Prediction of the rate of hand injuries in Singapore

Prediction of the rate of hand injuries in Singapore | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prediction of the rate of hand injuries in Singapore Glen Zi Qiang Liau, Joel Yat Seng Wong, Wei Xuan Tay, Jia Yi Weng, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-806073/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Purpose This study aims to analyze the correlation between the incidence rate of hand injuries and various construction and manufacturing indicators in Singapore. We hypothesize that the number of hand injuries is correlated to activity in the construction and manufacturing industries in Singapore. Methods 20,764 patients who underwent hand surgeries in a tertiary institution between 2012 to 2018 were reviewed. Two independent, blinded observers extracted the frequency of hand surgeries performed from Electronic Medical Records. Economic indicators pertinent to Singapore’s labor force, construction and manufacturing industries were collected and smoothed by simple moving average of the prior 3 months. Results were analyzed using IBM SPSS v25.0. Results Significant independent univariate variables were Purchasing Manager Index for Manufacturing and Industrial Production Index. Multivariate regression of quarterly reported figures showed that Purchasing Manager Index for Manufacturing, Construction Index, Labor Productivity Change for Gross Domestic Product and Labor Productivity Change for Manufacturing were significantly correlated with hand injuries, with r square = 60.9%. Conclusion Quarterly economic indicators from construction and manufacturing industries can be used to predict the incidence of hand injuries with a 60.9% correlation. These findings may be useful for anticipating healthcare resource allocation to treat hand injuries. Type of Study and Level of Evidence Economic and decision, Level II. Toxicology Demand Supply Labor Health 1. Introduction Hand injuries are frequently encountered by doctors involved in trauma care. 1 Studies in the Emergency Department (ED) have shown that hand injuries comprise up to 10% of the visits and range from simple lacerations or finger sprains to mutilating injuries or amputations. 2 The high incidence rate of hand injuries in Singapore is not limited to those that present to emergency departments. AIG Asia Pacific Insurance Pte. Ltd analyzed 3,500 claims in a 12-month period and found that hand injuries accounted for 36% of the overall claims reported. In contrast, slip, trip and fall accidents contributed 24%. 3 Hand injuries make up a significant percentage of acute injuries in Singapore and form the most common traumatic occupational injury. 4 Various studies have evaluated the epidemiology of wrist and hand injury in numerous countries. Burridge JD et. al. reported that the occupations in New Zealand with the highest rate of hand injuries are machine operators, construction, forestry workers and meat processing workers. Michal Grivna et al. 5 found that hand injuries constitute 7%-28% of all injuries in the United Arab Emirates (UAE) 6 , 7 , and account for approximately 20% of all emergencies presenting to hospital emergency departments. 8 Polinder S. et al. found that in the Netherlands, 42% of all emergency department visits were due to upper extremity injuries, of which injuries to the wrist and hand were the most common. 9 Construction and manufacturing industries are the highest contributors of hand injuries. AIG Asia Pacific Insurance Pte. Ltd reports that 35% of the total annual claims value was incurred by workers in the construction and manufacturing trade. 3 Hey et al. studied 504 patients admitted to the ED (National University Hospital (NUH) Singapore) with hand injuries over a course of three months and found that 43% of these patients suffered from industrial injuries, comprising of lacerations and crush trauma. 10 If there is a significant correlation between hand injuries and activity in the construction and manufacturing industries, a fluctuation in the labor force of these industries may intuitively cause the number of hand injuries to fluctuate correspondingly. Singapore’s labor workforce is flexible, with the total labor force fluctuating over the years. The Report on Labor Force in Singapore by the Ministry of Manpower details that between 1994 to 1996, the percentage change year on year was 4.5–5.04% to 15.75% respectively; and from 2000 to 2002, the percentage change was − 0.74–6.3% to -0.42% respectively. 11 Moreover, as Singapore has long counted on its people as its biggest resource, Singapore's economy is heavily dependent on foreign labor, particularly in blue collar jobs. There are 1,382,900 foreign workers (36% of Singapore’s total labor force), of which approximately 300,000 of them are in the construction industry 12 , while 50% of the manufacturing industry are foreign workers. 13 Workers in sectors requiring manual labor, in particular the construction and manufacturing industry, tend to face a higher risk of suffering from hand injuries. Grivna et al. found that in the UAE, workers in the construction industry were at a higher risk of suffering hand injuries. Hand injury rates of workers operating machinery was 51.1% compared to heavy objects (27.7%), traffic (0%) and animal (0%). 5 To the author’s knowledge, no studies have been conducted to evaluate the correlation between the incidence rate of hand injuries and manpower in the construction and manufacturing industries in Singapore. Our study aims to analyze the correlation between the incidence rate of hand injuries and manpower in the construction and manufacturing industries in Singapore. We hypothesize that economic indicators in the construction and manufacturing industries are directly correlated to the rate of hand injuries. 