Skip to main content
PMC home page
International Journal of Environmental Research and Public Health logoLink to International Journal of Environmental Research and Public Health
. 2016 Mar 8;13(3):296. doi: 10.3390/ijerph13030296

The Risk Factors of Child Lead Poisoning in China: A Meta-Analysis

You Li 1, Jian Qin 1, Xiao Wei 1, Chunhong Li 1, Jian Wang 1, Meiyu Jiang 1, Xue Liang 1, Tianlong Xia 1, Zhiyong Zhang 1,*
Editor: Howard W Mielke1
PMCID: PMC4808959  PMID: 27005641

Abstract

Background: To investigate the risk factors of child lead poisoning in China. Methods: A document retrieval was performed using MeSH (Medical subject heading terms) and key words. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies, and the pooled odd ratios with a 95% confidence interval were used to identify the risk factors. We employed Review Manager 5.2 and Stata 10.0 to analyze the data. Heterogeneity was assessed by both the Chi-square and I2 tests, and publication bias was evaluated using a funnel plot and Egger’s test. Results: Thirty-four articles reporting 13,587 lead-poisoned children met the inclusion criteria. Unhealthy lifestyle and behaviors, environmental pollution around the home and potential for parents’ occupational exposure to lead were risk factors of child lead poisoning in the pooled analyses. Our assessments yielded no severe publication biases. Conclusions: Seventeen risk factors are associated with child lead poisoning, which can be used to identify high-risk children. Health education and promotion campaigns should be designed in order to minimize or prevent child lead poisoning in China.

Keywords: children, lead poisoning, risk factors, meta-analysis, China

1. Introduction

Lead has been impacting human health since the Romans began mining it over 2500 years ago [1]. Lead widely exists in the environment and can pollute the food chain, soil, water and air, leading to human diseases [2]. Lead exposure likely impairs motor function [3], and negatively impacts intellectual development, hemoglobin formation and childhood growth [4]. Many human activities such as home painting; smoking; using leaded petrol; eating foods contaminated with lead like popcorn, canned food and preserved eggs; drinking from leaded water pipes; smelting; and especially industry manufacturing processes are associated with lead exposure [5]. Children, who are still growing, are more likely to be sensitive to the harmful effects of lead [6]. The diagnostic criteria for child lead poisoning have been revised in some developed countries [7,8]. Currently, the Centers for Disease Control and Prevention in the U.S. recommend a reference level of five micrograms per deciliter to identify children with blood lead levels. However, we used the recommendation (10 μg/dL) in the light of included studies of our meta-analysis.

Though the number of child lead poisoning cases has decreased during recent decades in some countries [9,10], lead poisoning still remains an important public health issue for tens of millions of children in the world, especially in developing countries [11,12,13], including China.

Although numerous studies have identified the risk factors of child lead poisoning, inconsistency has been presented for different risk factors among various study populations. On account of the increasing importance of the identification of high-risk children, this meta-analysis was conducted with the objective of investigating the overall risk factors of child lead poisoning in China.

2. Methods

2.1. Literature Selection

Two reviewers independently identified relevant studies published in English and Chinese from January 1980 to October 2015 by searching the following electronic databases: PubMed, EMBASE, the Cochrane Library, Science Citation Index, Chinese biomedical literature database (CBM), Wangfang database, VIP database and China National Knowledge Infrastructure (CNKI). The following keywords were used: ((lead OR Pb or blood lead OR lead poisoning) AND (children) AND (risk factors OR influence factors) AND (China)). These studies were included in this meta-analysis if: (1) blood lead level was up to 100 μg/L (or more than 10 μg/dL or 4.83 μmol/L) for lead poisoning; (2) there were sufficient data to calculate the odds ratio (OR) and 95% confidence interval (CI); (3) the study followed a case-control or cohort design; (4) at least one risk factor was identified as being associated with lead poisoning; and (5) the full text was available. Studies were excluded if: (1) they did not comply with the requirements listed above; (2) did not study the relevant research population group or its studied populations had overlaps; (3) had incomplete information or abnormal data; or (4) were themselves reviews. The discrepancies were resolved by discussion.

2.2. Data Extraction

Data were extracted from each included study by two reviewers, separately. The following data were recorded: (1) name of the first author; (2) year of publication; (3) numbers in case and control groups; (4) name of journal; and (5) the study site. Additional information was extracted when required.

2.3. Quality Assessment

The Newcastle-Ottawa Scale (NOS) for case-control study was used to evaluate the quality of our studies [14]. The criteria included three categories: (1) selection (4 items); (2) comparability (1 item); and (3) exposure for case-control study (2 items). A study was awarded a maximum of one star for each item, with the exception of comparability for which two stars were given. Articles with more than seven stars were considered to be of a high quality; those with four to six stars were considered as moderate quality studies; and of a poor quality if they had fewer than four stars.

2.4. Statistical Analysis

The statistical analysis was conducted using Review Manager 5.2 (Cochrane Collaboration, Oxford, UK) and Stata version 10.0 (Stata Corporation, College Station, TX, USA). The results were reported as pooled odds ratios (ORs) and corresponding 95% confidence intervals (CI). A two-sided p < 0.05 was considered statistically significant. The heterogeneity of the included studies was evaluated using the Cochran’s Q test and the I2 test [15]. I2 is the proportion of total variation attributable to between-study heterogeneity as opposed to random error or chance, and I2 values of 25%, 50% and 75% are considered to indicate low, moderate, and high heterogeneity, respectively. Commonly, we selected a random-effects model to calculate corresponding parameters when the I2 value was more than 50%. Otherwise, a fixed-effects model was used. A funnel plot (Review Manager 5.2) and Egger’s test [16] (Stata 10.0) were used to assess publication bias—the statistical publication bias was set at p < 0.10. The funnel plot and Egger’s test were not used to analyze publication bias when less than 5 studies were available [17]. For these data, we checked the outlier studies and analyzed the reasons for the abnormal values.

