Introduction
Over the past three decades, China has experienced a significant demographic transition, characterised by a dramatic rise in the number of rural-to-urban migrant workers – individuals who migrate from impoverished rural villages to prosperous cities to seek better job opportunities and pursue higher quality of life (Xiao, Reference Xiao2016). In 2015, there were 277 million migrant workers in China, making up approximately one-fifth of the entire Chinese population (National Bureau of Statistics of China, 2016). These workers have been the backbone of China's manufacturing and export orientated economy; however, due to the administrative barriers of China's household registration system (hukou), migrant workers are still classified as temporary residents of the cities (Wong et al. Reference Wong, Li and Song2007). Because hukou plays an important role in social resource allocation, migrant workers have very limited access to benefits such as social welfare, labour security, health insurance, public education of their children and housing subsidies that are available for registered urban residents (Gong et al. Reference Gong, Liang, Carlton, Jiang, Wu, Wang and Remais2012). Accordingly, migrant workers often have to take up low-wage ‘3D’ (dirty, dangerous and demanding) jobs that urban people eschew, work long hours to increase their income, expose to workplace hazardous factors and experience various forms of stigmatisation and rural-to-urban acculturative stress (Li et al. Reference Li, Zhang, Fang, Xiong, Chen, Lin, Mathur and Stanton2007; Lau et al. Reference Lau, Cheng, Gu, Zhou, Yu, Holroyd and Yeung2012; Fitzgerald et al. Reference Fitzgerald, Chen, Qu and Sheff2013; Zhong et al. Reference Zhong, Liu, Huang, Fung, Chan, Conwell and Chiu2016b). As such, migrant workers have long been identified as a particularly vulnerable group of Chinese society and therefore are more likely to be mentally unhealthy.
Mental disorders, especially depressive and anxiety disorders, are notable contributors to the global burden of disease worldwide (Whiteford et al. Reference Whiteford, Degenhardt, Rehm, Baxter, Ferrari, Erskine, Charlson, Norman, Flaxman, Johns, Burstein, Murray and Vos2013). In Global Burden of Disease Study 2013, China alone accounted for 17% of the global mental illness burden and the burden of mental illness was expected to increase by 10% in China between 2013 and 2025 (Charlson et al. Reference Charlson, Baxter, Cheng, Shidhaye and Whiteford2016). Given the very large number of migrant workers and their potentially high risk of mental health problems, interventions targeted at migrant workers might be a cost-effective way to reduce the burden of mental disorders in China.
During the past decades, many studies have extensively investigated the prevalence of common mental health problems (CMHPs) in Chinese migrant workers. While most existing studies have demonstrated that migrant workers are more susceptible to a variety of mental health problems such as depression, anxiety and loneliness (Wen & Wang, Reference Wen and Wang2009; Qiu et al. Reference Qiu, Caine, Yang, Chen, Li and Ma2011; Zhong et al. Reference Zhong, Liu, Chiu, Chan, Hu, Hu, Xiang and Caine2013, Reference Zhong, Xu, Jin, Zou and Liu2016a; Yang et al. Reference Yang, Gao, Wang, Yang, Liu, Shen, Gong, Dai, Zhou, Gu, Pan and Zhu2016), prevalence estimates of CMHPs in migrant workers still vary substantially across studies. For example, data from studies using the depression subscale of Symptom Checklist-90-Revised (SCL-90-R) and the Center for Epidemiologic Studies Depression Scale (CES-D) showed that 6.5–56.4 and 10.5–52.9% of migrant workers had a clinically relevant level of depressive symptoms (Wang, Reference Wang2005; Chen et al. Reference Chen, Zhang, Chen, Chen, Wei, Hu, Huang and Li2006; Mou et al. Reference Mou, Cheng, Griffiths, Wong, Hillier and Zhang2011; Qiu et al. Reference Qiu, Caine, Yang, Chen, Li and Ma2011; Zhuo et al. Reference Zhuo, Ding, Hong, Song and Zhuo2011; Zeng et al. Reference Zeng, Luo, Cui and Tu2012; Dai et al. Reference Dai, Zhong, Xiang, Chiu, Chan, Yu and Caine2015), respectively. Although methodological