Factors associated with notification of noise-induced hearing loss in Brazil, 2013-2015: an ecological study

Gusmão, Aline Cristina; Meira, Tatiane Costa; Ferrite, Silvia

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Epidemiologia e Serviços de Saúde

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Original Article • Epidemiol. Serv. Saúde 30 (2) • 2021 • https://doi.org/10.1590/S1679-49742021000200018 copy

Factors associated with notification of noise-induced hearing loss in Brazil, 2013-2015: an ecological study² 1 Article derived from the master’s degree dissertation entitled ‘Contextual factors associated with the notification of noise-induced hearing loss on Sinan, in Brazil’, submitted by Aline Cristina Gusmão Souza Gomes to the Public Health Postgraduate Program of the Federal University of Bahia, on July 24, 2019. The study received financial support from the Coordination for the Improvement of Higher Education Personnel/Ministry of Education (Capes/MEC): Process No. 001.

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Objective

To investigate factors associated with the notification of noise-induced hearing loss (NIHL), on the Notifiable Health Conditions Information System (SINAN) in Brazil.

Methods

This was an ecological study to estimate the proportion of municipalities that had notified NIHL. Logistic regression models were used to identify associated factors.

Results

Between 2013-2015, 277 (5.0%) municipalities notified NIHL. Notification was more prevalent among municipalities in an Occupational Health Referral Center (CEREST) coverage area (OR=1.62 - 95%CI 1.02;2.59) or those that had a CEREST in their territory (OR=4.37 - 95CI% 2.75;6.93), those that were closer to the state capital (OR=1.43 - 95%CI 1.06;1.92) and those with a high human development index (OR=2.35 - 95%CI 1.16;4.75). Among the municipalities located in a CEREST coverage area, notification was more frequent when there was a speech-language-hearing professional in the team (OR=1.96 - 95%CI - 1.47;2.63) and when employee turnover was low (OR=1.88 - 95%CI 1.40;2.52).

Conclusion

Contextual factors influence NIHL notification, particularly the presence of CERESTs and their qualification.

Keywords:
Hearing Loss, Noise-Induced; Health Information Systems; Public Health Surveillance; Occupational Health; Ecological Studies

Variables	N	%
Cerest^a Coverage
No	1,170	21.0
Yes	4,400	79.0
Municipality home to a Cerest^a
No	5,392	96.8
Yes	178	3.2
Macro-region
North	450	8.1
Northeast	1,794	32.2
Southeast	1,668	29.9
South	1,191	21.4
Midwest	467	8.4
Distance to the capital (km)
≥275.0	2,781	49.9
<275.0	2,789	50.1
Territorial extension (km²)
≤418	2,785	50.0
>418	2,785	50.0
Occupied population (workers)^b
≤5,000	2,942	52.9
5,001 - 20,000	1,973	35.4
20,001- 50,000	399	7.2
50,001 - 100,000	126	2.3
>100,000	125	2.2
Workers in manufacturing/mining/construction industries (%)
<15.0	2,974	53.4
≥15.0	2,596	46.6
Workers in manufacturing industry (%)
≤6,4	2,785	50.0
>6,4	2,785	50.0
Workers in mining industry (%)
≤0.1	2,871	51.5
>0.1	2,699	48.5
Construction workers (%)
≤6.0	2,796	50.2
>6.0	2,774	49.8
Workers with formal employment (%)
≤34.1	2,780	50.0
>34.1	2,785	50.0
Municipal human development index (HDI-M)^b
Low/very low	1,399	25.1
Medium	2,263	40.7
High/very high	1,903	34.2

Variable	N	%
Year Reference Cerest^a accredited
>2005	2,158	49.1
≤2005	2,242	50.9
Average number of team members (2013-2015)
<10	1,557	35.4
≥10	2,843	64.6
Team members with statutory employment relationship (%)
≤50.0	1,926	43.8
>50.0	2,474	56.2
Average number of speech-language-hearing professionals (2013-2015)
<1	2,837	64.5
≥1	1,563	35.5
Team^b turnover
Higher turnover (>33,3%)	2,261	52.8
Lower turnover (≤33,3%)	2,020	47.2