3. Results

3.1. Identification of Selected Studies

A total of 1153 articles were obtained from the online databases. Five hundred and forty-nine studies were excluded because they were reviews, duplicates or irrelevant studies, and 604 studies were retained. However, 570 of them lacked the necessary data, a control group or normal data, so they were excluded. Eventually, 34 papers [18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51] were entered into the final meta-analysis, as shown in Figure 1. Of these, 12 articles earned eight stars, 15 others obtained seven stars, and the remaining seven papers were awarded six stars. Hence, the included studies were of a relatively high quality.

Figure 1.

Figure 1

Open in a new tab

Flow chart of study selection.

3.2. Study Characteristics

Thirty-four studies from January 1980 to October 2015 with 13,587 lead-poisoning cases were enrolled. The basic characteristics of these studies are summarized in Table 1.

Table 1.

Basic characteristics of the studies in this meta-analysis.

No. Year of Publication First Author Journal Total Lead-Poisoning Cases (n) Total Controls (n) Research Site
1 2001 Qi Ye Journal of Huaihai Medicine 9 91 Lianyungang
2 2003 Xizheng Ouyang Practical Preventive Medicine 301 823 Shaoyang
3 2003 Xinxin Chen Zhonghua Liu Xing Bing Xue Za Zhi 807 1455 Beijing
4 2004 Qingrong Zhang Maternal and Child Health Care of China 600 412 Guangzhou
5 2004 Sun Li Int. J. Hyg. Environ. Health 63 154 Zhejiang
6 2004 Hongzhong Zhang Huazhong University of Science and Technology 418 120 Zhuhai
7 2005 Xiping Ma Studiesof Trace Elements and Health 316 702 Pingdingshan
8 2005 Yan Yi Maternal and Child Health Care of China 69 61 Shiyan
9 2006 Xiaozhen Xiao Guangdong Trace Elements Science 41 161 Huizhou
10 2006 Hong Tian J. Appl. Clin. Pediatr. 459 596 Beijing
11 2006 Aifang Huang Zhejiang Prev. Med. 320 529 Yuhuan
12 2006 Bin He Practical Preventive Medicine 87 1085 Changsha
13 2006 Shuang Yang Dalian Medical University 30 143 Dalian
14 2006 Sulin Fu Anhui J. Prev. Med. 92 919 Hefei
15 2006 Xianxiang Feng Journal of Youjiang Medical College For Nationalities 764 1187 Liuzhou
16 2007 Jiazheng Xu China Tropical Medicine 274 1997 Haikou
17 2007 Shuwei Zhang China Tropical Medicine 523 1193 Jining
18 2007 Huiyan Liu Huazhong University of Science and Technology 83 1518 Wuhan
19 2008 Xiaohua Liu Journal of Zhengzhou University(Medical Sciences) 120 27 Xinxiang
20 2010 Shiqiong Wang Journal of Jianghan University (Natural Sciences) 96 197 Wuhan
21 2010 Ailan Gou Maternal and Child Health Care of China 158 158 Nanping
22 2011 Guiping Chang Journal of Yangtze University (Natural Science Edition) 42 415 Jingzhou
23 2011 Jie Shan Prev. Med. Trib. 233 3990 Weifang
24 2011 Meilin Peng Chinese Journal of Child Health Care 51 3343 Hefei
25 2011 Zangwen Tan Chin. J. Pediatr. 5295 64,673 China
26 2012 Xiulan Ma Chinese Journal of Healthy Birth & Child Care 153 1357 Lanzhou
27 2012 Jianghong Liu Paediatr Perinat Epidemiol 105 1239 Jintan
28 2013 Yinyun Long Journal of Chinese Physician 239 5612 Changde
29 2013 Xiaofeng Gao Maternal and Child Health Care of China 38 263 Tangshan
30 2014 Shengliang Sun Chin. Med. J. Metall. Indus. 101 101 Dalian
31 2014 Pi Guo PloS ONE 165 658 Shantou
32 2014 Zhenyan Gao Suzhou University 179 1849 Taizhou
33 2015 Zhong Chen Chinese Journal of Child Health Care 592 7590 Wuhan
34 2015 Ning Jin Chinese Journal of Modern Drug Application 764 236 Shanxi
Open in a new tab

3.3. Assessment of Heterogeneity

Heterogeneities were discovered in the distribution for the between-study variance of these factors: home painting; living near main roads; passive smoking; often eating foods containing lead; frequent consumption of dairy products; potential for father’s occupational exposure to lead; potential for mother’s occupational exposure to lead; sex; industry around the home; hand-to-mouth activity; living on the ground floor of a building; coal burning; daily intake of calcium, iron, and/or zinc supplements; mother’s educational level; father’s educational level; often not washing hands at key times; picky eating; and peeling walls in the living quarters. Therefore, we calculated the pooled OR values, using a random-effects model, and the results are listed in Table 2.

Table 2.

Results of heterogeneity test using random-effects and fixed-effects models.

Risk Factors Paper Number χ2 p I2 (%) Meta Analytical Model
Home painting 13 100.75 <0.00001 88 random
Living near main roads 12 77.72 <0.00001 86 random
Passive smoking 12 103.17 <0.00001 89 random
Often eating foods containing lead 22 581.00 <0.00001 96 random
Frequent consumption of dairy products 6 14.67 0.01 66 random
Daily intake of calcium, iron, and/or zinc supplements 4 5.23 0.16 43 fixed
Potential for father’s occupational exposure to lead 16 97.60 <0.0001 85 random
Potential for mother’s occupational exposure to lead 8 34.52 <0.0001 80 random
Mother’s educational level 11 12.95 0.23 23 fixed
Father’s educational level 7 10.21 0.12 41 fixed
Sex 21 42.70 0.002 53 random
Industry around the home 7 32.10 <0.0001 81 random
Hand-to-mouth activity 14 83.04 <0.00001 84 random
Often not washing hands at key times 10 15.91 0.07 43 fixed
Picky eating 7 7.52 0.28 20 fixed
Living on the ground floor 9 114.04 <0.00001 93 random
Coal burning 6 15.68 0.008 68 random
Peeling walls 3 3.79 0.15 47 fixed
Open in a new tab

3.4. Risk Factors

The review identified 30 risk factors associated with child lead poisoning from the 34 studies. The ORs, along with their 95%CIs, of the risk factors are presented in Table 3. Of these, 12 factors were examined in only one or two studies, and the remaining 18 factors were included in three or more studies. We were then able to estimate the pooled ORs for these 18 factors. The results of the pooled analysis are displayed in Table 3. The forest plots for the risk factors are shown in Figure S1.

