Risk factors for unintentional injuries among the rural elderly: a county-based cross-sectional survey

This study aimed to provide evidence for the prevention and reduction of unintentional injuries in the rural elderly by analysing epidemiological data of injuries among rural older adults (65+) and identifying the involved risk and protective factors. The prevalence of unintentional injuries was 44.4%; according to the multivariate regression analysis, ten variables, including gender, floor tiles, cane use, sleeping duration, roughage intake frequency, mental health status, diabetes, arthritis and cataracts, were involved in the injury patterns.

1SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
www.nature.com/scientificreports
Risk factors for unintentional
injuries among the rural elder
a county-based cross-sectiona
survey
Hongping Zhang1, Feng Wei2, Mo Han2, Jianquan Chen3, Songxu Peng1 & Yukai Du1
This study aimed to provide evidence for the prevention and reduction of unintentiona
rural elderly by analysing epidemiological data of injuries among rural older adults (65+) and identifying
the involved risk and protective factors. This study analysed all information, including
demographic characteristics, chronic disease condition, lifestyle, living environment, m
activities of daily living and detailed information about the nature of the injuries. Chi-s
tests and a multivariate logistic regression were performed. The prevalence of uninten
was 44.4%; according to the multivariate regression analysis, ten variables, including
cane use, sleeping duration, roughage intake frequency, mental health status, diabete
cataracts, were involved in the injury patterns. Low roughage intake (OR = 2.34, 95% C
the use of a cane (OR = 1.78, 95% CI 1.31–2.41), a sleeping duration of five hours (OR =
1.27–2.42) and severe mental disorders (OR = 1.61, 95% CI 1.01–2.57) were the top 4 r
conclusion, we found that unintentional injuries among the rural elderly were closely r
disease, mental health and residence environment. These findings could be beneficial
of unintentional injuries and for policy makers and health service managers.
Unintentional injuries among older adults are an increasing public health concern due to the over
the population. The mortality rate due to injury has increased over the past decade among adults
older1–4
. According to Karb, the mortality rate (per 100,000) due to all unintentional injuries among
65–84 years was 66.87, which is approximately 10 times that observed among children aged 0–1
the mortality rate among those aged 85 years or older was 337.27, which is nearly 50 times that
children aged 0–14 years in the United States between 1999 and 20125. In Korea, injury-related mortality has
increased among adults aged 65 years or older. In particular, injury-related mortality among wom
80 years has doubled since 1996. Falls replaced transport as the leading cause of injury-related d
the elderly6. In addition, the elderly are often afflicted with a variety of diseases, such as cardiovasc
and diabetes, that reduce the likelihood of survival in the case of non-fatal injuries. Furthermore,
rates of emergency department (ED)-treated and the high number and proportion of inpatient tra
to unintentional injuries among elderly adults poses a challenge to the health care system and in
nomic burden on society3,7,8
. Therefore, more effective measures are needed to prevent and reduce un
injuries among elderly people and minimize the negative health effects and increasing health cos
Age has been considered a risk factor for unintentional injuries among the elderly because the
tentional injury is higher among the older-elderly population6,9–11
. However, age has also been reported to hav
no influence on the rate of injuries among the elderly3,12
. According to Saveman, the injury rate among elder
females is higher than that among elderly males10
; the unintentional fatal injury rate is higher among femal
than that among males; and females older than 70 years are more likely to fall than males, leadin
1Department of Social Medicine and Health Management, School of Public Health, Tongji Medical Colleg
University of Science & Technology, HangKong Road 13, Wuhan, 430030, China.2Centers for Disease Prevention &
Control of Huangpi District of Wuhan, BaiXiu Street 255#, Huangpi District, Wuhan, 430300, China.3Department
of Disease Control, Health and Family Planning Commission of Huangpi District of Wuhan, BaiJing Stree
Huangpi District, Wuhan, 430300, China. Correspondence and requests for materials should be addres
(email: [e-mail])
Received: 17 February 2017
Accepted: 14 September 2017
Published: xx xx xxxx
OPEN

www.nature.com/scientificreports/
2SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
likelihood of bone fractures2. Certain chronic diseases, including lumbar spondylosis, orthostatic hypot
diabetes and cataracts, are risk factors for falls among elderly individuals13
. Severe bilateral visual deficits increase
the risk of unintentional mortality among adults over the age of 18 years (including the elderly)14
. Depression15–17
and other mental illnesses18 are related to the risk of injuries. Elderly individuals with Alzheimer’s disea
more prone to unintentional poisoning19
. The use of medications also explains the increased rate of uninte
injuries among the elderly; for example, elderly individuals who consume opioid drugs are more l20
.
Furthermore, sleep duration affects unintentional injuries among adults; sleeping less than 6 hou
factor for unintentional injuries21
. The fall risk among elderly individuals is closely related to the activitie
living (ADL) capability, physical activity habits, poor living conditions and environmental factors22
. Furthermore,
poverty at the county level confers a greater risk of unintentional injury, and high poverty areas h
the burden of the recent national increases in the mortality rate due to unintentional injuries2,5,23
. In India, more
than 80% of unintentional injury-related deaths occurred in rural areas2. There is an increasing socioeconomic
disparity among all combined unintentional injuries. The injuries observed in rural areas and amo
from low socioeconomic classes are more severe24
.