2. Methods Twenty thousand, seven hundred and sixty-four consecutive patients who had undergone Hand & Reconstructive Microsurgery (HRM) surgeries in a single tertiary trauma institution between January 2012 and December 2018 were included in our retrospective study. A non-observer team member extracted the relevant patient data from the Electronic Medical Records and performed de-identification of data. The study was performed by two independent observers who were blinded to the patient identifiers. Various economic markers that were pertinent to Singapore’s labor force, construction and manufacturing industries were used for this study, as shown in Table 1 . These economic indicators were collected and published online by Singapore government agencies. The various economic indicators were smoothed by a calculation of simple moving average of the prior 3 months. Table 1 List of economic markers relevant to Singapore’s labor force, construction and manufacturing industries. Economic marker Abbreviation Source Frequency Manufacturing Index MI CEIC Data, Department of Statistics Monthly Construction Index CI CEIC Data, Department of Statistics Monthly Total Manufacturing Output TMO CEIC Data, Department of Statistics Yearly Purchasing Manager Index PMI Singapore Institute of Purchasing and Material Management Monthly Labor Productivity Change for Gross Domestic Product LPCgdp Ministry of Trade and Industry Quarterly Labor Productivity Change for Manufacturing LPCmanu Ministry of Trade and Industry Quarterly Labor Productivity Change for Construction LPCcons Ministry of Trade and Industry Quarterly Composite Leading Index CLI Ministry of Trade and Industry Construction Contracts Awarded CCA Building and Construction Authority Monthly Contracts Awarded CA CEIC Data, Department of Statistics Yearly Change in Value Added per worker per actual hour worked for Manufacturing CVAmanu CEIC Data, Department of Statistics Yearly Change in Value Added per worker per actual hour worked for Construction CVAcons CEIC Data, Department of Statistics Yearly Industrial Production Index IPI Singapore Economic Development Board Monthly IBM SPSS software version 25.0 was used for data analysis. Chi Square test was performed to compare the various economic indicators against incidence rate of hand injuries. Statistical significance was defined as p-value < 0.05. This study was approved by an Institutional Review Board. 3. Results Demographics 73.68% of our patients were between 21 to 60 years old. There was a male predominance 71.57%, and 53.69% of our patients were Chinese (Table 2 ) . Table 2 Demographics of 20, 764 patients according to age, gender, nationality and race. Percentage (%) Age (years old) # 1 to 20 9.77 21 to 40 42.13 41 to 60 31.55 61 to 80 15.44 80 to 98 ^ 1.11 Gender Male 71.57 Female 28.43 Nationality Singaporean 58.79 Non-Singaporean 41.21 Race % Chinese 53.68 Malay 11.59 Indian 15.58 Others 19.14 # Mean age is 40.93 years old ^ Oldest patient is 98 years old % The “CMIO model” is the dominant organizing framework of race in Singapore 14 , 15 Univariate and Multivariate analysis The results for the univariate analysis and multivariate linear regression analysis conducted via SPSS to analyze the correlation between the various economic variables and the incidence rate of hand injuries is shown in Table 3 . Table 3 Univariate and Multivariate analysis of various economic indicators Univariate analysis Multivariate analysis R square (%) p value R square (%) p value Quarterly Purchasing Manager Index for Manufacturing 0.161 0.034* 60.9 0.001* Construction Index 0.020 0.471 Labor Productivity Change (GDP) 0.024 0.427 Labor Productivity Change (Manu) 0.073 0.165 Labor Productivity Change (Cons) 0.024 0.429 - - Industrial Production Index 0.132 0.057 - - Manufacturing Index 0.004 0.757 - - Monthly Purchasing Manager Index for Manufacturing 0.084 0.008* - - Construction Index 0.009 0.390 - - Construction Contracts Awarded 0.321 0.011* 0.48 0.005* Industrial Production Index 0.070 0.016* Manufacturing Index 0.003 0.637 *: Significant values (p < 0.05) Univariate analysis showed that the correlations were significant (p < 0.05) between incidence rate of hand injuries and quarterly PMI (r = 0.161, p = 0.034), monthly PMI (r = 0.084, p = 0.008), monthly IPI (r = 0.070, p = 0.016) and monthly CCA (r = 0.321, p = 0.011). Multivariate linear regression showed that the combination of economic variables in the quarterly analysis of PMI, CI, LPCgdp and LPCManu gave a combined highest significant (p < 0.05) R square value of 0.609, or 60.9%. For monthly comparison, IPI and CCA were significant (p < 0.05) independent variables for the incidence of hand injuries, yielding a R square value of 0.480 or 48.0%. Equation An equation to predict the number of hand injuries was derived including all four significantly independent economic variables using the quarterly analysis: Number of hand injuries = 22.9 (PMI d ) + 2.77 (CI e ) − 36.7 (LPCgdp f ) + 6.88 (LPCmanu g ) − 4033 Legend: d PMI: Purchasing Manager Index for Manufacturing e CI: Construction Index f LPCgdp: Labor Productivity Change for Gross Domestic Product g LPCmanu: Labor Productivity Change for Manufacturing for Manufacturing Variables were smoothed to simple moving average of 3 months 4. Discussion The Singapore economy is susceptible to global economic activity. It is a small island state with a lack of natural resources. 16 At the outset of industrialization in the 1960s, the country depended on foreign direct investment from multinationals in labor-intensive manufacturing industries to secure the requisite markets, technical knowledge and management expertise. 17 Over the years, openness to trade and investment allowed Singapore to raise its productive and technological capabilities, transforming the state into a high value-added manufacturing node in regional production networks. 17 As an export driven economy reliant on global trade, Singapore’s Gross Domestic Product (GDP) has seen both expansion and contraction over the years with GDP growth (annual %) fluctuating 4.46% (2012), 4.84% (2013), 3.94% (2014), 2.99% (2015), 3.24% (2016), 4.34% (2017), 3.44% (2018). 18 The Straits Times Index (STI), a market capitalization weighted index that tracks the performance of the top 30 companies listed on SGX 19 also fluctuates: 7.92% (2012) to 4.78% (2013) to 12.79% (2014) to -14.06% (2015) to -7.45% (2016) to 9.00% (2017) to 8.06% (2018). 20 Singapore’s labor force has seen fluctuation across the years. The Report on Labor Force in Singapore by the Ministry of Manpower details that between 1994 to 1996, the percentage change year on year was 4.5–5.04% to 15.75% respectively. 11 ; and from 2012 to 2018, the percentage change was 3.71–2.38% to 2.47–2.21% to 1.69% to -0.43–0.51% respectively. 21 In 2018, Singapore’s Ministry of Manpower’s reported in their labor force findings that the total labor force stood at 3,675,600, with the employment rate being 97.3% (3,575,300). 11 The resident labor force at that time was 2,292,700, with a median age of 43 years old and labor force participation rate of 67.7%. 22 With a high employment rate of 97.3%, economic indicators such as the Straits Times Index (STI) and Gross Domestic Product (GDP) performed well for that year, with the 2018 economy expanding by 1.9 per cent from 2017. 