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BY 4.0 license Open Access Published by De Gruyter February 4, 2021

Blood lead level in school going children of Jodhpur, Rajasthan, India

Shailja Sharma ORCID logo, Prasenjit Mitra ORCID logo, Pankaj Bhardwaj and Praveen Sharma



Lead exposure in children contributes to 600,000 new cases of intellectual disabilities every year with maximum occurrence in developing countries. Currently limited information is available on the blood lead level (BLL) in children of India. The aim was to estimate BLL in the school going children of local population of Jodhpur.


Four hundred twenty-six primary school children of government and private schools participated in this cross sectional study. Information regarding possible lead exposure was collected. BLL was estimated on Lead Care II analyser (Magellan Diagnostics, USA).


The mean and median BLL were 4.25 ± 1.75 μg/dL (<3.3–22.6 μg/dL) and 3.5 μg/dL (Inter Quartile Range 0.9). BLL was higher in children of illiterate mothers, those residing near traffic dense areas, urban region and studying in government schools of urban region.


BLL in children residing in Jodhpur is much higher in comparison to western counterparts. Screening and awareness programs regarding potential sources of lead exposure can help in improving BLL.


Lead (Pb) is a highly toxic heavy metal occurring naturally in the Earth’s crust. Due to its environmental persistence, transportability and non-biodegradable nature, it has the potential to cause many deleterious systematic effects [1]. Globally approximately 815 million children are estimated to have blood lead level (BLL) > 5 μg/dL and out of those, nearly 50% children are residing in Southeast Asia. This analysis was undertaken using the Global Burden of Disease dataset for 2019 and includes all countries [2]. In 2017 alone, Pb exposure in India resulted in over 230,000 premature deaths, amounting to a cumulative loss of over 5.2 million years of life. Long-term disability from Pb exposure resulted in the loss of an additional 7 million years of healthy life. Troublingly, these numbers represent an increase of 53 and 30% in death and disability respectively since the 1996–2000 phase out of leaded gasoline [3].

Potential Pb exposure occurs from various human activities such as mining, manufacturing, burning fossil fuels, drinking water where Pb pipes are used, old leaded paint, pigments, glazed pottery, some healthcare products and folk remedies [4], [5], [6], [7]. A larger percentage of Pb is absorbed and retained by children because of their behaviour and developing organ systems resulting in disproportionately higher side effects at lower levels of exposure than adults [6]. Lead affects all organ systems and eventually majorly deposits in bones [6]. BLL >5 μg/dL were associated with lower intelligence quotient and even lower BLL has been reported to be associated with poor academic performance and attention-related problems [6].

The George Foundation under the “Project Pb Free” in late nineties assessed BLL of 22,000 children from seven major cities of India and concluded that 51% of children up to 12 years, had blood Pb level (BLL) more than 10 μg/dL [8]. A recent meta analysis reported pooled arithmetic mean for BLL in Indian children to be 6.86 μg/dL (95% CI: 4.38–9.35). This analysis did not have any representation from Rajasthan state [9].

According to World Health Organisation, BLL of any concentration is not considered safe and level as low as 5 μg/dL, may be related to diminished intelligence in children, behavioural and learning problems [10]. It is reported that increased Pb exposure is associated with increased severity of symptoms and effects [10]. Evidence from a number of scientific studies corroborated that even low BLL can cause lifelong health-related side effects [6], [11], [12]. Children exposed to lead after being followed for 30 years, reported difficult personality traits in their adulthood and greater psychiatric and behavioural consequences in adult life [13]. Eventually BLL of concern from 10 μg/dL was reduced to 5 μg/dL by Centre for Disease Control and prevention (CDC) [5]. Lead pollution is widely prevalent in India [10] and contributes towards behavioural deficits with lower functional skills during childhood and later in life [13], [14]. Leaded gasoline was one of the major source of Pb in environment globally which was phased out in early 2001 from India [15]. Alleviation of an important source of Pb exposure warrants examination and re-evaluation of the prevalence of childhood Pb poisoning. Regional data regarding BLL in population of Rajasthan is scant [16] with none so far documenting BLL in children of this region. Jodhpur houses more than two thousand small Pb-based industries like handicrafts, tie and dye printing, steel products manufacturing and textile industries [17]. We aimed at estimating BLL in the 5–12 year old school going children. The present study was designed to determine BLL and associated risk factors among the children of Jodhpur following the introduction of unleaded petrol.