In China, most elderly people continue to live in the countryside. Because the young adult labo
migrated from the rural areas to the cities, the elderly population remaining in the rural areas mu
without the support of their adult offspring (usually referred to as “empty nesters”). More attentio
to the older rural population because this population is more likely to experience unintentional in
elderly people work as active farmers under poor economic conditions with less support from you
Population-based surveys covering the range of injuries among older rural adults are scarce10
. Our study attempts
to address these shortcomings.
In this study, we performed cluster sampling using our self-designed questionnaire. The questi
social demographic characteristics, financial situations, conditions of offspring, prevalence of chro
living environment, mental condition, ADL and instrumental ADL (IADL) among elderly individuals
aims to identify policies, programmes, and resources that ensure a safe environment and promot
to prevent injury. Therefore, the situations responsible for unintentional injuries and the risk and
tors that minimize these injuries were analysed. Comparisons of specific injury-related mortality b
should be conducted with caution because the large differences in the unspecified injury mortalit
states could create a bias4. Furthermore, unintentional injuries are not homogeneous phenomena from a
miological transition perspective25
. This study was conducted amongst the rural population in one entire
under the jurisdiction of Wuhan City, Hubei Province, China.
Results
General description of the investigation.Of the 3,900 questionnaires distributed, we received 3,7
completed questionnaires, representing a response rate of 96.2%. The database included 1,673 m
2,079 females (55.4%), and the average age of these individuals was 72.74 ± 6.44 years, with a
years. Of those surveyed, 64.8% were 65–74 years old, and 5.3% were 85 years old or older. In to
were reported by 805 victims in a sample of 3,752 respondents aged 65 years and older during th
period covered by this investigation. The observed injury prevalence in this rural elderly populatio
(Table 1). The questionnaire responses included 487 cases (59.8%) of one injury, 127 cases (15.8
Causes of injuries
Total Sex Age group in years (y)
N = 3752
n (%)
Male
N = 1673
n (%)
Female
N = 2079
n (%) P-value
65–74
N = 2431
n (%)
75–84
N = 1122
n (%)
≥85 N = 199
n (%) P-value
Total 1665(44.4) 578(34.5) 1087(52.3) 0.000** 1035(42.6) 548(48.8) 82(41.2) 0.130
Falls 1124(30.0) 347(20.7) 777(37.4) 0.000** 639(26.3) 430(38.3) 55(27.6) 0.000**
Cuts 201(5.4) 79(4.7) 122(5.9) 0.476 149(6.1) 49(4.4) 3(1.5) 0.021*
Choking or
swallowing a foreign
body
164(4.4) 77(4.6) 87(4.2) 0.415 121(5.0) 33(2.9) 10(5.0) 0.195
Burns 36(1.0) 5(0.3) 31(1.5) 0.013* 23(0.9) 7(0.6) 6(3.0) 0.258
Traffic accidents 31(0.8) 20(1.2) 11(0.5) 0.004* 23(0.9) 7(0.6) 1(0.5) 0.485
Sunstroke 30(0.8) 12(0.7) 18(0.9) 0.435 23(0.8) 6(0.5) 1(0.5) 0.729
Crushing accidents22(0.6) 13(0.8) 9(0.4) 0.044* 16(0.7) 6(0.5) 0(0.0) 0.630
Animal bites 19(0.5) 10(0.6) 9(0.4) 0.219 11(0.4) 7(0.6) 1(0.5) 0.706
Percussions 17(0.5) 3(0.2) 14(0.7) 0.326 11(0.4) 1(0.1) 5(2.5) 0.180
Poisoning 6(0.2) 5(0.3) 1(0.0) 0.055 6(0.2) 0(0.0) 0(0.0) 0.284
Drowning 4(0.1) 2(0.1) 2(0.1) 0.638 4(0.2) 0(0.0) 0(0.0) 0.367
Domestic violence 3(0.1) 0(0.0) 3(0.1) 0.262 1(0.0) 2(0.2) 0(0.0) 0.812
Electric shock 1(0.0) 1(0.1) 0(0.0) 0.206 1(0.0) 0(0.0) 0(0.0) 0.779
Other injuries 7(0.2) 4(0.2) 3(0.1) 0.504 7(0.3) 0(0.0) 0(0.0)
Table 1. Prevalence of different types of unintentional injuries by age and gender among the stu
*P < 0.05;**P < 0.01; % = prevalence.

www.nature.com/scientificreports/
3SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
and 191 cases (23.7%) of three or more injuries. Falls (30.0%) and cuts (5.4%) were the most com
tional injuries, followed by choking or swallowing a foreign body (4.4%), burns (1.0%), traffic acci
and sunstroke (0.8%) (Table 1).
Sex- and age-based injury patterns.The incidence of the unintentional injuries was significantly hi
among the female respondents (52.3%) than among the male respondents (34.5%) (P < 0.001). F
significantly more likely to experience fall-related injuries (37.4% vs. 20.7%, P < 0.001) and burn
vs. 0.3%, P = 0.049). Males were significantly more likely to experience a traffic injury (1.2% vs. 0
and crushing injuries (0.8% vs. 0.4%, P = 0.044) than females (Table 1).
