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The circumstances favoring the worker accidents in the metalworking industry in Kenitra City and in its area (Morocco).

Introduction

In many developed or developing, a multitude of institutions are involved in the management of records related to accidents and occupational illnesses. Among these institutions there is the Ministry of Employment and Vocational Training, insurance houses, the institution of belonging and family circle of the victim. The share of each of these institutions is not the same, but it is always important. For example, in case of accidents at work, in the financial consequences of legal liability of the employer, the home insurance must cover the costs of different kinds. The main ones are the payment of daily allowances, disability benefits or pensions, payment of medical, pharmaceutical and hospitalization for the victim herself. The worker may be unable to continue regular activities; so, the institution of the belonging loses a skilled labor. The social environment, especially the small family of the victim is faced to the new conditions of life that, most often, are unbearable and sometimes catastrophic (or a ref or two that already resumed or new).

However, most of these accidents and their consequences can be avoided by developing the systems to prevent these accidents including:

* The development of knowledge of the hazards, risks and exposures in the workplace.

* The strengthening the effectiveness of control

* The encouraging companies to be involved in occupational health.

This prevention requires knowledge of the nature of accidents and their main causes according the industry type.

To determine the principal circumstances that accompany accidents in the metalworking sector, we have analyzed in this present work, the database of the accidents reported in the Delegation of the job of the city and the region of Kenitra (Morocco).

Material and Methods

The institutions surveyed

These are all the main metallurgical industrial units located in the city and in the region of Kenitra (Morocco), which the main activies are:

* Hydromechanical and electromechanical equipment

* Stainless steel boilers, sheet stainless steel and black

* Structural steel and timber gantry and tubular

* Steel construction and mechanical, piping, rolling tubes, formwork, manufacturing flanges, storage tanks and bridges, turning and milling.

* Industrial assembly, sanding, painting, roofing, siding, silo building, ramp door, conveyor, storage bin and food industry, industrial packagers

* Hot dip galvanizing and surface treatment

Victims taken into account

The study addresses all of the workers or employees administratively reported as having suffered an accident in one of the institutions studied and whose record of accident was received by the Delegation of Kenitra job. They were 145 victims

Moreover, for each individual we have taken into account five variables divided into fourteen classes were studied (Table 1).

All data were statistically processed by a multivariate analysis, the Correspondence Analysis (CCA). The mathematical principles of this method have been developed by several authors such as Benzecri, 1973, Legendre and Legendre, 1984 [1, 2]. It is a method based on the correlation of variables and the reduction of the characters number then we build new synthetic axis by linear combination of initial characters. This statistical method has been used in various study types where the phenomenon to explain is controlled by many environmental factors.

Data matrix

For a given variable, each class is represented either by the value 1 when the characteristics of the class are provided or 0 when the opposite is true. Theoretically, taking account of the 145 victims of accidents and the 14 class studied and eliminating cases of the class that represents the value 1 with a frequency of less than 5% (Table 1 in Appendix 1).

Results and Interpretation

The F1 axis represents 22.7% of explained inertia, the second axis F2 represents 15.9% and the third axis F3, only 15%, totaling 53.6% of inertia available. The eigenvalues and percentages of inertia of the first three axes are given in Table 2.

With 53.6% as a total inertia accumulated by the first three axes, we saw it necessary to analyze three projection planes of the variables and individuals' F1 x F2, F1 x F3 <<and<< F2 x F3

The overall contributions of each variable in the formation of axes F1, F2 and F3 are noted in Table 3. These contributions have enabled us to search for Meanings of three axes:

Axis F1

Table 4 shows that the classes of the variables symbolized A1, A2 and E contribute mostly to the formation of this axis; all these variables indicate the time when the accident was performed: A1 indicates that the accident was conducted during 2008, A2 indicates that the accident was conducted during 2009 and E indicates that the accident was happened in summer.

Axis F2

Table 4 shows that only two variables contribute significantly to the formation of this axis: MeM which indicates that the accident was conducted by a moving mass and M which indicates that the accident was conducted by a machine.

Axis F3

Two variables contribute significantly to the formation of this axis: Ma which indicates that the accident was conducted in the morning and S wich indicates the time of the accident was an afternoon.

Analysis of << F1 x F2 >> plan

This plan shows that in 2008 the accidents were mostly happened in summer; unlike in 2009, the accidents were mostly happened in other seasons particularly in autumn.

