• Users Online: 419
  • Print this page
  • Email this page


 
 
Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 10  |  Issue : 3  |  Page : 141-147

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


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

Date of Submission14-Dec-2020
Date of Decision05-Jun-2021
Date of Acceptance20-Jul-2021
Date of Web Publication11-Oct-2021

Correspondence Address:
Dr. Maryam Afshari
Department of Public Health, School of Public Health, Hamadan University of Medical Sciences, Shahid Fahmideh Ave, Hamadan 6517838695
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/atr.atr_117_20

Get Permissions

  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: Accidental falls, farmers, Iran, protective factors, trees


How to cite this article:
Bashirian S, Khazaei S, Afshari M, Jenabi E, Shokoohi H, Zobdeh Z, Biglari M, Gholamaliee B. Factors affecting the use of protective measures of farmers to prevent falling during the walnut collection period in Tuyserkan County. Arch Trauma Res 2021;10:141-7

How to cite this URL:
Bashirian S, Khazaei S, Afshari M, Jenabi E, Shokoohi H, Zobdeh Z, Biglari M, Gholamaliee B. Factors affecting the use of protective measures of farmers to prevent falling during the walnut collection period in Tuyserkan County. Arch Trauma Res [serial online] 2021 [cited 2021 Nov 30];10:141-7. Available from: https://www.archtrauma.com/text.asp?2021/10/3/141/328033




  Introduction Top


Fall is one of the main reasons for fatal injuries in the workplace.[1] Fall is the main cause of death among farmers and farm workers; most common falls happen when descending or climbing a tree or vehicle.[2] Especially, falling from trees in the agricultural areas due to climbling the trees to harvest yields is another form of falling from heights.[3],[4],[5] Falling from a tree can result in main visceral, disabling spinal, and complex facial injuries.[6] In the USA in 2017, falls to the lower level estimated for 887 deaths in the private industry and 28 deaths in the section of agriculture.[7] Fall from the tree is one of the most common types of injuries in Iran and leads to a great number of admissions to health centers and hospitals.[8] Hence, during September until October 2017, a total of 52 injured cases due to falling from walnut trees in Tuyserkan County were reported.[9]

The walnut trees are cultivated in rural areas of Iran.[10] Tuyserkan is one of the natural places of walnut trees in worldwide. Walnut production has the most role in the economy of Tuyserkan with an overall zone of about 5100 ha which even lies in the first area in Iran.[11] However, the methods of harvesting walnuts in Tuyserkan are still traditional and nontechnical method, and gardeners climb the trees and harvest walnuts.[9] This action imposed them at risk of falling trees.[12] Falls frequently occur in the agriculture segment because no protections are taken or any equipment that is used is flawed, not suitable, or used wrongly.[8]

Studies indicate that unsafe working conditions and workers' behavior are effective in fall and injuries in the workplace.[13] Protective methods are not commonly used by farmers and farm workers.[14] The use of personal protective devices and engaging in protective behaviors by farmers depend on a diversity of factors.[15] Factors including knowledge and attitude about risks and right use of protective measures,[16] reinforcing factors and enabling factors about preventive behaviors and measures.[17] Identifying the effective factors in using protective measures is necessary to any interventional plan.[3] Nevertheless, studies considering the role of an extensive series of factors based on a definite framework are restricted.[18] Selecting the model of health education is the first step in identifying the various effective factors.[19]

The PRECEDE framework was developed and introduced to find behavioral, designing, planning, and evaluation problems of health.[20] The study by Rezapur-Shahkolai et al. indicated that the PRECEDE model can be useful in determining the predictive causes of injuries.[17] In the world, there are no enough data in identifying the various effective factors of falls from height in the agricultural sector. Data about reasons type or other specific features of falling from height incidents are unknown. Besides, there are no studies in this area, especially addressing falling from height in farmers and farm workers. Because of the unavailability of the agricultural databank and lack of researches concerning reasons and factors of fall-related injuries, taking preventive PRECEDE measures to reduce the potential risk of injuries is difficult.

Thus, in this study, we used the model to recognize causes and factors that can be related to the acceptance of the protective measures for prevention farmers and farm workers from falling from the walnut tree.


