Study of Bacteriological Content and Risk Factors of Drinking Water Consumption Patterns in Cases of Stunting Toddler
Bibliographic record
Abstract
Stunting is one of global nutrition problems, especially in developing countries including Indonesia. The prevalence of stunting in Demak Regency, Indonesia, in 2021 was 4.34%, and in 2022 it was 2.99%. However, stunting problem remains a priority because the impact of stunting can hinder efforts to enhance the health of the society and the development of the quality of human resources. Risk factors for stunting are influenced by behavioral aspects of the environment, like sanitation and drinking water. This study aimed to determine the content of bacteriological factors that contribute to the risk pattern of drinking water consumption in cases of stunting toddlers in Temuroso Village, Working Area of Guntur I Health Center, Demak Regency, Indonesia. This study was a quantitative observational case study. The population included families and toddlers in Temuroso Village, totaling as many as 854 people. The sampling technique was purposive sampling, so the sample size was 182 people for cases and controls. Data analysis used Chi-Square test and linear regression test. The bacteriological content was predominantly negative (66.5%), with the majority of subjects showing no infections (67%). Most participants fell into the high drinking water consumption category (62.1%). Stunting incidence was significantly associated with bacteriological content (p <0.0001) and drinking water consumption patterns (p <0.0001). Among these, bacteriological content was the most dominant factor influencing stunting (exp B =0.199). In summary, the primary risk factors for stunting among toddlers in Temuroso Village, within the Guntur I Health Center working area, Demak Regency, were bacteriological content (p <0.000) and drinking water consumption patterns (p <0.000).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".