By sharing this plan into four compartments A, B, C and D, each corresponding to a group of observations, separated between them by the axis F1 and F2 (Fig. 1), we can characterize each of these groups such as:

Group A: the workers are victims of an accident most likely due to a machine, in 2009, not during a summer season and most likely will in fall season, and that led to permanent disability;

Group B: workers are victims of an accident in 2008, most likely due to a machine during the summer and leading to permanent disability;

Group C: workers are victims of an accident in 2009, during a summer season and most likely were not caused of a moving mass, and the accident have led to a temporary disability;

Group D: The worker is victim of an accident in 2008, during the summer, and the accident was made by a moving mass which led to a temporary disability.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

In the same manner as in the case of the analysis plan F1xF2 The projection of the <<observation-points<< (Fig. 2) shows a differentiation between four groups of individuals A', B', C' and D'. The characteristics of groups A' and B' are respectively the same as those of groups A and B but in noting that these people were victims of accident in the morning.

In groups C 'and D', the characteristics of Individus are respectively the same as those of groups C and D but noting that these accidents occurred in the afternoon.

Analysis << F2 x F3 >> Plan

The "F2xF3" plan shows also four groups of observations A", B":"C separated each other by the axes F2 and F3. Their respective chracteristics are:

Group A": the accidents were caused by a machine, in the morning and causing permanent disability of the victim.

Group B": the accidents were due to a machine during the afternoon and causing permanent disability of the victim.

Group C": the accidents were caused by a moving mass in the morning and leading to a temporary disability of the victim.

Group D": the accidents were due to a moving mass, in the evening and causing temporary disability of the victim.

[FIGURE 3 OMITTED]

Moreover, as shown by the analysis of Figures 1, 2 and 3, the factor <<season>>, the mass movement, machinery and moment of day (morning or afternoon) are the main factors that determine the conditions Event <<accident.>> Also, we can deduce that when some conditions are grouped in a factory of industrial metallurgy, the probability that an accident occurs becomes important such as: a summer or fall period, an afternoon moment, a mass moving or a dangerous machine in working.

All these conditions can be ranged in the group of those causing a stress state. So, the probability of a stressing worker becomes important. Indeed, According to the American Institute of Stress, this psychological state is responsible for 60-80% of workplace accidents (Garneau, 1978) [3]. The decreasing of the vigilance of a stressy worker to the point that his attention to the risk, which he is exposed to, becomes reduced [4, 5, 6, 7].

For the worker, we conclude that it is a set of conditions that promote a fatigue and stress state are the favorably moments to accidents. Similarly, according to the physiological view, such as that of Gun (1995) [5], the increasing of the ambient heat can also cause to the human a state of stress. Add that the effect of ambient high heat is more felt in older individuals [8], too fat or too skinny and pregnant women [9].

The effect of extending the workday by doing overtime is also a cause of stress for some types of individuals including workers too fat or too skinny or pregnant women. [10, 11, 12].

The results further show that the machinery and masses in motion are the tools that are causing an alarming number of accidents at work in the metallurgical sector.

Conclusion

In the studied metallurgical industry sector, the high ambient heat of the summer and autumn, the daily number of hours worked during that period and the stress of workers seem to be the main causes of the work accidents. Also, the tools that require

an important alertness, such as the machinery and the moving masses, are responsible for most of the accidents.

* Taking count of the results of this work, it appears that the reduction of accidents in the <<Metallurgy>>, require a series of precautions. The main ones are:

* The time to rest the worker must be in the hottest time of the period of work;

* During the warmer periods of the year, a water spring must be planted very close to the workplace;

* To equip the environment which is exposed to heat by a ventilation or air conditioning system;

* Banning of overtime to the aged or the obese workers;

* To select the appropriate profile employers for items of machinery and equipment orientation of the moving masses and to inform them to the dangers of these tools.

Schedule 1

References cited

[1] Benzecri, J.P. L'analyse des donnees, Tome 2: L'analyse des Correspondances, 1973. Dunod, Paris.

[2] Legendre, L. et Legendre, P. 1984. <<Ecologie numerique. 1: Le traitement multiple des donnees ecologiques>>, 2eme ed. Masson, Paris, 260 p.

[3] Garneau J.-Le stress: causes et solutions. Infopsy << La lettre du Psy >>. Volume 2, No 8: Aout 1998

[4] Parsons K.-C.- Human thermal environments. The effects of hot, moderat and cold environments on human healty confort and performance. The principe and the practice. Londre, Taylor and Francis, 1993, 358.

[5] Gun R.-T. Effects of thermal, personal and bihavioural factors on the physiological strain, thermal confort and productivity of Australian sheares in hot weather. Ergonomics, 1995, 7, pp. 1368-1384;

[6] P. Mahingsa, T. Thiramanus, P. Meepradit. Effects of Stress on Occupational Injuries among the Workers at Automobile Body Parts Industry in Chonburi Province. The Public Health Journal of Burapha University, Vol.4 No.2 July December 2009

[7] NAKATA A. IKEDA T.; TAKAHASHI M; HARATANI T.; HOJOU M.; FUJIOKA Y.; SWANSON N.-G.; ARAKI S.--Impact of psychosocial job stress on non-fatal occupational injuries in small and medium-sized manufacturing enterprises. American journal of industrial medicine. 2006, vol. 49, no8, pp. 658-669

[8] Smolander J., Korhoner O., Ilmarnen R.--Reponses of young and older men durin prologed exercese in dry and humide heat. Eurpean Journal of Applied Pysiology. 1990, pp, 413-418.

