Research Article |
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Corresponding author: Lia Amalia ( lia_amalia@itb.ac.id ) Academic editor: Magdalena Kondeva-Burdina
© 2025 Maya Safitri, Lia Amalia, Benny Permana, Dida Achmad Gurnida.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Safitri M, Amalia L, Permana B, Achmad Gurnida D (2025) Stunting and blood lead levels in a non-industrial rural area: the role of microminerals in child growth risk assessment. Pharmacia 72: 1-8. https://doi.org/10.3897/pharmacia.72.e161066
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Stunting remains a major public health issue in low-resource settings, with emerging evidence linking it not only to nutritional deficiencies but also to environmental toxicants such as lead. Despite this, limited research has explored the interplay between lead exposure, microminerals, and child growth in non-industrial rural areas. This study aimed to investigate the association between blood lead levels (BLLs), essential microminerals (zinc, manganese, and iron), and stunting in children, while also identifying environmental sources of lead. A cross-sectional study was conducted among 58 children aged 0–59 months in Datar Village, Central Java, Indonesia. Anthropometric assessments and venous blood samples were collected, and trace elements were quantified using ICP-MS. Lead content in environmental samples (water, food, foliage, soil, and paint dust) was also analyzed by ICP-MS. BLL ≥5 μg/dL was found in 55.2% of children, with manganese levels exceeding the safe threshold in 67.2% of children. Normal zinc levels were found in 91.4% of subjects, while iron deficiency was detected in 65.5% of subjects. No significant association was observed between trace element levels and height-for-age Z-scores. Environmental analysis revealed excess lead in spinach, foliage (longan, hairy fruit), soil samples, and some paint dust samples. Elevated BLL and widespread micronutrient deficiencies may co-exist in non-industrial rural environments and contribute to child health risks. Integrated environmental monitoring is recommended.
blood lead, environmental exposure, iron deficiency, ICP-MS, rural health, stunting
Stunting remains one of the most pressing public health challenges affecting children in low- and middle-income countries (
Recent international studies have documented elevated blood lead levels (BLLs) in children and their association with impaired growth. In Uganda, a study by
Despite these important findings, few studies have simultaneously examined the interaction between blood lead levels, essential microminerals (e.g., zinc, manganese, and iron), and stunting in rural, non-industrial settings, especially in Southeast Asia (
This is the first study in a rural, non-industrial Indonesian population to examine the relationship between stunting, blood lead levels, and microminerals, while simultaneously identifying environmental sources of lead exposure (
This cross-sectional study was carried out in Datar Village, a non-industrial rural area located in Banyumas Regency, Central Java, Indonesia. The study population consisted of children aged 0 to 59 months who regularly attended four integrated community health posts (Posyandu). A total of 58 children were enrolled using purposive sampling, comprising 29 stunted and 29 non-stunted children, as determined by height-for-age Z-scores based on the WHO Child Growth Standards and recorded in their Health Card (Kartu Menuju Sehat [KMS]). Children were eligible for inclusion if their caregivers were literate and willing to participate and if the children were healthy enough to undergo venipuncture. Children with known severe illnesses or medical contraindications were excluded. The study protocol received ethical approval from the Universitas Harapan Bangsa Ethics Committee (Approval No: B.LPPM-UHB/4303/2021), and written informed consent was obtained from all participating caregivers.
Anthropometric measurements were conducted using WHO-calibrated equipment provided by the Banyumas District Health Office. Height was measured to the nearest 0.1 cm using a stadiometer, and weight was recorded using a digital scale. These measurements were used to assess stunting status based on height-for-age Z-scores. Blood samples (3 mL) were collected from the antecubital vein of each child by trained phlebotomists using sterile 3 cc syringes and transferred into EDTA-coated BD Microtainer® tubes. All collections took place at the Posyandu centers under aseptic conditions and were coordinated with local midwives and health cadres. The blood samples were immediately stored in insulated cool boxes maintained at 2–8 °C and transported within two hours to the Pharmacy Laboratory at Universitas Harapan Bangsa, where they were stored at 4 °C prior to further analysis.
