ABSTRACT
Background As the population ages, there has been a growing focus on the decline in fertility. Research has identified age and fertility history as the primary influencing factors. Nevertheless, there is a deficiency in fundamental data regarding the fertility status among different industries. Objective To investigate the fertility status and influencing factors among female workers aged 22-35 years in different industries. Methods From July 2020 to February 2021, a cross-sectional survey was conducted using a staged sampling approach. This survey specifically targeted 22-35-year-old married female workers with a history of pregnancy in industries such as education, healthcare, finance, and telecommunications, totaling 22903 participants. The survey encompassed industry, demographic characteristics, pregnancy history, time to pregnancy (TTP), and other influencing factors. The influencing factors of decline in fertility were identified by chi-square test and Cox proportional hazards regression. Subsequent industry-specific Cox proportional hazards regression models were used to compared fertility decline patterns across a spectrum of industries after selected influencing factors were adjusted. Results Among the 22903 respondents, 19194 valid questionnaires were collected, with a valid recovery rate of 83.8%. The cumulative pregnancy rates (CRP) of 1-6 months and 1-12 months for the 22-35-year-old female workers were 67.23% and 91.33% respectively. The multivariate analysis showed that region, age, education level, personal annual income, housework time, coping style, gravidity, parity, and spontaneous abortion were influencing factors of fertility decline (P<0.05). Female workers with ≥3 gravidities and ≥2 spontaneous abortions had a higher risk of fertility decline, with hazard ratios (HR) and associated 95% confidence interval (95%CI) of 0.633 (0.582, 0.688) and 0.785 (0.670, 0.921) respectively (P<0.01). Compared to the education industry, the healthcare and finance industries showed a higher risk of fertility decline, with HR (95%CI) values of 0.876 (0.834, 0.920) and 0.909 (0.866, 0.954), respectively (P<0.05). These two HR (95%CI) values remained statistically significant [0.899 (0.852, 0.948) and 0.882 (0.833, 0.934) respectively, P<0.05)] after further adjustment with nine influencing factors such as region and age. Conclusion Regions, age, education level, personal annual income, housework time, coping style, pregnancy and childbirth times, and natural abortion times are influencing factors of fertility decline in female workers. Compared to the education industry, the healthcare and finance industries have a higher risk of declining fertility.
ABSTRACT
The existing measuring methods of noise exposure on the basis of equal energy hypothesis are applicable to Gaussian noise while not fully applicable to non-Gaussian noise. Studies have shown that temporal structure (kurtosis) combined with noise energy has the potential to quantify non-Gaussian noise exposure effectively. However, there is no unified measuring method adopting this joint metric. In this paper, the measuring method of non-Gaussian noise exposure based on kurtosis adjustment was introduced, detailing measurement indicators, adjustment schemes, applicable objects, instrument requirements, and measurement steps. Adjusting the exposure duration of cumulative noise exposure (CNE) by kurtosis or adjusting the equivalent continuous A-weighted sound pressure level (LAeq) by an adjustment coefficient based on animal or population studies can more accurately quantify workers' exposure to non-Gaussian noise and improve the underestimation of hearing loss caused by non-Gaussian noise. A large number of population studies are warranted in the future to verify the effectiveness of these two adjustment schemes.
ABSTRACT
Background Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases in the world. With the development of industry, noise sources in the workplace have become increasingly complex. Objective To apply kurtosis-adjusted cumulative noise exposure (CNE) to assess the occupational hearing loss among furniture manufacturing workers, and to provide a basis for revising noise measurement methods and occupational exposure limits in China. Methods A cross-sectional survey was conducted to select 694 manufacturing workers, including 542 furniture manufacturing workers exposed to non-Gaussian noise, and 152 textile manufacturing workers and paper manufacturing workers exposed to Gaussian noise. The job titles involving non-Gaussian noise were gunning and nailing, and woodworking, while those involving Gaussian noise were weaving, spinning, and pulping. High frequency noise-induced hearing loss (HFNIHL) and noise exposure data were collected for each study subject. Noise energy metrics included eight-hour equivalent continuous A-weighted sound pressure level (LAeq,8 h) and CNE. Kurtosis was a noise temporal structure metric. Kurtosis-adjusted CNE was a combined indicator of noise energy and temporal structure. Results The age of the study subjects was (35.64±10.35) years, the exposure duration was (6.71±6.44) years, and the proportion of males was 75.50%. The LAeq,8 h was (89.43±6.01) dB(A). About 81.42% of the study subjects were exposed to noise levels above 85 dB(A), the CNE was (95.85±7.32) dB(A)·year, with a kurtosis of 99.34 ± 139.19, and the prevalence rate of HFNIHL was 35.59%. The mean kurtosis of the non-Gaussian noise group was higher than that of the Gaussian noise group (125.33±147.17 vs. 5.86±1.94, t=−21.04, P<0.05). The results of binary logistic regression analysis showed that kurtosis was an influential factor of workers' HFNIHL after correcting for age, exposure duration, and LAeq,8 h (OR=1.49, P<0.05). The results of multiple linear regression analysis showed that the effects of age, exposure duration, LAeq,8 h, and kurtosis on noise-induced permanent threshold shift at frequencies of 3, 4, and 6 kHz of the poor hearing ear were statistically significant (all P<0.05). The results of chi-square trend analysis showed that when CNE ≥ 90 dB(A)·year, the HFNIHL prevalence rate elevated with increasing kurtosis (P<0.05). The mean HFNIHL prevalence rate was higher in the non-Gaussian noise group than in the Gaussian noise group (31.7% vs. 22.0%, P<0.05). After applying kurtosis-adjusted CNE, the linear equation between CNE and HFNIHL prevalence rate for the non-Gaussian noise group almost overlapped with that for the Gaussian noise group, and the mean difference in HFNIHL prevalence rate between the two groups decreased from 9.7% to 1.4% (P<0.05). Conclusion Noise kurtosis is an effective metric for NIHL evaluation. Kurtosis-adjusted CNE can effectively evaluate occupational hearing loss due to non-Gaussian noise exposure in furniture manufacturing workers, and is expected to be a new indicator of non-Gaussian noise measurement and assessment.
