in 2013 , about 973 million people sustained injuries that warranted some type of healthcare globally .
non - fatal injuries cause 36.8 million years lived with disability ( yld ) , accounting for 14.8% of injury - induced disability adjusted life years ( dalys ) .
accurate statistics concerning non - fatal conditions are critical to valid calculation of the burden of injury . currently , there are two commonly - used methods to collect non - fatal injury data : hospital - based surveillance systems or population - based surveys .
hospital - based surveillance systems , such as the national injury surveillance system ( niss ) of china , have the advantage of written records collected typically in a systematic manner , but they fail to collect data concerning injured individuals who do not visit the hospital because of physical , financial or other barriers that lead to comparatively minor but still burdensome injuries relevant to public health
they permit detailed collection of injury morbidity data from the people who are injured but suffer from limitations including  lay diagnoses ( incorrect reporting by lay persons in the population rather than medical professionals ) , low response rate to surveys , and recall bias in reporting information that occurred months or years ago .
given the expense involved in population - based surveys , especially in populous countries like china , this study was designed to evaluate the extent to which medically - relevant injuries are incurred by individuals in china but are not accompanied by hospital visits .
if such cases are uncommon , hospital - based surveillance can serve as an excellent means to understand the burden of injuries in the chinese population .
if they are common , population - based surveys may be required to obtain accurate data about injury morbidity in the population .
therefore , we addressed two research questions : ( i ) what is the extent of injury events incurred by residents who did not visit a hospital following the injuries ? and ( ii ) what are the main reasons for individuals experiencing injury events but not visiting hospitals following them ?
the first provincial health household interview survey of hunan , china , conducted in 2013 , included items assessing illness and injury prevalence over the previous 2 weeks , including information about whether the persons having injuries over that time period visited hospitals or not , and the reasons for not visiting hospitals if applicable .
data from the first provincial health household interview survey of hunan , china were used .
the survey was organized by the provincial health and family planning commission of hunan and all interviews were completed by trained local interviewers from july through october , 2013 . in the survey , a multi - stage stratified random cluster sampling method selected 8400 households for face - to - face interviews .
adults in the household who were home at the time of the survey participated themselves .
for children ( under age 15 ) and household adults not home at the time of the survey , parents or other adult family members answered on their behalf .
injury events were defined as the occurrence of any of the following circumstances in the prior 14 days : ( i ) receiving medical treatment at a hospital ( defined to include any medical facility with physicians or other health care professionals present ) following an injury ; ( ii ) receiving medical treatment outside a hospital following an injury ( e.g. , treatment by self or others at home , such as taking medications , or receiving massage or hot compress ) ; and/or ( iii ) being off work or school , or in bed for more than 1 day , following an injury . based on variables identified in the survey that related
literature suggests are relevant to our hypotheses , we included the following variables in the statistical analysis : urban vs. rural setting , sex , age group , household income per capita .
we divided household income equally into four categories based on the household income per capita in the last year for urban and rural areas : lowest ( urban , < 9000 cny ; rural , < 4000 cny ) ; low ( urban , 900014 999 cny ; rural , 40006666 cny ) ; high ( urban , 15 00024 959 cny ; rural , 66679999 cny ) ; and highest ( urban 24 960 cny ; rural 10 000 cny ) .
injury prevalence rates over the past 2 weeks were calculated as  number of injuries divided by total number of respondents  1000%. injury events that occurred earlier than 2 weeks were regarded as 
injuries at other times. sampling weights ( the multiplicative inverse of respondents probability of being selected , w=1 ) were applied to correct unequal probabilities of being selected and non - response so as to obtain unbiased estimates . the probability (  ) that a study subject was randomly selected was calculated as the product of the probabilities of being chosen at all four stages ( =1234 ) , where 1 is the probability that the primary sample unit ( district / county ) being sampled in stage one , 2 is the probability that the second sample unit ( subdistrict / town ) was selected at stage two , 3 is the probability that the third sample unit ( community / village ) was chosen at stage three , and 4 is the probability that the fourth sample unit ( household ) was sampled at last stage . using the probabilities of being sampled , we calculated the sample weight as w=11234 in this study .
when the complex sample design ( sampling weight ) is considered , the confidence interval can be significantly wider than may be expected .
when the complex sample design is ignored , standard errors are often greatly underestimated , increasing the probability of type i error for the statistical test .
poisson regression with robust estimates is suggested as an alternative to control for overestimation of errors in binomial data for cross - sectional studies when the algorithms do not converge .