Each blood sample was prepared for analysis by pipetting 200 μL of whole blood and diluting it at a 1:20 ratio with an aqueous solution containing 0.1% Triton X-100 (Sigma–Aldrich, France) and 0.1% ultrapure nitric acid (≥69%, Suprapur®, Merck, Germany). The mixture was vortexed for 1 minute and transferred into acid-washed glass tubes to prevent contamination. Prepared samples were shipped on ice to the Center for Health Laboratory (Balai Besar Laboratorium Kesehatan, BBLK) in Jakarta for elemental analysis. Elemental quantification was conducted using Inductively Coupled Plasma Mass Spectrometry (ICP-MS, Agilent 7800, Agilent Technologies, USA), equipped with a MicroMist (borosilicate glass) concentric nebulizer, a Scott-type double-pass quartz spray chamber, and a High Matrix Introduction (HMI) system. The temperature was controlled from –5 °C to 20 °C. The system was operated in both helium collision modes to minimize polyatomic interferences. High-purity argon gas (99.999%) was used for plasma generation. Calibration curves for each element were prepared using six-point standard solutions (0.01, 0.02, 0.04, 0.06, 0.08, and 0.1 mg/L) from Merck Certipur® and Agilent, with coefficients of determination (R²) ≥ 0.999. Certified reference materials (Seronorm™ Trace Elements Whole Blood, Sero AS, Norway) were included in each run to ensure analytical accuracy. Instrument control was performed using ICP-MS MassHunter Workstation software. The limits of detection (LoD) and quantification (LoQ) were as follows: Pb, < 0.07 μg/dL and < 0.2 μg/dL; Mn, < 0.14 μg/dL and < 0.5 μg/dL; Zn, < 0.15 μg/dL and < 0.5 μg/dL; Fe, < 0.2 μg/dL and 0.7 μg/dL.
To investigate environmental sources of lead exposure, multiple environmental samples were collected from households and surrounding areas. Drinking water was collected in 600 mL pre-cleaned, acid-washed plastic bottles. Food items, including snacks, vegetables, rice, and fish, were placed in sealed bags, while foliage was gathered from roadside and home garden plants. Soil and wall dust samples were air-dried and homogenized in clean, sealed bags. For heavy metal analysis, 0.1 g of each soil or dust sample was digested in an Erlenmeyer flask with 4 mL of a 5:1 mixture of hydrofluoric acid (HF) and perchloric acid (HClO₄), followed by heating to 260 °C on a hotplate within a fume hood. After the initial digestion, 2 mL of aqua regia (HCl:HNO₃ = 3:1) and 10 mL of 10% aqua regia were added. The cooled digest was transferred into a 100 mL volumetric flask and brought to volume with ultrapure water. All samples were analyzed by ICP-MS using the same instrumentation and analytical conditions as for blood samples.
All statistical analyses were conducted using SPSS version 26.0 (IBM Corp., Armonk, NY, USA). Subgroup analysis by age category (0–23 and 24–59 months) was performed to evaluate cumulative lead exposure. The Shapiro–Wilk test was applied to assess the normality of continuous variables. Blood levels of Pb, Mn, Zn, and Fe were summarized using descriptive statistics (mean, median, and interquartile range). Multiple linear regression analysis was employed to examine associations between metal concentrations and children’s height-for-age Z-scores.
A total of 58 toddlers aged 0–59 months were enrolled and classified into stunted (n = 29) and non-stunted (n = 29) groups based on WHO height-for-age Z-scores. Participants were selected through purposive sampling from four integrated health posts (Posyandu) in Datar Village, Banyumas Regency, Central Java. The village, known for its mountainous terrain and tourism potential, is divided into three RW (community units), each comprising three RT (neighborhood units). Community health services are supported by five health cadres at each integrated health post (Posyandu), a village midwife, a family planning officer (PLKB), and the village head.
Blood concentrations of lead (Pb), manganese (Mn), zinc (Zn), and iron (Fe) were measured in all study participants. As presented in Table
| Trace element | Category | Stunted (n) | Non-stunted (n) | Total (n) | Reference range |
|---|---|---|---|---|---|
| Lead (Pb) | ≥5.0 μg/dL | 14 | 18 | 32 | ≤ 3.5 μg/dL* ( |
| 3.6–4.9 μg/dL | 11 | 9 | 20 | ||
| ≤3.5 μg/dL | 4 | 2 | 6 | ||
| Manganese (Mn) | >2 μg/dL | 20 | 19 | 39 | 0.9–2 μg/dL**( |
| 0.9–2 μg/dL | 2 | 0 | 2 | ||
| <0.9 μg/dL | 7 | 10 | 17 | ||
| Zinc (Zn) | >949.2 μg/dL | 2 | 2 | 4 | 234.9–949.2 μg/dL ** |
| 234.9–949.2 μg/dL | 26 | 27 | 53 | ||
| <234.9 μg/dL | 1 | 0 | 1 | ||
| Iron (Fe) | >50000 μg/dL | 4 | 3 | 7 | 40.000–50.000 μg/dL*** ( |
| 40000–50000 μg/dL | 5 | 8 | 13 | ||
| <40000 μg/dL | 20 | 18 | 38 |
Lead burden was higher in older toddlers. Table
A multiple linear regression analysis was performed to evaluate the influence of Pb, Mn, Zn, and Fe levels on height-for-age (HAZ). As shown in Table
Regression coefficients of Pb, Mn, Zn, and Fe in relation to child height.
