impact of natural disasters on the functional and health status of patients with rheumatoid...
TRANSCRIPT
ORIGINAL ARTICLE
Impact of natural disasters on the functional and health statusof patients with rheumatoid arthritis
Jun Tomio • Hajime Sato • Hiroko Mizumura
Received: 5 November 2010 / Accepted: 28 December 2010 / Published online: 26 January 2011
� Japan College of Rheumatology 2011
Abstract To examine the effects of natural disasters on
rheumatoid arthritis (RA) patients we conducted a ques-
tionnaire survey targeted to 1,477 members of a nationwide
RA patient group in Japan who lived in the municipalities
affected by natural disasters between 2004 and 2006.
Functional statuses measured by the modified Health
Assessment Questionnaire and self-rated health statuses
before and after the events were retrospectively examined.
The associations between the changes in functional and
health status and socio-demographics, direct damage, and
preparedness status were statistically analyzed. Of the 665
individuals who responded, the data on 192 women RA
patients were analyzed. The values at 1 and 6 months post-
event were the same, with 14% experiencing deteriorations
of functional status, while 22% experienced a worsening of
self-rated health status. Those in poorer functional status
before the events were more likely to experience deterio-
rations of functional [odds ratio (OR) 4.4, 95% confidence
interval (CI) 1.5–13.6] and health (OR 2.8, 95% CI
1.2–6.7) status at both 1 month and 6 months (OR 3.9,
95% CI 1.3–12.0, and OR 2.8, 95% CI 1.2–6.7,
respectively) after the events. Based on these results, we
conclude that the functional and health status of women
RA patients could worsen due to the consequences of a
natural disaster, with a disproportionately large impact
upon those with a poorer functional status.
Keywords Functional status � Natural disasters �Rheumatoid arthritis
Introduction
Recent natural disasters have raised concerns about the
disaster preparedness of the healthcare system for chronic
disease patients [1]. Reports from such disasters in devel-
oped countries have pointed out the burden of chronic
diseases, including hypertension [2, 3] and diabetes [4–6],
emphasizing the need to develop disaster planning for such
patient populations [7]. Policy responses should therefore
be considered for vulnerable subgroups.
Rheumatoid arthritis (RA) is a common chronic disease
with a prevalence of about 0.5–1% in the total population
in Western countries [8], and more than 300,000 people are
estimated to be suffering from RA in Japan [9]. RA
patients, in general, require continuous treatment to
achieve and maintain their remission, otherwise they can
experience flares, resulting in a deterioration of functional
status and the development of severe complications
[10, 11]. Due to the specific nature of the disease, RA
patients require special support under disaster situations to
maintain their routine treatment [12].
Despite the need for preparedness, the impact of natural
disasters on RA patients has not been fully studied. A
survey from the USA after Hurricane Hugo and the Loma
Prieta earthquake in 1989 showed that natural disasters
J. Tomio � H. Sato (&)
Department of Public Health, Graduate School of Medicine,
The University of Tokyo, Hongo 7-3-1,
Bunkyo-ku, Tokyo 113-0033, Japan
e-mail: [email protected]
J. Tomio
Department of Preventive Medicine,
St. Marianna University School of Medicine, Sugao 2-16-1,
Miyamae-ku, Kawasaki, Kanagawa 216-8511, Japan
H. Mizumura
Department of Human Environment Design,
Faculty of Human Life Design, Toyo University,
Oka 48-1, Asaka, Saitama 351-8510, Japan
123
Mod Rheumatol (2011) 21:381–390
DOI 10.1007/s10165-011-0414-y
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could cause physical and mental damage to RA patients
[13], while another survey after the Los Angeles earth-
quake in 1994 found no association between disasters and
health outcomes among RA and systemic lupus erythe-
matosus (SLE) patients [14]. However, these surveys
included only a small number of patients and provide
limited information to develop an effective preparedness
plan for RA patients.
The objectives of this study are to describe the change in
functional and health status among RA patients affected by
natural disasters and to investigate the risk factors associ-
ated with the deterioration of functional and health status.
Materials and methods
Study subjects
The study subjects comprised members of a nationwide RA
patient group in Japan. Of the 17,834 members in January
2007, 1,477 (9%) individuals who, at the end of January
2007, had registered their addresses to the municipalities
where the Disaster Relief Act (DRA) was applied from
January 2004 to December 2006 were enrolled in the study.