  Methods Top


Research design

This cross-sectional study was conducted in Tuyserkan County, placed in the Hamadan province (west of Iran), from July 1, 2018, to November 30, 2018. Tuyserkan County with a harvest level of 54,000 ha is an important county of walnuts production in Iran.[21]

Sampling

According to the values derived from Darçin and Darçin,[8] and considering the 95% confidence level and a precision of 2%, the overall required sample size was obtained as 240 farmers and farm workers.

The inclusion criteria were farmers and farm workers residing in one of these villages and having a history of climbing from the walnut trees. The farmers and farm workers who changed their living location or who had not experienced the climb of walnut trees and farmers and farm workers not willing to participate in this research were considered as exclusion criteria. Multistage sampling method (stratified-cluster-random) was used for this purpose so that first Tuyserkan county was divided into five districts based on the distribution of walnut orchards (Tuyserkan city and Sarabi orchards, Sarkan orchards, orchards of the villages located in the central part of the county, orchards of Khorramrud district, and orchards of Qhelqhelrud district). A sample size of 50 people is considered for each district. Then, two villages were selected from each district in rural areas using the cluster sampling method and the sample size assigned to each village was based on random sampling among gardeners whose names were already provided to the team by the village council or village mayor. In connection with the city of Tuyserkan, the city was divided into four districts: Sarabi, Ainabad and its suburbs, Mir Razi al-Din and its suburbs, and Ghale-ghazi and its suburbs, and a sample size of 10 people was allocated to each part. Samples were randomly selected from these areas.

Data collection

We gathered data in cooperation with community health workers in health houses from 12 villages. Data were gathered by face-to-face interviews with certain farmers and farm workers. Interviews were conducted in the health houses of villages. The questionnaire was developed according to the review of literature.[2],[8],[13],[17] We measured the predisposing factor (knowledge), predisposing factor (attitude), enabling factors, reinforcing factors, protective measures, and demographic data through a self-reported questionnaire. To collect the data, five expert health workers held interviews with individuals.

Data collection instruments

We collected data on key factors influencing the protective measures to fall from the walnut tree by farmers and farm workers using the PRECEDE model. The study involved a questionnaire that involved three sections. The study involved questions about demographics, injured farmers, history of injuries, and PRECEDE model constructs including predisposing factors (knowledge) about protective measures (10 items), predisposing factors (attitude) about protective measures (10 items), enabling factors to approve protective actions (3 items), reinforcing factors to approve protective actions (2 items), and protective measures for reducing fall of the walnut tree (12 items).

Validity and reliability

The primitive version of the questions was developed by investigators. Afterward, to measure content validity and face validity, the questions of the questionnaire were appraised by ten specialists in occupational health and health education. At first, the content validity ratio was considered by specialists' judgment and items with the score ≤0.62 kept on in the questionnaire. Then, the content validity index was considered by researchers. The score of 0.79 was measured as the minimum appropriate content validity index. In addition, the face validity of questions was testified by eight farmers and farm workers. so that the questions were recited for them, and we considered the level of difficult questions.

To estimate the reliability, Cronbach's alpha was used. Cronbach's alpha was assessed although directing a pilot study on 30 farmers and farm workers. The Cronbach's alpha for reliability was above 0.76 for all constructs. The validity and reliability step recommended minor changes to the questionnaire before finalization.

Data analysis

SPSS 24, IBM, Armonk, NY, United States of America) and the partial least squares (SmartPLS GmbH P.O. Box 1123 D-25474 Bönningstedt Germany) approach were applied to examine the reliability of the measures. Furthermore, data were recorded in SPSS (version 24) and were analyzed using Chi-square. We directed the confirmatory factor analysis to review homogeneity (factor loading and t-value),[22] reliability (composite reliability and Cronbach's alpha),[23] and convergent validity (average variance extracted [AVE])[23] of the latent variable indicators. In the study, the t-value was more than ±1.96 and factor loading measurements of ≥0.6 were approved. The composite reliability score was ≥0.81 and Cronbach's alpha value was 0.72 and above for each construct. In addition, the results of the AVE test show that the score constructs were ≥0.51. Therefore, any items of the construct were not removed from the model. At last, after the model was found to meet the criteria for the measurement model, the structural models were confirmed [Table 1].
Table 1: The validity and reliability of the PRECEDE model scales

Click here to view


Ethical approval

After clarifying the purpose of the study, clearly, and confidentiality of information for farmers and farm workers, all of them participated in the study voluntarily. Verbal informed consent was obtained from them. This study was approved by the Ethical Committee of Hamadan University of Medical Sciences (No.: IR.UMSHA.REC.1397.266).


