Factors affecting the use of protective measures of farmers to prevent falling during the walnut collection period in Tuyserkan County

Authors

1 Department of Public Health, Social Determinants of Health Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

2 Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran

3 Department of Public Health, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

4 Pediatric Developmental Disorders Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

5 Department of Emergency Medicine, George Washington University, Washington, DC, United States of America

6 Department of Nursing, School of Nursing and Midwifery, Hamadan University of Medical Sciences, Hamadan, Iran

7 Tuyserkan Health Center, Hamadan University of Medical Sciences, Hamadan, Iran

Abstract

Background and Objectives: Fall is one of the main reasons for serious injuries in workplaces. Protective measures are not frequently used by farmers and farm workers. In Iran, there are no adequate data in recognizing the various effective factors of falls from height in the agricultural sector. Thus, we used the PRECEDE model to recognize causes and factors which can affect the acceptance of the protective measures for the prevention of fall from the walnut tree. Materials and Methods: From July until November 2018, a cross-sectional research was conducted in Tuyserkan County in the west of Iran among 222 farm workers and farmers from 12 villages. A questionnaire was developed to measure demographic features, history of injuries, and constructs recommended in the PRECEDE model. Data were gathered by face-to-face interviews. Results: Predisposing factors (β =0.348, t = 5.116), enabling factors (β =0.131, t = 3.672), and reinforcing factors (β =0.164, t = 2.128) had a positive impact on protective measures, with an explained variance of 35.3%. In this study, the goodness-of-fit value was obtained as 0.455, indicating an excellent overall fit of the model to the data. Conclusions: The results of this research recognized the causes of protective measures among farmers and farm workers. Our findings suggest that the PRECEDE model could help as a guide for developing a more effective intervention for the prevention of fall from the walnut tree.