DRA and the events
The DRA in Japan, implemented in 1947, defines the
support provided by the government in terms of relief
activities for a designated disaster event to protect victims
and to maintain social order [15]. The DRA is implemented
at the municipality level, i.e., city, town, and village, by
the authority of the prefectural governor of the affected
municipalities. Designation criteria for the disaster event
generally depend on the number of households whose houses
were destroyed and the population size of the municipality.
For example, the DRA is to be applied to a city with a pop-
ulation of 100,000–300,000 if there are greater than 100
households whose houses were destroyed by a disastrous
event [16].
For the 16 disaster events that occurred in Japan during the
3 years from 2004 to 2006, the DRA was applied to 113
municipalities in 21 prefectures, out of the total 1,839
municipalities and 47 prefectures in Japan (Table 1) [17].
The estimated population of these 113 affected municipali-
ties at the beginning of 2007 was about 11 million (9% of the
national population), which corresponded to the proportion
of the enrolled subjects to total members of the patient group
of our study (9%). Of the 16 events, nine occurred in 2004,
two in 2005, and five in 2006. Two were major earthquakes,
and the other 14 were meteorological disasters, including
eight typhoons, three torrential rains, one heavy snow fall,
and one tornado. The damage was largest in Mid Niigata
Prefecture earthquake in 2004, in which 68 people died,
4,795 were injured, and 121,604 houses belonging to
130,077 households were damaged [18].
Survey
Self-administered questionnaires were sent by mail to the
registered address of each subject in February 2007, with
the request that the completed questionnaire be returned
Table 1 List of the disasters for which the Disaster Relief Act was applied (2004–2006)
Month, year Event Affected areaa
November, 2006 Tornado Hokkaido
September, 2006 Typhoon 0613 Miyazaki
July, 2006 Torrential rain Nagano, Kagoshima, Miyazaki
June, 2006 Torrential rain Okinawa
January, 2006 Heavy snow Niigata, Nagano
September, 2005 Typhoon 0514 Tokyo, Yamaguchi, Kochi, Miyazaki, Kagoshima
March and April, 2005 West-off Fukuoka prefecture earthquake Fukuoka
October, 2004 Mid Niigata prefecture earthquake Niigata
October, 2004 Typhoon 0423 Gifu, Kyoto, Hyogo, Tokushima, Kagawa, Miyazaki
October, 2004 Typhoon 0422 Shizuoka
September and October, 2004 Typhoon 0421 and seasonal torrential rain Mie, Hyogo, Ehime
September, 2004 Typhoon 0418 Hiroshima
August and September, 2004 Typhoon 0416 Okayama, Kagawa, Ehime, Miyazaki
August, 2004 Typhoon 0415 Kochi, Ehime
July and August, 2004 Typhoon 0410 Tokushima
July, 2004 Torrential rain Niigata, Fukui
a Names of the prefectures are given although the Disaster Relief Act (DRA) is applied at the municipality level
382 Mod Rheumatol (2011) 21:381–390
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by mail by the end of March 2007. The questionnaire
consisted of two parts; (1) questions about pre- and post-
disaster conditions targeted to those who were affected by
the listed disasters, and (2) questions about current pre-
paredness status targeted to all of the subjects enrolled.
In this study, we exclusively used information from the
former part of the questions. The study protocol and the
questionnaire were reviewed and approved by the institu-
tional review board of Toyo University. The purposes of
the study were explained in the cover letter of the ques-
tionnaire, and only those subjects who agreed to them were
requested to answer and return the questionnaires.
Variables
We developed the questionnaire to determine the following
four domains of variables: (1) socio-demographic factors,
(2) functional and health status, (3) damage-related factors,
and (4) preparedness-related factors. Socio-demographic
factors included patient age as of 1 January 2007, occu-
pational status (employed or unemployed/retired), and
educational level (college graduate level or not). Because
there were only a small number of male patients among the
subjects, analysis was conducted exclusively on female
patients.
The functional status was measured using a modified
Health Assessment Questionnaire (MHAQ) score [19].
Subjects were stratified into two subgroups: (1) better
functional subgroup with a MHAQ score equal to or lower
than the median; (2) poorer functional group with a MHAQ
score higher than the median. Self-rated health status at the
time of the event was determined using a five-grade scale:
excellent, very good, good, fair, and poor. To identify
physical disability status and the requirement for special
supports in daily living, the patients were asked whether they
had a class 1 or 2, i.e. the severest subgroups, physically
disabled persons’ certificate and whether they were receiv-
ing healthcare services under the Long-term Care Insurance
(LTCI) system in Japan at the time the disaster occurred.