The prevalence of the injuries varied according to the age group and type of injury (Table 1). T
participants aged 75–84 years had the highest rates of all injuries (48.8%), followed by those age
(42.6%), and the group of participants aged 85 years or older had the lowest rate (41.2%). Howev
icant differences were observed among these groups (P = 0.130). The group aged 75–84 years ha
of fall-related injuries (38.3%) than the older group (27.6%) or younger group (26.3%) (P < 0.001
aged 65–74 years had higher rates of cut injuries (6.1%) than the older group (4.4%) and the olde
(P = 0.010).
Treatments and costs.Upper and lower limb injuries were the most commonly reported injuries, f
by head and neck injuries and spine-backbone/back injuries. Bruises, fractures and sprains were t
common injuries. The most common settings in which the injuries occurred were at home (40.6%
place (22.3%) (Table 2). In total, 44.4% (n = 357) of the study population sought medical help, 28
the study population did not receive any treatment and 27.4% (n = 221) of the study population
The total medical costs of the 1,665 injuries were 1,656,845 RMB; 144 people (20.3%) were admi
days in hospitals, representing an expenditure of 1,330,600 RMB. In total, 51.3% of the elderly wa
the New Rural Cooperative Medical Care Scheme, 40.3% of the elderly paid for their treatments a
elderly used another health insurance carrier, such as free medical service or commercial insuran
Risk factors.Our study identified 27 factors related to injuries by performing a single-factor logis
sion analysis with the occurrence of injuries as the dependent variable. This study subsequently a
above-mentioned 27 factors by performing a multivariable logistic regression analysis. According
ten variables, including gender, the presence or absence of floor tiles, a residence near a road, us
walking stick, sleep duration, food intake, mental health, diabetes, arthritis and cataracts, were a
injury patterns (presented in Table 4).
In general, women had a 46% greater chance of injury than men, and these higher odds reach
fall-related injuries. Compared with people with a non-slippery floor, elderly adults with slippery fl
higher probability of injury, and those who had no floor (i.e., those living in a dwelling with an ear
floor) had a 60% higher chance of sustaining an injury. Using approximately 9 hours of sleep as a
adjusted injury risk (odds ratio) for those who sleep less than 4 hours/day was 0.88. The odds rati
those sleeping 5 hours per day, 1.45 for those sleeping 6 hours per day, 1.01 for those sleeping 8
1.10 for those sleeping 9 hours or more per day. The risk difference was significantly different be
6-hour cohorts. In this study, the risk increased as sleep duration decreased from 7 hours to less
The use of a cane or walking stick increased the odds of injury by 78%. The group with the lowest
had a 2.34-fold higher probability of sustaining an injury than the group with normal food intake.
with severe mental disorders were 61% more likely to sustain recurrent injuries and 59% more lik
injury than the individuals in the moderate mental disorder group. People who had a chronic dise
risk of injury as follows: individuals with diabetes had a 42% higher probability of sustaining an in
als with arthritis had a 27% higher probability, and individuals with cataracts had a 38% higher p
Discussion
This is the first study to investigate the rate of unintentional injury among rural elderly individual
hensive information regarding the socio-demographic characteristics, chronic disease condition, l
environment, mental condition, ADL and IADL. The prevalence of unintentional injuries was 21.5%
elderly population. The top six unintentional injuries were falls, cuts, choking or swallowing a fore
burns, traffic accidents and sunstroke. Prior domestic and foreign studies mostly investigated the
or community environment, in which falling and traffic injuries are the most common injury types2,26
. By con-
trast, this study was conducted among the elderly in rural areas, and injuries from cuts ranked th
this population typically uses blades or other sharp-edged implements for agricultural production
individuals use wood instead of gas or coal as fuel to heat their homes and cook. Therefore, these
prone to injuries from blades as they prepare wood for burning. Because these individuals use wo
cooking, they are also more prone to burns sustained when feeding the stove. Due to their age, t
experience a burn- or fire-related injury increases as a function of the ageing process, co-morbidi
financial means27
. These individuals are also prone to sunstroke while working outside. In this investi
incidence of swallowing a foreign body and choking was 1.6%, ranking as the third most common
has not been observed in other studies. The elderly are more prone to dysphasia-choking than ch
more prone to choke by swallowing a foreign body. Among unintentional deaths in Japan, choking
number one cause28
. Among the approximately 800 choking cases attributed to food, mochi ranks the
20%, and this rate is particularly high among elderly individuals aged more than 65 years. Mochi
Japanese food and an important festive feature during the New Year’s holiday, particularly among
Mochi is made by steaming sticky rice. Mochi is highly cohesive and adhesive and can easily lead

www.nature.com/scientificreports/
4SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
people in this Chinese study area also have a custom of eating a similar traditional food named “
made by steaming sticky rice. The role of food in choking injury requires further investigation.
