LI Xu Dong, TU Hong Wei, LIU Yi Ming, WEN Xian Zhong, YU Hong Wei,

QU Hong Ying2,4,#, and CHEN Qing1,#

Pneumoconiosis is a restrictive lung disease mostly caused by occupational exposure to dust,including silica dust, asbestos, and other fibers.Inhalable particles smaller than 10 μm can enter the bronchioles, injure lung cells, and induce lung fibrosis. This hard-to-cure disease places a substantial burden on patients and society[1].Although preventive measures have been taken for years in occupational environments, pneumoconiosis is still one of the most important occupational diseases in the world. Relative to developed countries, low- and middle-income countries have a higher prevalence of pneumoconiosis[2]. China has a high prevalence of pneumoconiosis, which accounted for 90% of all occupational diseases reported[3]. Pneumoconiosis accounted for the largest proportion of all occupational diseases in Guangdong in 2011-2013[4]. In Guangdong, silicosis is the most prevalent type of pneumoconiosis,followed by welder’s pneumoconiosis, potter’s pneumoconiosis, and coal worker’s pneumoconiosis.However, little is known about the spatial and temporal variations in the occurrence of pneumoconiosis[3].

In this study, we firstly explored the tendency of pneumoconiosis incidence to change from 2006 to 2015 in the Pearl River Delta region and describe the spatial and temporal features of pneumoconiosis using a geographic information system (GIS), which can store, maintain, imitate, and analyze geographic information, and can further provide more insight into the spatial attributes of patients affected by a certain disease[5]. As pneumoconiosis is a rarely fatal but highly crippling disease, years lived with disability (YLD) represents the main part of the disability-adjusted life years (DALY) and was used in this study to evaluate the contributions of different districts/counties. This information may be beneficial in the occupational prevention of the disease and in establishing an administrative incident database.

The pneumoconiosis database covering the Pearl River Delta region for 2006-2015 was established using the China Disease Prevention and Control Information System, pneumoconiosis report card,and hospital medical records of pneumoconiosis in Guangdong Province. A total of 1,675 cases of new incidence pneumoconiosis during the studied period were identified in 53 counties/districts in the Pearl River Delta region, Guangdong; their spatial and temporal variations were analyzed using ArcGIS 10.2 software in this study. The case level of pneumoconiosis is classified using the Jenks natural breaks optimization, which has shown good adaptability and high accuracy for units of the geographical environment[6]. GIS was used to locate each case of pneumoconiosis, and the coordinates were derived to express the original residential location of each case in the format of latitude(denoted as X point east) and longitude (denoted as Y point north). With the number of cases in each node of the projected grid matrix represented by the Z axis, directional trend curves were produced using the ordinary least square (OLS) technique[7].

YLD was estimated using the methods used to capture the Global Burden of Disease (GBD)[8].Default parameters were applied and disability weights were set according to the stage of pneumoconiosis (Supplementary Table S1 available in www.besjournal.com). The total YLD was based on the life expectancy and age at onset in each patient,and the average YLD was calculated by dividing the total YLD by the number of cases. Detailed methods of YLD estimation have been described in GBD studies[9].

Finally, the general information in each category was analyzed using the chi-squared test. The average YLD of each category was analyzed using two-way ANOVA. A statistically significant difference was set atP＜ 0.05. For spatial statistical analysis, the Global Moran’s Index was applied to analyze whether an autocorrelation trend existed for pneumoconiosis[10],which reveals the aggregation of pneumoconiosis incidence.

General information regarding the 1,675 pneumoconiosis cases was analyzed and is presented in Supplementary Table S2 available in www.besjournal.com. The number of cases of pneumoconiosis rapidly increased during 2006-2015, except for a decrease in 2012. The distribution among age groups varied from 2006 to 2015. The percentage of 30-40-year-old workers with the disease decreased slightly from 2011, while the percentage in the 40-50 age group and 50-60 age group increased and reached a maximum in 2015. Private enterprise and manufacturing accounted for more than 65% of all cases. The differences in the proportion of cases among age groups, enterprise scales, enterprise economic types, and industries were statistically significant.Age groups, an ordered categorical dataset,correlated with the year and number of years worked (χ2= 398.1 for age group andχ2= 89.7 for working-year group). This relation was not a simple linear relation because the partial linear regressionχ2values were statistically significant as well.

Pneumoconiosis was classified into five types in this study: silicosis (S), coal-worker’s pneumoconiosis(CWP), welder’s pneumoconiosis (WP), potter’s pneumoconiosis (PP), and other pneumoconiosis(OP). Silicosis accounted for a great proportion of the total pneumoconiosis incidence (47.55%-91.07%,Supplementary Figure S1 available in www.besjournal.com). Potter’s pneumoconiosis accounted for a high proportion-approximately 10%-in 2009-2011, whereas the rate of welder’s pneumoconiosis increased remarkably in 2012 and 2014 and accounted for a sizeable proportion of pneumoconiosis cases (13.67%-30.87%).