differences may partly explain the prevalence variations, i.e. random v. convenience sampling, large v. small sample sizes and SCL-90-R v. CES-D mental health assessments, our meta-analysis based on 48 surveys revealed that heterogeneity in characteristics of study samples contribute considerably to the large variations in CMHPs prevalence (Zhong et al. Reference Zhong, Liu, Chiu, Chan, Hu, Hu, Xiang and Caine2013). Several recent studies (Yang et al. Reference Yang, Xu, Li, Rockett, Zhu and Ellison-Barnes2012, Reference Yang, Gao, Wang, Yang, Liu, Shen, Gong, Dai, Zhou, Gu, Pan and Zhu2016; Li et al. Reference Li, Chang, Yip, Li, Jordan, Tang, Hao, Huang, Yang, Chen and Zeng2014) also found that the prevalence of poor mental health among migrant workers varied widely across age-groups, genders, educational attainments, industries (i.e. manufacturing v. construction), working conditions, geographic regions of origin (i.e. north v. south China) and even cities they worked in. It seems that CMHPs prevalence varies depending on the composition of migrant worker sample (i.e. proportion of high-risk subgroup), suggesting that migrant workers are a highly heterogeneous population and multiple factors contribute to the pathogenesis of CMHPs of migrant workers. Therefore, it would be of greater importance to investigate the high-risk groups within migrant worker population, not merely the prevalence of CMHPs.
According to the theory of international migration (Kirmayer et al. Reference Kirmayer, Narasiah, Munoz, Rashid, Ryder, Guzder, Hassan, Rousseau and Pottie2011), migration per se is a dynamic process and can be divided into three phases: pre-migration, migration and post-migration. Risk factors specific to each phase would negatively influence the mental health of immigrants, i.e. early age at first migration and ‘no clear motive for migration’ before migration (Takeuchi et al. Reference Takeuchi, Chung, Lin, Shen, Kurasaki, Chun and Sue1998; Fenta et al. Reference Fenta, Hyman and Noh2004), exposure to violence during migration (Bhugra, Reference Bhugra2003) and poor language skills in the host country language after migration (Mirsky et al. Reference Mirsky, Kohn, Levav, Grinshpoon and Ponizovsky2008; Im et al. Reference Im, Lee and Lee2014). Consequently, CMHPs prevalence is also influenced by the trajectory of migration, varying over time. Because of Chinese migrant workers’ ‘clock pendulum’ pattern of migration-moving back and forth yearly between their home villages where they belong permanently and cities where they temporarily work in (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015), their process of migration is prolonged, even endless, and it is very likely that these migration-related risk factors have more profound effects on their mental health. In this case, a greater understanding on the epidemiology of CMHPs, particularly risk factors related to migration, may lend additional insights into prevention efforts for migrant workers. Unfortunately, most previous studies focused on the most basic socio-demographic correlates of CMHPs among migrant workers, very few have specifically examined migration-related factors of CMHPs (Shen et al. Reference Shen, Lu, Hu, Deng, Gao, Huang and Niu1998; Wang, Reference Wang2005; Chen et al. Reference Chen, Zhang, Chen, Chen, Wei, Hu, Huang and Li2006; Wong et al. Reference Wong, He, Leung, Lau and Chang2008; Mou et al. Reference Mou, Cheng, Griffiths, Wong, Hillier and Zhang2011; Qiu et al. Reference Qiu, Caine, Yang, Chen, Li and Ma2011; Zhuo et al. Reference Zhuo, Ding, Hong, Song and Zhuo2011; Yang et al. Reference Yang, Xu, Li, Rockett, Zhu and Ellison-Barnes2012, Reference Yang, Gao, Wang, Yang, Liu, Shen, Gong, Dai, Zhou, Gu, Pan and Zhu2016; Zeng et al. Reference Zeng, Luo, Cui and Tu2012; Li et al. Reference Li, Chang, Yip, Li, Jordan, Tang, Hao, Huang, Yang, Chen and Zeng2014).
We set out to investigate the prevalence and risk factors of CMHPs in Chinese migrant workers. The hypothesis of this study was that the CMHPs would be prevalent in migrant workers, and they will be associated with a number of socio-demographic and migration-related characteristics.
