International Journal of Injury Control and Safety Promotion, 2014 Vol. 21, No. 1, 1–2, http://dx.doi.org/10.1080/17457300.2014.885197
EDITORIAL Injury epidemiology research and secondary data It is often said that the findings of an epidemiologic investigation are only as good as the data upon which they are based (Friis & Sellers, 2014). This assertion is akin to the phenomenon of ‘GIGO’ or garbage in, garbage out – the fact that computers will unquestionably process unintended, even nonsensical, input data (‘garbage in’) and produce undesired, often nonsensical, output (‘garbage out’). The same phenomenon applies to injury research. The findings from an injury research may only be valid and have the desired impact as long as the data upon which they are based are valid and also appropriate. Basically, there are two main methods of acquiring data for use in any injury epidemiologic investigation: primary data collection and use of secondary or existing data, usually administrative data. In the first method, primary data collection, the investigators design and collect fresh data from study subjects. In the second, data already collected for some other purpose are used in whole or in part to answer appropriate, relevant research questions. Vital records or statistics represent the oldest and most commonly used secondary data source for investigations on injury mortality. It is important to point out that there are a few important things to consider in using secondary data. These include having a clear understanding of the nature of the data, their availability, the completeness of the population coverage, and the value and limitations of the data. Most public health data that serve as a repository for secondary data sources are obtained through routine mandatory reporting of events or via surveys. One data source that has been used a lot for injury investigations in the United States is the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is one of the world’s largest ongoing, state-based telephone health survey systems for data collection by the Centers for Disease Control and Prevention (CDC). It tracks health conditions and risk behaviours in the United States yearly since 1984. It has been used to advance safety promotion in many settings, for example for residential fire safety (Forjuoh, Coben, Dearwater, & Weiss, 1997) and firearm safety (Okoro et al., 2005). However, the data may be limited to answer certain questions because they are self-reported and exclude individuals without telephones. Therefore, no sensible or valid inferences can be made about the homeless. Generally, data-sets based on interview suffer from recall bias, interviewer variability, social desirability responses, inaccurate or incorrect recording, and selection or non-response bias. Similarly, observational data may
Ó 2014 Taylor & Francis
be limited by inaccurate or incorrect recording of observed data (e.g., age, gender) as well as surveyor variability. Nonetheless, many injury epidemiologic investigations could not be carried out without having access to secondary data as evidenced by some of the articles in the current issue of the journal. The most important thing is to be very familiar with the data-set, along with all the elements and their definitions and measures. Three articles in the current issue of the journal utilised secondary or administrative data-sets to study various injury types in diverse settings including Taiwan, Finland, Norway, Portugal, Sweden, and Malaysia. The first article by Wu-Chien, Chi-Hsiang, ChiHuang, and Chiu-Hsuan (2014) utilised the Taiwanese National Health Insurance Research Database to analyse injury types, causes of injury, medical utilisations, and the risk factors of injury mortality among hospitalised elderly. While they correctly described injuries with regard to person, causes, and cost, they also used logistic regression methods to evaluate correlates or risk factors of injury mortality from hospitalisation. They found falls and motor vehicle crashes as the most common cause of injury hospitalisation. Among the important correlates of mortality from injury were being male, having a skull fracture, presence of a comorbidity, and admission to a medical centre. The authors appropriately vouched for education and health promotion on fall prevention and traffic safety among the elderly. They also appropriately acknowledged some limitations of the dataset including missing such putative risk factors as injury severity, pulse, blood pressure, and other clinical data that were not collected as part of the database. Another limitation mentioned was the fact that the total medical expenditure reported was limited to the cost covered by the National Health Insurance, excluding expenditures for follow-up medical care such as rehabilitation. In the second article, Legrand et al. (2014) determined the presence of alcohol, illicit drugs, and psychoactive substances in the blood of drivers killed in road crashes in four European countries – Finland, Norway, Portugal, and Sweden – using national archival databases from these countries. The data from Finland were obtained from the Finnish Motor Insurers Centre and the Department of Forensic Medicine at the University of Helsinki. Similarly, the data from Norway were obtained from the Norwegian Road Accident Registry and Forensic Toxicology Database from the Norwegian Institute of Public Health.