ABSTRACT
Background Non-Gaussian noise has become the dominant noise type in industry. However, the epidemiological characteristics of non-Gaussian noise exposure and associated noise-induced hearing loss (NIHL) are still unclear. Objective To summarize the epidemiological characteristics of NIHL associated with non-Gaussian noise in manufacturing industry in China and provide a basis for the early prevention and control of occupational hearing loss. Methods Chinese and English literature on hearing loss associated with non-Gaussian noise in China were retrieved. The overall prevalence was calculated based on the prevalence data provided by each included study. A meta-analysis of studies with Gaussian noise as a control group was also performed and the overall weighted odds ratio (OR) was calculated to compare the effects of non-Gaussian noise and Gaussian noise on hearing loss. Publication bias was evaluated by funnel plot and Egger regression, and a sensitivity analysis was performed by eliminating references in turn. Results A total of 37 cross-sectional studies involving 25 055 Chinese manufacturing workers exposed to non-Gaussian noise were included, 92.5% of whom were male. These workers aged (32.7±9.6) years were exposed to non-Gaussian noise at (87.0±4.2) dB(A) for (6.8±4.9) years. The mean cumulative noise exposure (CNE) was (95.9±8.0) dB(A)·year. The prevalence rate of high-frequency NIHL (HFNIHL) and speech-frequency NIHL (SFNIHL) were 29.0% and 14.2%, respectively. The results of the meta-analysis treating 19 cross-sectional studies with Gaussian noise as a control group showed that there were no significant differences in age, exposure duration, and equivalent continuous A-weighted sound pressure level (LAeq), and CNE between the non-Gaussian noise group and the Gaussian noise group. The overall weighted OR of HFNIHL was 1.87 (95%CI: 1.46−2.41), which was statistically significant. The funnel plot showed good symmetry and the result of Egger regression was t=−0.11, P=0.910 (>0.05), suggesting a low risk of publication bias in this meta-analysis. The sensitivity analysis showed no significant changes of results after eliminating references in turn, indicating that the results were robust. Conclusion Chinese manufacturing workers, mainly young adult males, are exposed to non-Gaussian noise at high levels for a long time and have a high prevalence of NIHL. Compared to workers exposed to Gaussian noise, those exposed to non-Gaussian noise suffer from more serious hearing loss.
ABSTRACT
Background Noise is the most common occupational hazard in the automobile manufacturing industry with the most workers exposed. Automobile manufacturing industry is a high-risk industry for noise-induced hearing loss. Objective To understand the epidemiological characteristics of noise-induced hearing loss among workers in automobile manufacturing industry and explore related influencing factors. Methods A questionnaire survey, individual noise recording, and pure tone audiometry were conducted among workers (n=656) exposed to noise from five automobile manufacturing enterprises. The data on age, sex, exposure duration, noise intensity, kurtosis, and hearing loss were obtained. The positive rates of high-frequency noise-induced hearing loss (HFNIHL) and speech-frequency noise-induced hearing loss (SFNIHL) were calculated, and each factor was compared between workers with and without HFNIHL. Chi-square test and analysis of trend were conducted among different groups of age, sex, exposure duration, A-weighted equivalent continuous sound pressure level normalized to a nominal 8-hour working day (LAeq,8h), and kurtosis. Logistic regression analysis was conducted to analyze the factors influencing the positive rates of HFNIHL and SFNIHL. Results The exposure rates of non-Gaussian noise was 73.6%. The positive rates of HFNIHL and SFNIHL were 32.6% (214 workers) and 6.7% (44 workers), respectively. The HFNIHL workers showed older age, higher proportion of male, longer exposure duration, higher noise intensity (LAeq,8 h), and increased kurtosis than those without HFNIHL (P<0.05). The positive rates of HFNIHL increased with the increase of age, exposure duration, LAeq,8 h, and kurtosis (\begin{document}$ {\chi