Occupational inequalities and gender differences: work accidents, Brazil, 2019

Gomides, Luciana de Melo; Abreu, Mery Natali Silva; Assunção, Ada Ávila

doi:10.11606/s1518-8787.2024058005342

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Sumário

Original Article • Rev. Saúde Pública 58 • 2024 • https://doi.org/10.11606/s1518-8787.2024058005342 copy

Occupational inequalities and gender differences: work accidents, Brazil, 2019

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

OBJECTIVE

To analyze the distribution and association of sociodemographic and occupational factors with self-reported work accidents (WA) in a representative sample of the Brazilian population, with emphasis on occupational class, and to examine gender differences in this distribution.

METHODS

A population-based cross-sectional study, using data from the 2019 National Health Survey (PNS), analyzed the responses of a sample of adults aged 18 or over. Factors associated with WA were investigated using binary logistic regression and hierarchical analysis using blocks (sociodemographic and occupational variables). The final model was adjusted by variables from all blocks, adopting a significance level of 5%. The values of odds ratios (OR) and respective confidence intervals were obtained.

RESULTS

Among the participants, 2.69% reported having suffered a WA, with a higher prevalence in men (3.37%; 95%CI 2.97–3.82%) than in women (1.86%; 95%CI 1.55–2.23%). The analysis identified that age group, night work, working hours, and exposure to occupational risks were associated with WA, with emphasis on gender differences. The class of manual workers, both qualified (OR_women = 2.87; 95%CI 1.33–6.21 and OR_men = 2.46; 95%CI 1.37–4.40) and unskilled (OR_women = 2.55; 95%CI 1.44–4.50 and OR_men = 3.70; 95%CI 1.95–7.03), had a higher chance of WA than the class of managers/professionals.

CONCLUSION

Occupational factors contributed significantly to the increase in the probability of WA for men and women, with greater magnitude among those positioned in the lower strata of the occupational structure. The results obtained are clues for working out WA prevention actions.

Accidents, Occupational; Gender; Sociodemographic Factors; Risk Factors; Health Surveys

Occupational composition¹⁹19. Ministério do Trabalho e Emprego (BR). CBO - Classificação Brasileira de Ocupações. Brasília, DF: Ministério do Trabalho e Emprego; 2010 [cited 2023 Apr 28]. Available from: http://www.mtecbo.gov.br/cbosite/pages/home.jsf http://www.mtecbo.gov.br/cbosite/pages/h...	IBGE COD Large groups (GG)	IBGE COD Subgroups (SG)
Managers ans high-level professionals (High)	GG00 – Armed forces professionals, military firefighters
	GG01 – Directors and managers	SG11 – Executive directors, public administration directors and member of the executive branch
		SG12 – Administrative and commercial managers
		SG13 – Production and operation directors and managers
		SG14 – Managers of hotels, restaurants, shops and other services
	GG02 – Science professionals and intellectuals	SG21 – Science and engineering professionals
		SG22 – Health professionals
		SG23 – Teaching professionals
		SG24 – Specialist in administration organization
		SG25 – Information and communications technology professionals
		SG26 – Professionals in law, social, and cultural sciences
Technicians (Upper-middle)	GG03 – Technicians and midlevel professionals	SG31 – Mid-level science and engineering professionals
		SG 32 – mid-level healthcare and related professionals
		SG 33 – Mid-level professionals in financial and administrative operations
		SG34 – Mid-level professionals in legal, social, cultural, and related services
		SG35 – Mid-level information and communications technology technicians
Routine non-manual workers (Middle-middle)	GG04 – Administrative support workers	SG41 – Clerks
		SG42 – Direct customer service workers
		SG43 – Numerical calculation workers and those responsible for recording materials
		SG44 – Other administrative service workers
	GG05 – Service workers, commercial vendors, and markets	SG51 – Personal service workers
		SG52 – Salespeople
		SG53 – Personal care workers
		SG54 – Protection and security services workers
Skilled manual workers (Lower-middle)	GG07 – Skilled workers, laborers, and artisans in construction, mechanical arts, and other trades	SG71 – Skilled workers and construction workers, including electricians
		SG72 – Qualified workers and workers in metallurgy, mechanical construction, and similar areas
		SG73 – Craftsmen and graphic arts workers
		SG74 – Workers specialized in electricity and electronics
		SG75 – Wood, clothing, and related food processing workers and officers
	GG08 – Plant and machine operators and assemblers	SG 81 – Operators of stationary facilities and machinery
		SG82 – Assemblers
		SG83 – Drivers of vehicles and operators of heavy mobile equipment
Unskilled manual workers (Upper-lower)	GG09 – Elementary workers	SG91 – Domestic workers and other workers cleaning the interior of buildings
		SG93 – Basic workers in mining, construction, manufacturing, and transport
		SG94 – Food preparation helpers
		SG95 – Street vendors and similar workers
		SG96 – Garbage collectors and other
Rural workers (Lower-lower)	GG09 – Elementary workers	elementary occupations
	GG06 – Qualified agricultural, forestry, hunting, and fishing workers	SG61 – Qualified agricultural farmers
		SG62 – Skilled forestry workers and hunters

