to describe prefecture-level health status and investigate the associations mentioned above after adjusting for individual socioeconomic factors, utilizing individual-level data acquired from a national cross-sectional survey as well as officially reported prefecture-level data.
The data for this secondary analysis, an Internet survey on the effects of the Great East Japan Disaster on career and wage among a young generation (2012), were provided by the Social Science Japan Data Archive, Centre for Social Research and Data Archives, Institute of Social Science, The University of Tokyo. The Internet survey was conducted in January 2012 to investigate the short-term effect of the Great East Japan earthquake on the wages of college or high-school graduates focusing on the role of the quality of education, by the Economic and Social Research Institute, Cabinet Office, Government of Japan [
The survey recruited 12,000 young voluntary participants of a major Internet service in Japan based on quota sampling method [
Approximately 93% of respondents did not report clearly defined adverse effects caused by the disaster. A small percentage of these participants experienced the loss of second-degree relatives (0.3%) and 0.3% experienced injuries caused by the disaster. Other adverse events included collapse of their house or official evacuation because of the crisis at the Fukushima NPP.
The survey asked questions directly related to the disaster. The data included a change of self-perceived health status after the disaster. The question asked was, “Did your health status change because of the Great East Japan Disaster?” There were seven categories for answers: highly improved, improved, relatively improved, unchanged, relatively decreased, decreased, and highly decreased. We categorized these seven categories into two, not-decreased and decreased, because we intended to focus on the binary difference between health and poor health. Furthermore, few respondents answered “highly improved” and “improved,” so the two categories seemed to provide a valid comparison. This binary health status change was set as the outcome variable.
We categorized geographic location based on prefectures where respondents commuted according to the values assigned by the Japan Meteorological Agency Seismic Intensity scale (JMA-SI), 0-7, and the radiation dose published by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan [
We introduced six area indicators: Northwest region; Iwate, Miyagi, and Fukushima; Kanto region; Central region; Kansai region; and Western region as shown in
Map of Japan divided into six area indicators. The black square indicates the epicentre of the earthquake. The black star indicates the location of the Fukushima NPP.
Marital status was based on current status, so that widows or divorcées were classified as not married. These participants were categorized in the following manner: never married, 94.1%; married, 5.8%; widows, 0.1%; and divorced, 0.2%. Respondents were asked to answer “No” to the questions about change in employment if the corresponding conditions were caused by intentional career changes or other personal reasons. If a person had lived apart from other family members before the disaster, respondents were asked to answer “No” to questions about separation from their families. A change of working conditions included a reduction of sales (5.1%), reduction and upgrade of graduate recruitment (2.9%), merger and acquisition (0.8%), attrition (1.8%), damage of plants or capital (7.2%), temporary suspension of business (8.1%), and reduction of compensation (2.1%). Participants answered only when the condition was true. Individual economic status was assessed according to income. A difference in income between in 2010 and after the disaster in 2011 was categorized as “minus 2 levels” or “plus 1 level,” where a unit of “level” represented approximately one million yen. In contrast, an expected decrease of income in the 2012 fiscal year was answered yes or no.
We calculated the percentage of people with decreased self-perceived health status in each prefecture. Because sampling error from the Internet survey seemed to render the percentages highly variable due to the small sample size in individual prefectures, we smoothed the actual percentages with empirical Bayes predictions from the multilevel (mixed effects) logistic regression by introducing random intercepts for 47 prefectures and an overall constant (the mean across all clusters/population mean) [
To identify a regional association between the change of self-perceived health status and environmental factors (prefecture-level variables), the odds ratios (ORs) and their 95% CIs were calculated from fixed-effects logistic models. Predictor variables included (a) radiation dose, distance from the Fukushima NPP, JMA-SI, and number of aftershocks from March 11, 2011 to January 31, 2011 with or without (b) the area indicators in Japan. We calculated crude and adjusted ORs from univariable and from multivariable-adjusted logistic models, respectively. Model 1 included prefecture-level variables (a), Model 2 included the area indicator (b), and Model 3 simultaneously introduced all prefecture-level variables (a) and (b). We fitted different models for sensitivity analysis rather than for model building with a rejection of unnecessary covariates, although Akaike's Information Criterion (AIC, which measures prediction error by estimating the mean of Kullback-Leibler divergence over asymptotic sampling distributions) was presented not so as to search for an accurate prediction, but just as a reference for readers.