In the comparison of the injury types between the males and females, the females were more
ence falls (P < 0.001) and burn injuries (P = 0.013), and the males were more prone to experienc
(P = 0.038) and crushing injuries (P < 0.001). The most common settings in which the injuries occ
genders were at home and the workplace, but the incidence of females sustaining unintentional i
was higher (P = 0.006). No differences were observed in the types of injuries and the location and
the injuries between the genders (P > 0.05). The males had higher rates of admission to health fa
females, implying either that the males paid more attention to their health status or that the fem
more readily or lacked the authority to make financial decisions.
Ten variables were analysed to determine the injury patterns using a multivariate logistic regre
sis. These variables included gender, the presence or absence of floor tiles, a residence near a ro
cane, hours of sleep, intake of food, mental health, diabetes, arthritis and cataracts (Table 4). The
were more likely to suffer unintentional injuries than the elderly men, which is consistent with oth10,29
.
`
Total
Sex
P-value
Male Female
N % N % N %
Total 3752 1673 44.6 2079 55.4
Injuries <0.001**
Yes 805 21.5 301 18.0 504 24.2
No 2947 88.5 1372 82.0 1575 75.8
Age (y)
65–74 2431 64.8 1054 63 1377 66.2 0.026*
75–84 1122 29.9 537 32.1 585 28.2
≥85 199 5.3 82 4.9 117 5.6
Anatomical site of injury
Head and neck 89 11 36 12.1 52 10.3 >0.05
Spinal bone and back 52 6.5 21 6.9 32 6.3
Upper extremities 289 35.9 97 32.3 192 38
Lower extremities 297 36.9 118 39.1 180 35.7
Buttock 45 5.6 17 5.6 28 5.6
Other anatomical sites 33 4.1 12 4 21 4.1
Pathological type of injury
Bruise 401 49.8 155 51.6 245 48.7 >0.05
Fracture 152 18.9 48 16.1 103 20.5
Twist 147 18.3 51 16.9 96 19.1
Open (penetrating trauma)43 5.4 20 6.7 24 4.7
Brain dysfunction 22 2.7 9 3.1 12 2.4
Other 39 4.9 17 5.6 23 4.6
Injury place
At home 327 40.6 99 32.9 229 45.5 0.006**
Workplace (farmland) 180 22.3 80 26.7 98 19.5
On the road 159 19.8 71 23.6 88 17.4
In the yard 101 12.5 35 11.6 66 13.1
Public place 19 2.4 6 2.1 13 2.6
Other places 19 2.4 9 3.1 10 1.9
Activity
Recreational activity 350 43.5 99 32.9 255 50.6 <0.001**
Working 175 21.8 83 27.6 92 18.3
Walking 77 9.6 36 11.9 44 8.7
Exercising 43 5.3 17 5.7 25 5
Sleeping/resting 39 4.9 16 5.4 23 4.6
Cooking 55 6.8 20 6.8 34 6.7
Riding 22 2.7 11 3.6 6 1.1
Driving 15 1.9 10 3.2 6 1.1
Other 28 3.5 9 2.9 20 3.9
Table 2. Comparison of the anatomical site, pathological type and location of the unintentional i
between the genders in a rural elderly population.*P < 0.05;**P < 0.01; % = rate.

www.nature.com/scientificreports/
5SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
Elderly individuals who used canes were more likely to sustain unintentional injuries, likely becau
walking sticks cannot walk freely and, thus, are more likely to be injured in falls or traffic accident
at least one arm is occupied using the walking stick, making it easier to experience burns or cuts
those with 5 hours or less of sleep had 1.85-fold higher odds of injuries, and those with 6 hours o
higher odds more chance of injuries than those with approximately 9 hours of sleep (P < 0.05). Si
were obtained by Kim21 in his study, which investigated the relationship between hours of sleep and t
hood of unintentional injuries. Similarly, sleep deprivation has been shown to lead to fatigue, drow
driving, and impaired alertness, directly leading to an increased number of traffic accidents. More
or increase in sleep duration has been shown to have an effect on health, and sleep duration is a
reduced cognitive function30,31
.
Depression is related to the risk of injuries15–17
, but other mental illnesses are also risk factors for uninten
injury and injury recidivism18
. In this study, we used the Kessler 10-item Psychological Distress Scale (
measure the level of mental functioning and evaluate the risk of mental problems16,32,33
in the study population
because this test is applicable on a wider scale and has been validated in Chinese elderly populat
studies28,31,32
. This study used the K10 to determine the relationship between mental illness and the
injuries. The rate of injuries was higher in those with mental problems. Elderly Chinese men and w
larly those from rural areas, are not prone to discuss mental disorders. The K10 includes only ten
this test is easy to use in screening for mental disorders. The results of other studies28,31,32
have shown that this test
is applicable to a wide range of mental disorders.