Variables	Men			Women			p-value^a

	(n_exp = 50,541,462)			(n_exp = 41,991,625)

	n_exp/1000	%	Prevalence of accidents	n_exp/1000	%	Prevalence of accidents

			(95%CI)			(95%CI)
Work accident							< 0.001
No	48,837.17	96.63	-	41,211.19	98.14
Yes	1,704.30	3.37	3.37 (2.97–3.82)	780.43	1.86	1.86 (1.55–2.23)
Age range (years)							< 0.001
≥ 60	12,244.81	9.15	2.16 (1.48–3.13)	9,624.72	7.86	0.58 (0.34–1.01)
50–59	9,453.33	18.7	2.90 (2.16–3.87)	7,234.05	17.23	2.02 (1.39–2.94)
40–49	10,767.98	21.31	3.13 (2.18–4.47)	10,304.56	24.54	2.26 (1.71–2.98)
30–39	13,450.26	26.61	3.50 (2.79–4.39)	11,526.14	27.45	1.47 (1.06–2.04)
18–29	4,625.08	24.23	4.27 (3.37–5.39)	3,302.15	22.92	2.21 (1.40–3.48)
Race/color							< 0.001
White	20,971.49	41.49	2.75 (2.24–3.38)	18,866.19	44.93	1.55 (1.11–2.17)
Black	6,107.36	12.08	4.41 (3.28–5.91)	5,138.69	12.24	2.25 (1.30–3.86)
Mixed	22,649.09	44.81	3.74 (3.10–4.51)	17,465.47	44.81	2.11 (1.67–2.66)
Others^b	813.52	1.61	1.21 (0.59–2.45)	521.27	1.24	0.67 (0.25–1.76)
Education level							< 0.001
Higher	7,583.61	15	1.22 (0.74–1.99)	10,238.29	24.38	1.17 (0.79–1.72)
Secondary	19,026.78	37.65	2.95 (2.43–3.58)	17,560.47	41.82	2.29 (1.71–3.06)
Primary	8,450.14	16.72	4.52 (3.15–6.45)	5,255.97	12.52	1.94 (1.34–2.79)
No schooling	15,480.93	30.63	4.32 (3.62–5.14)	8,936.90	21.28	1.75 (1.26–2.43)
Occupational class							< 0.001
Managers/professionals	5,682.31	11.24	1.01 (0.60–1.71)	7,329.41	17.45	0.97 (0.62–1.51)
Technical	4,194.52	8.3	1.52 (1.01–2.29)	3,340.87	7.96	2.18 (1.38–3.43)
No routine manual	11,527.50	22.81	2.05 (1.46–2.85)	17,316.08	41.24	1.62 (1.16–2.26)
Qualified manual	16,757.40	33.16	3.9 (3.27–4.64)	3,639.55	8.67	3.00 (1.60–5.55)
Rural	6,675.94	13.21	5.44 (3.86–7.62)	1,643.65	3.91	1.66 (0.97–2.84)
Unqualified manual	5,703.79	11.29	5.80 (4.24–7.88)	8,722.08	20.77	2.51 (1.83–3.45)
Night work							< 0.001
No	42,496.53	84.08	3.2 (2.77–3.69)	37,930.93	90.33	1.72 (1.40–2.10)
Yes	8,044.93	15.92	4.29 (3.34–5.50)	4,060.70	9.67	3.17 (2.17–4.61)
Weekly working hours							< 0.001
< 40	25,314.06	20.54	1.96 (1.56–2.46)	27,766.83	39.24	1.26 (0.89–1.77)
40–44	10,861.41	51.04	3.34 (2.86–3.90)	6,887.88	43.29	2.23 (1.69–2.94)
> 44	14,365.99	28.42	4.46 (3.50–5.66)	7,336.92	17.47	2.28 (1.71–3.02)
Exposure to occupational risk							< 0.001
No	19,932.25	39.44	1.12 (0.81–1.54)	27,014.29	64.33	0.91 (0.69–1.19)
Yes	30,609.22	60.56	4.84 (4.22–5.54)	14,977.33	35.67	3.57 (2.83–4.49)