Table 3.

Meta-analysis of the risk factors for child lead poisoning in China.

Risk Factors Number of Papers Total Lead-Poisoning Cases (n) Total Control Cases (n) OR (95% CI ) Z p
Home painting 13 2337 9963 0.12 (0.05, 0.19) 3.24 0.001
Living near main roads 12 2449 13,358 2.22 (1.53, 3.22) 4.22 <0.0001
Passive smoking 12 2209 7476 2.10 (1.38, 3.20) 3.46 0.0005
Often eating foods containing lead 22 10,320 90,875 2.99 (1.95, 4.59) 5.03 <0.00001
Frequent consumption of dairy products 6 6512 72,047 0.84 (0.69, 1.01) 1.88 0.06
Daily intake of calcium, iron, and/or zinc supplements 4 6083 74,212 0.80 (0.74, 0.86) 6.07 <0.00001
Potential for father’s occupational exposure to lead 16 2549 15,401 2.26 (1.62, 3.15) 4.81 <0.00001
Potential for mother’s occupational exposure to lead 8 1359 13,566 1.53 (1.04, 2.26) 2.15 0.03
Mother’s educational level 11 7273 76,429 0.66 (0.63, 0.70) 15.38 <0.00001
Father’s educational level 7 1538 9640 0.54 (0.46, 0.63) 7.84 <0.00001
Sex 21 5263 23,536 1.39 (1.24, 1.55) 5.66 <0.00001
Industry around the home 7 6203 70,253 1.67 (1.25, 2.22) 3.51 0.0005
Hand-to-mouth activity 14 7329 73,958 1.68 (1.29, 2.17) 3.91 <0.0001
Often not washing hands at key times 10 6480 74,330 1.22 (1.16, 1.29) 7.09 <0.00001
Picky eating 7 1601 4315 2.62 (2.15, 3.20) 9.49 <0.00001
Living on the ground floor 9 7658 82,256 1.58 (1.14, 2.18) 2.77 0.006
Coal burning 6 1705 10,597 1.45 (1.04, 2.02) 2.18 0.03
Peeling walls 3 5655 67,729 1.17 (1.09, 1.25) 4.55 <0.00001
Open in a new tab

3.5. Publication Bias

We conducted the Egger’s test and funnel plots to evaluate potential publication bias. The results of the Egger’s test (shown in Table 4) suggested that the publication biases among all of the risk factors were not statistically significant (p > 0.10).The visual inspection of the funnel plots (Figure S2)—narrow tops and wide bottoms—indicated no significant asymmetry. Hence, our investigation indicated no severe publication biases.

Table 4.

Publication bias of the risk factors for child lead poisoning in China.

Risk Factors Paper Number Egger’s Test (p-Value)
Home painting 13 0.199
Living near main roads 12 0.215
Passive smoking 12 0.109
Often eating foods containing lead 22 0.777
Frequent consumption of dairy products 6 0.755
Potential for father’s occupational exposure to lead 16 0.142
Potential for mother’s occupational exposure to lead 8 0.111
Mother’s educational level 11 0.135
Father’s educational level 7 0.335
Sex 21 0.834
Industry around the home 7 0.310
Hand-to-mouth activity 14 0.143
Often not washing hands at key times 10 0.152
Picky eating 7 0.229
Living on the ground floor 9 0.372
Coal burning 6 0.260
Open in a new tab

4. Discussion

This research makes an attempt to sum up the findings concerning the risk factors for child lead poisoning in China during the last three decades. Thirty-four studies eventually met the study criteria and were included into our meta-analysis. Some of these risk factors were among different studies. The pooled analysis from our findings confirmed that children faced a lower likelihood of experiencing lead poisoning if they live home painting, take daily supplements of calcium, iron and zinc, have a father or mother of a higher educational level. Factors such as living near main roads, passive smoking, often eating foods containing lead, potential for parents’ occupational exposure to lead, sex, industry around the home, hand-to-mouth activity, often not washing hands at key times, picky eating, living on the ground floor of a building, coal burning and peeling walls in the living quarters were associated with an increased likelihood of being lead poisoned. Our findings are in line with those of a previous study in China [52]. Lead poisoning not only has a negative effect on the development of children’s intelligence and behavior, but it also leads to anemia and can even cause death [53]. The risks of lead poisoning are multifactorial; therefore, future study is needed in order to explore on how the risk factors interact with each other.

4.1. Home Painting and Peeling Walls

Lead-based paint is a well-established cause of lead poisoning among children. The most common lead materials are paint and coating used in home decorations. In our study the OR of home painting was less than 1, which meant that home painting showed a beneficial effect on children’s health. This may be due to the fact that Xiulan Ma [43], Huiyan Liu [35] and MeilinPeng’s [40] articles had a higher percentage of home painting in the control group than the lead-poisoning group. Whether leaded paint was used or not was not mentioned in those articles, so we could not analyze the data for home painting separately. Consequently, the meta-analysis requires more studies to verify home painting as a risk factor. Meanwhile, peeling walls contain lead, e.g., in the paint and/or pigment; thus, children are more likely to contact lead under such circumstances. Consequently, peeling walls is one of the risk factors for child lead poisoning.