we conducted poisson regression to detect differences in prevalence rates by urban vs. rural setting , sex , age group and household income per capita .
sampling weights were considered in all statistical analyses ; details about sample weighting appear elsewhere .
all procedures were reviewed and approved by the medical ethics committee of central south university , changsha , china .
data from the first provincial health household interview survey of hunan , china were used .
the survey was organized by the provincial health and family planning commission of hunan and all interviews were completed by trained local interviewers from july through october , 2013 . in the survey , a multi - stage stratified random cluster sampling method selected 8400 households for face - to - face interviews .
adults in the household who were home at the time of the survey participated themselves .
for children ( under age 15 ) and household adults not home at the time of the survey , parents or other adult family members answered on their behalf .
injury events were defined as the occurrence of any of the following circumstances in the prior 14 days : ( i ) receiving medical treatment at a hospital ( defined to include any medical facility with physicians or other health care professionals present ) following an injury ; ( ii ) receiving medical treatment outside a hospital following an injury ( e.g. , treatment by self or others at home , such as taking medications , or receiving massage or hot compress ) ; and/or ( iii ) being off work or school , or in bed for more than 1 day , following an injury . based on variables identified in the survey that related
literature suggests are relevant to our hypotheses , we included the following variables in the statistical analysis : urban vs. rural setting , sex , age group , household income per capita .
we divided household income equally into four categories based on the household income per capita in the last year for urban and rural areas : lowest ( urban , < 9000 cny ; rural , < 4000 cny ) ; low ( urban , 900014 999 cny ; rural , 40006666 cny ) ; high ( urban , 15 00024 959 cny ; rural , 66679999 cny ) ; and highest ( urban 24 960 cny ; rural 10 000 cny ) .
injury prevalence rates over the past 2 weeks were calculated as  number of injuries divided by total number of respondents  1000%. injury events that occurred earlier than 2 weeks were regarded as 
injuries at other times. sampling weights ( the multiplicative inverse of respondents probability of being selected , w=1 ) were applied to correct unequal probabilities of being selected and non - response so as to obtain unbiased estimates . the probability (  ) that a study subject was randomly selected was calculated as the product of the probabilities of being chosen at all four stages ( =1234 ) , where 1 is the probability that the primary sample unit ( district / county ) being sampled in stage one , 2 is the probability that the second sample unit ( subdistrict / town ) was selected at stage two , 3 is the probability that the third sample unit ( community / village ) was chosen at stage three , and 4 is the probability that the fourth sample unit ( household ) was sampled at last stage . using the probabilities of being sampled , we calculated the sample weight as w=11234 in this study .
when the complex sample design ( sampling weight ) is considered , the confidence interval can be significantly wider than may be expected .
when the complex sample design is ignored , standard errors are often greatly underestimated , increasing the probability of type i error for the statistical test .
poisson regression with robust estimates is suggested as an alternative to control for overestimation of errors in binomial data for cross - sectional studies when the algorithms do not converge .
we conducted poisson regression to detect differences in prevalence rates by urban vs. rural setting , sex , age group and household income per capita .
sampling weights were considered in all statistical analyses ; details about sample weighting appear elsewhere .
all procedures were reviewed and approved by the medical ethics committee of central south university , changsha , china .
the weighted injury prevalence was 4.9 per 1000 persons during the previous 2 weeks , with a 95% confidence interval ( ci ) of 2.96.9 per 1000 persons .
rural inhabitants had a prevalence rate over two times that of urban inhabitants ( adjusted prevalence ratio : 2.5 ; 95% ci , 1.16.4 ) . compared to children aged 014 years old , persons aged 4564 years and aged 65 + had higher prevalence rates , with adjusted prevalence rate ratios of 3.9 ( 95% ci : 1.98.0 ) and 7.0 ( 95% ci : 2.321.7 ) , respectively .
inhabitants from households with the lowest and low per capita household income were at higher risk of suffering injuries compared to those from households with the highest per capita household income ( adjusted prevalence rate ratio : 4.7 , 95% ci : 1.121.9 and 1.9 , 95% ci : 1.03.6 , respectively ) . 