Damage-related factors included health-related damage,
property damage, and evacuation status. For health-related
damage, direct health damage due to the disaster, inter-
ruption of medication treatment, or disturbance of routine
healthcare visit were determined. Patients were considered
to have experienced an interruption of medication if they
missed at least one dose of prescribed medications for RA
during the acute phase of the disaster. Similarly, patients
were considered to have experienced a disturbance of a
routine visit if they could not visit a medical facility, if they
were forced to postpone a visit, or if they visited alternative
medical facilities during the acute phase of the disaster.
Property damage was defined as positive if the damage to
patients’ residences was equivalent to inundation above the
floor level in floods and partial destruction in earthquakes.
Lifeline damage was defined as the interruption of either
electricity, gas, water, or telecommunications, or any
number of these, in their residences. For an assessment of
evacuation status, the patients were asked whether they
evacuated when the event occurred.
For preparedness behaviors, we asked whether the
subjects fulfilled each of 15 preparedness actions in the
following four domains: medication treatment, access to
healthcare facilities, household level preparedness, and
community level preparedness (Appendix). Patients were
regarded as fulfilling the preparedness behaviors of each
domain if they answered ‘‘yes’’ to at least one item in each
domain.
The outcomes were measured by a deterioration of
functional status and self-rated health status at 1 and
6 months post-event/disaster. Any change in functional
status was measured using eight items of the MHAQ with a
three-grade scale: better, about the same, and worse at 1
and 6 months post-event compared to before the event. The
score of -1, 0, and 1 were allocated for the answer of
better, about the same, and worse, respectively; an average
score for the eight items of \0 was regarded as indicative
of a deterioration of functional status. Changes in health
status at 1 and 6 months post-event were measured using
the five-grade scale: much better, somewhat better, about
the same, somewhat worse, and much worse, with either
somewhat worse or much worse being recognized as a
deterioration of health status.
Statistical analysis
The prevalence of those RA patients who experienced
deteriorations in functional and health status at 1 and
6 months post-event was presented with frequency distri-
butions. For each outcome variable, odds ratios (ORs) were
calculated for patient characteristics, health status, damage-
related factors, and preparedness status. In order to identify
the associations after controlling for the effects of relevant
factors, we performed multivariable logistic regression
analysis for each outcome variable. Those variables with
P values \ 0.1 in the bivariate analysis as well as the age
variable were included into the multivariable models. All
statistical analyses were performed using STATA ver. 10.1
(StataCorp, College Station, TX).
Results
Of the 1,477 enrolled subjects, 665 (45%) returned a
completed questionnaire providing valid information on
age and sex. Of these, 346 (52% of the valid responses) had
been affected by the disasters shown in Table 1, and of
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these 346, 246 (71% of those affected by disasters) had
been diagnosed with RA prior to the disasters. Of these 246
respondents meeting these two criteria, 229 (93%) were
women; 192 (84%) of these women provided valid
responses to the questions on functional status just before
the event and at 1 and 6 months post-event. The study
cohort therefore comprised 192 women.
The mean age of the participants was 60.8 years, and 75
(39%) were C65 years of age; 164 (85%) were unemployed
or retired, and 58 (31%) were college graduates (Table 2).
Forty-seven (24%) patients had class 1 or 2 physically
disabled persons’ certificates; 25 (13%) received LTCI
services; 101 (53%) had comorbid conditions other than
RA. Before the event the median MHAQ score was 0.625
(interquartile range 0.125–1.375), and 109 (57%) were
assessed as having a fair to poor health status. Seventy-three
(38%) patients were mainly affected by earthquakes,
including 34 affected by the Mid Niigata Prefecture earth-
quake in 2004, while the other 119 (62%) were affected by
typhoons and/or heavy rains. Nearly half of the subjects
suffered damage to their own houses or to lifelines, and 16%
experienced evacuation. With regards to health-related
damage, 8% had direct health damages, including injuries
and illnesses due to the disasters, 13% experienced distur-
bance of routine healthcare visits, and 10 (5%) of the 185
subjects receiving prescribed medications for RA experi-
enced an interruption to their medication treatment. In terms
of preventive behaviors, 77% prepared for continuing
medication treatment and 26% for maintaining healthcare
access. Half of the subjects took preventive behaviors at the
household level and 24% at the community level.