4.2. Living Near Main Roads

Previous studies have consistently documented that the residential location near main traffic roads is a vital variable in the effect of traffic-related air pollution on health [54,55]. Although leaded gasoline has been banned for use in China since 1 July 2000, a small amount of lead can still be found in crude leaded oil and so it is also in gasoline. Due to the widespread use of leaded gasoline before, the lead from automobile exhaust was deposited in water, soil and in different species [56], and finally absorbed by children. Therefore, automobile exhaust is an important lead pollution source, especially in heavy-traffic populated areas [57]. Our findings revealed that living near main roads is a risk factor for child lead poisoning. Due to living near main roads children have more opportunities to contact lead, in the air they breathe and at the same time in the polluted foods by automobile exhaust they eat. Additionally, living near main roads is not only related to the occurrence of lead poisoning but also to allergic diseases [58].

4.3. Passive Smoking

China is the largest producer and consumer of tobacco globally. According to the data, over 350 million smokers [59], 740 million passive smokers and 180 million children under the age of 15 live in China [60,61]. While cigarettes contain heavy metals such as cadmium and lead, second-hand smoking exposure can increase the level of lead in child blood. A recent study found that parental smoking at home is associated with an elevated level of lead in the blood [62]. Moreover, second-hand smoke can cause the respiratory diseases like chronic cough or asthma in children [63,64]. The present study revealed that the children with lead poisoning were exposed to more passive smoking compared with the control children.

4.4. Often Eating Foods Containing Lead

Our meta-analysis showed that eating foods containing lead often is a risk factor for child lead poisoning (OR=2.99, 95%CI: 1.95, 4.59). Among the foods containing lead were popcorn, preserved eggs, fried potato chips, spoiled traditional Chinese moon cakes, canned food and seafood. As traditional popcorn machines in China are made from lead alloy and high temperature can release lead vapors, the lead levels in Chinese traditionally-made popcorn can be elevated.

4.5. Potential for Parents’ Occupational Exposure to Lead

Childhood family members of workers engaged in a lead-related occupation are considered to be at additional risk of child lead poisoning. Such parents tend to pay little or no attention to carrying lead dust from the workplace to their household.

Our investigation suggested that the parents’ occupational exposure to lead is a risk factor for lead poisoning among children.

4.6. Mother’s or Father’s Educational Levels

Parental educational levels have a great effect on the healthy growth of children [65]. Maternal or paternal educational level, for example, can indirectly affect the children’s blood lead concentration. We found that a mother (OR = 0.66, 95%CI: 0.63, 0.70) or father (OR = 0.54, 95%CI: 0.46, 0.63) with an educational attainment level above a high school degree was a protective factor against child lead poisoning. The higher the mother’s and/or father’s educational level, the more attention they tend to the healthy growth of children; hence, the chance of the children of such parents to contact lead is relatively smaller, and the incidence them suffering lead poisoning is lower than that of their counterparts.

4.7. Sex

The pooled analysis of 21 studies indicated that boys were more likely to develop lead poisoning than girls, which was in agreement with the findings of the majority of the included papers. Nevertheless, we did not analyze various ages as a risk factor because there were differences in the age segmentations between the papers.

4.8. Industry Around the Home

The pollution of lead mainly comes from the environment and often involves industrial smelting, manufacturing and other related industrial and mining enterprises.

The lead dust sediments on the ground in the form of granules or suspends in the air with gel. A number of industries, including those dealing with battery manufacturing, metal smelting, printing, mechanical manufacturing and shipbuilding are found in China. Thus, it is possible for the lead dust to contaminate local residents. The data show that industry around the home is a risk factor that can give rise to child lead poisoning.

4.9. Hand-to-Mouth Activity, Often Not Washing Hands at Key Times

Our findings indicated that hand-to-mouth activity and often not washing hands at key times are risk factors that can lead to child lead poisoning among children. These behaviors not only influence one’s health but also increase the burdens of both the family and the nation [66]. For example, not handwashing with soap at key times not only increase diarrheal disease and acute respiratory infection [67,68,69], but it may also lead to chronic lead poisoning. What is more, the behaviors developed during childhood can affect one’s health during both youth and adulthood. Thus, it is important to help children establish healthy lifestyles and behaviors before the unhealthy ones are firmly developed.

4.10. Picky Eating, Daily Intake of Calcium Iron Zinc Supplements

Picky eating among children is a public health issue in China. During childhood, children are rapidly growing and need more nutrients. Therefore, their dietary habits are critical to their physical development. Picky eaters often consume a small amount of food and may be prone to deficiencies in trace elements more easily, potentially impacting their childhood growth [70,71,72]. Furthermore, deficiencies in trace elements like zinc, iron, calcium, copper and so on in the diet could increase the absorption of lead [73,74].Evidence from our study showed that picky eating is a risk factor, and that the daily intake of calcium, iron, and zinc supplements is a protective factor against child lead poisoning. Therefore, it is important for parents to instruct their children to have a healthy diet.

4.11. Living on the Ground Floor of a Building

Living on the ground floor may facilitate the contact with lead dust and smoke. Lead floating in the air and in the soil can enter the living quarters of lower floors with more ease than those living on higher floors, which leads to the children of such families having a higher rate of lead poisoning occurrence. Our meta-analysis showed that living on the ground floor is a risk factor for child lead poisoning.

4.12. Coal Burning

The use of solid fuels is a significant public health concern. With the rapid economic expansion and industrial growth, demand for energy is increasing in China. It relies on coal for about 70%–75% of its energy needs [75]. The smoke of burning coal contains polycyclic aromatic hydrocarbons, fine particles, sulfur dioxide, carbon monoxide, lead, and other harmful matter [76]. Coal burning can release lead and mercury and other heavy metals into the atmosphere [77,78,79]. Thus, in China, it has resulted in massive amounts of environmental pollution. Our results indicated that burning coal at home is a risk factor for child lead poisoning, so we should decrease the burning of coal at home in order to protect children’s health.