Materials and methods

The study was approved by the institutional ethics committee and ethical clearance was obtained (letter no. AIIMS/IEC/2014/330 dated 15/09/2014). This was a cross sectional study conducted between Oct 2015 and Dec 2017. A list of all the private and government schools was procured from the office of District Education Officer (DEO). From this list, seven private and seven government schools were selected randomly. From each school 30 students were recruited randomly. The figure of 30 was finalized considering the less enrolment of students in most of the government schools located in the peripheral areas of Jodhpur.

Total five hundred primary school children (5–12 years) were selected randomly. The method ensured better representation of different socio-demographic profile of the Jodhpur city. Written informed consent was sought from parents/guardians. Four hundred twenty-six parents/guardians consented for the study. Consenting parents/guardians were required to complete a questionnaire. The questionnaire entailed the personal details, educational status of parents, complaints suggestive of Pb toxicity like fatigue, loss of appetite, stomach ache, poor academic performance, behavioural problems, dietary habits, history of pica. Special note on the place of dwelling, proximity of home to highway/traffic density etc. were noted.

Sample collection

Blood sample was collected in the school in the designated clean area to minimize contamination, after collecting the informed consent sheet and questionnaire. The skin at the site of the blood draw was thoroughly washed to remove any external traces of Pb to minimize potential external contamination of blood sample. About 3 mL blood was collected by trained phlebotomist in EDTA vacutainer (BD, USA) after cleaning the venipuncture site with alcohol swab. The samples were kept in coolers with ice packs while sampling and transported to departmental laboratory.

Measurement of BLL

Blood lead level was measured with Lead Care II (Magellan Diagnostics, Inc. 101 Billerica Ave, Building 4 N. Billerica, Massachusetts 01862-1271 USA) blood Pb analyzer at our institute within the same day or maximum within 24 h of sample collection. This device estimates Pb between 3.3 and 65 μg/dL and is based on the principle of anodic stripping voltammetry. The reliability and validity of Lead Care II has been well established and it is used worldwide for blood lead screening [18], [19].The device was calibrated for each 48-batch run and quality controls were run with every 20 samples, every new batch, and kit lot. The quality control values for level 1 were 6.3 ± 3 μg/dL and level 2 were 26.5 ± 4.6 μg/dL. Any value below the detection limit of 3.3 μg/dL was allocated a value of 1.65 μg/dL (midpoint between 0 and 3.3 μg/dL) for statistical analysis. Any sample with BLL ≥5 μg/dL was repeated to verify and the average value was taken as final value.

Statistical analysis

Data was analysed using SPSS version 21(IBM) and Graphpad prism version 8.0 software. Shapiro Wilk’s test was used to check for normal distribution of data. The values were expressed as mean ± SD and median interquartile range (IQR). Mann–Whitney and Kruskal–Wallis test were applied to assess the statistical significance of various variables in predicting BLL. Chi square test was done to see association of increased BLL with various contributing factors. Logistic Regression analysis was done to study the effect of various independent variables on BLLs. p<0.05 was considered significant.


The study was conducted on 426 school going children. Out of these, 277 (65%) were boys 149 (35%) were girls. The mean age of children was 9 years (5–12 years). Their mean BLL was 4.25 ± 1.75 μg/dL (<3.3–22.6 μg/dL) with median 3.5 μg/dL (IQR 0.9). The mean BLL in boys was 4.21 ± 1.42 μg/dL (<3.3–22.6 μg/dL) with median 3.5 μg/dL (IQR 0.82) and in girls 3.7 ± 1.22 μg/dL (<3.3–10.5 μg/dL) with median 3.5 μg/dL (IQR 0.97). Out of the total, 61.7% (n=253) children had BLL <3.5 μg/dL, 19.5%(n=81) had 3.5–<5 μg/dL, 17.37% (n=74) had 5–<10 μg/dL, 0.94% (n=4) had 10–<15 μg/dL and 0.47% (n=1) had BLL >15 μg/dL. Therefore 18.87% (n=80) of children crossed the CDC intervention level of 5 μg/dL (Figure 1).

Figure 1: 
Blood lead level in children.
BLL estimated in 5–12 years old children (n=426) with lead Care II analyser (Magellan Diagnostics, USA).

Figure 1:

Blood lead level in children.

BLL estimated in 5–12 years old children (n=426) with lead Care II analyser (Magellan Diagnostics, USA).