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These two data-sets were merged to result in a database that corresponded to 59% of all car and van drivers killed in road crashes with blood samples taken during legal autopsy. The Portuguese and Swedish databases included drivers of fatal road crashes for which autopsy was carried out by the respective national medico-legal services. Due to standardisation of the data collection procedures, the authors were able to merge these data-sets while limiting the merged database to drivers of cars and vans aged 18 years or older in order to compute comparative statistics for these four European countries. For example, the authors found more male drivers and fewer drivers aged 18–24 years in Portugal than the other countries. Another interesting finding was the fact that drivers in Finland and Sweden were older than 50 years compared to the other two countries. In general, about 42% of the drivers tested positive for alcohol, with the highest prevalence found among the Portuguese. The authors concluded that the differences in alcohol and drug findings in the different countries reflected differences in drug and alcohol use among drivers in the respective countries. The last article by Amar-Singh, Tan, and Hashim (2014) studied childhood drowning in Malaysia using multiple secondary data-sets. The data-sets included drowning mortality from the Department of Statistics compiled by the National Registration Department, Ministry of Health, and the Royal Malaysian Police, non-fatal drowning data from the Health Informatics Centre of the Malaysia Ministry of Health, and newspaper archives on drowning focusing on location of drowning incidents compiled by Life Saving Society Malaysia. Cognisant of the severe limitations with each data-set, the authors did not make any attempts to merge the data-sets. Rather, findings from each data source were reported individually. In addition, the authors appropriately focused their analysis on simple descriptive statistics. These limitations notwithstanding, the article represented the first comprehensive national study on childhood drowning in Malaysia and served to highlight the magnitude of the previously unrecognised problem. The journal definitely encourages the use of secondary or administrative data for injury research as demonstrated by the publication of these three articles. However, it cautions authors to pay attention to the unique strengths and
limitations of each data source so as to use secondary data for injury epidemiologic research appropriately. In addition, there are other things that authors can do with secondary data sources such as merging or linkage of multiple sources to answer important questions as was done by Legrand et al. (2014). Besides serving to answer complex research questions, data linkage capitalises on existing resources to allow longitudinal analysis and also reduce respondent burden and cost of survey. Using secondary data appropriately for injury epidemiologic research will help to advance injury control and safety promotion. References Amar-Singh, H.S.S., Tan, P.S., & Hashim, L. (2014). Childhood drowning in Malaysia. International Journal of Injury Control and Safety Promotion, 21, 83–88. Forjuoh, S.N., Coben, J.H., Dearwater, S.R., & Weiss, H.B. (1997). Identifying homes with inadequate smoke detector protection from residential fires in Pennsylvania. Journal of Burn Care and Rehabilitation, 18, 86–91. Friis, R.H., & Sellers, T.A. (2014). Epidemiology for public health practice (5th ed.). Burlington, MA: Jones and Bartlett Learning. ISBN: 978-1-4496-6549-4. Legrand, S., Gjerde, H., Isalbert, C., Van der Linden, T., et al. (2014). Prevalence of alcohol, illicit drugs, and psychoactive medicine in killed drivers in four European countries. International Journal of Injury Control and Safety Promotion, 21, 17–28. Okoro, C.A., Nelson, D.E., Mercy, J.A., Balluz, L.S., Croby, A.E., Mokdad, A.H. (2005). Prevalence of household firearms and firearm-storage practices in the 50 states and the District of Columbia: Findings from the Behavioral Risk Factor Surveillance System, 2002. Pediatrics, 116, e370– e376. Wu-Chien, C., Chi-Hsiang, C., Chi-Huang, L., & Chiu-Hsuan, C. (2014). A retrospective population-based study of injury types among elderly in Taiwan. International Journal of Injury Control and Safety Promotion, 21, 3–8.