Variables	n_exp/1000	Not adjusted		Adjusted

		OR	p-value	Block 1 Sociodemographic	Block 2 Occupational	Final model (Block 1+2)

				OR (95%CI)	OR (95%CI)	OR (95%CI)
Age range (years)
≥ 60	9,624.72	Ref.		Ref.	-	-
50–59	7,234.05	3.53	< 0.001	3.56 (1.81–6.97)	-	-
40–49	10,304.56	3.95	< 0.001	3.95 (2.11–7.41)	-	-
30–39	11,526.14	2.55	0.005	2.54 (1.30–4.96)	-	-
18–29	3,302.15	3.86	< 0.001	3.54 (1.73–7.24)	-	-
Race/color
White	44.93	Ref.		-	-	-
Black	12.24	1.46	0.268	-	-	-
Mixed	44.81	1.36	0.142	-	-	-
Others^a	1.24	0.43	0.108	-	-	-
Education level
Higher	10,238.29	Ref.		Ref.	-	-
Secondary	17,560.47	1.98	0.007	1.94 (1.21–3.12)	-	-
Primary	5,255.97	1.67	0.064	1.64 (0.95–2.83)	-	-
No schooling	8,936.90	1.5	0.121	1.57 (0.93–2.64)	-	-
Occupational class
Managers/professionals	7,329.41	Ref.		-	Ref.	Ref.
Technical	3,340.87	2.27	0.012	-	1.60 (0.84–3.03)	1.64 (0.86–3.11)
No routine manual	17,316.08	1.68	0.068	-	1.74 (0.98–3.07)	1.71 (0.98–2.98)
Qualified manual	36.39.55	3.15	0.004	-	2.86 (1.32–6.20)	2.87 (1.33–6.21)
Rural	1,643.65	1.72	0.133	-	1.26 (0.60–2.63)	1.36 (0.65–2.86)
Unqualified manual	8,722.08	2.63	0.001	-	2.48 (1.40–4.38)	2.55 (1.44–4.50)
Night work
No	37,930.93	Ref.		-	Ref.	Ref.
Yes	4,060.70	1.87	0.005	-	1.60 (1.00–2.53)	1.59 (1.00–2.56)
Weekly working hours
< 40	27,766.83	Ref.		-	Ref.	Ref.
40–44	6,887.88	1.8	0.01	-	1.85 (1.19–2.86)	1.87 (1.20–2.90)
> 44	7,336.92	1.83	0.008	-	1.60 (1.02–2.53)	1.58 (1.00–2.49)
Exposure to occupational risk
No	27,014.29	Ref.		-	Ref.	-
Yes	14,977.33	4.03	< 0.001	-	3.79 (2.58–5.58)	-
Age group (years) #work risks
50–59 #risks (yes)	2,445.40	-	-	-	-	-
40–49 #risks (yes)	4,016.07	-	-	-	-	-
30–39 #risks (yes)	4,452.58	-	-	-	-	-
18–29 #risks (yes)	908.36	-	-	-	-	-

Variables	OR (95%CI)