table 1weighted 2-week prevalence of non - fatal injuries in hunan province , china , 2013demographic variablenprevalence/1000 persons ( 95% ci)adjusted prr ( 95% ci)total24 2824.9 ( 2.9 , 6.9)setting  urban11 9662.4 ( 0.8 , 4.1)reference  rural12 3165.6 ( 0.3 , 8.0)2.5 ( 1.1 , 6.4)*sex  male12 8145.9 ( 4.3 , 7.5)1.5 ( 0.8 , 2.9 )  female12 0984.0 ( 0.9 ,
6.9)referenceage group ( years )  01444131.5 ( 0.4 , 2.5)reference  154474063.7(0.0 , 7.9)3.2 ( 0.6 , 18.5 )  456486445.3 ( 3.5 , 7.1)3.9 ( 1.9 , 8.0 ) *  65381910.9 ( 3.6 , 18.2)7.0 ( 2.3 , 21.7)*household income per capita  lowest726611.0 ( 1.1 , 21.0)4.7 ( 1.1 , 21.9 ) *  low64434.3 ( 2.2 , 6.4)1.9 ( 1.0 , 3.6 ) *  high46042.9 ( 0.1 , 5.7)1.4 ( 0.3 , 6.6 )  highest58962.3 ( 0.9 , 3.7)referenceci confidence interval.aprevalence rate ratio.bcontrolling for setting , sex , age group , and household income per capita.chousehold income per capita was equally classified into four categories based on quartiles : lowest ( urban , < 9000 cny ; rural , < 4000 cny ) ; low ( urban , 900014 999 cny ; rural , 40006666 cny ) ; high ( urban , 15 00024 959 cny ; rural , 66679999 cny ) ; and highest ( urban , 24 960 cny ; rural , 10 000 cny ) . due to missing value , the sum of numbers of four categories was less than 24 282.*p < 0.05 . weighted 2-week prevalence of non - fatal injuries in hunan province , china , 2013 ci confidence interval . prevalence rate ratio .
household income per capita was equally classified into four categories based on quartiles : lowest ( urban , < 9000 cny ; rural , < 4000 cny ) ; low ( urban , 900014 999 cny ; rural , 40006666 cny ) ; high ( urban , 15 00024 959 cny ; rural , 66679999 cny ) ; and highest ( urban , 24 960 cny ; rural , 10 000 cny ) . due to missing value ,
we identified 108 injury cases , including 56 in the previous 2 weeks and 52 at other times ( table 2 ) .
of the 56 injury events occurring during the previous 2 weeks , 14 were not treated at a hospital ( weighted proportion 41.2% , 95% ci : 084.7% ) . for injury events occurring at other times ,
table 2weighted proportions of injuries treated outside a hospital during the previous 2 weekstime of injurynumber of injuriesinjuries treated outside a hospitalnumberproportion ( 95% ci)during the previous 2 weeks561441.2% ( 0.0% , 84.7%)at other times521638.8% ( 5.6% , 72.1%)ci , confidence interval
. weighted proportions of injuries treated outside a hospital during the previous 2 weeks ci , confidence interval .
participants reported that  perceiving the injury to be too minor to be treated ,  economic limitations to travel to the hospital and receive treatment , and  having no time to seek medical care were the three most common reasons to explain why they did not visit a hospital following an injury event that occurred in the past 2 weeks , accounting for 56.9 , 36.4 and 6.3% of all reasons , respectively ( table 3 ) . 

table 3reasons given for not obtaining treatment at a hospital following an injury during the previous 2 weeksreasonsnumberweighted proportion ( % ) ( 95% ci)injury perceived as too minor to need treatment756.9% ( 39.2% , 74.5%)economic limitations to travel to a hospital and receive treatment436.4% ( 21.8% , 50.9%)having no time to travel to a hospital and receive treatment26.3% ( 0.0% , 21.8%)long waiting time to see a doctor10.4% ( 0.0% , 1.4%)ci , confidence interval .
reasons given for not obtaining treatment at a hospital following an injury during the previous 2 weeks ci , confidence interval .
about 40% of injuries reported by participants in the first provincial household interview survey in hunan province , china , were not treated in a hospital or medical facility .
participants explained they did not go to a hospital for various reasons , including perceptions that the injuries were too minor to need treatment or not having time to go to a hospital , as well as unaffordable access to hospital care due to economic limitations or distance limitations due to transportation barriers .
based on the survey results , the 2-week injury prevalence of the full population was 4.9 per 1000 persons .
the findings concord with previous reports and indicate that many non - fatal injury events are not captured by the hospital - based surveillance system in china due to economic and physical restrictions to access of care at hospitals , and disparities in how serious an injury is for hospital - based treatment to be considered worthwhile by citizens .