Method
Setting and sampling
This study was part of a large-scale cross-sectional survey (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015), which investigated mental health of factory migrant workers in Shenzhen, China, between August 2012 and January 2013. Shenzhen is a modern metropolis in southeastern China. As one of the major destinations for migrants from impoverished western and central inland regions of China, it has been China's largest migrant city with 7.8 million rural-to-urban migrants in 2012 (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015). Eligible subjects were workers registered as rural residents, aged 16 years or older, working in manufacturing factories and living in Shenzhen. Multistage sampling method was used to obtain a representative sample of factory migrant workers. The details of sampling, recruitment process, data collection and quality control have been described elsewhere (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015). In brief, we first purposively selected ten factories (three electronic, two machinery, two shoes, two cosmetic and one garment) to represent factories of Shenzhen. Second, a total of 41 production units (2–6 units/factory) were randomly selected from the 397 production units of the ten factories. Finally, all eligible subjects of these identified units were invited to participate in this survey.
The study protocol was approved by the Survey and Behavioral Ethics Committee of the Chinese University of Hong Kong. All participants provided written informed consent prior to participating in the survey. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Procedures
Before the formal study, a pilot study was conducted to test our survey questionnaires and procedures. This survey was composed of three parts. First, the survey team leader gave all subjects a brief introduction on the survey and instructions for filling out the questionnaires. Second, migrant workers independently and anonymously completed the questionnaires. Trained investigators were assigned to read out questions in the questionnaires for participants who were illiterate or had difficulties in reading. Last, trained investigators checked the questionnaires for illogical responses or missing values before the collection of questionnaires.
Measures
Basic socio-demographic factors in the questionnaire included age, gender, education, marital status, self-rated living condition in Shenzhen (good, moderate and poor) and average monthly income.
Physical health of respondents was assessed with the 2-week morbidity. This health indicator was directly adapted from China's National Health Services Surveys (Zhu et al. Reference Zhu, Sun, Geng, Fu, Yang and Jiang2015), which asked whether the subject had experienced any physical health problems, including infectious diseases and chronic non-communicable diseases during the past 2 weeks.
Migration-related variables were age at first migration, geographic region of origin (eastern, central and western China) (National Bureau of Statistics of China, 2015), length of working outside hometown, total number of cities that migrant workers had worked in, frequencies of contacting families by phone and hometown visit, migration pattern (alone, with some family members and with all family members), self-rated standard Mandarin (the official language in China) proficiency (good, moderate and poor), Scale of Perceived Benefits of Migration (PBM), total number of jobs that migrant workers had engaged in and average working hours per day.
Age at first migration was the exact age when migrant workers first came to cities for jobs. Considering that migration should not be all bad for the mental health of migrant workers, the self-rated Scale of PBM was specifically developed to assess migrant workers’ subjective feelings about the benefits of out-migration work. First, 23 migrant workers of various types of factories were invited to join a Focus Group Discussion study, in which they were guided to talk about their individual experiences about the benefits of out-migration work. Based on these qualitative data, we generated an item pool of the scale and pilot tested it among 204 factory migrant workers. By using the pilot test data, item and exploratory factor analyses were performed and the final version of the Scale of PBM, a seven-item unidimensional scale, was developed. Finally, the psychometric property of the scale was tested in another sample of 210 factory migrant workers and the Cronbach's α coefficient of it was 0.90. The seven items were: (1) Migration work improves my personal economic conditions; (2) Migration work improves my family's economic conditions; (3) Migration work improves my working abilities; (4) Migration work gives me a good opportunity to make many friends; (5) Migration work makes me realise personal economic independence and freedom; (6) Migration work enriches my social experiences; and (7) Migration work makes me realise personal life value. These items were assessed on a five-point scale (ranging from ‘1 = disagree’ to ‘5 = strongly agree’) and summed up to generate a total score, with higher total score indicating higher level of PBM.
The primary outcome of this study, CMHPs, was measured by the Chinese 12-item General Health Questionnaire (GHQ-12). This scale was developed as a screening tool to detect those likely to have or be at risk of developing mental illness (Goldberg, Reference Goldberg1972) and has been widely used an indicator of CMHPs in a variety of settings (Craig, Reference Craig2007). Each GHQ item has four-point responses: ‘not at all = 0’, ‘same as usual = 0’, ‘rather more than usual = 1’, and ‘much more than usual = 1’. The GHQ score, obtained by summing up the scores of the 12 items, measures the severity of minor psychiatric morbidity (Pevalin, Reference Pevalin2000). The Chinese GHQ-12 is reliable and valid in Chinese population and a score of three or above was used to denote the presence of CMHPs (Yang et al. Reference Yang, Huang and Wu2003).