23 Singapore’s gross domestic product (GDP) is the most important measure to evaluate the performance of Singapore’s economy. 24 Labor force fluctuations also occur internationally. The countries with the smallest fluctuation in labor force are part of the European Union (EU). From 2012 to 2018, The European Union faced an average percentage change in labor force of 0.37%, with Italy, France and Germany experiencing 0.47%, 0.70%, 0.80% respectively 25 . In comparison, Singapore experienced 1.50% change 26 , a figure which is more than its Asian counterparts Japan (0.66%) and Korea (1.32%) 25 . The comparatively smaller fluctuations in the labor force of the EU with Singapore can perhaps be attributed to the EU’s employee centric employment laws, making it more difficult to lay off workers. 27 Whereas Singapore is more employer centric. 28 In Singapore, hand injuries make up a significant portion of acute injuries 29 , many of which are sustained in the industrial workplace. In 2020, there were 46 out of 463 (9.34%) cases where workers lost their hands or fingers in amputation accidents. 30 , 31 The number of hand injuries would fluctuate with fluctuations in the total number of labor force in a country. Formulation of equation Indeed there are multiple correlations of Singapore’s hand injuries with economic indicators. Significant (p < 0.05) multivariate variables were PMI, CI, LPCgdp, LPCmanu, which yielded 60.9% R square, p value 0.001 in the quarterly analysis. In the monthly analysis, significant (p < 0.05) multivariate variables were IPI and CCA which yielded a R square value of 0.480 or 48.0%. PMI is a measure of the prevailing direction of economic trends in manufacturing, summarizing whether market conditions from the perspectives of managers are expanding, staying the same or contracting. 32 , 33 , 34 CI indicates the level of economic activity in the Construction sector. 35 LPC indicates whether output is increasing or decreasing per worker. 36 , 37 Greater productivity describes being able to do more in the same amount of time, this in turn frees up resources to be used elsewhere. An equation to predict the number of hand injuries was derived including all four significant economic variables using the quarterly analysis: Number of hand injuries = 22.9 (PMI) + 2.77 (CI) − 36.7 (LPCgdp) + 6.88 (LPCmanu) − 4033 How to use the equation The equation is used in the following way: To predict the number of hand injuries, using the economic indicator of PMI as an example, keeping all others constant, if PMI goes up by 1%, there will be a 22.9 increase in the number of hand injuries. Strengths To the authors’ knowledge, this paper represents the first paper to analyze the correlation of economic factors against the number of hand injuries. In our data, there is a relatively high proportion of foreign patients (41.21%) that undergo hand surgeries. As of 2018, the total foreign workforce in Singapore stood at 1,386,000 (24.58% of the entire population). However, they are usually under-represented in studies. In this study, we present a large cohort of foreign patients, compared to the national proportion. The clinical implications of the study may allow us to forecast the clinical resources required to treat hand injuries from the construction and manufacturing industry in relation to economic indicators. Limitations We identified a few limitations in our study. Firstly, surgical factors. We used the incidence rate for hand surgeries as a proxy for the incidence rate for hand injuries. These hand surgeries included both elective and emergency operations and therefore may not be reflective of patients who presented with hand injuries but did not undergo hand surgeries. However, our large sample size of 20,764 patients is likely to account for exceptions pertaining to these cases. Hand injuries are typically emergency injuries such as lacerations and crush trauma; but our data combines both. Fortunately, elective operations are not known to fluctuate much. For example, trigger finger operations are not known to fluctuate from month to month. 38 , 39 , 40 Since we have found in our results there is a significant correlation between the incidence of hand injuries and economic indicators, an extrapolation between two time points effectively nullify the electives, leaving the emergencies to account for the cause of fluctuations. Secondly, our tertiary institution covers referrals from the south and western regions of Singapore where a higher proportion of construction and manufacturing industries are located. Hence, there may be a higher proportion of hand injuries that may present to our institution as opposed to other local tertiary institutions. However, this allows us to have an increased sensitivity to the fluctuations in hand surgeries done emergently in response to fluctuations in the labor force. Lastly, factor selection. Some of the factors used in our study were not reported in a timely fashion. For example, PMI is reported monthly, because companies use it to purchase equipment but others such as CI was published one year later. Therefore, the reporting time lag of the economic variables may dampen the usage of our equation as a timely method of forecasting. In conclusion, a correlation of 60.9% (p value = 0.001) was found between the number of hand injuries and the following economic indicators: PMI, CI, LPCgdp and LPCmanu for hand injuries from 2012 to 2018. These findings may enable us to forecast clinical resources required to treat hand injuries from the construction and manufacturing industry in relation to economic indicators. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and material Data may be made available upon reasonable request Competing interests/Conflicts of Interest There are no conflicts of interest to declare. Funding This study was not funded. Acknowledgements Authors’ contributions: GZQ Liau and AEJ Cheah conceptualised the research question and design of the manuscript. GZQ Liau, WX Tay, JYS Wong and JY Weng contributed to the design of the study, analysis and interpretation of data. All authors contributed to manuscript drafting and revision. All authors read and approved the final version of the manuscript. Nil funding was obtained for this study. References 1. Cheung K, Hatchell A, Thoma A. Approach to traumatic hand injuries for primary care physicians. Can Fam Physician . 2013;59(6):614-618. 2. Otto C. ABC of Emergency Radiology . Oxford, UK: Blackwell Publishing Ltd. 2007. 3. Client Risk Solutions AIG Asia Pacific Insurance Pte. Ltd. Beyond Insurance: Liabilities’ Risk Management for Workplace Injuries. 