5. Conclusions

The evidence from this review indicates that 17 risk factors are associated with child lead poisoning in China, which can be used to identify high-risk children. Health education and promotion campaigns that aim to tackle challenges like correcting bad habits in children, paying attention to children’s personal hygiene and strengthening nutrition guidance should be designed and implemented in order to minimize or prevent the occurrence of lead poisoning among children in China.

Acknowledgments

This work was supported by the Guangxi science and technology development project (14124005-2-11).

Supplementary Materials

Click here for additional data file. (364KB, pdf)

The following are available online at www.mdpi.com/www.mdpi.com/1660-4601/13/3/296/s1, Figure S1: Forest plots for risk factors of children’s lead poisoning.(a)home painting; (b) living near main roads; (c) passive smoking; (d) often eating foods containing lead; (e) frequent consumption of dairy products; (f) daily taking calcium, iron, zinc supplements; (g) potential for father's occupational exposure to lead; (h) potential for mother's occupational exposure to lead; (i) mother's educational level; (j) father's educational level; (k) sex; (l) industry around the home; (m) hand-to-mouth activity; (n) no often washing hands at key times; (o) picky eating; (p) living on the ground floor; (q) coal burning; (r) peeling walls. Figure S2. Funnel plots of risk factors for children’s lead poisoning. (a) home painting—living near main roads; (b) passive smoking—often eating foods containing lead; (c) frequent consumption of dairy products—potential for father's occupational exposure to lead; (d) potential for mother's occupational exposure to lead—father's educational level; (e) mother's educational level—sex; (f) industry around the home—hand-to-mouth activity; (g) no often washing hands at key times—picky eating; (h) living on the ground floor—coal burning.