There was no difference in the values at 1 and 6 months
post-event, and at both time points 14% of the respondents
reported having experienced a deterioration of functional
status and 22% reported a worse self-rated health status
(Table 3).
Multivariable logistic regression analysis showed that
the subjects with a higher MHAQ score, or poorer func-
tional status, were more likely to experience a deterioration
of functional status both at 1 month [OR 4.4, 95% confi-
dence interval (CI) 1.5–13.6] and at 6 months (OR 3.9,
95% CI 1.3–12.0) after the event after controlling for the
effects of other variables (Table 4). Those that suffered
property damage were also at a higher risk of experiencing
a deterioration of functional status at 1 month post-event
(OR 3.1, 95% CI 1.0–9.2) and of experiencing a borderline
higher risk at 6 months post-event (OR 2.7, 95% CI
1.0–7.6) (Table 5). The respondents with a higher MHAQ
score and those who experienced evacuation were also
more likely to have experienced a deterioration of self-
rated health status at both 1 month (OR 2.8, 95% CI
1.2–6.7, and OR 3.6, 95% CI 1.3–9.4, respectively) and
6 months (OR 2.8, 95% CI 1.2–6.7, and OR 3.3, 95% CI
1.2–9.1, respectively) after the event. Those with lifeline
damages were more likely to experience a deterioration of
self-rated health status at 1 month post-event (OR 2.3, 95%
CI 1.0–5.4), although statistically significant associations
were not found at the 6 month time point. Those with a fair
to poor health status before the event were more likely to
experience a deterioration of self-rated health status at
6 months post-event (OR 3.3, 95% CI 1.3–8.5).
Socio-demographic status, type of the hazards, and the
scale of the disaster were not significantly associated with
any of the outcomes, and preparedness behaviors were
generally not associated with the outcomes. The crude OR
for functional deterioration at 1 month post-event suggested
negative effects of preparedness at the community level,
although the association was not statistically significant after
controlling for other variables (OR 1.9, 95% CI 0.7–5.3).
Discussion
In the present study, we investigated the health conse-
quences and potential risk factors for deterioration of
functional and health status after natural disasters in
women RA patients who belonged to a large nationwide
RA patient group in Japan. Among them, about one in
seven patients experienced a deterioration of functional
status at 1 month and 6 months after the natural disaster,
and about one quarter of the patients rated their health
status as being worse post-event than before the event.
To date, there has not been any other study that has
compared the functional status of RA patients before and
after they experienced a natural disaster. Our finding that
14% of the respondents reported a worsening in functional
status at 1 and 6 months post-event suggests that natural
disasters could adversely affect the functional status of RA
patients quite soon after the disaster, a change that still has
an impact at 6 months, although further assessments using
a control group are required to confirm this. On the other
hand, the finding that exactly the same proportion of
respondents reported a worsening of functional status at
6 months suggests that the adverse effect of disaster does
not wane after the acute phase. Similar patterns were
observed for the change of self-rated health status. Dete-
riorations compared to the baseline were found in 22% of
patients at both 1 and 6 months after the event. This result
is similar to that (22%) in the study on Sjogren syndrome in
which patients reported experiencing a deterioration of
their symptoms after the Great Hanshin-Awaji earthquake
in 1995 [20], although the study did not specify when they
measured the outcome. However, smaller proportions of