To simultaneously estimate the association of prefecture-level variables and demographic variables (individual-level variables), including loss of family, changes in work conditions, individual economic status, experience of evacuation and separation from family, to self-perceived health status, we fitted multilevel logistic regression models that included random-intercepts for 47 prefectures and the above prefecture- and individual-level variables. The sensitivity of individual-level effects to adjustment for prefecture-level variables was analysed by fitting different models conducted in the same manner as above: Model 1 included individual-level variables only; Model 2 adjusted Model 1 with the prefecture-level variables (a); and Model 3 simultaneously adjusted for prefecture-level variables (a) and area indicators (b).
The variables included in the models were selected from a questionnaire regarding the existing literature, which investigated the effects of the disaster on subsequent distress. Because of unclear previous knowledge on interactions, we did not conduct stratified analyses and did not include interaction terms in the multivariable models. Conformity with a linear gradient in the model was checked graphically before fitting regression models. All statistical and graphical analyses were conducted using R version 3.0.1 for Windows. The lme4 and glmmML packages were primarily used.
Respondents’ demographic characteristics are shown in
The decrease in self-perceived health status differed significantly among respondents in the prefectures as shown in
Compared with Tokyo, respondents commuting in Miyagi and Fukushima prefectures, which are located adjacent to Fukushima, showed a statistically significant decrease in health status. Respondents commuting in Iwate and Tochigi prefectures also reported an increased reduction in health status, although the differences were not statistically significant. The values were higher for respondents commuting in the Tohoku area (Iwate, Miyagi, and Fukushima), which faces the Pacific Ocean, while the values for Akita and Yamagata prefectures, which do not face the Pacific Ocean, were lower than those of Tokyo. In contrast, there were many prefectures where respondents’ health status was less likely to be reduced, particularly in Hokkaido and the central and western regions of Japan. In addition to those in Tokyo, those commuting in Okinawa, Kochi, and Toyama prefectures also reported a high frequency of decreased health status. In general, young people commuting in Tokyo reported a relatively higher reduction of their perceived health status compared with those commuting in many western regions of Japan.
Demographic characteristics by the change of subjective health.
|
Perceived health status | ||
Variables | Decreased (n=649) | Not decreased (n=6686) | |
|
n (%) or mean (SD) | n (%) or mean (SD) | |
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Male | 262 (40.37) | 3097 (46.32) |
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Female | 387 (59.63) | 3589 (53.68) |
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17 years old | 4 (0.62) | 49 (0.73) |
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18 years old | 5 (0.77) | 107 (1.60) |
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19 years old | 14 (2.16) | 196 (2.93) |
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20 years old | 24 (3.70) | 372 (5.56) |
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21 years old | 38 (5.86) | 459 (6.87) |
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22 years old | 77 (11.86) | 794 (11.88) |
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23 years old | 107 (16.49) | 984 (14.72) |
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24 years old | 127 (19.57) | 1363 (20.39) |
|
25 years old | 132 (20.34) | 1269 (18.97) |
|
26 years old | 67 (10.32) | 623 (9.32) |
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27 years old | 54 (8.32) | 470 (7.03) |
|
Mean age (SD) | 23.74 (2.04) | 23.48 (2.17) |
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College students | 462 (71.19) | 4701 (70.31) |
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Not college students | 187 (28.81) | 1985 (29.69) |
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Married | 42 (6.47) | 390 (5.83) |
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Not married | 607 (93.53) | 6296 (94.17) |
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Regular employee | 248 (38.21) | 2375 (35.52) |
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Not regular employee | 401 (61.87) | 4311 (64.48) |
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Yes | 245 (37.50) | 1371 (20.51) |
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No | 404 (62.25) | 5315 (79.49) |
Difference of income 2011–2010a, mean (SD) | 0.27 (1.50) | 0.20 (1.38) | |
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Will be decreased | 45 (6.93) | 361 (5.40) |
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Will be increased/stable | 604 (93.07) | 6325 (94.60) |
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> 1 | 3 (0.46) | 16 (0.24) |
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0 | 646 (99.54) | 6670 (99.76) |
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Yes | 24 (3.70) | 263 (3.93) |
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No | 625 (96.30) | 6423 (96.07) |
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> 4 weeks | 66 (10.17) | 396 (5.92) |
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≤ 4 weeks | 583 (89.83) | 6290 (94.08) |
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> 4 weeks | 91 (14.02) | 528 (7.90) |
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≤ 4 weeks | 558 (85.98) | 6158 (92.10) |
aChange of categorical level, where a unit of “level” represented approximately one million yen. Example: difference is −2 when the level was 5 in 2010 and 3 in 2011.