	Women without exposure to occupational risk	Women exposed to occupational risk
Age range (years)
≥ 60	Ref.	Ref.
50–59	2.83 (1.16–6.93)	3.40 (1.28–9.00)
40–49	3.53 (1.38–9.05)	3.19 (1.31–7.80)
30–39	1.91 (0.63–5.73)	2.25 (0.92–5.51)
18–29	1.06 (0.39–2.91)	5.55 (2.16–14.30)
Occupational class
Managers/professionals	Ref.	Ref.
Technical	1.45 (0.41–5.17)	1.62 (0.80–3.28)
No routine manual	1.87 (0.70–4.98)	1.62 (0.83–3.13)
Qualified manual	1.92 (0.45–8.19)	3.31 (1.40–7.84)
Rural	3.71 (0.75–1.83)	1.07 (0.50–2.26)
Unqualified manual	2.81 (0.98–8.05)	2.42 (1.28–4.58)
Night work
No	Ref.	Ref.
Yes	0.88 (0.38–2.05)	1.84 (1.05–3.24)
Weekly working hours
< 4	Ref.	Ref.
40–44	2.17 (1.12–4.21)	1.72 (0.97–3.06)
> 44	2.19 (0.98–4.91)	1.35 (0.78–2.34)

Variables	n_exp/1000	Not adjusted		Adjusted

		OR	p-value	Block 1 Sociodemographic	Block 2 Occupational	Final model (Block 1+2)

				OR (95%CI)	OR (95%CI)	OR (95%CI)
Age range (years)
≥ 60	12,244.81	Ref.		Ref.		Ref.
50–59	9,453.33	1.35	0.224	1.41 (0.87–2.29)		1.19 (0.73–1.95)
40–49	10,767.98	1.46	0.158	1.61 (0.96–2.71)		1.25 (0.73–2.17)
30–39	13,450.26	1.65	0.028	2.01 (1.27–3.20)		1.42 (0.91–2.23)
18–29	4,625.08	2.02	0.003	2.37 (1.47–3.80)		1.84 (1.15–2.94)
Race/color
White	20,971.49	Ref.		-		-
Black	6,107.36	1.63	0.007	-		-
Mixed	22,649.09	1.37	0.034	-		-
Others^a	813.52	0.43	0.027	-		-
Education level
Higher	7,583.61	Ref.		Ref.		-
Secondary	19,026.78	2.47	0.001	2.27 (1.32–3.88)		-
Primary	8,450.14	3.84	< 0.001	3.57 (1.88–6.78)		-
No schooling	15,480.93	3.66	< 0.001	4.01 (2.32–6.95)		-
Occupational class
Managers/professionals	5,682.31	Ref.			Ref.	Ref.
Technical	4,194.52	1.51	0.233		1.21 (0.61–2.40)	1.17 (0.59–2.33)
No routine manual	11,527.50	2.04	0.027		1.89 (1.00–3.56)	1.80 (0.96–3.37)
Qualified manual	16,757.40	3.97	< 0.001		2.52 (1.40–4.52)	2.46 (1.37–4.40)
Rural	6,675.94	5.64	< 0.001		3.64 (1.88–7.07)	3.63 (1.87–7.04)
Unqualified manual	5,703.79	6.02	< 0.001		4.03 (2.12–7.70)	3.70 (1.95–7.03)
Night work
No	42,496.53	Ref.			Ref.	Ref.
Yes	8,044.93	1.36	0.044		1.50 (1.10–2.04)	1.47 (1.08–2.00)
Weekly working hours
< 40	25,314.06	Ref.			Ref.	Ref.
40–44	10,861.41	1.73	< 0.001		1.74 (1.31–2.31)	1.73 (1.31–2.30)
> 44 hours	14,365.99	2.33	< 0.001		2.17 (1.48–3.17)	2.19 (1.51–3.20)
Exposure to occupational risk
No	19,932.25	Ref.			Ref.	Ref.
Yes	30,609.22	4.49	< 0.001		3.36 (2.38–4.74)	3.37 (2.40–4.74)

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[1] Correspondence: Luciana de Melo Gomides Rua Irmã Ivone Drumond, 200 35903-087 Itabira, MG, Brazil E-mail: luciana.gomides@unifei.edu.br