[9] Semenza J., Rubin C., Falter K.--Heat related deaths during the july 1995 heat wave in Chicago. The New England Journal of Medecine, 1996, 335 (2), pp. 84-90

[10] Morrissey S.- Work place desin recommandations for the pregnant worker. International Journal of Industrial Ergonomics, 1998, 21, pp; 383-395.

[11] A E Dembe, J B Erickson, R G Delbos, S M Banks--The impact of overtime and long work hours on occupational injuries and illnesses: new evidence from the United States.Occup Environ Med 2005; 62:588-597.

[12] Pandolf K.-B.--Time course of heat acclimatation and its decay. International Journal of Medecine, 1998, 19, pp; 157-160.

Driss Raougui (1) *, Ahmed Ahami (1), Youssef Aboussaleh (1), Mohamed Fadli (2) and Adil Sbayi (2)

(1) UFR of Human Biology and Population Health, Clinique Cognitive Neurosciences Team Nutrition and Health, Laboratory for Biology and Health, Faculty of Science, University Ibn Tofail; Kenitra, Morocco.

(2) Life sciences; Laboratory of Biodiversity and Natural Resources, Faculty of Science, University Ibn Tofail; Kenitra, Morocco.

* Corresponding Author E-mail: raouguirdriss@yahoo.fr
Table 1: Meaning of the studied variables, their classes and the
percentage of cases where each class has been realized.

 Variable Meaning Staff %

Causes CH Accident made by a fall 25 19
 from a height (CH)
 O Accident made by a 21 16
 tool (O)
 MeM Accident made by a 36 27
 moving mass (MeM)
 M Accident made a 49 37
 machine (M)
Consequent inability IP Accident causing 20 15
 permanent
 disability (IP)
 IT Accident causing 115 85
 temporary
 incapacity (IT)
the moment of the Ma The accident has been 41 28
accident conducted in the
 morning (Ma)
 S The accident has been 99 68
 conducted in the
 afternoon (S)
Year A1 Accident made in 80 55
 2008 (A1)
 A2 Accident made in 65 45
 2009 (A2)
Saison P Accident made in 23 16
 spring (P)
 E Accident made in 63 43
 summer (E)
 A Accident effectue en 45 31
 autumn (A)
 H Accident made in 14 10
 Winter (H)

Table 2: Eigenvalues and percentages of contribution first three axes.

Principal axes Eigenvalues % of inertia % of accumulated
 inertia

[F.sub.1] 0,0223 22,7 22,7
[F.sub.2] 0,0156 15,7 38,4
[F.sub.3] 0,0147 15 53,6

Table 3: Contribution of the studied variables in the first
three axes.

Settings [F.sub.1] (en %) [F.sub.2] (en %) [F.sub.3] (en %)

CH 0,001 0,001 0,016
O 0,000 0,008 0000
MeM 0,013 0,361 0,116
M 0,001 0,419 0,157
IP 0,026 0,247 0,092
IT 0,028 0,262 0,084
Ma 0,103 0,145 0,682
S 0,134 0,122 0,662
Al 0,768 0,012 0,051
A2 0,774 0,015 0,054
P 0,003 0,286 0,013
E 0,456 0,042 0,004
A 0,241 0,206 0,001
H 0,094 0,154 0,047

Table 1: Data matrix statistically analyzed by the Factorial Analysis
of Correspondence.

 S CH O MeM V Au PP E L ENT APD MM M IP

1 1 1
2 1 1
3 1 1
4 1 1
5 1 1
6 1 1
7 1 1
8 1 1
9 1 1
10 1 1
11 1 1
12 1 1
13 1 1
14 1 1
15 1 1
16 1 1
17 1 1
18 1 1
19 1 1
20 1 1
21 1 1
22 1 1
23 1 1
24 1 1
25 1 1
26 1 1
27 1 1
28 1 1
29 1 1
30 1 1
31 1 1
32 1
33 1 1
34 1 1
35 1 1
36 1 1 1
37 1 1 1
38 1 1 1 1
39 1
40 1 1 1
41 1 1
42 1 1
43 1 1
44 1 1 1
45 1 1
46 1 1
47 1 1
48 1 1
49 1 1
50 1 1 1
51 1 1
52 1 1
53 1 1 1
54 1 1
55 1 1 1
56 1 1
57 1 1
58 1 1
59 1 1
60 1 1
61 1 1
62 1 1
63 1 1
64 1 1 1
65 1 1 1
66 1 1 1
67 1 1 1
68 1 1
69 1 1
70 1 1 1
71 1 1
72 1 1
73 1 1
74 1 1
75 1 1
76 1 1
77 1 1
78 1 1
79 1 1
80 1 1
81 1 1
82 1 1
83 1 1
84 1 1
85 1 1
86
87 1 1
88 1 1
89 1 1
90 1 1
91
92 1 1
93 1 1
94 1 1
95 1 1
96 1
97 1 1 1
98 1 1
99 1 1
100 1 1
101 1 1
102 1 1
103 1 1
104 1 1
105 1 1
106 1 1
107 1 1
108 1 1
109 1 1
110 1 1
111 1 1
112 1 1
113 1 1
114 1 1
115 1 1
116 1 1
117 1
118 1 1
119 1 1
120 1 1
121 1 1
122 1 1
123 1 1
124 1 1
125 1 1
126 1 1
127 1 1 1
128 1 1
129 1 1 1
130 1 1
131 1 1
132 1 1 1
133 1 1
134 1 1
135 1 1
136 1 1 1
137 1 1
138 1 1
139 1 1
140 1 1
141 1 1
142 1 1 1
143 1 1
144 1 1
145 1 1 1