Median BLL is mentioned across the variables of interest as shown in Table 1. There was significant difference between the median BLL in children in context of educational status of their mothers (3.5 μg/dL [IQR 0.4] vs. 3.7 μg/dL [IQR 1.85], p=0.0001*).

Table 1:

Factors associated with BLL in school children.

Characteristics Number % BLL, µg/dL

Median (IQR)
 Boys 277 65 3.5 (0.82) 0.65
 Girls 149 35 3.5 (0.97)
Highway/Traffic near residence
 <1 km 136 31.9 4.4 (0.15) 0.0001*
 >1 km 290 68.1 3.5 (2.35)
Mother’s education status
 Illiterate 49 11.5 3.7 (1.85) 0.0001*
 Primary 59 13.8 3.8 (1.4)
 Secondary 84 19.7 3.5 (2.2)
 Graduate and above 234 54.9 3.5 (0.4)
 Urban 293 66.7 3.95 (1.3) 0.01*
 Peri urban 133 33.3 3.5 (0.2)
School (urban region)
 Government 79 26.1 4.9 (2.45) 0.0001*
 Private 214 73.9 3.5 (0.22)

  1. BLL, blood lead level, *p value <0.05 considered significant.

The children in urban region had significantly higher BLL in comparison to periurban inhabitants (3.95 μg/dL [IQR 1.3] vs. 3.5 μg/dL [0.2], p=0.01*). It was observed that higher percentage of urban region children had BLL >5 μg/dL (22.2%, n=65) in comparison to periurban inhabitants (9.02%, n=12). Out of 293 children of urban locality, government school children had significantly higher BLL in comparison to those attending private schools (4.9 μg/dL [IQR 2.45] vs. 3.5 μg/dL [IQR 0.22], p=0.0001*).

Factors contributing towards increased BLL in urban region children were explored. It was seen that significantly higher percentage of children going to urban government schools were residing in old housing and using cosmetics like surma/kohl, folk medicines, potable water without any purification system (Table 2). Logistic regression was used to study the effect of various independent variables on BLL. Mother’s education status (p=0.007) and the highway/traffic near residence (p<0.001) were found to be significantly associated with BLL (Table 3).

Table 2:

Determinants for BLL >5 μg/dL in urban school children (n=293).

Determinants Govt. (n=79) Private (n=214) p-Value
No water purifier 51 (64.5%) 14 (6.5%) <0.00001
Old housing 39 (49.3%) 19 (8.8%) <0.00001
Cosmetics (surma/kohl) 26 (32.9%) 17 (7.9%) <0.00001
Herbal medicine use 15 (18.9%) 21 (9.8%) 0.0337

  1. BLL, blood lead level, p<0.05 considered significant.

Table 3:

Determinants of BLL (logistic regression).

Variables p-Value OR (95%CI) p-Value AOR (95%CI)
Mother’s education Graduate and above <0.001 4.02 (2.09–7.73) 0.007 5.84 (1.63–21.00)
Secondary 0.023 2.31 (1.12–4.76) 0.058 2.26 (0.97–5.23)
Primary 0.214 1.69 (0.74–3.86) 0.135 2.06 (0.80–5.30)
Illiterate   1   1
School Private. 0.008 1.98 (1.20–3.28) 0.908 1.07 (0.34–3.33)
Traffic Traffic (>1 km) <0.001 7.59 (4.42–13.04) <0.001 9.42 (5.20–17.07)
Traffic (<1 km)
Gender Female 0.278 1.34 (0.79–2.29) 0.291 1.39 (0.75–2.57)