| Predictor | Coefficient (B) | Std. Error | Beta | t-value | p-value |
|---|---|---|---|---|---|
| Constant | 83.477 | 4.659 | – | 17.918 | 0.000 |
| Lead (Pb) | 0.521 | 0.703 | 0.104 | 0.741 | 0.462* |
| Mn | -0.451 | 0.354 | -0.187 | -1.274 | 0.208* |
| Zn | -0.125 | 0.190 | -0.148 | -0.661 | 0.512* |
| Fe | 0.003 | 0.003 | 0.248 | 1.137 | 0.260* |
As shown in Table
Pb and Mn concentrations in drinking water from households with BLL ≥ 5 μg/dL.
| No | Types of drinking water sources | Pb (μg/dL) | Pb Standard | Mn (μg/dL) | Mn Standard |
|---|---|---|---|---|---|
| 1 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 2 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 3 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 4 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 5 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 6 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 7 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 8 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 9 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 10 | Village public water supply systems/PAM | 0.2 | 1.0 | 2.6 | 40 |
| 11 | Village public water supply systems/PAM | 0.2 | 1.0 | 0.5 | 40 |
| 12 | Dug well water | 0.2 | 1.0 | 0.5 | 40 |
| 13 | Dug well water | 0.2 | 1.0 | 0.5 | 40 |
| 14 | Dug well water | 0.2 | 1.0 | 0.5 | 40 |
| 15 | Refill drinking water | 0.2 | 1.0 | 0.5 | 40 |
| 16 | Refill drinking water | 0.2 | 1.0 | 0.5 | 40 |
| 17 | Refill drinking water | 0.2 | 1.0 | 0.5 | 40 |
| 18 | Refill drinking water | 0.2 | 1.0 | 0.5 | 40 |
| 19 | Refill drinking water | 0.2 | 1.0 | 0.5 | 40 |
| 20 | Natural spring water | 0.2 | 1.0 | 0.5 | 40 |
| 21 | Natural spring water | 0.2 | 1.0 | 1.5 | 40 |
Table
| Sample category | Sample description | Pb concentration | Regulatory limit | Unit |
|---|---|---|---|---|
| Food (snacks) | Crackers | 0.06 | 0.25 | mg/kg |
| Biscuits 1 | 0.07 | 0.25 | mg/kg | |
| Biscuits 2 | 0.04 | 0.25 | mg/kg | |
| Cereal | 0.05 | 0.25 | mg/kg | |
| Food (milk) | Ultra-high temperature (UHT) milk | 0.02 | 0.25 | mg/kg |
| Food (fish) | Catfish | 0.02 | 0.3 | mg/kg |
| Salted fish | 0.01 | 0.3 | mg/kg | |
| Food (vegetables) | Spinach leaf 1* | 0.4 | 0.2 | mg/kg |
| Spinach leaf 2 | 0.12 | 0.2 | mg/kg | |
| Spinach leaf 3 | 0.1 | 0.2 | mg/kg | |
| Carrot | 0.05 | 0.2 | mg/kg | |
| Cabbage | 0.03 | 0.2 | mg/kg | |
| Food (grains) | Rice sample 1 | 0.08 | 0.25 | mg/kg |
| Rice sample 2 | 0.02 | 0.25 | mg/kg | |
| Rice sample 3 | 0.03 | 0.25 | mg/kg | |
| Foliage | Guava leaf around the main road | 0.14 | 0.2 | mg/kg |
| Red shoots leaf around the main road | 0.14 | 0.2 | mg/kg | |
| Longan leaf around the main road* | 0.39 | 0.2 | mg/kg | |
| Duku leaf around the main road | 0.14 | 0.2 | mg/kg | |
| Guava Leaf around the house | 0.11 | 0.2 | mg/kg | |
| Longan Leaf around the house | 0.06 | 0.2 | mg/kg | |
| Hairy fruit leaf around the house * | 0.24 | 0.2 | mg/kg | |
| Soil | Soil around the house A | <0.002 | 400 | ppm |
| Soil around the house B | <0.002 | 400 | ppm | |
| Soil around the house C | <0.002 | 400 | ppm | |
| Soil around the house D | <0.002 | 400 | ppm | |
| Soil around the house E | <0.002 | 400 | ppm | |
| Soil around the rice fields | 230 | 400 | ppm | |
| Soil around the main road* | 730 | 400 | ppm | |
| Paint dust | House paint dust 1* | 6100 | 90 | ppm |
| House paint dust 2 | <0.002 | 90 | ppm | |
| House paint dust 3 | <0.002 | 90 | ppm | |
| House paint dust 4 | <0.002 | 90 | ppm | |
| House paint dust 5* | 380 | 90 | ppm | |
| School environment paint dust* | 3880 | 90 | ppm |
To the best of our knowledge, this is the first study conducted in a non-industrial rural region of Central Java, Indonesia, that comprehensively examines the intersection of blood lead levels (BLL), micronutrient status (zinc, manganese, and iron), and environmental sources of lead exposure in relation to child stunting and trace element toxicity. The results demonstrate a concerning public health scenario: more than half of the sampled children (55.2%) presented with elevated BLLs (≥5 μg/dL); normal zinc levels (Zn: 234.9–949.2 μg/dL) were found in 91.4% of subjects; 67.2% had manganese levels above the upper reference range; and iron deficiency (Fe < 40,000 μg/dL) was found in 65.5% of subjects. No statistically significant associations were observed between trace element concentrations (Pb, Mn, Zn, Fe) and height-for-age Z-score (HAZ). These biological findings were further contextualized by the detection of lead contamination in several local environmental matrices, including vegetables (particularly spinach), plant foliage (longan and hairy fruit), household soil, and paint dust.