Author Contributions

You Li initiated the research topic. You Li, Jian Qin, Xiao Wei, Chunhong Li, Jian Wang, Meiyu Jiang, Xue Liang, Tianlong Xia, Zhiyong Zhang participated in the study design and the manuscript revision. All authors have approved the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  • 1.Warren C. Brush with Death: A Social History of Lead Poisoning. Johns Hopkins University Press; Baltimore, MD, USA: 2000. [Google Scholar]
  • 2.Witt K., Granert O., Daniels C., Volkmann J., Falk D., Van E. T., Deuschl G. Relation of lead trajectory and electrode position to neuropsychological outcomes of subthalamic neurostimulation in Parkinson’s disease: Results from a randomized trial. Brain. 2013;136:2109–2119. doi: 10.1093/brain/awt151. [DOI] [PubMed] [Google Scholar]
  • 3.Cecil K.M., Brubaker C.J., Adler C.M., Dietrich K.N., Altaye M., Egelhoff J.C., Wessel S., Elangovan I., Hornung R., Jarvis K., Lanphear B.P. Decreased brain volume in adults with childhood lead exposure. PLoS. Med. 2008;5:741–750. doi: 10.1371/journal.pmed.0050112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Xie X., Ding G.D., Cui C., Chen L.M., Gao Y., Zhou Y.J., Shi R., Tian Y. The effects of low-level prenatal lead exposure on birth outcomes. Environ. Pollut. 2013;175:30–34. doi: 10.1016/j.envpol.2012.12.013. [DOI] [PubMed] [Google Scholar]
  • 5.Tong S., von Schirnding Y.E., Prapamontol T. Environmental lead exposure: A public health problem of global dimensions. Bull. World Health Organ. 2000;78:1068–1077. [PMC free article] [PubMed] [Google Scholar]
  • 6.Hernberg S. Lead poisoning in a historical perspective. Am. J. Ind. Med. 2000;38:244–254. doi: 10.1002/1097-0274(200009)38:3&#x0003c;244::AID-AJIM3&#x0003e;3.0.CO;2-F. [DOI] [PubMed] [Google Scholar]
  • 7.Etchevers A., Glorennec P., le Strat Y., Lecoffre C., Bretin P., le Tertre A. Screening for elevated blood lead levels in children: Assessment of criteria and a proposal for new ones in France. Int. J. Environ. Res. Public Health. 2015;12:15366–15378. doi: 10.3390/ijerph121214989. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Lanphear B.P., Hornung R., Khoury J., Yolton K., Baghurst P., Bellinger D.C., Canfield R.L., Dietrich K.N., Bornschein R., Greene T., et al. Low-level environmental lead exposure and children’s intellectual function: An international pooled analysis. Environ. Health Perspect. 2005;113:894–899. doi: 10.1289/ehp.7688. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Stromberg U., Lundh T., Skerfving S. Yearly measurements of blood lead in Swedish children since 1978: The declining trend continues in the petrol-lead-free period 1995–2007. Environ. Res. 2008;107:332–335. doi: 10.1016/j.envres.2008.03.007. [DOI] [PubMed] [Google Scholar]
  • 10.Hruba F., Stromberg U., Cerna M., Chen C., Harari F., Harari R., Horvat M., Koppova K., Kos A., Krskova A., et al. Blood, cadmium, mercury, and lead in children: An international comparison of cities in six European countries, and China, Ecuador, and Morocco. Environ. Int. 2012;41:29–34. doi: 10.1016/j.envint.2011.12.001. [DOI] [PubMed] [Google Scholar]
  • 11.Huo X., Peng L., Xu X.J., Zheng L.K., Qiu B., Qi Z.L., Zhang B., Han D., Piao Z.X. Elevated blood lead levels of children in Guiyu, an electronic waste recycling town in China. Environ. Health Perspect. 2007;115:1113–1117. doi: 10.1289/ehp.9697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Li T., Dai Y.H., Xie X.H., Tan Z.W., Zhang S.M., Zhu Z.H. Surveillance of childhood blood lead levels in 11 cities of China. World J. Pediatr. 2014;10:29–37. doi: 10.1007/s12519-014-0452-6. [DOI] [PubMed] [Google Scholar]
  • 13.Cao J., Li M.M., Wang Y., Yu G.J., Yan C.H. Environmental lead exposure among preschool children in Shanghai, China: Blood lead levels and risk factors. PLoS ONE. 2014;9:296. doi: 10.1371/journal.pone.0113297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur. J. Epidemiol. 2010;25:603–605. doi: 10.1007/s10654-010-9491-z. [DOI] [PubMed] [Google Scholar]
  • 15.Higgins J.P., Thompson S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 2002;21:1539–1558. doi: 10.1002/sim.1186. [DOI] [PubMed] [Google Scholar]
  • 16.Egger M., Davey S.G., Schneider M., Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–634. doi: 10.1136/bmj.315.7109.629. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Sutton A.J., Duval S.J., Tweedie R.L., Abrams K.R., Jones D.R. Empirical assessment of effect of publication bias on meta-analyses. BMJ. 2000;320:1574–1577. doi: 10.1136/bmj.320.7249.1574. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Ye Q. Investigation and analysis of 1000 children’s blood lead level. J. Huaihai Med. 2001;19:485. (In Chinese) [Google Scholar]
  • 19.Chen X.X., Teng H.H., Wang F.Z., He J.P., Zhou S.Z., Jian Y.J., Xiao X., Liu G. Blood lead level and related risk factors among children aged 0–6 years in Beijing. Zhonghua Liu Xing Bing Xue Za Zhi. 2003;24:868–871. (In Chinese) [PubMed] [Google Scholar]
  • 20.Ouyang X.Z. Investigation of children’s lead poisoning in Shaoyang City. Pract. Prev. Med. 2003;10:760–761. (In Chinese) [Google Scholar]
  • 21.Zhang Q.R., Chen L.N., Zeng M.M., Lin L.Z., Xu S.F., Hong G.Z., Su B. Lead exposure and high-risk factors in children. Matern. Child Health Care China. 2004;19:34–36. (In Chinese) [Google Scholar]
  • 22.Sun L., Zhao Z.Y., Li L., Cheng H.Y. Preschool children’s lead levels in rural communities of Zhejiang province, China. Int. J. Hyg. Environ. Health. 2004;207:437–440. doi: 10.1078/1438-4639-00312. [DOI] [PubMed] [Google Scholar]
  • 23.Zhang H.Z. Master’s Thesis. Huazhong University of Science and Technology; Wuhan, China: May 1, 2004. Blood Lead Level and Influential Factors among Children Aged 0–5 Years in Zhuhai. [Google Scholar]
  • 24.Ma X.P., Guo J.Y. Investigation on 3–6 years old children’s blood lead in Pingdingshan city in Hennan province and analysis on the risk factor of lead poisoning. Stud. Tr. Elem. Health. 2005;22:35–36. (In Chinese) [Google Scholar]
  • 25.Yi Y. Analysis of 130 children’s blood lead level in Shiyan City. Matern. Child Health Care China. 2005;20:1386–1387. (In Chinese) [Google Scholar]