  1. BLL, blood lead level, p<0.05 considered significant; OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval.


Lead has a wide range of industrial use and human exposure results in well recognized adverse health effects [4]. In late nineties more than 50% children in India had BLL >10 μg/dL [8]. Previously BLL up to 10 μg/dL was acceptable which was further brought down to 5 µg/dL [5]. Evidence suggests that BLL ≥5 μg/dL is associated with irreversible neurologic damage and behavioural problems [13], [14], [20]. Currently CDC statement considers no BLL to be safe for children [5]. The median BLL 3.5 μg/dL (IQR 0.9) observed in the present study is lower than mean BLL of children from other parts of India [9]. Invariably 18.8% of children crossed the CDC intervention level of 5 μg/dL in the present study. Children residing in areas rich in traffic density or closer to highway had significantly higher BLL(Tables 1 and 3). Similar findings have been supported by others also [21]. It has been reported that soil, water, and air around highways and traffic dense area have significantly higher Pb content [22], [23] with major contribution from vehicular emission which is responsible for more than 90 percent of all atmospheric emission and roadside soil Pb content [24]. Roadside soil Pb and traffic density of the road were also found to be linked [25], [26]. Seasonal variation of Pb in soil has been found to be associated with BLL variation. Zahran et al. [27] have hypothesized that Pb in soil enters blood through inhalation of contaminated air dust. In other words, having residence near highway or traffic dense area can be a risk factor for increased BLL [28]. The urban subset of children had significantly higher BLL in comparison to periurban school children as reported earlier [29]. 24.2% children going to government schools and 12.04% to private schools in urban locality had BLL >5 μg/dL. There are reports of elevated BLL in developing countries in urban areas where exposure to industrial paint sources and fossil-fuel burning are relatively high [30], [31], [32]. Socioeconomic conditions reflect BLL [30]. Jain et al. [32] reported that standard of living correlated with a 32.3% increase in BLLs (p=0.02). We did not directly estimate socioeconomic status (SES) index but it was observed that parents of the urban government school students majorly belonged to lower socioeconomic status as depicted by their occupation which can be an indirect indicator of SES. Poor nutrition of children belonging to low SES may also increase their susceptibility to the Pb-related health effects [21]. Few studies have focussed on rural children, and have found lower Pb exposure or lower BLL in rural vs. urban population [29], [33].

BLL was significantly higher in children of illiterate mothers when compared to graduate mothers (Table 1). In Indian education system, being graduate entails 15 years of formal education. Mother’s illiteracy was predictor of BLL (Table 3). Education brings awareness to the parent about different sources of Pb exposure and subsequently its influence on children’s health. Hence dearth in education would generally result in lack of any preventive measures at individual level.

Older housing is potentially linked with exposure to not only leaded paints but also Pb piping, a known risk factor for high BLL [34]. Around 76% children in urban region were residing in old houses with metallic plumbing in comparison to children of periurban region (57.1%). In addition to this 52% of urban children with increased BLL were residing in houses which were recently painted. Indian paints are high in Pb content. Recent Indian study assessed store-bought cans of enamel paint for Pb levels and found that 46% of those tested contained >10,000 ppm Pb [35]. Others have also suggested Pb-based paints to be contributory factor for BLL [36]. Houses of most of the children in periurban region were not painted/freshly painted which could be the reason for lower BLL observed in this subset. Herbal medications, cosmetics like kohl, surma are rich in Pb and hence potential cause of Pb toxicity [4], [5], [6], [37]. Usage of herbal/folk medicines along with surma/kohl usage was also observed in children with BLL>5 μg/dL (Table 2). Water can be a potential source of Pb exposure [38] and the local water body supplying to the Jodhpur population has been reported to have high Pb content of 250 ppb as reported previously [39] whereas Environmental Protection Agency advocates 15 ppb to be the upper permissible limit for consumption [7]. Children from urban backgrounds with increased BLL were dependent on municipal water supply and were not using any water purification system in 76.1% of the cases. In contrast, all the children with increased BLL from periurban part of the city did not have water purification system at home but were buying water from a local supplier which was true for other students of periurban region as well.


In the present study, 18.87% of school going children had BLL (>5 μg/dL) which is considerably higher in comparison to western counterparts. Lead toxicity is preventable and no level of exposure to this widely prevalent metal is known to be without deleterious health effects. Hence regular screening programs for Pb exposure by estimating BLL are recommended for school children along with aggressive awareness programs for the community. The information would be invaluable to formulate strategies for public health implications of Pb exposure and its detrimental effects on children.

Corresponding author: Praveen Sharma, Department of Biochemistry, All India Institute of Medical Sciences Jodhpur, Jodhpur, India, E-mail:

Funding source: All-India Institute of Medical Sciences

Award Identifier / Grant number: AIIMS/Res(01)/2014/07

  1. Research funding: The study was supported by institutional grant no AIIMS/Res (01)2014/07.

  2. Author contributions: PS and SS conceptualized and executed the study. PB, PM and SS made the study design and analysed the results. PS, SS, PB and PM drafted the paper.

  3. Competing interests: Authors state no conflict of interest.

  4. Ethical approval: Ethical clearance was obtained from institutional ethics committee (letter no. AIIMS/IEC/2014/330 dated 15/09/2014).


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Received: 2020-08-26
Accepted: 2020-12-26
Published Online: 2021-02-04

© 2021 Shailja Sharma et al., published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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