Barriers to effective usage of insecticide-treated mosquito nets (ITNS) among women of reproductive age in Tanzania: a national cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Malaria remains a significant public health challenge in Tanzania, with women of reproductive age particularly vulnerable to its effects. Insecticide-treated mosquito nets (ITNs) are a proven vector control strategy; however, their usage remains suboptimal due to various barriers. This study examines the sociodemographic, behavioural, and environmental factors associated with ITN use among women of reproductive age in Tanzania. METHODS: A cross-sectional analysis was conducted using data from the 2022 Tanzania Demographic and Health Survey (TDHS). A total of 15,254 women aged 15-49 years were included in the study. Survey-weighted logistic regression was employed to determine adjusted odds ratios (AOR) and 95% confidence intervals (CI) for factors associated with ITN usage. All data cleaning and analyses were done using STATA 17 software. RESULTS: Several factors were significantly associated with ITN use. Women with primary education had 2.2 times higher odds of ITN use compared to those with no education (AOR: 2.2, 95% CI: 1.23-4.06). Women residing in the Southern zone had nearly three times higher odds of using ITNs (AOR: 2.8, 95% CI: 1.57-5.09), while those in the Lake zone had 1.6 times higher odds (AOR: 1.6, 95% CI: 1.12-2.33) compared to the Western zone. Women in polygamous marriages had lower odds of ITN use (AOR: 0.76, 95% CI: 0.61-0.95) compared to those in monogamous relationships. Perceived ITN effectiveness was a strong predictor, with those in the high-effectiveness category having 2.7 times higher odds of ITN use (AOR: 2.7, 95% CI: 0.94-5.46). CONCLUSION: ITN usage among women of reproductive age in Tanzania is influenced by education level, geographic location, marital status, and perceived ITN effectiveness. These findings highlight the need for targeted interventions, such as educational campaigns, equitable ITN distribution, and context-appropriate malaria prevention strategies, to improve ITN coverage and reduce the malaria burden.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".