2017. Available from https://www.aig.sg/content/dam/aig/apac/singapore/documents/other/apac-sg-workers-safety-infographic-2017.pdf, accessed May 18, 2021. 4. 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Hand (N Y) . 2019;1558944719867135 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 20 Sep, 2021 Review # 1 received at journal 09 Sep, 2021 Review # 2 received at journal 05 Sep, 2021 Reviewer # 2 agreed at journal 24 Aug, 2021 Reviews received at journal 23 Aug, 2021 Reviewers invited by journal 23 Aug, 2021 Reviewer # 1 agreed at journal 22 Aug, 2021 Editor assigned by journal 17 Aug, 2021 Submission checks completed at journal 16 Aug, 2021 Editor invited by journal 16 Aug, 2021 First submitted to journal 11 Aug, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-806073","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":47585155,"identity":"9a2ba22e-381b-4e26-9bd2-366f2f2174e4","order_by":0,"name":"Glen Zi Qiang Liau","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDACdiB+wMAgB2IfeECUFmYgTmBgMAZrSSBFS2IDA4RBGMg7Mx97kPDHOn1+2OGHQFvs5HQbCGgxPMyWbpDAk5678XaaAVBLsrHZAUJamnnMJBIkDudunJ0A0nIgcRthLfzfJBIMDqcbzk7/QJwWeWYeNomEhMMJ8tI5RNpiwMwGdNiBdMMN0jkFBxIMiPCLfHvzM4kPf6zl5Wenb/7wocJOjqAWA4gCZijDgIBysC0NUC1QxigYBaNgFIwCTAAA7otC1TBgvGsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0498-9237","institution":"NUHS: National University Health System","correspondingAuthor":true,"prefix":"","firstName":"Glen","middleName":"Zi Qiang","lastName":"Liau","suffix":""},{"id":47585156,"identity":"c1626dd4-52fa-4653-a1bc-3805d2101f3e","order_by":1,"name":"Joel Yat Seng Wong","email":"","orcid":"","institution":"NUS Yong Loo Lin School of Medicine: National University Singapore Yong Loo Lin School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Joel","middleName":"Yat Seng","lastName":"Wong","suffix":""},{"id":47585157,"identity":"917923de-9ed1-45df-851c-50271b5af207","order_by":2,"name":"Wei Xuan Tay","email":"","orcid":"","institution":"NUS Yong Loo Lin School of Medicine: National University Singapore Yong Loo Lin School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"Xuan","lastName":"Tay","suffix":""},{"id":47585158,"identity":"df8edd7c-5399-4a4c-b41b-4d8d4f55b65d","order_by":3,"name":"Jia Yi Weng","email":"","orcid":"","institution":"NUS Yong Loo Lin School of Medicine: National University Singapore Yong Loo Lin School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"Yi","lastName":"Weng","suffix":""},{"id":47585159,"identity":"584018cf-a706-4162-ad8e-20457ad9d7ea","order_by":4,"name":"Andre Eu Jin Cheah","email":"","orcid":"","institution":"NUHS: National University Health System","correspondingAuthor":false,"prefix":"","firstName":"Andre","middleName":"Eu Jin","lastName":"Cheah","suffix":""}],"badges":[],"createdAt":"2021-08-12 10:41:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-806073/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-806073/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13711353,"identity":"66936a30-1495-47b5-9686-4fde5d50ddaf","added_by":"auto","created_at":"2021-09-17 14:22:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":267905,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-806073/v1/420c0c9f-c10d-4d47-b297-1ef9ba0982a2.pdf"}],"financialInterests":"","formattedTitle":"Prediction of the rate of hand injuries in Singapore","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHand injuries are frequently encountered by doctors involved in trauma care.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Studies in the Emergency Department (ED) have shown that hand injuries comprise up to 10% of the visits and range from simple lacerations or finger sprains to mutilating injuries or amputations.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The high incidence rate of hand injuries in Singapore is not limited to those that present to emergency departments. AIG Asia Pacific Insurance Pte. Ltd analyzed 3,500 claims in a 12-month period and found that hand injuries accounted for 36% of the overall claims reported. In contrast, slip, trip and fall accidents contributed 24%.\u003csup\u003e3\u003c/sup\u003e Hand injuries make up a significant percentage of acute injuries in Singapore and form the most common traumatic occupational injury.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eVarious studies have evaluated the epidemiology of wrist and hand injury in numerous countries. Burridge JD et. al. reported that the occupations in New Zealand with the highest rate of hand injuries are machine operators, construction, forestry workers and meat processing workers. Michal Grivna et al.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e found that hand injuries constitute 7%-28% of all injuries in the United Arab Emirates (UAE)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and account for approximately 20% of all emergencies presenting to hospital emergency departments.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Polinder S. et al. found that in the Netherlands, 42% of all emergency department visits were due to upper extremity injuries, of which injuries to the wrist and hand were the most common.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eConstruction and manufacturing industries are the highest contributors of hand injuries. AIG Asia Pacific Insurance Pte. Ltd reports that 35% of the total annual claims value was incurred by workers in the construction and manufacturing trade.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Hey et al. studied 504 patients admitted to the ED (National University Hospital (NUH) Singapore) with hand injuries over a course of three months and found that 43% of these patients suffered from industrial injuries, comprising of lacerations and crush trauma.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIf there is a significant correlation between hand injuries and activity in the construction and manufacturing industries, a fluctuation in the labor force of these industries may intuitively cause the number of hand injuries to fluctuate correspondingly. Singapore\u0026rsquo;s labor workforce is flexible, with the total labor force fluctuating over the years. The Report on Labor Force in Singapore by the Ministry of Manpower details that between 1994 to 1996, the percentage change year on year was 4.5\u0026ndash;5.04% to 15.75% respectively; and from 2000 to 2002, the percentage change was \u0026minus;\u0026thinsp;0.74\u0026ndash;6.3% to -0.42% respectively.