  Results Top


The study response rates were 92.5%, and the information of 7.5% did not include in the analysis due to failure to answer the questions. Demographic features of the farmers and farm workers are indicated in [Table 2].
Table 2: Demographic characteristics of the participating farm workers and farmers (n=222)

Click here to view


According to [Table 3], our findings also indicated that 10 farmers and farm workers (4.5%) had a history of falling from walnut trees.
Table 3: Background information of farmers falling from the walnut tree (n=10)

Click here to view


Farmers' protective measures were inadequate as follows

Avoiding go out of the walnut tree during fatigue and decentralization (43.2%), avoiding go out of the walnut tree when the wind starts (49.5%), and avoid of going out of the walnut tree during the bad physical condition (52.3%) were the most frequent protective behaviors (PBs). There were no significant differences between the protective measures of participants and their demographic characteristics (P > 0.05) (data not shown).

[Figure 1] shows the conceptual framework of PRECEDE model used in the study.
Figure 1: Structural model in the forecast of path coefficients

Click here to view


We experienced all paths proposed by the PRECEDE model. According to the suggested paths by the PRECEDE model, 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, showing an excellent overall fit of the model to the data. The predictive validity (Q2) value for protective measures was 0.320. These values confirm that the PRECEDE model has the power to forecast the variations in protective measure constructs [Table 4].
Table 4: The result of the structural model for examining paths in the PRECEDE model

Click here to view



  Discussion Top


This current study developed a research model that was to enrich our understanding of the effective factors on protective measures among farmers and farmworkers. The study results show that a significant amount of variance in the proposed model's dependent constructs was explained by the model's independent constructs. There is a lack of data supporting the role of a number of surveyed structures in agricultural health and injuries studies.

Our research is one of the few theoretical framework studies considering farmers' protective measures. Our findings showed that the implementation of protective measures by the farmers and farm workers is poor. This result is in line with the results of Singh and Gupta[24] and Zveglich et al.,[25] indicating that most fall injuries occur in conditions where prevention practices are not done. Farmers do not use protective equipment for various reasons. These reasons included unattractiveness of protective measures, perceived fewer hazards, knowledge and attitude fewer about hazards, cumbersome protective measures, and slowing down work by farmers.[26] In addition, in this study, farmers and farm workers believed that the use of protective measures for the prevention of fall from the walnut tree is not hard. The above reasons point out the need to incorporate farmers' safety preferences in interventional programs that are designed to promote protective measures for fall prevention from the walnut tree among farmers and farm workers.

Our study showed that knowledge and attitude have a positive influence on protective measures so that the knowledge and attitude of the farmer are effective in taking protective measures in farmers and agricultural workers. Consistent with another study,[27] the results confirmed that a rise in knowledge and attitude enhanced safety behaviors. Contrary to our results, the results of the Derafshi et al.'s[28] study showed the lack of significant relationship between knowledge and attitude and use of personal protective equipment. Usually, the support of public health prevention, work on the hypothesis that poor knowledge and attitude result in protective measures that cause injuries. By increasing their knowledge and proper attitudes, they will involve in safer behaviors.

We also found that the enabling factors were associated with protective measures, which was consistent with the results suggested in previous studies.[17],[29] Enabling factors are those internal and external conditions directly related to the issue that helps people accept and continue healthy or unhealthy behaviors or to embrace or discard specific environmental conditions.[20] Based on previous studies, several of these factors include the resource,[30] and safety education and experience[31] are the most usually cited enabling factors to protective measures. Maybe, these factors make an item to carry out.

Findings supported that the reinforcing factors are effective on the protective measures. These results are consistent with the results of the previous study.[32] Reinforcing factors are the individual and community attitudes that support or make it difficult to adopt healthy behaviors or fostering healthy environmental conditions.[20] Probably, farmers who have experienced the social pressure of others indicated the heightened concern about the health effects of fall and were more likely to do behaviors.

Limitations

The results of this study should be considered in light of its limitations. First, the findings of the study might be affected via self-report bias. Second, this study was directed in a restricted zone, and therefore, caution should be exercised regarding its generalizability.


