Association Between Hair Trace Element Content and Children’s Growth and Development: Protocol for a Cross-Sectional Surveillance Study
Bibliographic record
Abstract
BACKGROUND: Western Kazakhstan, a major industrial region, faces environmental challenges from the release of toxic elements due to intensive industrial activities. The combined impact of anthropogenic factors, trace element deficiencies, and harsh climatic conditions contributes to the deterioration of child health and growth. OBJECTIVE: This study aimed to investigate the elemental profile of the child population in the western region of Kazakhstan. METHODS: A total of 2279 school-aged children (aged 5 to 18 years) who are permanent residents of the Aktobe, Mangystau, Atyrau, and West Kazakhstan regions will be included in the study using a cluster sampling method. The elemental composition of their hair will be analyzed using inductively coupled plasma mass spectrometry on an Agilent 8900 inductively coupled plasma mass spectrometer (Agilent Technologies). Children's physical growth will be assessed according to the World Health Organization (2007) growth standards and characterized using the following z score values: body weight for age for children aged younger than 10 years, height for age, and BMI for age. The cutoff points of z score values make it possible to diagnose thinness, stunting, overweight, or obesity. Multiple linear regression analysis will be applied to assess the association between chemical element content in hair and z score measures of children's physical growth, as well as associations with gender, age, sociodemographic factors, and residential status. Reference values for chemical element content in biological substrates of the western Kazakhstan population will be established using 95% coverage intervals with 95% CIs following International Union of Pure and Applied Chemistry recommendations. The chemical element content will be reflected in a web-based atlas. RESULTS: After recruitment of participants, data will be collected between September 2023 and March 2025. Data processing and analysis will be completed in September 2025. Publication of the results is expected in December 2025. An analysis will be conducted to determine the differences in the levels of elements in groups of boys and girls, urban and rural children, and groups of children of different ages. According to the results of multiple regression analysis, chemical elements influencing the indicators of the physical development of children will be identified. CONCLUSIONS: The identified associations between trace and macroelement content and children's growth indicators will allow for the development of region-specific public health measures, such as nutritional supplements, environmental remediation, and policies aimed at reducing exposure to toxic elements. In addition, identifying differences between rural and urban populations could inform the development of targeted prevention strategies. The developed web-based atlas of trace and macroelement content will be necessary for further research on the prevalence, etiology, risk factors, and possible mechanisms of development of environmentally dependent, endemic diseases in the region. Reference values of trace and macroelement content will also be established. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72207.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".