 IT Dec N M S A1 A2 P E A H

1 1 1 1
2 1 1 1
3 1 1 1
4 1 1 1
5 1 1 1
6 1 1 1
7 1 1 1
8 1 1 1
9 1 1 1
10 1 1 1
11 1 1 1
12 1 1 1
13 1 1 1
14 1 1 1
15 1 1 1
16 1 1 1
17 1 1 1
18 1 1 1
19 1 1 1
20 1 1 1
21 1 1 1
22 1 1 1
23 1 1 1 1
24 1 1 1 1
25 1 1 1 1
26 1 1 1 1
27 1 1 1 1
28 1 1 1 1
29 1 1 1 1
30 1 1 1
31 1 1 1
32 1 1 1
33 1 1 1
34 1 1 1 1
35 1 1 1 1
36 1 1 1
37 1 1 1
38 1 1
39 1 1 1 1
40 1 1 1
41 1 1 1 1
42 1 1 1 1
43 1 1 1 1
44 1 1 1
45 1 1 1 1
46 1 1 1 1
47 1 1 1 1
48 1 1 1 1
49 1 1 1 1
50 1 1 1 1
51 1 1 1 1
52 1 1 1 1
53 1 1 1
54 1 1 1 1
55 1 1 1
56 1 1 1 1
57 1 1 1 1
58 1 1 1 1
59 1 1 1 1
60 1 1 1 1
61 1 1 1 1
62 1 1 1 1
63 1 1 1 1
64 1 1 1
65 1 1 1
66 1 1 1
67 1 1 1
68 1 1 1 1
69 1 1 1 1
70 1 1 1
71 1 1 1 1
72 1 1 1 1
73 1 1 1 1
74 1 1 1 1
75 1 1 1
76 1 1 1 1
77 1 1 1 1
78 1 1 1 1
79 1 1 1 1
80 1 1 1
81 1 1 1 1
82 1 1 1 1
83 1 1 1 1
84 1 1 1 1
85 1 1 1 1
86 1 1 1 1
87 1 1 1 1
88 1 1 1 1
89 1 1 1 1
90 1 1 1 1
91 1 1 1 1
92 1 1 1 1
93 1 1 1 1
94 1 1 1 1
95 1 1 1 1
96 1 1 1 1
97 1 1 1
98 1 1 1 1
99 1 1 1 1
100 1 1 1 1
101 1 1 1 1
102 1 1 1 1
103 1 1 1 1
104 1 1 1 1
105 1 1 1 1
106 1 1 1 1
107 1 1 1 1
108 1 1 1 1
109 1 1 1 1
110 1 1 1 1
111 1 1 1 1
112 1 1 1 1
113 1 1 1 1
114 1 1 1 1
115 1 1 1 1
116 1 1 1 1
117 1 1 1 1
118 1 1 1 1
119 1 1 1 1
120 1 1 1 1
121 1 1 1 1
122 1 1 1 1
123 1 1 1 1
124 1 1 1 1
125 1 1 1 1
126 1 1 1 1
127 1 1 1
128 1 1 1 1
129 1 1 1
130 1 1 1 1
131 1 1 1 1
132 1 1 1
133 1 1 1 1
134 1 1 1 1
135 1 1 1 1
136 1 1 1
137 1 1 1 1
138 1 1 1 1
139 1 1 1 1
140 1 1 1 1
141 1 1 1
142 1 1 1
143 1 1 1 1
144 1 1 1 1
145 1 1 1
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Author:Raougui, Driss; Ahami, Ahmed; Aboussaleh, Youssef; Fadli, Mohamed; Sbayi, Adil
Publication:International Journal of Biotechnology & Biochemistry
Date:Sep 1, 2011
Words:3602
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