\u003csup\u003e11\u003c/sup\u003e Moreover, as Singapore has long counted on its people as its biggest resource, Singapore's economy is heavily dependent on foreign labor, particularly in blue collar jobs. There are 1,382,900 foreign workers (36% of Singapore\u0026rsquo;s total labor force), of which approximately 300,000 of them are in the construction industry\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, while 50% of the manufacturing industry are foreign workers.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWorkers in sectors requiring manual labor, in particular the construction and manufacturing industry, tend to face a higher risk of suffering from hand injuries. Grivna et al. found that in the UAE, workers in the construction industry were at a higher risk of suffering hand injuries. Hand injury rates of workers operating machinery was 51.1% compared to heavy objects (27.7%), traffic (0%) and animal (0%).\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo the author\u0026rsquo;s knowledge, no studies have been conducted to evaluate the correlation between the incidence rate of hand injuries and manpower in the construction and manufacturing industries in Singapore.\u003c/p\u003e \u003cp\u003eOur study aims to analyze the correlation between the incidence rate of hand injuries and manpower in the construction and manufacturing industries in Singapore. We hypothesize that economic indicators in the construction and manufacturing industries are directly correlated to the rate of hand injuries.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eTwenty thousand, seven hundred and sixty-four consecutive patients who had undergone Hand \u0026amp; Reconstructive Microsurgery (HRM) surgeries in a single tertiary trauma institution between January 2012 and December 2018 were included in our retrospective study.\u003c/p\u003e \u003cp\u003eA non-observer team member extracted the relevant patient data from the Electronic Medical Records and performed de-identification of data. The study was performed by two independent observers who were blinded to the patient identifiers.\u003c/p\u003e \u003cp\u003eVarious economic markers that were pertinent to Singapore\u0026rsquo;s labor force, construction and manufacturing industries were used for this study, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These economic indicators were collected and published online by Singapore government agencies. The various economic indicators were smoothed by a calculation of simple moving average of the prior 3 months.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of economic markers relevant to Singapore\u0026rsquo;s labor force, construction and manufacturing industries.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic marker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbbreviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Manufacturing Output\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurchasing Manager Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingapore Institute of Purchasing and Material Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change for Gross Domestic Product\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPCgdp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Trade and Industry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change for Manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPCmanu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Trade and Industry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change for Construction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPCcons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Trade and Industry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposite Leading Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Trade and Industry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction Contracts Awarded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBuilding and Construction Authority\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContracts Awarded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in Value Added per worker per actual hour worked for Manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVAmanu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in Value Added per worker per actual hour worked for Construction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVAcons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCEIC Data, Department of Statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYearly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustrial Production Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIPI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingapore Economic Development Board\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIBM SPSS software version 25.0 was used for data analysis. Chi Square test was performed to compare the various economic indicators against incidence rate of hand injuries. Statistical significance was defined as p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e This study was approved by an Institutional Review Board.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDemographics\u003c/h2\u003e \u003cp\u003e73.68% of our patients were between 21 to 60 years old. There was a male predominance 71.57%, and 53.69% of our patients were Chinese (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e)\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics of 20, 764 patients according to age, gender, nationality and race.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years old)\u003c/b\u003e\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21 to 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41 to 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61 to 80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80 to 98\u003csup\u003e^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNationality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingaporean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Singaporean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003csup\u003e%\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChinese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e#\u003c/sup\u003eMean age is 40.93 years old\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e^\u003c/sup\u003eOldest patient is 98 years old\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e%\u003c/sup\u003eThe \u0026ldquo;CMIO model\u0026rdquo; is the dominant organizing framework of race in Singapore\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and Multivariate analysis\u003c/h2\u003e \u003cp\u003eThe results for the univariate analysis and multivariate linear regression analysis conducted via SPSS to analyze the correlation between the various economic variables and the incidence rate of hand injuries is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariate analysis of various economic indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eR square (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eR square (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuarterly\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurchasing Manager Index for Manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e60.