25
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Features and Risk Factors of Nonfatal Injury among the Rural Children: A Survey of Seven Schools in a Mountain Area in Southwest China

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          We aimed to investigate the patterns and risk factors of nonfatal injuries among rural mountain-area children in southwest China.

          Methods

          A stratified sampling method was used to recruit rural children aged 8 to 17 years (mainly 9–14 years) from 7 schools. Self-reported injuries during the past 12 months and relevant concerns were collected from June to December 2012 by using a structured questionnaire in a class interview.

          Results

          The mean age of the 2,854 children was 12.2±1.5 years. The probability of annual injury was 16.7% (95% confidence interval [95% CI] 15.3–18.1%), with slightly higher injury risk for boys than girls (17.7% vs. 16.0%; P>0.05). The top 3 causes of injuries were falls (37.3%), animal-related incidents (20.6%), and burns (14.9%). The main injury risk factors included being involved in a violent episode (odds ratio [OR] 1.34, 95% CI 1.08–1.66, P = 0.007), maltreatment by parents or guardians (1.42, 1.17–1.72, P<0.001), and being from a single-child family (1.30, 1.10–1.66, P = 0.039). Older age was a protective factor (0.81, 0.76–0.87, P<0.001).

          Conclusions

          The incidence of nonfatal injury among rural children was high, and falls were the leading cause. Younger children and boys from poor-care and poor-living environments were at increased risk of injury, which requires urgent attention. Injury prevention programs targeting these issues are needed in this mountain area and similar rural regions of China.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: found
          • Article: not found

          Sample size determination for logistic regression revisited.

          There is no consensus on the approach to compute the power and sample size with logistic regression. Some authors use the likelihood ratio test; some use the test on proportions; some suggest various approximations to handle the multivariate case. We advocate the use of the Wald test since the Z-score is routinely used for statistical significance testing of regression coefficients. The null-variance formula became popular from early studies, which contradicts modern software, which utilizes the method of maximum likelihood estimation (MLE), when the variance of the MLE is estimated at the MLE, not at the null. We derive general Wald-based power and sample size formulas for logistic regression and then apply them to binary exposure and confounder to obtain a closed-form expression. These formulas are applied to minimize the total sample size in a case-control study to achieve a given power by optimizing the ratio of controls to cases. Approximately, the optimal number of controls to cases is equal to the square root of the alternative odds ratio. Our sample size and power calculations can be carried out online at www.dartmouth.edu/ approximately eugened.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Injury-related fatalities in China: an under-recognised public-health problem.

            The May 2008 earthquake in Wenchuan drew attention to the important but largely unrecognised public-health problem of injury-related mortality and morbidity in China. Injuries account for more than 10% of all deaths and more than 30% of all potentially productive years of life lost due to premature mortality in China. Traffic-related injuries (mainly among cyclists and pedestrians), suicide, drowning, and falls account for 79% of all injury deaths. Rural injury death rates are double those of urban rates and male rates are double those of female rates. Despite an 81% increase in the traffic-related mortality from 1987 to 2006-associated with rapid motorisation-the overall injury mortality decreased by 17%, largely due to a surprising (and unexplained) 57% reduction in the suicide rate. Low-cost prevention measures that are most likely to produce large reductions in injury deaths include enforcement of laws for drinking and driving and for seat belt and helmet use, restriction of access to the most potent pesticides, and teaching children to swim. China needs to improve monitoring of fatal and non-fatal injuries, promote intersectoral collaboration, build institutional capacities, and, most importantly, mobilise community support and political will for investment in prevention.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Sample size and optimal design for logistic regression with binary interaction.

              There is no consensus on what test to use as the basis for sample size determination and power analysis. Some authors advocate the Wald test and some the likelihood-ratio test. We argue that the Wald test should be used because the Z-score is commonly applied for regression coefficient significance testing and therefore the same statistic should be used in the power function. We correct a widespread mistake on sample size determination when the variance of the maximum likelihood estimate (MLE) is estimated at null value. In our previous paper, we developed a correct sample size formula for logistic regression with single exposure (Statist. Med. 2007; 26(18):3385-3397). In the present paper, closed-form formulas are derived for interaction studies with binary exposure and covariate in logistic regression. The formula for the optimal control-case ratio is derived such that it maximizes the power function given other parameters. Our sample size and power calculations with interaction can be carried out online at www.dartmouth.edu/ approximately eugened. Copyright (c) 2007 John Wiley & Sons, Ltd.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                10 July 2014
                : 9
                : 7
                : e102099
                Affiliations
                [1 ]Epidemiology and Health Statistics, School of Public Health, Zunyi Medical College, Zunyi, China
                [2 ]Center for Disease Control and Prevention of Zunyi City, Zunyi, China
                [3 ]Center for Injury Research and Policy, Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus, Ohio, United States of America
                [4 ]Affiliated Hospital of Zunyi Medical College, Zunyi, China
                Brighton and Sussex Medical School, United Kingdom
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: XQS CY. Performed the experiments: YHQ DS BLC DL LRL HYW. Analyzed the data: YHQ BLC XQS. Wrote the paper: XQS YHQ DL. Made scientific comments and revisions: JXS.

                Article
                PONE-D-13-54888
                10.1371/journal.pone.0102099
                4092098
                25010712
                29b89810-ce04-430f-8b58-f38aee08cc31
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 January 2014
                : 14 June 2014
                Page count
                Pages: 6
                Funding
                This project was funded by the National Natural Science Foundation of China (grant No. 81160350) and the Specific Foundation for the Scientific Educational Talent of President of Guizhou Province, China (grant No. Qian [2011]55). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Epidemiology
                Pediatric Epidemiology
                Health Care
                Health Care Policy
                Child and Adolescent Health Policy
                Communication in Health Care
                Pediatrics
                Child Health
                Public and Occupational Health
                Global Health
                Health Screening
                Preventive Medicine
                Research and Analysis Methods
                Research Design
                Survey Research
                Survey Methods
                Clinical Research Design

                Uncategorized
                Uncategorized

                Comments

                Comment on this article