The location of a person’s residence in relation to a road is a contributing factor for the likeliho
Those located far from a road are more likely to be injured than those located close to a road. Tho
far from a road experience more difficulties in accessing the more difficult terrain to cultivate me
Therefore, a greater extent of manual labour is observed, which increases the likelihood of cuts a
The elderly individuals with uneven mud or concrete floors in their residences were more likely
injuries than those with finished floors with anti-slip floor tiles. The absence of a finished floor in t
consequence of a lower economic status. The economic status of a household was not a contribu
rural elderly likely because these individuals are reluctant to disclose their true economic situatio
Total
Sex
Male Female
P-valueN % N % N %
Treatment
no treatment 227 28.2 85 28.1 143 28.3 >0.05
self-treatment 221 27.4 78 25.9 143 28.3
town hospitals 127 15.8 49 16.4 78 15.4
district hospitals 104 12.9 41 13.5 64 12.6
village clinics 74 9.2 25 8.4 48 9.6
city level hospitals or above 29 3.6 13 4.4 16 3.1
private clinic 23 2.9 10 3.3 14 2.7
Injury severity
mild 581 72.2 222 73.6 359 71.3 >0.05
moderate 205 25.5 71 23.6 135 26.7
severe 19 2.3 8 2.8 10 2
Hospitalization
yes 163 20.3 76 25.1 87 17.3 0.012
no 642 79.7 225 74.9 417 82.7
Types of payments
new type of rural cooperative medical system413 51.3 157 52 257 50.9 >0.05
self-paying 324 40.3 117 39 207 41.1
urban residents’ health insurance 51 6.3 15 5.1 35 7
free medical service 12 1.5 8 2.8 4 0.7
commercial insurance 5 0.6 3 1.1 2 0.3
Limited function
without limitations 336 41.8 139 46.1 197 39.1 >0.05
1–14 d 68 8.5 29 9.7 39 7.7
15d-30 d 159 19.8 54 17.8 106 21
1–3 m 49 6.1 16 5.3 33 6.6
>3 m 122 15.2 43 14.2 80 15.9
Table 3. Comparison of the treatments and outcomes of unintentional injuries between the gend
elderly population.*P < 0.05;**P < 0.01; % = rate.

www.nature.com/scientificreports/
6SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
The home is normally a place of safety. However, in this study, 45.5% of the elderly women an
elderly men sustained injuries at home. Certain risk factors are associated with the physical cond
dence. Improving the economic condition and living environment and reducing the physical cond
to an increased risk of injuries in the residence can effectively decrease the incidence of injuries.
Of the 17 types of common chronic diseases, the following 3 diseases were prominent in our in
model: diabetes, arthritis and cataracts. Elderly individuals with these conditions require more ca
prone to suffer unintentional injuries.
This study shows that daily roughage intake is a protective factor against unintentional injuries
study has reported a relationship between the risk of injuries and regular roughage intake. Furthe
be performed to explore this relationship. Particular attention must be paid to the age of the elde
ied. A growing body of research is examining ageing as a risk factor for falls or other unintentiona7,10,34
.
However, these studies indicate that ageing alone is not a risk factor for unintentional injuries. Ag
sidered in the context of the functionality of an individual. Rural elderly individuals usually work o
thus, are likely to retain better ADL functions with age.
In summary, this study analysed the unintentional injuries sustained by elderly people in rural
found that unintentional injuries are closely related to chronic disease, mental health status and o
environment. The findings of this study could be beneficial for the prevention of unintentional inju
could be vital for policy makers, health service managers and stakeholders.
Methods
Study design and setting.This study used a county-based, cross-sectional survey design, with a c
ience sample collected from one county. We aimed to study the epidemiology of unintentional inj
rural older adults (65 years or older) and analyse the risk and protective factors to provide eviden
used to prevent and reduce unintentional injuries and minimize the increasing health costs. The q
was administered to a randomized, stratified sample in different stages and was proportional in a
lation. A minimum sample size of 3,630 rural individuals aged 65 years and older is recommende
size formula was N = Za/2
2 × π (1−π)/δ2. The sample size was obtained to achieve a confidence level of 95
a 5% margin of error and 50% prevalence of unintentional elderly injuries (no national studies ha
the same age categories) with an expected response rate of 90%. We considered mountainous ar
economic level as the layering factors.
All Injuries
Odds ratio 95% CI P-value
Female 1.46 1.20–1.77 0.000
Floor
non-slippery floor 1.00 Reference
slippery floor 1.07 0.82–1.39 0.630
without floor 1.60 1.30–1.99 0.000
Domicile near road 1.37 1.13–1.66 0.001
Using a cane 1.78 1.31–2.41 0.000
Sleeping time
≤4 h 0.88 0.60–1.30 0.526
5 h 1.75 1.27–2.42 0.001
6 h 1.45 1.06–1.98 0.021
7 h 1.01 0.72–1.41 0.952
8 h 1.10 0.80–1.51 0.557
≥ 9 h 1.00 Reference
Roughage intake frequency
daily 1.00 Reference
often 1.70 1.18–2.43 0.004
occasionally 1.84 1.29–2.63 0.001
hardly 2.34 1.64–3.35 0.000
Mental capacity
likely well 1.00 Reference
mild mental disorder 1.15 0.89–1.50 0.288
moderate mental disorder 1.59 1.09–2.32 0.017
severe mental disorder 1.61 1.01–2.57 0.045
Diabetes 1.42 1.08–1.88 0.013
Arthritis 1.27 1.02–1.59 0.032
Cataracts 1.38 1.06–1.79 0.017
Table 4. Multivariate logistic regression analysis results: risk factors for injury.