deteriorations were reported by another survey conducted
by the authors that targeted outpatients with various
chronic conditions living in a flood affected area (9% at
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1 month, and 4% at 6 months after the event) [21]. These
findings suggest that patients with collagen disease,
including RA, might be more vulnerable to the conse-
quences of natural disasters compared to those with other
chronic conditions. Interestingly, the pattern of change was
quite similar to that observed for functional status. This
trend was also seen in the change in pain ratings among the
RA patients affected by Hurricane Hugo or the Loma Prieta
earthquake in 1989 [13]. One small survey of RA and SLE
patients after the Los Angeles earthquake in 1994 showed
no deterioration after the earthquake in some clinical
indicators, such as the experience of clinical flare and
erythrocyte sedimentation rate [14]. However, our results
suggest that natural disasters will lead to some adverse
effect, at least in the short term. Although the functional
status of RA patients naturally gradually worsen with time
Table 2 Characteristics of the
study subjects
SD Standard deviation,
IQR interquartile range,
RA rheumatoid arthritis,
MHAQ modified Health
Assessment Questionnairea Missing data were excludedb Only 185 prescribed patients
were included
Variable Value (n = 192)
Socio-demographic factors
Age (year)
Mean (SD) 60.8 (11.4)
C65 years of age, n (%) 75 (39)
Occupational status
Employed or self-employed, n (%) 28 (15)
Unemployed or retired, n (%) 164 (85)
Highest educational levela
Under college graduate level, n (%) 127 (69)
College graduate level or higher, n (%) 58 (31)
Health-related factors
Pre-event health statusa
Good to Excellent, n (%) 81 (43)
Fair to Poor, n (%) 109 (57)
Physically disabled persons’ certificate
Class 1–2, n (%) 47 (24)
Class 3? or no, n (%) 145 (76)
Receiving Long-term Care Insurance services, n (%) 25 (13)
Comorbid conditions other than RA, n (%) 101 (53)
Pre-event MHAQ score (0–3 points)
Median (IQR) 0.625 (0.125–1.375)
0–0.625, n (%) 98 (51)
0.750–3, n (%) 94 (49)
Disaster-related factors
Direct health damage, n (%) 15 (8)
Property damage, n (%) 81 (42)
Lifeline damage, n (%) 87 (45)
Evacuation, n (%) 31 (16)
Disturbance of healthcare visit, n (%) 25 (13)
Medication interruptionb, n (%) 10 (5)
Type of hazard
Earthquake, n (%) 73 (38)
Meteorological, n (%) 119 (62)
Scale of disaster
Large, n (%) 34 (18)
Moderate–Mild, n (%) 158 (82)
Preparedness behaviors
Preparedness for medication treatmentb, n (%) 143 (77)
Preparedness for healthcare access, n (%) 49 (26)
Household level preparedness, n (%) 96 (50)
Community based preparedness, n (%) 47 (24)
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[22], the gap between the considerable changes in the first
1 month and almost no change in the proportion of patients
deteriorating thereafter supports the fact that the deterio-
rations observed in our study cannnot be considered to be
simply due to the natural progression of the disease.
In terms of the risk factors for health damage after a
disaster, we found that those patients with a poorer func-
tional status before the event were more likely to report a
worsening in functional and self-rated health status at both
1 and 6 months post-event. Those with a relatively poorer
functional status before the event (as measured by the
MHAQ score) were about fourfold more likely to suffer
Table 3 The numbers and proportions of respondents experiencing a
deterioration of functional and self-rated health status at 1 and
6 months post-event
Variable Value (n = 192)
Functional status deterioration
1 month after the event, n (%) 27 (14)
6 months after the event, n (%) 27 (14)
Self-rated health status deteriorationa
1 month after the event, n (%) 42 (22)
6 months after the event, n (%) 42 (22)