Keywords

References

1. Nabi DG, Rashid TS, Kangoo KA, Ahmed DF. Fracture patterns resulting from falls from walnut trees in Kashmir. Injury 2009;40:591‑4.
2. Caffaro F, Roccato M, Micheletti Cremasco M, Cavallo E. Falls from agricultural machinery: Risk factors related to work experience, worked hours, and operators’ behavior. Hum Factors 2018;60:20‑30.
3. World Health Organization (WHO), Injuries, WHO Press, Geneva, Switzerland, 2020, https://www.who.int/topics/ injuries/en/.
4. Wesson HK, Boikhutso N, Bachani AM, Hofman KJ, Hyder AA. The cost of injury and trauma care in low‑ and middle‑income countries: A review of economic evidence. Health Policy Plan 2014;29:795‑808.
5. ILO. Agriculture; plantations; other rural sectors [Internet]. Geneva: International Labour Organization; 2014. Available from: http://www. ilo.org/global/industries-and-sectors/agriculture- plantations-otherrural-sectors/lang–en/index.htm. [cited 2016 Sept 02].
6. Sato H, Yamaguchi T, Ohori S, Yamauchi A, Inoue S, Abe T. Surgical treatment of traumatic disruption of the thoracic aorta due to fall from 6 meters height tree; report of a case. Kyobu Geka 2004;57:877‑80.
7. Statistics BL. Injuries, illnesses, and fatalities. Management. 2015;17(3):7.
8. Darçin ES, Darçin M. Falling from a height injuries in Agriculture: A 8‑year experience with 173 samples. Biomed Res 2016;27 :825-8.
9. Khazaei S, Jenabi E, Zobdeh Z, Biglari M, Afshari M, Gholamaliee B, Bashirian S. Pattern of trauma related to falling from walnut tree as an occupational injury: A cross‑sectional study in the west of Iran. Arch 
Trauma Res 2019;8:99‑103.
10. Anderson RN, Smith BL. Deaths: Leading causes for 2002. Natl Vital Stat Rep 2005;53:1‑89.
11. Thierauf A, Preuss J, Lignitz E, Madea B. Retrospective analysis of fatal falls. Forensic Sci Int 2010;198:92‑6.
12. Tabish SA, Jan RA, Rasool T, Geelani I, Farooq BM. Fall from walnut tree: An occupational hazard. Injury Extra 2004;35:65‑7.
13. Chi S, Han S, Kim DY. Relationship between unsafe working conditions and workers’ behavior and impact of working conditions on injury severity in US construction industry. J Constr Eng Manage 2012;139:826‑38.
14. Sepúlveda M, Oliva D. Interactions between South American sea lions Otaria flavescens (Shaw) and salmon farms in Southern Chile. Aquac Res 2005;36:1062‑8.
15. Jallow MF, Awadh DG, Albaho MS, Devi VY, Thomas BM. Pesticide knowledge and safety practices among farm workers in Kuwait: Results of a survey. Int J Environ Res Public Health 2017;14:340.
16. Kwon MS. Relations among knowledge, fear and efficacy of fall in the community dwelling elderly. J Korean Acad Community Health Nurs 2010;21:139‑47.
17. Rezapur‑Shahkolai F, Afshari M, Moghimbeigi A, Hazavehei SM. Home‑related injuries among under‑five‑year children and mothers’ care regarding injury prevention in rural areas. Int J Inj Contr Saf 
Promot 2017;24:354‑62.
18. Griffin MA, Neal A. Perceptions of safety at work: A framework for linking safety climate to safety performance, knowledge, and motivation. J Occup Health Psychol 2000;5:347‑58.
19. Crosby RA, Kegler MC, DiClemente RJ. Theory in health promotion practice and research. Emerging theories in health promotion practice and research. 2009;2:3-17.
20. Glanz K, Rimer BK, Viswanath K. Health Behavior and Health Education: Theory, Research, and Practice. John Wiley and Sons; 2008.
21. Agriculture Organization of Hamadan Province. Twiserkan; 2017. Available from: http://www.hamedan.agri‑jahad.ir.
22. Hair JF, Ringle CM, Sarstedt M. PLS‑SEM: Indeed a silver bullet. J Mark Theory Pract 2011;19:139‑52.
23. Henseler J, Ringle CM, Sinkovics RR. The use of partial least squares path modeling in international marketing. In: New Challenges to International Marketing. Emerald Group Publishing Limited; 2009. p. 277‑319.
24. Singh B, Gupta MK. Pattern of use of personal protective equipments and measures during application of pesticides by agricultural workers in a rural area of Ahmednagar district, India. Indian J Occup Environ Med 2009;13:127‑30.
25. Zveglich J, Joseph E, Rodgers Yvd M. The impact of protective measures for female workers. J Labor Econ 2003;21:533‑55.
26. Sharifzadeh MS, Damalas CA, Abdollahzadeh G. Perceived usefulness of personal protective equipment in pesticide use predicts farmers’ willingness to use it. Sci Total Environ 2017;609:517‑23.
27. Rostami F, Afshari M, Rostami‑Moez M, Assari MJ, Soltanian AR. Knowledge, attitude, and practice of pesticides use among agricultural workers. Indian J Occup Environ Med 2019;23:42‑7.
28. Derafshi M, Black C, Agnew R. Pesticide knowledge, attitudes, and clothing practices of Turkish farmers. Environ Manage Sustain Develop 2017;6:149‑67.
29. DeRoo LA, Rautiainen RH. A systematic review of farm safety interventions. Am J Prev Med 2000;18:51‑62.
30. McCurdy SA, Samuels SJ, Carroll DJ, Beaumont JJ, Morrin LA. Agricultural injury in California migrant Hispanic farm workers. Am J Ind Med 2003;44:225‑35.
31. Elmore RC, Arcury TA. Pesticide exposure beliefs among Latino farm workers in North Carolina’s Christmas tree industry. Am J Ind Med 2001;40:153‑60.
32. Le Dang H, Li E, Nuberg I, BruwerJ. Understanding farmers’ adaptation intention to climate change: A structural equation modelling study in the Mekong Delta, Vietnam. Environ Sci Policy 2014;41:11‑22.
Archives of Trauma Research
Volume 10, Issue 3
July 2021
Pages 141-147

Files

History

  • Receive Date: 15 September 2022
  • Accept Date: 15 September 2022

Share

How to cite

Statistics