  Conclusions Top


The findings of this research recognized the causes of farmers' and farm workers' protective measures. In addition, farmers' and farmworkers' protective measures to prevent falling during the walnut collection period were inadequate. Considering the direct effect of the PRECEDE model component on protective measures, it seems that the PRECEDE model could serve as a guide to developing a more effective intervention for safety measures of Iranian farm workers and farmers. According to the study, the results suggested that safety education among farmers could raise awareness and attitude of falling during the walnut collection risk and the adverse health consequences. Therefore, there is a critical need to educate and create knowledge regarding the use of protective measures. Hence, must training programs to focus on safety education. Further, policy and regulations on safety should be made stringent in Iran.

Acknowledgment

This project has been accepted by the Research and Technology Deputy of Hamadan University of Medical Sciences.

Financial support and sponsorship

This study was supported by Hamadan University of Medical Sciences (reference number: 9704262393).

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Nabi DG, Rashid TS, Kangoo KA, Ahmed DF. Fracture patterns resulting from falls from walnut trees in Kashmir. Injury 2009;40:591-4.  Back to cited text no. 1
    
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.  Back to cited text no. 2
    
3.
World Health Organization (WHO), Injuries, WHO Press, Geneva, Switzerland, 2020, https://www.who.int/topics/ injuries/en/.  Back to cited text no. 3
    
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.  Back to cited text no. 4
    
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-other-rural-sectors/lang–en/index.htm. [cited 2016 Sept 02].  Back to cited text no. 5
    
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.  Back to cited text no. 6
    
7.
Statistics BL. Injuries, illnesses, and fatalities. Management. 2015;17(3):7.  Back to cited text no. 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.  Back to cited text no. 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.  Back to cited text no. 9
  [Full text]  
10.
Anderson RN, Smith BL. Deaths: Leading causes for 2002. Natl Vital Stat Rep 2005;53:1-89.  Back to cited text no. 10
    
11.
Thierauf A, Preuss J, Lignitz E, Madea B. Retrospective analysis of fatal falls. Forensic Sci Int 2010;198:92-6.  Back to cited text no. 11
    
12.
Tabish SA, Jan RA, Rasool T, Geelani I, Farooq BM. Fall from walnut tree: An occupational hazard. Injury Extra 2004;35:65-7.  Back to cited text no. 12
    
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.  Back to cited text no. 13
    
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.  Back to cited text no. 14
    
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.  Back to cited text no. 15
    
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.  Back to cited text no. 16
    
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.  Back to cited text no. 17
    
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.  Back to cited text no. 18
    
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.  Back to cited text no. 19
    
20.
Glanz K, Rimer BK, Viswanath K. Health Behavior and Health Education: Theory, Research, and Practice. John Wiley and Sons; 2008.  Back to cited text no. 20
    
21.
Agriculture Organization of Hamadan Province. Twiserkan; 2017. Available from: http://www.hamedan.agri-jahad.ir.  Back to cited text no. 21
    
22.
Hair JF, Ringle CM, Sarstedt M. PLS-SEM: Indeed a silver bullet. J Mark Theory Pract 2011;19:139-52.  Back to cited text no. 22
    
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.  Back to cited text no. 23
    
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.  Back to cited text no. 24
[PUBMED]  [Full text]  
25.
Zveglich J, Joseph E, Rodgers Yvd M. The impact of protective measures for female workers. J Labor Econ 2003;21:533-55.  Back to cited text no. 25
    
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.  Back to cited text no. 26
    
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.  Back to cited text no. 27
[PUBMED]  [Full text]  
28.
Derafshi M, Black C, Agnew R. Pesticide knowledge, attitudes, and clothing practices of Turkish farmers. Environ Manage Sustain Develop 2017;6:149-67.  Back to cited text no. 28
    
29.
DeRoo LA, Rautiainen RH. A systematic review of farm safety interventions. Am J Prev Med 2000;18:51-62.  Back to cited text no. 29
    
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.  Back to cited text no. 30
    
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.  Back to cited text no. 31
    
32.
Le Dang H, Li E, Nuberg I, Bruwer J. Understanding farmers' adaptation intention to climate change: A structural equation modelling study in the Mekong Delta, Vietnam. Environ Sci Policy 2014;41:11-22.  Back to cited text no. 32
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
Introduction
Methods
Results
Discussion
Conclusions
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed556    
    Printed22    
    Emailed0    
    PDF Downloaded58    
    Comments [Add]    

Recommend this journal