a Missing data were excluded (n = 190)
Table 4 Associations between deterioration of functional status and potential risk factors at 1 and 6 months after the events (n = 192)
Variable 1 month post-event 6 months post-event
Bivariate OR
(95% CI)
Multivariable OR
(95% CI)
Bivariate OR
(95% CI)
Multivariable OR
(95% CI)
Socio-demographic factors
Age (C65 years) 1.5 (0.7–3.5) 1.1 (0.4–3.0) 1.8 (0.8–4.2) 1.2 (0.5–3.2)
Occupational status (employed or self-employed) 1.0 (0.3–3.2) – 0.4 (0.1–1.9) –
Educational levela (college graduate B) 0.5 (0.2–1.3) – 0.6 (0.2–1.6) –
Health-related factors
Pre-event health statusa (fair to poor) 1.0 (0.4–2.4) – 3.8 (1.4–10.9)** 2.3 (0.8-7.2)
Disability (class 1–2) 0.9 (0.3–2.3) – 1.4 (0.6–3.4) –
Receiving LTCI services 4.7 (1.7–12.5)*** 1.7 (0.5–5.5) 4.7 (1.7–12.5)*** 1.7 (0.6–5.3)
Comorbid conditions 2.0 (0.8–4.7) – 1.0 (0.4–2.2) –
Pre-event MHAQ score (C0.75) 4.4 (1.6–11.8)** 4.4 (1.5–13.6)** 5.7 (2.0–16.4)*** 3.9 (1.3–12.0)*
Disaster-related factors
Direct health damage 3.5 (1.1–11.5)* 2.3 (0.5–9.7) 3.5 (1.1–11.5)* 2.1 (0.6–7.9)
Property damage 4.9 (1.9–12.6)*** 3.1 (1.0–9.2)* 4.0 (1.6–9.8)** 2.7 (1.0–7.6)�
Lifeline damage 3.4 (1.4–8.4)** 2.0 (0.7–5.7) 1.4 (0.6–3.1) –
Evacuation 3.3 (1.3–8.3)** 1.2 (0.4–4.3) 3.3 (1.3–8.3)** 1.8 (0.6–5.7)
Disturbance of visit 3.7 (1.4–9.9)** 2.9 (0.9–9.2)� 1.7 (0.6–4.9) –
Medication interruptionb 0.7 (0.1–5.5) – 0.7 (0.1–5.5) –
Type of hazard (earthquake) 1.1 (0.5–2.6) – 1.9 (0.9–4.4) –
Scale of disaster (large) 2.3 (0.9–5.7)� 0.9 (0.2–3.2) 1.8 (0.7–4.7) –
Preparedness behavior
Medication treatmentb 1.3 (0.4–3.6) – 1.3 (0.4–3.6) –
Healthcare access 1.6 (0.7–3.8) – 1.6 (0.7–3.8) –
Household level 1.1 (0.5–2.5) – 1.1 (0.5–2.5) –
Community based 2.5 (1.0–5.9)* 1.9 (0.7–5.3) 2.0 (0.9–4.9) –
LTCI Long-term Care Insurance, OR odds ratio, 95% CI 95% confidence interval� P \ 0.10
* P \ 0.05
** P \ 0.01
*** P \ 0.001a Missing data were excludedb Only 185 patients receiving prescriptions were included
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deteriorations of functional status and had about a threefold
higher risk of a deterioration of the self-rated health status
at both 1 and 6 months. In our study, we stratified the
MHAQ score by the median (0.625); this means that if a
respondent, for example, reports trouble in at least six
items among the eight MHAQ items, the risk of deterio-
ration of activities of daily living (ADL) or health status
after the disaster could increase. This result may indicate
the possibility of using the MHAQ score to identify a
vulnerable subgroup of RA patients requiring greater sup-
port during a disaster.
Those patients with a self-rated health status of fair to
poor were at a higher risk of experiencing a deterioration of
health at 6 months post-event although such associations
were not found at 1 month post-event. The possible
explanations for these results are that patients in a poor
condition are generally in poor control of their RA and/or
other comorbid conditions and, therefore, find recovery
more difficult. Continuous support, not only in the acute
phase, would be necessary for those having a poor health
status before the event.
Other health-related factors, including having a physi-
cally disabled persons’ certificate, receiving the LTCI ser-
vices, and having comorbid conditions, were not statistically
significantly associated with the outcomes in the multivari-
able analysis. However, receiving the LTCI services did
show a significant association with a deterioration of both
functional and self-rated health status in the bivariate anal-
ysis. In Japan, local governments often use the criteria of a
physically disabled persons’ certificate and receiving LTCI
services to identify those who need special help during
disasters [23] as such information is easily accessible.