these results also suggest the burden of non - fatal injury is substantially underestimated by the hospital - based national injury surveillance system in china and reinforce the need for china and other nations to use population - based survey data in conjunction with hospital surveillance systems to correctly estimate the burden of injury morbidity . in china , a good option to collect ancillary data would be through the national household health interview survey , which is conducted every five years .
appropriate questions about injury incidents could be designed and included in the survey to obtain adjustment coefficients between population - based survey data and hospital - based surveillance data .
due to lack of incidence and prevalence data over longer recall periods for the same population , we can not quantify differences in non - fatal injury incidence between 2-week and longer recall periods .
considering the potential for recall bias over longer time periods , it would be valuable to conduct studies that obtain transformation coefficients of injury morbidity incidences between short and long ( e.g. 12 months ) recall periods , thus offering accurate input to the calculation of daly .
in addition , we also detected significant gaps between urban areas and rural areas , and across age group and income groups .
these results are consistent with previous studies and reflect the substantial disparities present in chinese culture , where rural inhabitants , older persons and low - income households are at elevated risk of injuries .
the precise reason for elevated risk among rural , older , and lower - income individuals is not known definitively , but the literature points to multiple contributing factors . risk among both rural and low - income individuals is likely elevated for a variety of factors , including societal prejudice or bias , reduced financial and tangible resources , and diminished social capital .
there may also be reduced access to quality health care services and both physical and financial barriers to obtain medical care .
the mechanisms behind risk for older individuals overlap somewhat but may also include risks that emerge with physical , perceptual , and other biological changes that occur as humans grow older , many of which increase injury risk .
this study was limited by the lack of detailed information over different recall periods for injury incidence and prevalence , cause of injury , type of injury and severity of injury . without such information
, we can not set up comparability coefficients of different operational injury definitions with varying recall periods .
such information would provide a basis to compile data based on various injury definitions and estimate global , national , or local injury burden .
in addition , the sample size was inadequate to obtain stable proportions of injury events not visiting a hospital and to do subgroup analysis .
analysis based on larger samples will provide stable and valuable proportions that can be used to reliably estimate injury incidence or prevalence .
this work was supported by the national natural science foundation of china ( 81573260 ) . 

key pointsthe weighted injury prevalence was 4.9 per 1,000 persons during the last 2 weeks in hunan , china.of the 56 injury events occurring in the previous 2 weeks , 14 ( weighted proportion 41.2% ) were treated outside a hospital.major reasons for skipping hospital visits included perceiving injuries were too minor and economic limitations to travel to hospitals or seek treatment . 
 
the weighted injury prevalence was 4.9 per 1,000 persons during the last 2 weeks in hunan , china .
of the 56 injury events occurring in the previous 2 weeks , 14 ( weighted proportion 41.2% ) were treated outside a hospital .
major reasons for skipping hospital visits included perceiving injuries were too minor and economic limitations to travel to hospitals or seek treatment .
 abstract 
 background : injury morbidity data are collected through hospital - based surveillance in many countries . we assessed the extent of non - fatal injures treated outside a hospital . 
 methods : data from the first provincial health household interview survey of hunan , china , conducted in 2013 , were used . 
 injury events were identified and included as medically significant when any of the following circumstances occurred in the prior 14 days : ( i ) receiving medical treatment from a doctor at a hospital following an injury ; ( ii ) receiving medical treatment by self or others outside a hospital following an injury ( e.g. taking medications , or receiving massage or hot compress ) ; and/or ( iii ) being off work or school , or in bed for more than 1 day , following an injury . 
 the 2-week prevalence of non - fatal injuries and 95% confidence intervals were calculated . 
 we calculated the proportion of injury events treated outside a hospital and the reasons for not visiting a hospital for injury events occurring during the previous 2 weeks . 
 results : we captured 56 injury events during the previous 2 weeks . 
 the weighted injury prevalence was 4.9 per 1000 persons during the last 2 weeks ( 95% confidence interval : 2.96.9 per 1000 persons ) . 
 of the 56 events , 14 ( weighted proportion 41.2% ) were treated outside a hospital . 
 primary explanations for skipping hospital visits included perceiving injuries were too minor and economic limitations to travel to hospitals or seek treatment . 
 conclusion : results imply the burden of non - fatal injury may be underestimated by hospital - based surveillance systems such as that used in china . 
Introduction
Methods
Data source
Outcome measure and demographic variables
Statistical analysis
Results
Discussion
Funding