Samuel N. Forjuoh Department of Family and Community Medicine, Scott & White Healthcare, Texas A&M HSC College of Medicine, 1402 West Ave H, Temple, TX 76504, USA Email: [email protected]
Copyright of International Journal of Injury Control & Safety Promotion is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
EDITORIAL Injury epidemiology research and secondary data It is often said that the findings of an epidemiologic investigation are only as good as the data upon which they are based (Friis & Sellers, 2014). This assertion is akin to the phenomenon of ‘GIGO’ or garbage in, garbage out – the fact that computers will unquestionably process unintended, even nonsensical, input data (‘garbage in’) and produce undesired, often nonsensical, output (‘garbage out’). The same phenomenon applies to injury research. The findings from an injury research may only be valid and have the desired impact as long as the data upon which they are based are valid and also appropriate. Basically, there are two main methods of acquiring data for use in any injury epidemiologic investigation: primary data collection and use of secondary or existing data, usually administrative data. In the first method, primary data collection, the investigators design and collect fresh data from study subjects. In the second, data already collected for some other purpose are used in whole or in part to answer appropriate, relevant research questions. Vital records or statistics represent the oldest and most commonly used secondary data source for investigations on injury mortality. It is important to point out that there are a few important things to consider in using secondary data. These include having a clear understanding of the nature of the data, their availability, the completeness of the population coverage, and the value and limitations of the data. Most public health data that serve as a repository for secondary data sources are obtained through routine mandatory reporting of events or via surveys. One data source that has been used a lot for injury investigations in the United States is the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is one of the world’s largest ongoing, state-based telephone health survey systems for data collection by the Centers for Disease Control and Prevention (CDC). It tracks health conditions and risk behaviours in the United States yearly since 1984. It has been used to advance safety promotion in many settings, for example for residential fire safety (Forjuoh, Coben, Dearwater, & Weiss, 1997) and firearm safety (Okoro et al., 2005). However, the data may be limited to answer certain questions because they are self-reported and exclude individuals without telephones. Therefore, no sensible or valid inferences can be made about the homeless. Generally, data-sets based on interview suffer from recall bias, interviewer variability, social desirability responses, inaccurate or incorrect recording, and selection or non-response bias. Similarly, observational data may
Ó 2014 Taylor & Francis
be limited by inaccurate or incorrect recording of observed data (e.g., age, gender) as well as surveyor variability. Nonetheless, many injury epidemiologic investigations could not be carried out without having access to secondary data as evidenced by some of the articles in the current issue of the journal. The most important thing is to be very familiar with the data-set, along with all the elements and their definitions and measures. Three articles in the current issue of the journal utilised secondary or administrative data-sets to study various injury types in diverse settings including Taiwan, Finland, Norway, Portugal, Sweden, and Malaysia. The first article by Wu-Chien, Chi-Hsiang, ChiHuang, and Chiu-Hsuan (2014) utilised the Taiwanese National Health Insurance Research Database to analyse injury types, causes of injury, medical utilisations, and the risk factors of injury mortality among hospitalised elderly. While they correctly described injuries with regard to person, causes, and cost, they also used logistic regression methods to evaluate correlates or risk factors of injury mortality from hospitalisation. They found falls and motor vehicle crashes as the most common cause of injury hospitalisation. Among the important correlates of mortality from injury were being male, having a skull fracture, presence of a comorbidity, and admission to a medical centre. The authors appropriately vouched for education and health promotion on fall prevention and traffic safety among the elderly. They also appropriately acknowledged some limitations of the dataset including missing such putative risk factors as injury severity, pulse, blood pressure, and other clinical data that were not collected as part of the database. Another limitation mentioned was the fact that the total medical expenditure reported was limited to the cost covered by the National Health Insurance, excluding expenditures for follow-up medical care such as rehabilitation. In the second article, Legrand et al. (2014) determined the presence of alcohol, illicit drugs, and psychoactive substances in the blood of drivers killed in road crashes in four European countries – Finland, Norway, Portugal, and Sweden – using national archival databases from these countries. The data from Finland were obtained from the Finnish Motor Insurers Centre and the Department of Forensic Medicine at the University of Helsinki. Similarly, the data from Norway were obtained from the Norwegian Road Accident Registry and Forensic Toxicology Database from the Norwegian Institute of Public Health.