Table 5 The associations between deterioration of self-rated health status and potential risk factors at 1 and 6 months post-event (n = 190)
Variable 1 month after the event 6 months after the event
Bivariate OR
(95% CI)
Multivariable OR
(95% CI)
Bivariate OR
(95% CI)
Multivariable OR
(95% CI)
Socio-demographic factors
Age (C65 years) 1.7 (0.9–3.5) 1.4 (0.6–3.1) 1.3 (0.7–2.6) 1.0 (0.4–2.1)
Occupational status (employed or self-employed) 0.6 (0.2–1.7) – 0.6 (0.2–1.7) –
Educational levela (college graduate B) 0.6 (0.3–1.4) – 0.9 (0.4–1.9) –
Health-related factors
Pre-event health statusa (fair to poor) 1.7 (0.8–3.4) – 4.2 (1.8–10.0)*** 3.3 (1.3–8.5)*
Disability (class 1–2) 0.7 (0.3–1.6) – 1.1 (0.5–2.5) –
Receiving LTCI services 3.0 (1.2–7.6)* 1.3 (0.4–4.0) 2.8 (1.1–6.9)* 1.2 (0.4–3.5)
Comorbid conditions 2.0 (1.0–4.0)� 2.0 (0.9–4.6) 1.5 (0.7–3.0) –
Pre-event MHAQ score (C0.75) 3.5 (1.6–7.5)*** 2.8 (1.2–6.7)* 4.0 (1.8–8.9)*** 2.8 (1.2–6.7)*
Disaster-related factors
Direct health damage 3.6 (1.2–10.7)* 2.1 (0.6–7.3) 2.6 (0.9–7.9)� 1.3 (0.4–4.6)
Property damage 2.8 (1.4–5.8)** 1.5 (0.6–3.6) 2.8 (1.4–5.8)** 1.7 (0.7–4.0)
Lifeline damage 2.8 (1.3–5.8)** 2.3 (1.0–5.4)* 1.6 (0.8–3.3) –
Evacuation 5.5 (2.3–13.2)*** 3.6 (1.3–9.4)* 3.9 (1.7–9.1)*** 3.3 (1.2–9.1)*
Disturbance of visit 1.6 (0.6–4.1) – 0.9 (0.3–2.7) –
Medication interruptionb 0.9 (0.2–4.2) – 1.5 (0.4–6.2) –
Type of hazard (earthquake) 1.1 (0.6–2.3) – 1.0 (0.5–2.0) –
Scale of disaster (large) 1.8 (0.7–4.7) – 1.4 (0.6–3.2) –
Preparedness behavior
Medication treatmentb 0.6 (0.3–1.4) – 1.3 (0.5–3.1) –
Healthcare access 1.3 (0.6–2.7) – 1.4 (0.7–3.0) –
Household level 0.8 (0.4–1.5) – 1.1 (0.6–2.2) –
Community based 1.1 (0.5–2.4) – 0.9 (0.4–2.1) –
� P \ 0.10
* P \ 0.05
** P \ 0.01
*** P \ 0.001a Missing data were excludedb Only 183 patients receiving prescriptions were included
Mod Rheumatol (2011) 21:381–390 387
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However, our results imply that the validity of using these
criteria as indicators of special help, especially that of the
physically disabled persons’ certificate, should be re-examined
to achieve the most effective disaster preparedness.
Property damage was associated with a deterioration of
functional status at 1 month post-event, and a suggestive
association was also found for 6 months post-event. Those
respondents with property damage were not only exposed to
the direct hazard of destroyed buildings but also with the
physical and mental stress of cleaning, making repairs, and
meeting financial burdens. Thus, the health impacts would
last well beyond the acute phase. On the other hand, lifeline
damage was only associated with a deterioration of self-
rated health status at 1 month post-event. Lifelines, includ-
ing electricity, gas, water, and telecommunication services,
would be restored within days or weeks, even after large-
scale disasters, so any health damage due to the lack of
lifelines should recover within a relatively shorter period.
Medication interruption and disturbance of routine
healthcare visits were not associated with the outcome
although disturbance of a healthcare visit might be asso-
ciated with a deterioration of functional status at 1 month
after the event. This result is contradictory to previous
findings that medication interruptions were associated with
a deterioration of health status after disasters [7, 21]. This
difference may be due to a very high medication compli-
ance among our study subjects, even after the disaster.
Interruption in medication was reported by only 5% of the
respondents, which is much smaller than the 9% in a study
in a flood-affected area in Japan [21] and the 20.6% in a
study after Hurricane Katrina [7]. Any disturbance in
healthcare visits might have adverse effect on the func-
tional status in the short period immediately following a
disaster, although compliance to medication might com-
pensate for the potential adverse effect of a lack of
healthcare visits. During the study period, however, the
majority of patients in our study received oral medication
treatment rather than the administration of biological
agents, which usually require hospital visits. This result
emphasizes that any disturbance to healthcare visits would
have a greater impact if treatment with biological agents
becomes more popular among RA patients. Plans to guar-
antee the continuity of such treatment are required.
Contrary to expectations, no positive effects were found
for preventive behaviors. In the survey reported above which
targeted outpatients with chronic conditions in a flood-
affected area, the authors reports a number of positive effects
on preventive behaviors for continuing medication treat-
ment [21], but our results did not confirm such relationships.