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change (GDP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change (Manu)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLabor Productivity Change (Cons)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustrial Production Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurchasing Manager Index for Manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction Contracts Awarded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustrial Production Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*: Significant values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUnivariate analysis showed that the correlations were significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between incidence rate of hand injuries and quarterly PMI (r\u0026thinsp;=\u0026thinsp;0.161, p\u0026thinsp;=\u0026thinsp;0.034), monthly PMI (r\u0026thinsp;=\u0026thinsp;0.084, p\u0026thinsp;=\u0026thinsp;0.008), monthly IPI (r\u0026thinsp;=\u0026thinsp;0.070, p\u0026thinsp;=\u0026thinsp;0.016) and monthly CCA (r\u0026thinsp;=\u0026thinsp;0.321, p\u0026thinsp;=\u0026thinsp;0.011).\u003c/p\u003e \u003cp\u003eMultivariate linear regression showed that the combination of economic variables in the quarterly analysis of PMI, CI, LPCgdp and LPCManu gave a combined highest significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) R square value of 0.609, or 60.9%. For monthly comparison, IPI and CCA were significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) independent variables for the incidence of hand injuries, yielding a R square value of 0.480 or 48.0%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEquation\u003c/h2\u003e \u003cp\u003eAn equation to predict the number of hand injuries was derived including all four significantly independent economic variables using the quarterly analysis:\u003c/p\u003e \u003cp\u003e \u003cem\u003eNumber of hand injuries\u0026thinsp;=\u0026thinsp;22.9 (PMI\u003c/em\u003e \u003csup\u003e \u003cem\u003ed\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e)\u0026thinsp;+\u0026thinsp;2.77 (CI\u003c/em\u003e \u003csup\u003e \u003cem\u003ee\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e) \u0026minus;\u0026thinsp;36.7 (LPCgdp\u003c/em\u003e \u003csup\u003e \u003cem\u003ef\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e)\u0026thinsp;+\u0026thinsp;6.88 (LPCmanu\u003c/em\u003e \u003csup\u003e \u003cem\u003eg\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e) \u0026minus;\u0026thinsp;4033\u003c/em\u003e \u003c/p\u003e \u003cp\u003eLegend:\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003ePMI: Purchasing Manager Index for Manufacturing\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003eCI: Construction Index\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003eLPCgdp: Labor Productivity Change for Gross Domestic Product\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003eLPCmanu: Labor Productivity Change for Manufacturing for Manufacturing\u003c/p\u003e \u003cp\u003eVariables were smoothed to simple moving average of 3 months\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe Singapore economy is susceptible to global economic activity. It is a small island state with a lack of natural resources.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e At the outset of industrialization in the 1960s, the country depended on foreign direct investment from multinationals in labor-intensive manufacturing industries to secure the requisite markets, technical knowledge and management expertise.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Over the years, openness to trade and investment allowed Singapore to raise its productive and technological capabilities, transforming the state into a high value-added manufacturing node in regional production networks.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e As an export driven economy reliant on global trade, Singapore\u0026rsquo;s Gross Domestic Product (GDP) has seen both expansion and contraction over the years with GDP growth (annual %) fluctuating 4.46% (2012), 4.84% (2013), 3.94% (2014), 2.99% (2015), 3.24% (2016), 4.34% (2017), 3.44% (2018).\u003csup\u003e18\u003c/sup\u003e The Straits Times Index (STI), a market capitalization weighted index that tracks the performance of the top 30 companies listed on SGX\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e also fluctuates: 7.92% (2012) to 4.78% (2013) to 12.79% (2014) to -14.06% (2015) to -7.45% (2016) to 9.00% (2017) to 8.06% (2018).\u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSingapore\u0026rsquo;s labor force has seen fluctuation across the years. The Report on Labor Force in Singapore by the Ministry of Manpower details that between 1994 to 1996, the percentage change year on year was 4.5\u0026ndash;5.04% to 15.75% respectively.\u003csup\u003e11\u003c/sup\u003e; and from 2012 to 2018, the percentage change was 3.71\u0026ndash;2.38% to 2.47\u0026ndash;2.21% to 1.69% to -0.43\u0026ndash;0.51% respectively.\u003csup\u003e21\u003c/sup\u003e In 2018, Singapore\u0026rsquo;s Ministry of Manpower\u0026rsquo;s reported in their labor force findings that the total labor force stood at 3,675,600, with the employment rate being 97.3% (3,575,300).\u003csup\u003e11\u003c/sup\u003e The resident labor force at that time was 2,292,700, with a median age of 43 years old and labor force participation rate of 67.7%.\u003csup\u003e22\u003c/sup\u003e With a high employment rate of 97.3%, economic indicators such as the Straits Times Index (STI) and Gross Domestic Product (GDP) performed well for that year, with the 2018 economy expanding by 1.9 per cent from 2017.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Singapore\u0026rsquo;s gross domestic product (GDP) is the most important measure to evaluate the performance of Singapore\u0026rsquo;s economy.