Statistical analyses
Participants were divided into subgroups according to socio-demographic and migration-related characteristics. Prevalence rates of CMHPs in the whole group and different subgroups of migrant worker sample were calculated. Chi-square (χ 2) test was used to compare rates between subgroups. Multiple logistic regression with a backward stepwise entry of all significant factors in univariate analysis was used to identify risk factors of CMHPs. Odds ratio (OR) and 95% confidence intervals (CI) were generated for each variable. The statistical significance level was set at p < 0.05 (two-sided). SPSS software version 15.0 package was used for analyses.
Results
A total of 3140 migrant workers were invited to join the study, 71 did not complete the questionnaire and 38 refused to participate; leaving 3031 subjects (96.5%) completed the survey. The 3031 completers and 109 non-completers were comparable in proportion of females (68.3 v. 61.5%, χ 2 = 2.278, P = 0.131), but not comparable in age (27.5 ± 6.8 v. 25.3 ± 10.0, t = 3.254, P = 0.001). Detailed socio-demographic and migration-related characteristics of the respondents are displayed in Table 1.
Table 1. Characteristics of subjects and prevalence rates of common mental health problems (CMHPs) by socio-demographic and migration-related factors
a ‘Others’ marital status included remarried, separated, cohabitating, divorced and widowed.
b Score of scale of perceived benefits of migration was dichotomised at the median value.
The mean score of GHQ-12 was (2.2 ± 2.5) in the whole sample. Totally 34.4% respondents had CMHPs, with 36.1% in men and 33.6 % in women.
Results of the univariate analysis (Table 1) show that significantly higher CMHPs prevalence rates were observed among migrant workers who were young, had a low level of educational attainment, had a marital status of ‘others’, reported poor living condition, had a low monthly income, were ill in the previous 2 weeks, migrated before adulthood, worked outside hometowns for less than 10 years, had worked in five cities or more, infrequently called family members, infrequently visited hometowns, migrated alone, reported poor Mandarin proficiency, had a low level of PBM, had engaged in five jobs or more and worked more than 8 h/day, compared with their corresponding counterparts.
Multivariate logistic regression analysis (Table 2) revealed that young age, low monthly income, poor living condition, physical illness in the past 2 weeks, having worked in many cities, infrequently visiting hometown, poor Mandarin proficiency, a low level of PBM and working more than 8 h/day were independently and positively associated with CMHPs. Taken together, these factors accounted for 27.6% of the variance in the prevalence of CMHPs among these subjects.
Table 2. Multivariable logistic regression results of risk factors for common mental health problems of migrant workers
Discussion
Main findings
The massive rural-to-urban migration has posed serious challenges to China's healthcare system, but its health services are still unprepared to cope with the needs of this large population (Mou et al. Reference Mou, Griffiths, Fong and Dawes2013; Zhong et al. Reference Zhong, Chiu and Conwell2016c), therefore understanding the mental health of its large migrant worker population is an essential component of a successful health strategy. The present study is one of the very few large-scale studies that examine the epidemiology of CMHPs in Chinese manufacturing factory migrant workers. We found that the prevalence of CMHPs in migrant workers was as high as 34.4%. Compared to studies using the GHQ-12, this prevalence is much higher than those found in other cohorts of Chinese general population, including the 21.7% prevalence in urban population (Yang et al. Reference Yang, Huang and Wu2003), the 15.2% prevalence in community residents (Yuan et al. Reference Yuan, Zhu, Li and Zhu2005), the 12.8% prevalence in workers of a state-owned enterprise (Liu & Zhu, Reference Liu and Zhu2011) and the 23.8% prevalence in older adults (Wang et al. Reference Wang, Li, Ungvari, Ng, Chiu, Kou, Liu, Tao, Wu, Fu, Qi, Yu and Xiang2016). The prevalence we found in migrant workers is similar to that reported among Latin American migrants of Australia (32.6%) (McDonald et al. Reference McDonald, Vechi, Bowman and Sanson-Fisher1996), among Romanian migrants of Spain (39.5%) (González-Castro & Ubillos, Reference González-Castro and Ubillos2011) and among rural-to-urban migrants of Peru (38.0%) (Loret et al. Reference Loret, Stanojevic, Ruiz, Gilman, Smeeth and Miranda2012). The higher prevalence in migrant workers than Chinese general population and comparable prevalence between migrant workers and international migrants in this study support the increased risk of CMHPs in Chinese migrant workers.
