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. 2025 Jul 10;15(1):24844.
doi: 10.1038/s41598-025-09575-x.

Global health burden and inequality patterns of occupational noise exposure from 1990 to 2019

Yifei Wang  1   2 , Nan Zhang  3   4 , Xiangxi Li  2 , Wenrui Du  2 , He Wang  2 , Xuepeng Shi  2
Affiliations

Global health burden and inequality patterns of occupational noise exposure from 1990 to 2019

Yifei Wang et al. Sci Rep. .

Abstract

Exposure to occupational noise has emerged as a major health issue worldwide. To better evaluate changes in the health impacts of occupational noise exposure from 1990 to 2021, this study conducted stratified analyses of spatiotemporal variations across regions, genders, age, and sociodemographic index (SDI) levels. Results indicate that low-income and rapidly industrializing countries bear higher burdens of occupational noise-related diseases. Males and middle-aged to elderly populations are the primary high-risk groups for occupational noise exposure, with a particularly notable increase in the burden among those aged 45-74. Disability-adjusted life years (DALYs) significantly decreased with increasing SDI, while estimated annual percentage change (EAPC) showed significant positive correlations with both DALYs (R = 0.3) and SDI (R = 0.4). Regions with an SDI of 0.4-0.6 experienced the most pronounced EAPC growth. By 2035, DALYs rates are projected to decrease to 125.0 ± 1.9 per 100,000, although the burden for individuals aged 65 and above is expected to increase significantly. Population growth and aging were identified as key drivers of DALYs increases, contributing 68.2% and 20.9%, respectively. From 1990 to 2021, the slope inequality index changed from - 9.6 to 2.5, and the concentration index curve became smoother. Although health inequality has improved, the disease burden in low-SDI countries remains significantly higher than theoretical minimum levels. This study provides robust support for reducing global occupational noise exposure and its associated health inequalities.

Keywords: Age-period-cohort analysis; Disability-adjusted life years; Efficiency frontier model; Health inequality; Occupational noise; Population aging and growth.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Map of GBD Regional Classifications.
Fig. 2
Fig. 2
Global distribution map of occupational noise-related EAPC.
Fig. 3
Fig. 3
Occupational noise-related DALYs in different regions in 1990 and 2021.
Fig. 4
Fig. 4
Occupational noise–related gender differences across regions.
Fig. 5
Fig. 5
Occupational noise–related gender differences by age groups.
Fig. 6
Fig. 6
Relationship between SDI and DALYs from occupational noise in 21 regions.
Fig. 7
Fig. 7
Relationship between SDI and DALYs from occupational noise in 204 countries.
Fig. 8
Fig. 8
Relationship among (a) EAPC and DALYs, (b) EAPC and SDI (Each dot represents a country, the curve denotes the fitted regression trend, and the shaded area indicates the 95% UI. Larger circles indicate higher values.).
Fig. 9
Fig. 9
Future changes in DALYs due to occupational noise exposure by age group.
Fig. 10
Fig. 10
Decomposition of changes in occupational noise-related DALYs.
Fig. 11
Fig. 11
Analysis of age and cohort effects related to occupational noise.
Fig. 12
Fig. 12
APC analysis of occupational noise-related DALYs. (a) Net drifts (b) Age effects; (c) Period effects; (d) Cohort effects.
Fig. 13
Fig. 13
Changes of SII in DALYs attributable to occupational noise, 1990–2021.
Fig. 14
Fig. 14
Changes of CI in DALYs attributable to occupational noise, 1990–2021.
Fig. 15
Fig. 15
Frontier analysis of occupational noise–related DALYs in relation to SDI. (a) Spatiotemporal distribution of DALY rates and SDI, with the frontier curve representing the theoretical minimum burden; (b) Comparison of DALY rates and SDI in 2021, showing deviation from the frontier and trends in disease burden across countries.
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