www.nature.com/scientificreports/
7SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
According to the different geographical locations (flatlands and mountainous areas) and econo
(good, medium and poor) (data on the per capita income of the rural residents was obtained from
district statistical yearbook (2015)), 2 townships were selected from each level, and 2 villages we
selected from each township. Finally, all qualified elderly people from 24 villages were selected a
ulation. We arranged for those aged between 65–79 years to be surveyed together in health clini
and in-home surveys and other appropriate methods were used to survey those over 80 years of
were physically inconvenienced. Huangpi County is a county in Wuhan City in Central China, and
capita income of the local farmers is in the middle level of that in Hubei Province. Generally, this
posed of “half mountain, half field”, indicating that mountains and plains exist in the same half ar
Huangpi County has a certain rural representation of rural county in the terrains and landforms.
In this study, we defined unintentional injuries as falls, traffic accidents, cuts, burns, swallowing
object or choking, sunstroke, animal bites, electric shocks, crushing injuries, getting hit by an obj
drowning, domestic violence and other injuries. The expected timeframe for completing the surve
and the study was performed between September 1st
, 2015 and September 1st
, 2016.
Data collection procedures.Sixteen medical postgraduate students were recruited and trained as
gators and interviewers to collect the relevant information. The participants were predominantly
uals (95.6%). If the elderly person could not communicate because of disease or language or hea
the immediate relatives or another responsible adult member of the household completed the int
ticipants were asked about any history of injuries during the last 12 months. For inclusion in the s
was determined according to one of the following circumstances: (a) if the elderly person was inju
with simple medical therapies by themselves or another relative; (b) if the injury was diagnosed b
nurse in a clinical setting; or (c) if the individual rested or remained in bed for a minimum period
a half a day because of the injury. To ensure the quality of the collected data, this study was first
small-scale pilot study, which involved 150 samples from one village after designing the question
study was also used to train the research staff in managing the data collection and data entry. Af
the questionnaire was modified.
Questionnaire.The questionnaire consisted of the following 5 parts: Part A covered the persona
demographic characteristics, including age, gender, nationality, marital status, education, occupa
situation and offspring condition, of the elderly adults. Part B included information regarding daily
chronic disease conditions. Part C collected detailed information regarding the nature of the injur
environment, the injury treatment and associated cost. Part D used the K10 to examine the ment
the elderly adults. The K10 is a questionnaire designed to identify individuals likely to have a diag
agnosed mental illness with symptoms that are severe enough to cause moderate to severe func
The K10 is embedded in the Sample Adult Questionnaire. Each of the ten components has the sam
responses including 0 (“none of the time”), 1 (“a little of the time”), 2 (“some of the time”), 3 (“m
and 4 (“all of the time”). The scores are summed to obtain a score between 0 and 40. In our stud
logical distress level was categorized as follows: 0–5 points indicate that the individual is function
mal level, 6–11 points indicate mild mental distress, 12–19 points indicate moderate mental distr
points indicate severe mental distress. Part E included an ADL scale and an IADL scale. Independe
was identified using the Barthel Index (BI). The BI is a questionnaire consisting of 10 items that in
bathing, grooming, dressing, continence of bowels and bladder, transferring from wheelchair to b
transferring to and from a toilet, walking on a level surface, and going up and down stairs. The to
BI ranges from 0–100, with a score of 0 indicating completely incapable of ADL, a score of 1–40 in
ously dependent ADL, a score of 41–60 indicating moderately dependent ADL, and a score of 61–
the individual is capable of independent ADL. The Lawton IADL a questionnaire assesses the follo
functions: using the telephone, using a transportation method, managing money, shopping, takin
cooking food, housekeeping and doing the laundry. The summary score ranges from 0 to 14, with
indicting totally incapable of IADL, a score of 1–5 indicating severely limited IADL, a score of 6–10
limited IADL, and a score of 11–14 indicating normal IADL.
The data from the final questionnaires were statistically analysed. Based on the Cronbach’s alp
tor analysis, the questionnaire has a high validity and reliability (Part B Cronbach’s Alpha reliabili
cient = 0.721, KMO validity coefficient = 0.739; Part C Cronbach’s Alpha reliability coefficient = 0
validity coefficient = 0.780; Part D Cronbach’s Alpha reliability coefficient = 0.940, KMO validity c
cient = 0.935; Part E Cronbach’s Alpha reliability coefficient = 0.939, KMO validity coefficient = 0
ing that this scale is reliable.
One question in Part C inquires about the floor condition in the house, and the options included
“non-slippery floor” and a “slippery floor”. However, 1,424 of the elderly participants (39.2%) res
“without a floor”, indicating that their house floor was either earth or cement. Since the proportio
option was high, we kept this as an additional optional answer.
Statistical analyses.All data were independently entered by two investigators using EpiData 3.1.
tical analyses were performed using SPSS version 21.0. The descriptive analyses were performed
(M) and standard deviations (M ± SD). The comparisons were performed using a two-tailed stude
single factor variance analysis (ANOVA) for the continuous variables. In all analyses, differences a
considered statistically significant.
We first described the prevalence and proportion of injuries among the participants based on t
and then compared the prevalence among groups defined by gender and age. We used the Chi-s

www.nature.com/scientificreports/
8SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
determine the association between the injury status and the social demographic characteristics, c
ease conditions, lifestyle, living environment, mental health, and ADL. Finally, a logistic regressio
performed to assess the injury risk. Ten variables were entered to study the injury patterns using
logistic regression analysis. The unintentional injuries were closely related to chronic disease, me
residence environment.