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLabor force fluctuations also occur internationally. The countries with the smallest fluctuation in labor force are part of the European Union (EU). From 2012 to 2018, The European Union faced an average percentage change in labor force of 0.37%, with Italy, France and Germany experiencing 0.47%, 0.70%, 0.80% respectively\u003csup\u003e25\u003c/sup\u003e. In comparison, Singapore experienced 1.50% change\u003csup\u003e26\u003c/sup\u003e, a figure which is more than its Asian counterparts Japan (0.66%) and Korea (1.32%)\u003csup\u003e25\u003c/sup\u003e. The comparatively smaller fluctuations in the labor force of the EU with Singapore can perhaps be attributed to the EU\u0026rsquo;s employee centric employment laws, making it more difficult to lay off workers.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Whereas Singapore is more employer centric.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn Singapore, hand injuries make up a significant portion of acute injuries\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, many of which are sustained in the industrial workplace. In 2020, there were 46 out of 463 (9.34%) cases where workers lost their hands or fingers in amputation accidents.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e The number of hand injuries would fluctuate with fluctuations in the total number of labor force in a country.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFormulation of equation\u003c/h2\u003e \u003cp\u003eIndeed there are multiple correlations of Singapore\u0026rsquo;s hand injuries with economic indicators. Significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) multivariate variables were PMI, CI, LPCgdp, LPCmanu, which yielded 60.9% R square, p value 0.001 in the quarterly analysis. In the monthly analysis, significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) multivariate variables were IPI and CCA which yielded a R square value of 0.480 or 48.0%.\u003c/p\u003e \u003cp\u003ePMI is a measure of the prevailing direction of economic trends in manufacturing, summarizing whether market conditions from the perspectives of managers are expanding, staying the same or contracting.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e CI indicates the level of economic activity in the Construction sector.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e LPC indicates whether output is increasing or decreasing per worker.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Greater productivity describes being able to do more in the same amount of time, this in turn frees up resources to be used elsewhere.\u003c/p\u003e \u003cp\u003eAn equation to predict the number of hand injuries was derived including all four significant economic variables using the quarterly analysis:\u003c/p\u003e \u003cp\u003e \u003cem\u003eNumber of hand injuries\u0026thinsp;=\u0026thinsp;22.9 (PMI)\u0026thinsp;+\u0026thinsp;2.77 (CI) \u0026minus;\u0026thinsp;36.7 (LPCgdp)\u0026thinsp;+\u0026thinsp;6.88 (LPCmanu) \u0026minus;\u0026thinsp;4033\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eHow to use the equation\u003c/h2\u003e \u003cp\u003eThe equation is used in the following way: To predict the number of hand injuries, using the economic indicator of PMI as an example, keeping all others constant, if PMI goes up by 1%, there will be a 22.9 increase in the number of hand injuries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStrengths\u003c/h2\u003e \u003cp\u003eTo the authors\u0026rsquo; knowledge, this paper represents the first paper to analyze the correlation of economic factors against the number of hand injuries. In our data, there is a relatively high proportion of foreign patients (41.21%) that undergo hand surgeries. As of 2018, the total foreign workforce in Singapore stood at 1,386,000 (24.58% of the entire population). However, they are usually under-represented in studies. In this study, we present a large cohort of foreign patients, compared to the national proportion.\u003c/p\u003e \u003cp\u003eThe clinical implications of the study may allow us to forecast the clinical resources required to treat hand injuries from the construction and manufacturing industry in relation to economic indicators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eWe identified a few limitations in our study. Firstly, surgical factors. We used the incidence rate for hand surgeries as a proxy for the incidence rate for hand injuries. These hand surgeries included both elective and emergency operations and therefore may not be reflective of patients who presented with hand injuries but did not undergo hand surgeries. However, our large sample size of 20,764 patients is likely to account for exceptions pertaining to these cases. Hand injuries are typically emergency injuries such as lacerations and crush trauma; but our data combines both. Fortunately, elective operations are not known to fluctuate much. For example, trigger finger operations are not known to fluctuate from month to month.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Since we have found in our results there is a significant correlation between the incidence of hand injuries and economic indicators, an extrapolation between two time points effectively nullify the electives, leaving the emergencies to account for the cause of fluctuations.\u003c/p\u003e \u003cp\u003eSecondly, our tertiary institution covers referrals from the south and western regions of Singapore where a higher proportion of construction and manufacturing industries are located. Hence, there may be a higher proportion of hand injuries that may present to our institution as opposed to other local tertiary institutions. However, this allows us to have an increased sensitivity to the fluctuations in hand surgeries done emergently in response to fluctuations in the labor force.\u003c/p\u003e \u003cp\u003eLastly, factor selection. Some of the factors used in our study were not reported in a timely fashion. For example, PMI is reported monthly, because companies use it to purchase equipment but others such as CI was published one year later. Therefore, the reporting time lag of the economic variables may dampen the usage of our equation as a timely method of forecasting.\u003c/p\u003e \u003cp\u003eIn conclusion, a correlation of 60.9% (p value\u0026thinsp;=\u0026thinsp;0.001) was found between the number of hand injuries and the following economic indicators: PMI, CI, LPCgdp and LPCmanu for hand injuries from 2012 to 2018. These findings may enable us to forecast clinical resources required to treat hand injuries from the construction and manufacturing industry in relation to economic indicators.