Our study further explored the associations between CMHPs and potential factors, especially migration-related factors, identified some risk factors that are unique to China's rural-to-urban migration context (i.e. infrequently visiting hometowns and low PBM) and replicated several findings from international migrant studies (i.e. the negative effect of poor language proficiency), thereby filling the gap between Chinese migrant worker and international migrant literature.
In our migrant worker sample, as shown in Table 1, nearly two-thirds had an educational attainment of junior high school or below, about 50% were unmarried, over 70% had a monthly income of 599 USD or lower (lower than 50% of the average monthly income of urban residents), approximately 80% worked more than 8 h/day and nearly 40% migrated alone. As a result, the majority of migrant workers had low socioeconomic status, often worked long hours and lacked social connections with their family members. Due to these disadvantages, it is not surprising to find a high CMHPs prevalence in our migrant worker sample.
In the general population, both old age and female sex are among the most common demographic risk factors for CMHPs (Wilhelm et al. Reference Wilhelm, Mitchell, Slade, Brownhill and Andrews2003; Ma et al. Reference Ma, Xiang, Cai, Li, Xiang, Guo, Hou, Li, Li, Tao, Dang, Wu, Deng, Wang, Lai and Ungvari2009; Drapeau et al. Reference Drapeau, Marchand and Beaulieu-Prévost2012), but we found a significant association between young age and CMHPs and no association between gender and CMHPs in the analysis. These findings are consistent with two previous international migrant studies (Furnham & Li, Reference Furnham and Li1993; Abbott et al. Reference Abbott, Wong, Williams, Au and Young1999). Perhaps there are particular pressures on young migrant workers arising from establishing new careers and adapting to the new environment, often without support of parents and the extended family. There is evidence that a low socioeconomic status is associated with poor mental health (Muntaner et al. Reference Muntaner, Eaton, Miech and O'Campo2004; Lund et al. Reference Lund, Breen, Flisher, Kakuma, Corrigall, Joska, Swartz and Patel2010); this is in accordance with our findings that migrant workers who had a low monthly income and poor living condition had higher prevalence of CMHPs. The significant association between recent 2-week physical morbidity and CMHPs is similar to two earlier studies (Silveira & Ebrahim, Reference Silveira and Ebrahim1998; Ortega et al. Reference Ortega, Feldman, Canino, Steinman and Alegría2006), which reported a strong link between poor mental health and physical illness in international migrants.
In the current study, infrequent visit of hometown was a risk factor for CMHPs. Because migrant workers are largely isolated from the mainstream of urban society (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015), family is the main available source of support for them when facing difficulties, though they work in remote cities. For migrant workers who infrequently visit hometown, their social support from family members might be inadequate to buffer against the negative effects of daily living stress and difficulties, thus a significant association between frequency of home visit and CMHPs was found in this study. Our study revealed that having worked in many cities was positively associated with CMHPs. As number of cities that migrant workers have worked in could be regarded as a measure of their mobility, this finding resembles the notion that high mobility is a risk factor for poor mental health of migrants (Ismayilova et al. Reference Ismayilova, Lee, Shaw, El-Bassel, Gilbert, Terlikbayeva and Rozental2014).
Similar to earlier findings in international migrants (Furnham & Li, Reference Furnham and Li1993), migrant workers with difficulties in Mandarin were more likely to have CMHPs in this study. China has many dialects, migrant workers from various parts of China speak different dialects. Owing to their low level of education, migrant workers often have difficulties in speaking fluent Mandarin and have to face many barriers such as problems in communication and making friends, which further increases the possibility of developing CMHPs.
The association between long working hours and CMHPs is consistent with the epidemiological evidence from a systematic review (Bannai & Tamakoshi, Reference Bannai and Tamakoshi2014), but such finding is seldom reported in international migrant literature, which is mainly attributed to different reasons of the two populations’ migration: migrant workers move for work while international migrants for permanent resettlement.