Ethical considerations.The study protocol was approved by the Ethics Committee of the Tongji M
College, Huazhong University of Science & Technology. The study was performed in accordance w
Declaration. A letter was presented to the participants or guardian(s) explaining the aims, study p
data confidentiality assurance. All participants or guardians provided a written informed consent
survey was conducted.
Limitations of the study.
1. A certain degree of selection bias may exist because rural elderly participants from only one
considered in the sampling. In a subsequent survey, more sampling points should be obtaine
province.
2. This study used a cross-sectional survey, and no interventions or follow-up analyses were per
References
1. Moudouni, D. K. & Phillips, C. D. In-hospital mortality and unintentional falls among older adults in the United St
applied gerontology: the official journal of the Southern Gerontological Society 32, 923–935, https://doi.org/10.1
(2013).
2. Jagnoor, J. et al. Unintentional injury mortality in India, 2005: nationally representative mortality survey of 1.1 m
public health 12, 487, https://doi.org/10.1186/1471-2458-12-487 (2012).
3. Gowing, R. & Jain, M. K. Injury patterns and outcomes associated with elderly trauma victims in Kingston, Ontar
journal of surgery. Journal canadien de chirurgie 50, 437–444 (2007).
4. Cheng, X., Wu, Y., Yao, J., Schwebel, D. C. & Hu, G. Mortality from Unspecified Unintentional Injury among Indivi
Years and Older by U.S. State, 1999–2013. International journal of environmental research and public health 13,
org/10.3390/ijerph13080763 (2016).
5. Karb, R. A., Subramanian, S. V. & Fleegler, E. W. County Poverty Concentration and Disparities in Unintentional
Fourteen-Year Analysis of 1.6 Million U.S. Fatalities. PloS one 11, e0153516, https://doi.org/10.1371/journal.pone
6. Hong, J., Lee, W. K. & Park, H. Change in Causes of Injury-Related Deaths in South Korea, 1996–2006. Journal of
500–506, https://doi.org/10.2188/jea.JE20110021 (2011).
7. DeGrauw, X., Annest, J. L., Stevens, J. A., Xu, L. & Coronado, V. Unintentional injuries treated in hospital emerge
among persons aged 65 years and older, United States, 2006-2011. Journal of safety research 56, 105–109, http
jsr.2015.11.002 (2016).
8. Varnaccia, G., Rommel, A. & Sass, A. C. Unintentional injuries in the German adult population. Results of the “G
Update” survey 2010. Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz 57, 604–612, https://d
s00103-014-1961-0 (2014).
9. Poulose, N. & Raju, R. Aging and injury: alterations in cellular energetics and organ function. Aging and disease
doi.org/10.14336/AD.2014.0500101 (2014).
10. Saveman, B. I. & Bjornstig, U. Unintentional injuries among older adults in northern Sweden–a one-year popula
Scandinavian journal of caring sciences 25, 185–193, https://doi.org/10.1111/j.1471-6712.2010.00810.x (2011).
11. Mack, K. A., Rudd, R. A., Mickalide, A. D. & Ballesteros, M. F. Fatal unintentional injuries in the home in the U.S.
American journal of preventive medicine 44, 239–246, https://doi.org/10.1016/j.amepre.2012.10.022 (2013).
12. Yan, Y. Y. Analysis of data from Luoyang injury surveillance system among the elderly, 2006–2012. Chronic Pat
15, 178–181 (2014).
13. Palagyi, A. et al. While We Waited: Incidence and Predictors of Falls in Older Adults With Cataract. Investigative
visual science 57, 6003–6010, https://doi.org/10.1167/iovs.16-20582 (2016).
14. Lee, D. J., Gomez-Marin, O., Lam, B. L. & Zheng, D. D. Visual impairment and unintentional injury mortality: the
Interview Survey (1986–1994).
15. Tiesman, H. M. et al. Depressive symptoms as a risk factor for unintentional injury: a cohort study in a rural co
prevention: journal of the International Society for Child and Adolescent Injury Prevention 12, 172–177, https://d
ip.2006.011544 (2006).
16. McAninch, J., Greene, C., Sorkin, J. D., Lavoie, M. C. & Smith, G. S. Higher psychological distress is associated w
injuries in US adults. Injury prevention: journal of the International Society for Child and Adolescent Injury Preven
https://doi.org/10.1136/injuryprev-2013-040958 (2014).
17. Kaminska, M. S., Brodowski, J. & Karakiewicz, B. Fall risk factors in community-dwelling elderly depending on th
function, cognitive status and symptoms of depression. International journal of environmental research and pub
3406–3416, https://doi.org/10.3390/ijerph120403406 (2015).
18. Wan, J. J., Morabito, D. J., Khaw, L., Knudson, M. M. & Dicker, R. A. Mental illness as an independent risk factor f
injury and injury recidivism. The Journal of trauma 61, 1299–1304, https://doi.org/10.1097/01.ta.0000240460.35
19. Mitchell, R. J., Harvey, L. A., Brodaty, H., Draper, B. & Close, J. C. Dementia and intentional and unintentional p
people: a 10 year review of hospitalization records in New South Wales, Australia. International psychogeriatrics
https://doi.org/10.1017/S1041610215001258 (2015).