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Editorial
These two data-sets were merged to result in a database that corresponded to 59% of all car and van drivers killed in road crashes with blood samples taken during legal autopsy. The Portuguese and Swedish databases included drivers of fatal road crashes for which autopsy was carried out by the respective national medico-legal services. Due to standardisation of the data collection procedures, the authors were able to merge these data-sets while limiting the merged database to drivers of cars and vans aged 18 years or older in order to compute comparative statistics for these four European countries. For example, the authors found more male drivers and fewer drivers aged 18–24 years in Portugal than the other countries. Another interesting finding was the fact that drivers in Finland and Sweden were older than 50 years compared to the other two countries. In general, about 42% of the drivers tested positive for alcohol, with the highest prevalence found among the Portuguese. The authors concluded that the differences in alcohol and drug findings in the different countries reflected differences in drug and alcohol use among drivers in the respective countries. The last article by Amar-Singh, Tan, and Hashim (2014) studied childhood drowning in Malaysia using multiple secondary data-sets. The data-sets included drowning mortality from the Department of Statistics compiled by the National Registration Department, Ministry of Health, and the Royal Malaysian Police, non-fatal drowning data from the Health Informatics Centre of the Malaysia Ministry of Health, and newspaper archives on drowning focusing on location of drowning incidents compiled by Life Saving Society Malaysia. Cognisant of the severe limitations with each data-set, the authors did not make any attempts to merge the data-sets. Rather, findings from each data source were reported individually. In addition, the authors appropriately focused their analysis on simple descriptive statistics. These limitations notwithstanding, the article represented the first comprehensive national study on childhood drowning in Malaysia and served to highlight the magnitude of the previously unrecognised problem. The journal definitely encourages the use of secondary or administrative data for injury research as demonstrated by the publication of these three articles. However, it cautions authors to pay attention to the unique strengths and
limitations of each data source so as to use secondary data for injury epidemiologic research appropriately. In addition, there are other things that authors can do with secondary data sources such as merging or linkage of multiple sources to answer important questions as was done by Legrand et al. (2014). Besides serving to answer complex research questions, data linkage capitalises on existing resources to allow longitudinal analysis and also reduce respondent burden and cost of survey. Using secondary data appropriately for injury epidemiologic research will help to advance injury control and safety promotion. References Amar-Singh, H.S.S., Tan, P.S., & Hashim, L. (2014). Childhood drowning in Malaysia. International Journal of Injury Control and Safety Promotion, 21, 83–88. Forjuoh, S.N., Coben, J.H., Dearwater, S.R., & Weiss, H.B. (1997). Identifying homes with inadequate smoke detector protection from residential fires in Pennsylvania. Journal of Burn Care and Rehabilitation, 18, 86–91. Friis, R.H., & Sellers, T.A. (2014). Epidemiology for public health practice (5th ed.). Burlington, MA: Jones and Bartlett Learning. ISBN: 978-1-4496-6549-4. Legrand, S., Gjerde, H., Isalbert, C., Van der Linden, T., et al. (2014). Prevalence of alcohol, illicit drugs, and psychoactive medicine in killed drivers in four European countries. International Journal of Injury Control and Safety Promotion, 21, 17–28. Okoro, C.A., Nelson, D.E., Mercy, J.A., Balluz, L.S., Croby, A.E., Mokdad, A.H. (2005). Prevalence of household firearms and firearm-storage practices in the 50 states and the District of Columbia: Findings from the Behavioral Risk Factor Surveillance System, 2002. Pediatrics, 116, e370– e376. Wu-Chien, C., Chi-Hsiang, C., Chi-Huang, L., & Chiu-Hsuan, C. (2014). A retrospective population-based study of injury types among elderly in Taiwan. International Journal of Injury Control and Safety Promotion, 21, 3–8.
Samuel N. Forjuoh Department of Family and Community Medicine, Scott & White Healthcare, Texas A&M HSC College of Medicine, 1402 West Ave H, Temple, TX 76504, USA Email: [email protected]
Copyright of International Journal of Injury Control & Safety Promotion is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