The high proportion of children with elevated BLLs aligns with earlier findings from other Southeast Asian studies, despite our study being conducted in a rural, non-industrial setting typically presumed to be at lower risk for lead exposure (
Manganese levels exceeded the safe threshold in 67.2% of children. Although an essential micronutrient, manganese in excess has been increasingly recognized as a neurotoxin (27.28).Elevated Mn levels have been associated with reduced IQ, attention deficit, and behavioral dysregulation, even at subclinical levels (
Iron deficiency (Fe < 40,000 μg/dL) was found in 65.5% of subjects. Although not all studies use Fe units in µg/dL of whole blood, a recent study by Mushi (2023). (
Environmental sampling identified multiple lead exposure pathways. While all household drinking water samples were within acceptable regulatory thresholds, one spinach leaf sample showed lead levels twice the permitted limit (
In parallel, three of six tested paint dust samples were found to exceed the permissible threshold of 90 ppm, with one sample measuring an extreme 6100 ppm. This level of contamination points to the legacy use of lead-based paint, a problem known to persist in many low-resource settings despite formal regulation (
This study possesses several notable strengths. It is among the first in Indonesia to integrate biological trace element testing and environmental sampling outcomes into a single analytic framework. The use of high-precision ICP-MS for biomonitoring ensures methodological rigor and data accuracy (
This study highlights a critical but underrecognized burden of environmental lead exposure and micronutrient imbalance among children in a rural, non-industrial region of Central Java. More than half of the participants showed elevated blood lead levels; the majority had excessive manganese concentrations, most had normal zinc concentrations, and many were iron deficient. Environmental sources such as contaminated vegetables, foliage, soil, and legacy paint dust were identified as potential contributors. While no significant association was found between trace element concentrations and stunting, the findings underscore the complex interplay of environmental and nutritional factors affecting child health. These results call for urgent public health action, including environmental surveillance, micronutrient screening, and early detection of blood lead levels to identify and reduce exposure risks and improve child health outcomes.
Conflict of interest
The authors have declared that no competing interests exist.
Ethical statements
The authors declared that no clinical trials were used in the present study.
The authors declared that experiments on humans or human tissues were performed for the present study.
The authors declared that no informed consent was obtained from the humans, donors or donors’ representatives participating in the study.
Informed consent from the humans, donors or donors’ representatives: The study protocol received ethical approval from the Universitas Harapan Bangsa Ethics Committee Approval No: B.LPPM-UHB/4303/2021, and written informed consent was obtained from all participating caregivers.
The authors declared that no experiments on animals were performed for the present study.
The authors declared that no commercially available immortalised human and animal cell lines were used in the present study.
Use of AI
No use of AI was reported.
Funding
No funding was reported.
Author contributions
All authors have contributed equally.
Author ORCIDs
Maya Safitri https://orcid.org/0009-0004-0245-5954
Lia Amalia https://orcid.org/0000-0002-0011-1558
Benny Permana https://orcid.org/0000-0002-6588-6557
Dida Achmad Gurnida https://orcid.org/0000-0002-0714-7772
Data availability
All of the data that support the findings of this study are available in the main text.