  • 26.Tian H., Qi K.M. Analysis of risk factors for lead poisoning in children. J. Appl. Clin. Pediatr. 2006;21:1221–1222. (In Chinese) [Google Scholar]
  • 27.Xiao X.Z. Investigation on blood lead level of 202 children aged 0~3 and its effecting factor. Guangdong Trace Elem. Sci. 2006;13:42–45. (In Chinese) [Google Scholar]
  • 28.Huang A.F. Analysis of blood lead level and related factors of 849 children. Zhejiang Prev. Med. 2006;18:39–42. (In Chinese) [Google Scholar]
  • 29.He B., Xiong C.D. The preliminary analysis of relations between lead poisoning and the family environment of children aged 0~6 years in the urban area of Changsha City. Pract. Prev. Med. 2006;13:1254–1256. (In Chinese) [Google Scholar]
  • 30.Fu S.L., Zhu M., Zhuang Z.M. Investigation on blood lead levels of children in Hefei. Anhui J. Prev. Med. 2006;12:294–296. (In Chinese) [Google Scholar]
  • 31.Feng X.X., Yu D.Y., Cui X.L. Investigation on blood lead level and its affected factors from Liuzhou school students aged 6~19 years old. J. Youjiang Med. Coll. Natl. 2006;6:935–937. (In Chinese) [Google Scholar]
  • 32.Yang S. The investigation on blood lead level of children in Dalian and analysis of influential factors. Dalian Med. Univ. 2015;2:159. [Google Scholar]
  • 33.Xu J.Z. Analysis of level of blood lead in children of Haikou City and relevant factors. China Trop. Med. 2007;7:1246–1247. (In Chinese) [Google Scholar]
  • 34.Zhang S.W. Survey of blood lead level in 3–7-year-old children in Jining City and influential factors. China Trop. Med. 2007;7:280–281. (In Chinese) [Google Scholar]
  • 35.Liu H.Y. Master’s Thesis. Huazhong University of Science and Technology; Wuhan, China: May 10, 2007. Study on Blood Lead Level and Influencing Factors of Preschool Children in Wuhan. [Google Scholar]
  • 36.Liu X.H., Chen P.P., Li N., Li W.J. Detection of blood lead level of preschool children in urban areas of Xinxiang city and analysis of its related factor. J. Zhengzhou Univ. (Med. Sci.) 2008;43:796–798. (In Chinese) [Google Scholar]
  • 37.Gou A.L. Study of the influence factors about lead poisoning in 158 children. Matern. Child Health Care China. 2010;25:1059–1060. (In Chinese) [Google Scholar]
  • 38.Wang S.Q. Analysis of children’s lead poisoning and living environment factors. J. Jianghan Univ. (Nat. Sci.) 2010;38:81–82. (In Chinese) [Google Scholar]
  • 39.Shan J., Zhang Y.M., Zhu J.X., Zhang J., Zhang H., Lu X.L. Survey on blood lead level among children aged 0~14 in Weifang City, 2010. Prev. Med. Trib. 2011;17:791–792. (In Chinese) [Google Scholar]
  • 40.Peng M.L., Su P.Y., Ding J.L., Xu X.R. Blood lead levels and the related risk factors among children between 2008 and 2009 in Hefei city. Chin. J. Child Health Care. 2011;19:740–742. (In Chinese) [Google Scholar]
  • 41.Tan Z.W., Xie X.H., Zhang S.M., Fan Z.Y., Jia N. Blood lead status and influencing factors among preschool children in urban areas of China. Chin. J. Pediatr. 2011;49:294–300. (In Chinese) [PubMed] [Google Scholar]
  • 42.Chang G.P. Analysis of blood lead levels of preschool children in Jingzhou city. J. Yangtze Univ. (Nat. Sci. Ed.) 2011;8:199–200. (In Chinese) [Google Scholar]
  • 43.Ma X.L., Chen X.Z., He L., Zhu Y., Yue L., Yue X., Chao L.L. Level and risk factors of blood level in children of Lanzhou. Chin. J. Healthy Birth Child Care. 2012;18:359–361. (In Chinese) [Google Scholar]
  • 44.Liu J.H., Ai Y.X., McCauley L., Pinto-Martin J., Yan C.H., Shen X.M., Needleman H. Blood lead levels and associated sociodemographic factors among preschool children in the South Eastern region of China. Paediatr. Perinat. Epidemiol. 2012;26:61–69. doi: 10.1111/j.1365-3016.2011.01234.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Long Y.Y., Gong Z.F. Investigation of blood lead levels of 5851 children aged 0–12 years in Changde City. J. Chin. Physician. 2013;15:717–718. (In Chinese) [Google Scholar]
  • 46.Gao X.F. Study on blood lead level and its influence factors of 301 children aged 3~6 years in Tangshan City. Matern. Child Health Care China. 2013;28:5635–5636. (In Chinese) [Google Scholar]
  • 47.Gao Z.Y. Master’s Thesis. Suzhou University; Suzhou, China: May 12, 2014. The Related Reasons of Childhood Lead Poisoning and Its Health Education. [Google Scholar]
  • 48.Sun S.L. The influence factors analysis of 101 children of lead poisoning in Shahekoudistrict of Dalian city. Chin. Med. J. Metall. Indus. 2014;31:195. (In Chinese) [Google Scholar]
  • 49.Guo P., Xu X.J., Huang B.L., Sun D., Zhang J., Chen X.J., Zhang Q., Huo X., Hao Y.T. Blood lead levels and associated factors among children in Guiyu of China: A population-based study. PLoS ONE. 2014;9:296. doi: 10.1371/journal.pone.0105470. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Chen Z., Qin L.Z., Xiong C., Zhang Y.Q., Qiu L., Du Y.K. Risk factor analysis of children lead poisoning food. Chin. J. Child Health Care. 2015;23:660–663. [Google Scholar]
  • 51.Jin N. Detection and analysis of 1000 children’s blood lead levels in Shanxi Province. Chin. J. Mod. Drug Appl. 2015;9:275–276. (In Chinese) [Google Scholar]
  • 52.Wang L., Li Z., Huang S.X., DU C., Wang H., He L.P., Bi Y.Y., Shi Y., Wang C.H. A systematic assessment of blood lead level in children and associated risk factors in China. Biomed. Environ. Sci. 2015;28:616–619. doi: 10.3967/bes2015.086. [DOI] [PubMed] [Google Scholar]
  • 53.Luo W.J., Ruan D.Y., Yan C.H., Yin S.T., Chen J.Y. Effects of chronic lead exposure on functions of nervous system in Chinese children and developmental rats. Neuro. Toxicol. 2012;33:862–871. doi: 10.1016/j.neuro.2012.03.008. [DOI] [PubMed] [Google Scholar]
  • 54.Karner A.A., Eisinger D.S., Niemeier D.A. Near-roadway air quality: Synthesizing the findings from real-world data. Environ. Sci. Technol. 2010;44:5334–5344. doi: 10.1021/es100008x. [DOI] [PubMed] [Google Scholar]
  • 55.Barzyk T.M., George B.J., Vette A.F., Williams R.W., Croghan C.W., Stevens C.D. Development of a distance-to-roadway proximity metric to compare near-road pollutant levels to a central site monitor. Atmos. Environ. 2009;43:787–797. doi: 10.1016/j.atmosenv.2008.11.002. [DOI] [Google Scholar]