Variables	N	Reported NIHL		Measures of association				Final model^a
		Reported NIHL		Crude		Adjusted by occupied population^a
		N	%	OR^b	95%CI^c	OR^b	95%CI^c	OR^b	95%C^Ic
Brazil	5,570	277	5.0
Cerest^d Coverage
No	1,170	23	2.0	1.00		1.00		1.00
Yes	4,400	254	5.8	3.06	1.98;4.70	1.81	1.15;2.83	1.62	1.02;2.59
Municipality home to a Cerest^d
No	5,392	186	3.4	1.00		1.00		1.00
Yes	178	91	51.1	29.28	21.08;40.65	3.90	2.52;6.05	4.37	2.75;6.93
Macro-region
North	450	7	1.6	0.47	0.21;1.04	0.35	0.15;0.81	0.32	0.13;0.79
Northeast	1,794	58	3.2	1.00		1.00		1.00
Southeast	1,668	124	7.4	2.40	1.75;3.31	1.64	1.16;2.34	1.39	0.87;2.23
South	1.191	46	3.9	1.20	0.81;1.78	1.07	0.70;1.65	0.85	0.50;1.46
Midwest	467	42	9.0	2.96	1.96;4.46	3.49	2.22-5.46	2.84	1.65;4.90
Distance to the capital (km)
≥275.0	2,781	89	3.2	1.00		1.00		1.00
<275.0	2,789	188	6.7	2.19	1.69;2.83	1.34	1.01;1.78	1.43	1.06;1.92
Territorial Extension (km²)
≤418	2,785	115	4.1	1.00		1.00
>418	2,785	162	5.8	1.43	1.12;1.83	0.95	0.72;1.26
Workers in manufacturing/mining/construction industries (%)
<15.0	2,974	70	2.4	1.00		1.00
≥15.0	2,596	207	8.0	3.59	2.73;4.74	1.64	1.20;2.25
Workers in manufacturing industry (%)
≤6.4	2,785	65	2.3	1.00		1.00
>6.4	2,785	212	7.6	3.45	2.60;4.58	1.72	1.26;2.35
Workers in mining industry (%)
≤0.1	2,871	114	4.0	1.00		1.00
>0.1	2,699	163	6.0	1.55	1.22;1.99	1.18	0.90;1.55
Construction workers (%)
≤6.0	2,796	67	2.4	1.00		1.00
>6.0	2,774	210	7.6	3.34	2.52;4.42	1.42	1.03;1.95
Workers with formal employment (%)^e
≤34.1	2,780	50	1.8	1.00		1.00
>34.1	2,785	227	8.2	4.85	3.55;6.61	2.00	1.41;2.83
Municipal human development index (IDH-M)^e,f
Low/very low	1,399	16	1.1	1.00		1.00		1.00
Medium	2,263	74	3.3	2.92	1.70;5.04	2.37	1.36;4.11	1.81	0.98;3.32
High/very high	1,903	187	9.8	9.42	5.63;15.77	3.44	1.99;5.94	2.35	1.16;4.75

Variables	N	Reported NIHL		Measures of association				Final model^b
		Reported NIHL		Crude		Adjusted by occupied population^b
		N	%	OR^c	95%CI^d	OR^c	95%CI^d	OR^c	95%CI^d
Municipalities covered by Cerests^a	4,400	254	5.8
Year Cerests accredited
>2005	2,158	103	4.8	1.00		1.00
≤2005	2,242	151	6.7	1.44	1.11;1.86	1.19	0.90;1.59
Average number of team members (2013-2015)
<10	1,557	70	4.5	1.00		1.00
≥10	2,843	184	6.5	1.47	1.11;1.95	1.30	0.95;1.77
Team members with statutory employment relationship (%)
≤50.0	1,926	108	5.6	1.00		1.00
>50.0	2,474	146	5.9	1.06	0.82;1.36	1.02	0.77;1.36
Average number of speech-language-hearing professionals (2013-2015)
<1	2,837	135	4.8	1.00		1.00		1.00
≥1	1,563	119	7.6	1.65	1.28;2.13	1.96	1.47;2.61	1.96	1.47;2.63
Team turnover^e
Higher turnover (>33,3%)	2,261	96	4.2	1.00		1.00		1.00
Lower turnover (≤33,3%)	2,020	157	7.8	1.90	1.46;2.47	1.85	1.38;2.47	1.88	1.40;2.52

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[1] Correspondence: Aline Cristina Gusmão - Universidade Federal da Bahia, Instituto de Saúde Coletiva, Programa Integrado em Saúde Ambiental e do Trabalhador, Rua Basílio da Gama, S/N, Canela, Salvador, BA, Brazil. Postcode: 40110-040. E-mail: aline.cristina@ufba.br