Commuting location and the decreased self-perceived health.
|
JMA-SI (level) a | Radi (µSv/h) | Quake (times) | Decreased (n) | Not decreased (n) | Decreased (%) |
|
Miyagi | 7 | 0.111b | 2841 | 28 | 93 | 23.1 | .002d |
Fukushima | 6 | 2.5c | 4211 | 26 | 44 | 37 | <.001e |
Tochigi | 6 | 0.154 | 1552 | 11 | 43 | 20 | .09 |
Iwate | 6 | 0.027 | 2304 | 9 | 40 | 18 | .19 |
Ibaraki | 6 | 0.176 | 3422 | 16 | 78 | 17 | .20 |
Aomori | 5 | 0.02 | 818 | 8 | 36 | 18 | .25 |
Tokyo | 5 | 0.048 | 691 | 232 | 1643 | 12.37 | Reference |
Chiba | 5 | 0.033 | 1526 | 22 | 176 | 10.9 | .73 |
Akita | 5 | 0.034 | 644 | 3 | 26 | 10 | 1.00 |
Saitama | 5 | 0.057 | 946 | 21 | 187 | 10.1 | .37 |
Nagano | 5 | 0.069 | 868 | 8 | 73 | 10 | .60 |
Kanagawa | 5 | 0.049 | 435 | 40 | 387 | 9.4 | .09 |
Yamagata | 5 | 0.04 | 862 | 3 | 33 | 8 | .61 |
Gunma | 5 | 0.08 | 939 | 6 | 75 | 7 | .22 |
Niigata | 5 | 0.047 | 817 | 6 | 82 | 7 | .13 |
Yamanashi | 5 | 0.044 | 262 | 2 | 30 | 7 | .42 |
Gifu | 4 | 0.062 | 212 | 9 | 106 | 7.8 | .18 |
Hokkaido | 4 | 0.027 | 395 | 17 | 229 | 6.9 | .01f |
Shizuoka | 4 | 0.037 | 371 | 11 | 172 | 6.0 | .008d |
Aichi | 4 | 0.041 | 79 | 19 | 533 | 3.4 | <.001e |
Toyama | 3 | 0.047 | 77 | 8 | 50 | 14 | .69 |
Shiga | 3 | 0.034 | 57 | 7 | 56 | 11 | 1.00 |
Nara | 3 | 0.048 | 42 | 5 | 61 | 8 | .34 |
Fukui | 3 | 0.045 | 54 | 3 | 47 | 6 | .27 |
Hyogo | 3 | 0.037 | 47 | 18 | 290 | 5.8 | <.001e |
Kyoto | 3 | 0.039 | 43 | 12 | 208 | 5.5 | .002d |
Mie | 3 | 0.046 | 38 | 5 | 87 | 5 | .048f |
Osaka | 3 | 0.043 | 43 | 31 | 693 | 4.3 | <.001e |
Ishikawa | 3 | 0.046 | 88 | 2 | 52 | 4 | .056 |
Shimane | 2 | 0.036 | 38 | 3 | 31 | 9 | .79 |
Wakayama | 2 | 0.032 | 92 | 4 | 45 | 8 | .51 |
Okayama | 2 | 0.049 | 31 | 5 | 109 | 4.4 | .007d |
Totori | 2 | 0.063 | 21 | 0 | 28 | 0 | .04f |
Tokushima | 2 | 0.039 | 29 | 0 | 41 | 0 | .007d |
Kochi | 1 | 0.026 | 33 | 4 | 26 | 13 | .78 |
Kagawa | 1 | 0.053 | 21 | 3 | 40 | 7 | .36 |
Nagasaki | 1 | 0.029 | 21 | 3 | 40 | 7 | .36 |
Fukuoka | 1 | 0.037 | 25 | 14 | 224 | 5.8 | .002d |
Oita | 1 | 0.05 | 39 | 2 | 39 | 5 | .22 |
Hiroshima | 1 | 0.05 | 52 | 7 | 147 | 4.5 | .002d |
Kumamoto | 1 | 0.027 | 75 | 2 | 49 | 4 | .08 |
Kagoshima | 1 | 0.035 | 130 | 1 | 41 | 2 | .053 |
Ehime | 1 | 0.047 | 28 | 1 | 60 | 2 | .007d |
Saga | 1 | 0.04 | 12 | 0 | 19 | 0 | .16 |
Okinawa | 0 | 0.021 | 56 | 5 | 29 | 15 | .60 |
Miyazaki | 0 | 0.027 | 44 | 3 | 24 | 11 | 1.00 |
Yamaguchi | 0 | 0.094 | 21 | 4 | 61 | 6 | .17 |
aJMA-SI, Japan Meteorological Agency seismic intensity; Radi, radiation dose on March 20, 2011 (µSv/h); Quakes, total number of aftershocks from March 11, 2011 to January 31, 2012.