As shown in Figure 1A, most pneumoconiosis occurred in Chancheng, Nansha, Shunde, Gaoming,and Huangpu, which have higher incidence rates (＞69 cases/million population) than those in other counties/districts in the Pearl River Delta. Chancheng district and Gaoming district also have the highest incidence rates of silicosis, with 178 cases/million population and 84 cases/million population,respectively (Figure 1B). The Huangpu district exhibited relatively high incidence rates of welder’s pneumoconiosis (Figure 1E). Incidence rates of coal worker’s pneumoconiosis, potter’s pneumoconiosis,and other types of pneumoconiosis showed a scattered distribution (Figures 1C, D, & F). According to the trend surface analysis (Supplementary Figure S2 available in www.besjournal.com), the trend of incidence rates is depicted as a parabolic curve, in the middle of which the highest incidence rates of pneumoconiosis is displayed in both the latitudinal and longitudinal axes.

Data from the ten-year period were divided into two groups: the first five years (2006 to 2010) and the last five years (2011 to 2015). According to Table 1, Moran’sIindex is 0.136 (2006-2010), with aZvalue higher than 1.96. This result indicates a collective model during this time period. However,the last five years and all ten years of data do not show a collective model. Among each category of pneumoconiosis, only silicosis has a collective characteristic according to the calculation of Moran'sI, whereas the remaining types do not have a global spatial autocorrelation.

YLD was calculated on the basis of life expectancy, onset age, and stage of pneumoconiosis.Illustrated by Figure 2A & C, the accumulative YLD in each area varied greatly in spatial distribution and the districts with the highest YLD were mainly concentrated in the central part of the PRD region,including Zhongshan, Chancheng, Shunde,Dongguan, and Baoan (Figure 1A, red areas). The average YLD (total YLD/cases) in each area did not demonstrate a notable variation among the 53 districts/counties (Figure 1B & D).

There was a significant difference in age, working years, enterprise scale, and industry between groups in the two-way ANOVA. As a result, patients aged 20-30 years who have worked with dust/fiber in the last 5 years may have a relatively higher YLD.Laborers who work in building materials, mining, and light industry may have greater YLD (＞ 10 years) on average than workers in other types of industries. In addition, welder’s pneumoconiosis showed the lowest contribution to YLD, and of the cases of welder’s pneumoconiosis, 60.54% were stage I pneumoconiosis, whereas 37% of all cases were stage I pneumoconiosis (Supplementary Table S3 available in www.besjournal.com).

In this study, the spatial and temporal distribution of occurrence and the related YLD were analyzed to understand the status of pneumoconiosis incidence in the Pearl River Delta in 2006-2015. The age at which pneumoconiosis occurs among workers in the last five years of the study period seems to be higher than that in the first five years. Private enterprise accounts for the largest number of patients compared with other types of enterprise, which may be due to the inadequate conditions of the working environment and lack of health protection. Meanwhile, some private enterprises cannot carry out their legally binding responsibilities to manage occupational hazards in the workplace[11]and may conceal patient information or even dismiss workers who become sick.

Among the different types of pneumoconiosis,silicosis was considered to be the most prevalent and most hazardous type[2,12]. In our data, cases diagnosed with silicosis accounted for more than45% of pneumoconiosis cases each year; these cases occurred mainly in the center of the Pearl River Delta and had a positive spatial autocorrelation calculated using Global Moran’sI. The remaining three types of pneumoconiosis had unique exposure factors, so they were less frequent.

Table 1. The global spatial autocorrelation of the Pearl River Delta region calculated using Global Moran’s I

We further estimated the YLD of each case of pneumoconiosis. The central area of the Pearl River Delta accounted for the largest number of YLD during the ten-year period, while the average YLD of different areas did not demonstrate remarkable discrepancies. The DALY of 17 occupational risk factors in Iran was reported and silica was the identified as the cause of 2,349 DALY in 2015[13]. The DALYs resulting from occupational exposure to silica globally reached 1,894,000 in 2015[14]. In this study,the YLD of silicosis were 1414.53 in 2015 in the Pearl River Delta, a level similar to that in Iran. In addition,pneumoconiosis is a progressive and life-long disease that has high potential for high medical costs and labor losses. Martin et al. showed that the medical costs of workers in mining or mining-related industries, as well as oil and gas extraction, were approximately 0.1 billion US dollars in 2005-2007 in Québec[15].

According to the 2015 China Statistical Yearbook,Guangdong province has approximately 80% of China’s factories and secondary industry, which require a huge number of workers[16], and of which the Pearl River Delta region is the political,economic, and cultural center. However, the data in this study demonstrated that the higher YLD was contributed by small, private enterprises and some special types of industry. Worker protection relies on the competence of the enterprise and the leaders’awareness of occupational health hazards. Our data have shown a deficiency in occupational health management and control of the work environment.Therefore, the development of related occupational health supervision and protection should be emphasized and promoted.

&These authors contributed equally to this work.

#Correspondence should be addressed to CHEN Qing,Professor, PhD, E-mail: qingchen@smu.edu.cn, Tel: 86-20-61648311; QU Hong Ying, Professor, PhD, E-mail:gdzfyb@126.com

Biographical notes of the first authors: LI Xu Dong,male, born in 1982, PhD, majoring in occupationalepidemiology; TU Hong Wei, female, born in 1988, PhD, majoring in environmental hygiene and food hygiene.

Supplementary Table S1. The disability weight of each gradation of pneumoconiosis-induced disability

Supplementary Table S2. General information on pneumoconiosis occurrence in the Pearl River Delta region each year from 2006 to 2015

Supplementary Table S3. Average YLD of pneumoconiosis in different categories in the Pearl River Delta region from 2006 to 2015

Received: October 6, 2019;Accepted: January 13, 2020