20. Soderberg, K. C., Laflamme, L. & Moller, J. Newly initiated opioid treatment and the risk of fall-related injuries.
register-based, case-crossover study in Sweden. CNS drugs 27, 155–161, https://doi.org/10.1007/s40263-013-00
21. Kim, Y. Y., Kim, U. N., Lee, J. S. & Park, J. H. The effect of sleep duration on the risk of unintentional injury in Ko
of preventive medicine and public health = Yebang Uihakhoe chi 47, 150–157, https://doi.org/10.3961/jpmph.20
22. Yokoya, T., Demura, S. F. S. S. & Sato, S. Relationships between physical activity, ADL capability and fall risk in
Japanese elderly population. doi:D - NLM: PMC2723624 OTO - NOTNLM.
23. Stewart, W. J. et al. Prevalence, risk factors and disability associated with fall-related injury in older adults in lo
incomecountries: results from the WHO Study on global AGEing and adult health (SAGE). BMC medicine 13, 147,
org/10.1186/s12916-015-0390-8 (2015).

www.nature.com/scientificreports/
9SCienTifiC REPORTS | 7: 12533 | DOI:10.1038/s41598-017-12991-3
24. Burrows, S., Auger, N., Gamache, P. & Hamel, D. Leading causes of unintentional injury and suicide mortality in
across the urban-rural continuum. Public health reports (Washington, D.C.: 1974) 128, 443–453 (2013).
25. Moniruzzaman, S. & Andersson, R. Relationship between economic development and risk of injuries in older ad
A global analysis of unintentional injury mortality in an epidemiologic transition perspective. European journal of
454–458, https://doi.org/10.1093/eurpub/cki014 (2005).
26. Xue, C. B., Yu, X., Liu, X. Q., Zhu, J. G. & M., Z. D. Non-fatal injuries and risk factors among older adults in Jiang
Journal of Disease Control & Prevention 14, 945–948 (2010).
27. Grant, E. J. Preventing burns in the elderly: a guide for home healthcare professionals. Home healthcare nurse
573–565, https://doi.org/10.1097/01.nhh.0000436217.56972.58 (2013).
28. Sanpei, R. et al. Video-endoscopic comparison of swallowing waxy rice mochi and waxy wheat mochi: improve
Japanese food that presents a choking hazard. Bioscience, biotechnology, and biochemistry 78, 472–477, https:/
68451.2014.877817 (2014).
29. Stevens, J. A. & Sogolow, E. D. Gender differences for non-fatal unintentional fall related injuries among older a
prevention: journal of the International Society for Child and Adolescent Injury Prevention 11, 115–119, https://d
ip.2004.005835 (2005).
30. Marshall, N. S., Glozier, N. & Grunstein, R. R. Is sleep duration related to obesity? A critical review of the epidem
Sleep medicine reviews 12, 289–298, https://doi.org/10.1016/j.smrv.2008.03.001 (2008).
31. Kim, H. J., Kim, J. H., Park, K. D., Choi, K. G. & Lee, H. W. A survey of sleep deprivation patterns and their effects
functions of residents and interns in Korea. Sleep medicine 12, 390–396, https://doi.org/10.1016/j.sleep.2010.09
32. Xu, H. et al. The application of the Chinese version of K6 and K10 screening scales for psychological distress on
investigation of college students. Modern Preventive Medicine 40, 4493–4496 (2013).
33. Zheng, W. G., Xu, L. Z., Zhou, C. C. & Li, X. Y. Application of Kessler 10 Rating Scale in Study on Relationship be
Injury and Mental Health Status. Chinese Mental Health Journal 23, 175–178,191, https://doi.org/10.3969/j.issn.1
6729.2009.03.007 (2009).
34. Lukaszyk, C. et al. Risk factors, incidence, consequences and prevention strategies for falls and fall-injury with
populations: a systematic review. Australian and New Zealand journal of public health 40, 564–568, https://doi.o
6405.12585 (2016).
Acknowledgements
This study was not funded by any sponsor. We are grateful to the investigators involved for their
to the enrolment of subjects and specifically thank all participants in the study. We would like to t
Research Editing Service (http://authorservices.springernature.com/language-editing/) for English
editing.
Author Contributions
All authors significantly contributed to this study. H.P.Z. participated in the preparation of this ma
M.H. and J.Q.C. contributed to the statistical analysis and managed the field investigation. S.X.P. c
the sampling selection schedule. All authors reviewed the manuscript. In addition, all authors app
draft.
Additional Information
Competing Interests: The authors declare that they have no competing interests.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in publish
institutional affiliations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 Interna
License, which permits use, sharing, adaptation, distribution and reproduction in any m
format, as long as you give appropriate credit to the original author(s) and the source, provide a
ative Commons license, and indicate if changes were made. The images or other third party mate
article are included in the article’s Creative Commons license, unless indicated otherwise in a cre
material. If material is not included in the article’s Creative Commons license and your intended u
mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission d
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2017