bObtained initially at 19:00 on March 29, 2011.
cObtained initially at 13:00 on April 6, 2011.
dMean < .01.
eMean <.001.
fMean < .05.
Empirical Bayes estimates from random-effects logistic models of each prefecture’s proportion of respondents with decreased self-perceived health status, as well as the actual percentages from
The percentages of respondents commuting in Tochigi and Ibaraki prefectures as well as Iwate, Miyagi, and Fukushima are the highest. Surprisingly, the percentages for respondents commuting in Tokyo and Chiba are higher compared with the rest of Japan. In contrast, the percentage of reports of decreased health status from central to the western region (Aichi, Osaka, and prefectures located at more western than them) is clearly lower (
Percentage of respondents reporting decreased self-perceived health status and empirical Bayes estimates in each prefecture. JMA-SI, Japan Meteorological Agency Seismic Intensity. For the same JMA-SI levels, we determined the rank order of prefectures based on the values of adjusted empirical Bayes estimates. In adjusted empirical Bayes estimates, percentages were also adjusted according to demographic factors (gender, age, education, marital and employment status, changed job condition, income, death of family member[s], being a parent, family separation, and evacuation).
Map of Japan depicting adjusted empirical Bayes estimates for percentage of people with decreased self-perceived health status. Red (>21%), orange (18%–21%), yellow (15%–18%), chartreuse green (12%–15%), aquamarine (9%–12%), blue (6%–9%), and gray (<6%). The black square indicates the epicenter of the earthquake. The black star indicates the location of the Fukushima NPP.
The regional association between the change of self-perceived health status and prefecture-level variables estimated from fixed-effects logistic models are depicted in
The results from random-intercept multilevel logistic models for the probability of decreased self-perceived health status including individual-level demographic variables and/or prefecture-level variables are presented in
The radiation levels reported relatively soon, or considerably after the Fukushima NPP crisis and the distance from the nuclear power plant are not significantly associated with decreased health status after adjusting for covariates and potential covariates. The death of family members is not significantly associated with decreased health status because of the small number of events.
Prefecture-level factors associated with decreased health status: regional-level logistic regression analysis.
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Model 1 | Model 2 | Model 3 | |||
Independent variables | Crude ORa
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Adjusted OR |
|
Adjusted OR |
|
Adjusted OR |
|
From Fukushima NPPb (km) | 0.99 (0.99-1.00) | 1.00 (0.99-1.00) | .29 | – | – | 1.00 (1.00-1.00) | .65 |
Radiationc (μSv/hr) | 2.09 (1.72-2.55) | 1.16 (0.87-1.53) | .31 | – | – | 1.11 (0.81-1.51) | .51 |
Total quakesd (x10−2) | 1.05 (1.04-1.06) | 1.03 (1.01-1.05) | <.001 | – | – | 1.03 (1.00-1.05) | .02 |
JMA-SIe | 1.38 (1.29-1.47) | 1.18 (1.08-1.29) | <.001 | – | – | 0.90 (0.68-1.20) | .46 |
Northwest region | 0.98 (0.68-1.44) | – | – | 1.69 (1.07-2.67) | .02 | 2.11 (0.80-5.58) | .13 |
Iwate, Miyagi, and Fukushima | 3.95 (2.93-5.34) | – | – | 6.29 (4.25-9.32) | <.001 | 4.63 (1.10-19.57) | .04 |
Kanto region | 1.82 (1.55-2.14) | – | – | 2.37 (1.77-3.16) | <.001 | 2.93 (0.99-8.66) | .05 |
Central region | 0.57 (0.44-0.74) | – | – | 1.05 (0.73-1.52) | .77 | 1.34 (0.56-3.23) | .51 |
Kansai region | 0.53 (0.41-0.67) | – | – | 1.01 (0.72-1.43) | .97 | 1.23 (0.65-2.32) | .53 |
|
|
AICf value = 4252 | AIC value = 4244 | AIC value = 4241 |
aOR, odds ratio
bNPP, nuclear power plant
cRadiation, radiation dose on March 20, 2011 (μSv/h)
dTotal quakes, total number of aftershocks from March 11, 2011 to January 31, 2012
eJMA-SI, Japan Meteorological Agency seismic intensity
fAIC, Akaike's Information Criterion
Individual- and prefecture-level factors associated with decreased health status: multilevel logistic regression analysis with random-intercept for 47 prefectures.