  • 56.Jankowski K., Ciepiela A.G., Jankowska J., Szulc W., Kolczarek R., Sosnowski J., Wiśniewska-Kadżajan B., Malinowska E., Radzka E., Czeluściński W., Deska J. Content of lead and cadmium in aboveground plant organs of grasses growing on the areas adjacent to a route of big traffic. Environ. Sci. Pollut. Res. 2015;22:978–987. doi: 10.1007/s11356-014-3634-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Lin Y., Fang F., Wang F., Xu M. Pollution distribution and health risk assessment of heavy metals in indoor dust in Anhui rural, China. Environ. Monit. Assess. 2015;187:565. doi: 10.1007/s10661-015-4763-4. [DOI] [PubMed] [Google Scholar]
  • 58.Jung D.Y., Leem J.H., Kim H.C., Kim J.H., Hwang S.S., Lee J.Y., Kim B.J., Hong Y.C., Hong S.J., Kwon H.J. Effect of traffic-related air pollution on allergic disease: Results of the children’s health and environmental research. Allergy Asthma Immunol. Res. 2015;7:359–366. doi: 10.4168/aair.2015.7.4.359. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Ma X.H., Xu Z.H. Smokers has exceeded 350 million and disease burden exceeds more than 200 billion yuan in China. Med. Soc. 2015;28:22. (In Chinese) [Google Scholar]
  • 60.Hsia J., Yang G.H., Li Q., Xiao L., Yang Y., Wu Y.W., Asma S. Methodology of the global adult tobacco survey in China, 2010. Biomed. Environ. Sci. 2010;23:445–450. doi: 10.1016/S0895-3988(11)60005-6. [DOI] [PubMed] [Google Scholar]
  • 61.Liu Y., Chen L. New medical data and leadership on tobacco control in China. Lancet. 2011;377:1218–1220. doi: 10.1016/S0140-6736(10)61391-8. [DOI] [PubMed] [Google Scholar]
  • 62.Friedman L.S., Lukyanova O.M., Kundiev Y.I., Shkiryak-Nizhnyk Z.A., Chislovska N.V., Mucha A., Zvinchuk A.V., Oliynyk I., Hryhorczuk D. Predictors of elevated blood lead levels among 3-year old Ukrainian children: A nested case-control study. Environ. Res. 2005;99:235–242. doi: 10.1016/j.envres.2004.12.006. [DOI] [PubMed] [Google Scholar]
  • 63.Cheraghi M., Salvi S. Environmental tobacco smoke (ETS) and respiratory health in children. Eur. J. Pediatr. 2009;168:897–905. doi: 10.1007/s00431-009-0967-3. [DOI] [PubMed] [Google Scholar]
  • 64.Tsai C.H., Huang J.H., Hwang B.F., Lee Y.L. Household environmental tobacco smoke and risks of asthma, wheeze and bronchitic symptoms among children in Taiwan. Respir. Res. 2010;11:11. doi: 10.1186/1465-9921-11-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Fernald L.C., Weber A., Galasso E., Ratsifandrihamanana L. Socioeconomic gradients and child development in a very low income population: Evidence from Madagascar. Dev. Sci. 2011;14:832–847. doi: 10.1111/j.1467-7687.2010.01032.x. [DOI] [PubMed] [Google Scholar]
  • 66.Khuwaja A.K., Khawaja S., Motwani K., Khoja A.A., Azam I.S., Fatmi Z., Ali B.S., Kadir M.M. Preventable lifestyle risk factors for non-communicable diseases in the Pakistan adolescent schools study 1 (PASS-1) J. Prev. Med. Public Health. 2011;44:210–217. doi: 10.3961/jpmph.2011.44.5.210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Curtis V., Cairncross S. Effect of washing hands with soap on diarrhoea risk in the community: A systematic review. Lancet Infect. Dis. 2003;3:275–281. doi: 10.1016/S1473-3099(03)00606-6. [DOI] [PubMed] [Google Scholar]
  • 68.Rabie T., Curtis V. Hand washing and risk of respiratory infections: A quantitative systematic review. Trop. Med. Int. Health. 2006;11:258–267. doi: 10.1111/j.1365-3156.2006.01568.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Aiello A.E., Coulborn R.M., Perez V., Larson E.L. Effect of hand hygiene on infectious disease risk in the community setting: A meta-analysis. Am. J. Public Health. 2008;98:1372–1381. doi: 10.2105/AJPH.2007.124610. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Goncalves J.A., Moreira E.A., Trindade E.B., Fiates G.M. Eating disorders in childhood and adolescence. Rev. Paul.Pediatr. 2013;31:96–103. doi: 10.1590/s0103-05822013000100016. [DOI] [PubMed] [Google Scholar]
  • 71.Li Y., Shi A., Wan Y., Hotta M., Ushijima H. Child behavior problems: prevalence and correlates in rural minority areas of China. Pediatr. Int. 2001;43:651–661. doi: 10.1046/j.1442-200X.2001.01446.x. [DOI] [PubMed] [Google Scholar]
  • 72.Steyn N.P., Nel J.H., Nantel G., Kennedy G., Labadarios D. Food variety and dietary diversity scores in children: Are they good indicators of dietary adequacy? Public Health Nutr. 2006;9:644–650. doi: 10.1079/PHN2005912. [DOI] [PubMed] [Google Scholar]
  • 73.Manser W.W. Lead: A review of the recent literature. J. Pak. Med. Assoc. 1989;39:296–302. [PubMed] [Google Scholar]
  • 74.Lacasana M., Romieu I., Sanin L.H., Palazuelos E., Hernandez-Avila M. Blood lead levels and calcium intake in Mexico City children under five years of age. Int. J. Environ. Health Res. 2000;10:331–340. doi: 10.1080/0960312002001537. [DOI] [PubMed] [Google Scholar]
  • 75.Zhang M.Q., Zhu Y.C., Deng R.W. Evaluation of mercury emissions to the atmosphere from coal combustion, China. Ambio. 2002;31:482–484. doi: 10.1579/0044-7447-31.6.482. [DOI] [PubMed] [Google Scholar]
  • 76.Karr C.J. Adding fuel to the fire: Increasing evidence for developmental toxicity of indoor solid fuel combustion. Arch. Pediatr. Adolesc. Med. 2011;165:565–566. doi: 10.1001/archpediatrics.2011.6. [DOI] [PubMed] [Google Scholar]
  • 77.Guo R.X., Yang J.L., Liu D.Y., Liu Z.Y. Transformation behavior of trace elements during coal pyrolysis. Fuel Process. Technol. 2002;77–78:137–143. doi: 10.1016/S0378-3820(02)00041-3. [DOI] [Google Scholar]
  • 78.Wang D., He L., Wei S., Feng X. Estimation of mercury emission from different sources to atmosphere in Chongqing, China. Sci. Total Environ. 2006;366:722–728. doi: 10.1016/j.scitotenv.2005.09.054. [DOI] [PubMed] [Google Scholar]
  • 79.Zhang J., Han C.L., Xu Y.Q. The release of the hazardous elements from coal in the initial stage of combustion process. Fuel Process. Technol. 2003;84:121–133. doi: 10.1016/S0378-3820(03)00049-3. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Click here for additional data file. (364KB, pdf)

Articles from International Journal of Environmental Research and Public Health are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)

RESOURCES