As shown above, although several negative aspects of migration work are harmful to the mental health, the positive aspects of migration work such as economic independence, improvement in economic conditions of migrant workers’ remote families and obtaining new social skills, could still increase migrant workers’ mental wellbeing, thereby reducing risk of CMHPs in migrant workers. Correspondingly, migrant workers who perceived inadequate benefits from migration work may be at higher risk of CMHPs, as suggested in the current study.
Limitations
Results of this study need to be interpreted with caution due to several limitations. First, our migrant worker sample was recruited from manufacturing factories of an affluent large city in southern China, migrant workers of other industries, i.e. service industry, and other cities were not included, potentially limiting the generalisability of our findings. Second, due to the cross-sectional and observational nature of our study, the causal relationships between CMHPs and identified risk factors need to be further verified in longitudinal studies. Third, because young migrant workers were at greater risk for CMHPs and the non-completers of this survey were significantly younger than completers, the present study may underestimate the true prevalence of CMHPs. Fourth, although we obtained a theoretically representative sample of factory migrant workers in Shenzhen by using multistage sampling, we were unable to provide specific data to prove the representativeness of our sample due to unavailable data on the demographic characteristics of the whole city's factory migrant workers. Due to the same reason, we have no data on sampling weights to adjust the prevalence estimate of CMHPs when necessary. Finally, some other risk factors of CMHPs in international migrants, such as discrimination, negative acculturation strategies and acculturative stress (Butler et al. Reference Butler, Warfa, Khatib and Bhui2015), were not measured in this study. More studies are warranted to determine the relationship between these factors and CMHPs in migrant workers.
Based on the same migrant worker sample, our previous study estimated the prevalence of DSM-IV major depression was only 1.4% (Zhong et al. Reference Zhong, Liu, Chan, Jin, Hu, Dai and Chiu2015), it is therefore very likely that quite a large number of detected CMHPs cases in the current study are subjects with sub-threshold mental disorders. However, accumulating evidence indicates that these subclinical psychiatric disorders are significantly associated with poor health-related quality of life, increased health services utilisation, high economic and disease burden, suicide risk and excess mortality (Rucci et al. Reference Rucci, Gherardi, Tansella, Piccinelli, Berardi, Bisoffi, Corsino and Pini2003; Balazs et al. Reference Balazs, Miklosi, Kereszteny, Hoven, Carli, Wasserman, Apter, Bobes, Brunner, Cosman, Cotter, Haring, Iosue, Kaess, Kahn, Keeley, Marusic, Postuvan, Resch, Saiz, Sisask, Snir, Tubiana, Varnik, Sarchiapone and Wasserman2013; Cuijpers et al. Reference Cuijpers, Koole, van Dijke, Roca, Li and Reynolds2014). Therefore, CMHPs of migrant workers still deserve greater attention from mental health professionals, social workers and health policymakers.
In summary, CMHPs are extremely prevalent among Chinese migrant workers, indicating the high mental health care needs of migrant workers. There is an urgent need for health authorities and health workers to address the epidemic of CMHPs in migrant workers. Amongst migrant workers, a range of risk factors, in particular migration-related factors, are associated with CMHPs. Efforts to promote the mental health of migrant workers may be useful to target on those who have worked in many cities, infrequently visit hometown, are unable to speak fluent Mandarin, have a low level of PBM and work long hours. Services for migrant workers (and for migrant workers of other industries) should include periodic evaluation of CMHPs, expanded social supports that specifically focus on improving mental wellbeing, and, when necessary, psychiatric assessment and treatment.
Acknowledgments
The authors thank all the research staff for their team collaboration work and all the migrant workers and factory owners/managers involved in this study for their cooperation and support.
Financial Support
This study was supported in part by Direct Grant 2041727 (S. Chan, PI) and 2041728 (H. Chiu, PI) from The Chinese University of Hong Kong; and by JCYJ20130401155103435 (T.B. Liu, PI) and JCYJ20130401155103442 (J. Dai, PI) from Shenzhen Science and Technology Innovation Committee. All the funding sources listed had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
Conflict of Interest
None.
Ethical Standard
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Availability of Data and Materials
All relevant data are available without any restriction. Requests for data can be sent to Dr. Bao-Liang Zhong at adam@cuhk.edu.hk.