|
|
Model 1 | Model 2 | Model 3 | |||
Independent variables | Crude ORa
|
Adjusted OR |
|
Adjusted OR |
|
Adjusted OR |
|
Regular employee (ref: not) | 0.89 (0.75-1.05) | 0.85 (0.71-1.01) | .07 | 0.85 (0.71-1.01) | .06 | 0.85 (0.71-1.02) | .07 |
Change in job condition |
2.35 (1.98-2.79) | 2.12 (1.77-2.52) | <.001 | 2.05 (1.72-2.45) | <.001 | 2.05 (1.72-2.45) | <.001 |
Difference in income |
1.03 (0.98-1.09) | 1.03 (0.97-1.09) | .35 | 1.03 (0.97-1.09) | .34 | 1.02 (0.97-1.09) | .35 |
Income will decrease |
1.31 (0.95-1.80) | 1.31 (0.94-1.83) | .11 | 1.31 (0.94-1.82) | .11 | 1.31 (0.95-1.84) | .10 |
Sex (male=1, female=0) | 0.78 (0.67-0.92) | 0.71 (0.60-0.84) | <.001 | 0.71 (0.60-0.84) | <.001 | 0.70 (0.59-0.84) | <.001 |
Age (year) | 1.06 (1.02-1.10) | 1.06 (1.02-1.11) | .006 | 1.06 (1.02-1.11) | .005 | 1.06 (1.02-1.11) | .005 |
Marital status |
1.12 (0.80-1.55) | 0.94 (0.66-1.33) | .72 | 0.92 (0.65-1.30) | .64 | 0.92 (0.65-1.30) | .63 |
College student (ref: not) | 1.04 (0.87-1.25) | 1.00 (0.82-1.22) | .99 | 0.99 (0.82-1.22) | .996 | 1.00 (0.83-1.27) | .95 |
Family separation |
1.80 (1.37-2.37) | 1.22 (0.85-1.74) | .28 | 1.21 (0.85-1.74) | .28 | 1.21 (0.85-1.73) | .30 |
Evacuation |
1.90 (1.50-2.41) | 1.48 (1.08-2.03) | .01 | 1.45 (1.06-1.98) | .02 | 1.44 (1.06-1.97) | .02 |
Death of family members |
1.94 (0.56-6.66) | 2.33 (0.66-8.26) | .19 | 2.28 (0.65-8.03) | .20 | 2.34 (0.66-8.26) | .19 |
Having a child/children |
0.94 (0.61-1.44) | 0.93 (0.60-1.44) | .75 | 0.94 (0.61-1.45) | .77 | 0.93 (0.59-1.44) | .74 |
From Fukushima NPPb
|
0.99 (0.99-1.00) | – | – | 0.99 (0.99-1.00) | .57 | 1.00 (0.99-1.00) | .66 |
Radiationc (μSv/hr) | 2.09 (1.72-2.55) | – | – | 1.17 (0.80-1.69) | .42 | 1.16 (0.82-1.64) | .41 |
Total quakesd ( x10−2) | 1.05 (1.04-1.06) | – | – | 1.04 (1.01-1.06) | .002 | 1.02 (1.00-1.05) | .049 |
JMA-SIe | 1.38 (1.29-1.47) | – | – | 1.07 (0.96-1.20) | .24 | 0.87 (0.65-1.17) | .36 |
Northwest region | 0.98 (0.68-1.44) | – | – | – | – | 2.21 (0.78-6.26) | .14 |
Iwate, Miyagi, and Fukushima | 3.95 (2.93-5.34) | – | – | – | – | 4.45 (0.99-20.01) | .05 |
Kanto region | 1.82 (1.55-2.14) | – | – | – | – | 2.94 (0.94-9.18) | .06 |
Central region | 0.57 (0.44-0.74) | – | – | – | – | 1.49 (0.59-3.78) | .40 |
Kansai region | 0.53 (0.41-0.67) | – | – | – | – | 1.32 (0.66-2.62) | .43 |
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AICf: 4185 |
|
AIC: 4155 |
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AIC: 4158 |
|
aOR, odds ratio
bNPP, nuclear power plant
cRadiation, radiation dose on March 20, 2011 (μSv/h)
dTotal quakes, total number of aftershocks from March 11, 2011 to January 31, 2012
eJMA-SI, Japan Meteorological Agency seismic intensity
fAIC, Akaike's Information Criterion
We first illustrate a prefecture-level difference that shows decreased health status because of the Great East Japan Disaster. Our study found three novel findings. First, the present study shows a coherent association between decreased health status and number of aftershocks. Second, the prefecture-level radiation dose reported after the Fukushima Nuclear Crisis and the distance from the NPP of each prefecture are not significantly associated with decreased health status after adjusting for covariates and potential covariates. Third, we showed coherently that changes in job condition, being female, higher ages in the late teens and 20s, and duration of evacuation longer than 4 weeks were associated with a nationwide decreased health status even after adjusting for regional-level and prefecture-level variables.