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and material\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eData may be made available upon reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests/Conflicts of Interest\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThere are no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study was not funded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions: GZQ Liau and AEJ Cheah conceptualised the research question and design of the manuscript. GZQ Liau, WX Tay, JYS Wong and JY Weng contributed to the design of the study, analysis and interpretation of data. All authors contributed to manuscript drafting and revision. All authors read and approved the final version of the manuscript. Nil funding was obtained for this study.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1. Cheung K, Hatchell A, Thoma A. Approach to traumatic hand injuries for primary care physicians.\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3681444/\"\u003e\u003cem\u003eCan Fam Physician\u003c/em\u003e\u003c/a\u003e. 2013;59(6):614-618.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Otto C. \u003cem\u003eABC of Emergency Radiology\u003c/em\u003e. Oxford, UK: Blackwell Publishing Ltd. 2007.\u003c/p\u003e\n\u003cp\u003e3. Client Risk Solutions AIG Asia Pacific Insurance Pte. Ltd. Beyond Insurance:\u003c/p\u003e\n\u003cp\u003eLiabilities\u0026rsquo; Risk Management for Workplace Injuries. 2017. 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Trigger finger: etiology, evaluation, and treatment. \u003cem\u003eCurr Rev Musculoskelet Med\u003c/em\u003e. 2008;1(2):92\u0026ndash;96.\u003c/p\u003e\n\u003cp\u003e38. Brozovich N, Agrawal D, Reddy G. A Critical Appraisal of Adult Trigger Finger: Pathophysiology, Treatment, and Future Outlook. \u003cem\u003ePlast Reconstr Surg Glob Open\u003c/em\u003e. 2019;7(8):e2360.\u003c/p\u003e\n\u003cp\u003e39. Junot HSN, Anderson Hertz AFL, Gustavo Vasconcelos GR, Debora C Esquerdo C da Silveira, Paulo Nelson B, Saulo F Almeida. Epidemiology of Trigger Finger: Metabolic Syndrome as a New Perspective of Associated Disease. \u003cem\u003eHand (N Y)\u003c/em\u003e. 2019;1558944719867135\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-occupational-medicine-and-toxicology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmet","sideBox":"Learn more about [Journal of Occupational Medicine and Toxicology](http://occup-med.biomedcentral.com/)","snPcode":"12995","submissionUrl":"https://submission.nature.com/new-submission/12995/3","title":"Journal of Occupational Medicine and Toxicology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Demand, Supply, Labor, Health","lastPublishedDoi":"10.21203/rs.3.rs-806073/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-806073/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aims to analyze the correlation between the incidence rate of hand injuries and various construction and manufacturing indicators in Singapore. We hypothesize that the number of hand injuries is correlated to activity in the construction and manufacturing industries in Singapore.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e20,764 patients who underwent hand surgeries in a tertiary institution between 2012 to 2018 were reviewed. Two independent, blinded observers extracted the frequency of hand surgeries performed from Electronic Medical Records. Economic indicators pertinent to Singapore\u0026rsquo;s labor force, construction and manufacturing industries were collected and smoothed by simple moving average of the prior 3 months. Results were analyzed using IBM SPSS v25.0.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSignificant independent univariate variables were Purchasing Manager Index for Manufacturing and Industrial Production Index. Multivariate regression of quarterly reported figures showed that Purchasing Manager Index for Manufacturing, Construction Index, Labor Productivity Change for Gross Domestic Product and Labor Productivity Change for Manufacturing were significantly correlated with hand injuries, with r square\u0026thinsp;=\u0026thinsp;60.9%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eQuarterly economic indicators from construction and manufacturing industries can be used to predict the incidence of hand injuries with a 60.9% correlation. These findings may be useful for anticipating healthcare resource allocation to treat hand injuries.\u003c/p\u003e\u003ch2\u003eType of Study and Level of Evidence\u003c/h2\u003e \u003cp\u003eEconomic and decision, Level II.\u003c/p\u003e","manuscriptTitle":"Prediction of the rate of hand injuries in Singapore","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-26 16:37:48","doi":"10.21203/rs.3.rs-806073/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-09-21T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-09-10T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorInvitedReview","content":"","date":"2021-09-06T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"reviewerAgreed","content":"","date":"2021-08-25T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-08-23T19:24:35+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-08-23T08:35:49+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-08-23T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2021-08-17T04:16:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-08-16T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-08-16T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Occupational Medicine and Toxicology","date":"2021-08-11T23:24:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-occupational-medicine-and-toxicology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmet","sideBox":"Learn more about [Journal of Occupational Medicine and Toxicology](http://occup-med.biomedcentral.com/)","snPcode":"12995","submissionUrl":"https://submission.nature.com/new-submission/12995/3","title":"Journal of Occupational Medicine and Toxicology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0b1e114-b949-4228-a810-1e229e2528fd","owner":[],"postedDate":"August 26th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":6689319,"name":"Toxicology"}],"tags":[],"updatedAt":"2022-04-11T14:56:49+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-26 16:37:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-806073","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-806073","identity":"rs-806073","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}