There are several explanations for these somewhat para-
doxical results. First, we could not confirm the quality of the
preparedness behaviors. Even though some respondents
believed that they were well prepared, they may not have
been sufficiently trained to manage themselves in the
aftermath of disasters. Second, the damage due to the
disasters considered in our study was not strong enough to
confirm the positive effects of the previously reported pre-
ventive behaviors. Third, there may be some potential con-
founders that we could not control for in our study. Although
we cannot conclude from our results that preventive
behaviors are not effective when patients are faced with a
natural disaster, we should be aware that such behaviors are
not always effective, and at the moment, such behaviors
should be complemented by social and/or governmental
support. Further research is required to examine the effec-
tiveness of preventive behaviors since most of them are
generally applied based on past experiences.
There are several limitations to our study. First, as the
study subjects were sampled from members of a patient
group, they may have a better level of disease awareness
and treatment compliance than the average RA patient.
Second, those who died or moved to other locations due to
more severe damage to their homes were not included.
Third, there was room for recall bias because the maximum
duration between the events and the survey was 2.5 years.
However, some amount of time lag between an event and a
survey is inevitable in disaster research, especially for the
survey enrolling a large number of the patients affected by
different events in different places. Most of the previous
studies, in fact, were based on a retrospective approach
with some recall periods, and in some of these, the recall
periods were much longer than those of the present study
[12, 24]. Although the effect of recall bias should be
considered, the findings of our study still have a high
impact as this is the first report to raise subject of aware-
ness of disaster preparedness among RA patients and health
practitioners. Fourth, no clinical indicators were examined.
As the survey was exclusively based on self-evaluation, we
could not estimate associations between risk factors and
clinical outcomes, nor could we apply other scales that
indicate disease activity, including the disease activity
score (DAS), clinical disease activity index (CDAI), and
simplified disease activity index (SDAI). Future studies
should also include surveys using these scales. Fifth, the
clinical relevance of the outcome measures in our study,
which take the average of the changes of each component
of MHAQ instead of measuring absolute changes in the
MHAQ score, has not been fully accredited as an indicator
of changes of functional status. However, the measures
used in our study were able to avoid the floor-and-ceiling
effect of MHAQ scoring [25, 26], enabling the more sen-
sitive detection of smaller change in functional status.
In summary, the functional and self-rated health status
in women RA patients could worsen after natural disasters.
Among the RA patients who responded to our question-
naire, the largest health impact was observed in those who
388 Mod Rheumatol (2011) 21:381–390
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had more severe conditions in terms of functional and self-
rated health status. Policy responses should be considered
to support the vulnerable subgroups although further
studies based on a timely survey involving healthcare
facilities are required to investigate the full extent of
clinical damage caused by natural disasters.
Acknowledgments We thank the Japan Rheumatism Friendship
Association and its members for conducting the survey. This study
was supported by Grant-in-Aids for Scientific Research from the
Japan Society for the Promotion of Science, ‘‘A Study on Develop-
ment of QOL Instrument for People Who Need Help and Support
When it Happens to Disaster, 2006–2008 (HM and HS)’’ and ‘‘Stra-
tegic Management and Communications of Health Risks, 2007–2009
(HS).’’ It was also partially supported by the Research Grant-in-Aids
by the Alliance for Global Sustainability of the University of Tokyo,
2009–2010 (HS).
Conflict of interest None.
Appendix
See Table 6.
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Table 6 The components of the four domains of disaster preparedness
behaviors
Preparedness for medication treatment
Keep extra doses of medications
Refill medications before being out of them
Prepare to go out with medications
Prepare to go out with prescription records
Preparedness for healthcare access
Discuss with your doctors about the plans in case of emergency
Arrange access to substitute healthcare facility in case
of emergency
Prepare to go out with the records of examinations
and/or treatments
Household level preparedness
Ensure emergency communication methods
with family members
Prepare emergency pack
Reinforce the house and/or secure furniture to the wall
and/or the ceiling
Keep some means of transportation in case of emergency
Community-based preparedness
Participate in disaster drills organized by community
or local government
Ensure the route to the designated evacuation center
Keep someone to help you evacuate
Register oneself on the official list of those who need
special support during disaster
For each item, the study subjects are asked to answer with a ‘‘yes’’ or
‘‘no’’. At least one ‘‘yes’’ in each domain was regarded as a positive
response for the domain
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