People living relatively far from the disaster site tended to be more concerned about the political and economic situation [
Consistent with a previous study [
We believe that the present study has several significant strengths. First, we considered self-perceived health, which could include both physical and psychological aspects of health. This allowed us to evaluate general health as a whole rather than focusing on specific diseases. For instance, we could include relatively moderate illnesses that would escape inclusion in studies based on hospital records. A previous study reported that people who were professionally exposed to a disaster reported more physical and mental health complaints even in the absence of abnormal clinical laboratory values [
Our study has several limitations. First, respondents may not represent the entire population of Japanese of the same age range because the data were not collected randomly. Therefore, the data may be biased toward participants possessing higher Internet literacy or health status and who are more likely to answer the questionnaire voluntarily. Despite the relatively limited target population analyzed here, we are confident that the results can be generalized to this entire age group across Japan, because of the common ability to access the Internet among those in this age range. Second, our data was derived from a cross-sectional survey, which does not allow determination of the direction of the relationships between demographic variables and self-perceived health status. Third, there is no information on specific reasons why participants answered that they were experiencing diminished health. However, the questionnaire was sufficiently well-controlled because all questions always included the criterion, “because of the disaster,” and not just “after the disaster.” Therefore, we could assume that we minimized the probability that the reported decrease in subjective health was derived from other causes. Last, one question asked study participants, “In what prefecture do you commute?” Therefore, we could not predetermine the location of residence. Because some employees or students might commute between prefectures, the distribution shown in the map of Japan may change if we specified the location of residence. Despite these limitations, the data presented here on post-earthquake subjective health status of this age group across the nation are worth reporting.
Future major earthquakes may affect health among the broader population, including youth, across the nation via persistent aftershocks and other socioeconomic disruption. Assessing public health status promptly across a nation is of major relevance to health policy decision makers as well as researchers looking at disasters. Assessments via the Internet may be a better measure in public health emergencies and subsequent phases compared to traditional paper-and-pencil-based surveys, especially for subgroups accustomed to Web technologies [
We first investigated the extent to which subjective health of participants in each prefecture across Japan decreased as a result of the Great East Japan Disaster. We found that the number of aftershocks was coherently associated with decreased subjective health. In contrast, radiation dose and distance from the Fukushima NPP were not associated. A Web-based survey can provide valuable information on public health issues after a disaster, especially if information technologies are developed that integrate with epidemiology research.
Akaike's Information Criterion
Japan Meteorological Agency seismic intensity
Ministry of Education, Culture, Sports, Science and Technology
Nuclear Power Plant
odds ratio
We appreciate the two reviewers who provided constructive comments on the previous version of our manuscript that we believe considerably improved the quality of the paper. We thank Atsuo Kishimoto, Akio Onishi, Satoko Nishimura, and Shunsuke Yamamoto, Graduate School of Public Policy, University of Tokyo, for fruitful comments on interpretation of the Great East Japan Disaster. We also thank Shigenobu Aoki for sharing R codes to draw a national map of Japan. Asami Matsunaga, Yuki Yonekura, and members of R-lovers let the first author appreciate statistical analysis with R. We thank the participants of the survey; the cabinet office of the japanese government; members of the Centre for Social Research and Data Archives, Institute of Social Science; and The University of Tokyo for their support and contribution to the public benefit. The authors declare that they have no actual or potential competing financial interests. Data for the analyses were obtained without any financial support.
None declared.