Factors affecting quality of life in hepatitis B patients in Herat, Afghanistan: A case–control study
Bibliographic record
Abstract
Hepatitis B virus is a global health concern with a high death rate in Afghanistan. Limited data exist on the disease's impact on quality of life in low-resource settings. This case-control study aims to identify potential risk factors and assess the quality of life among hepatitis B patients in Herat, Afghanistan, with a focus on sex differences. Understanding these factors can inform prevention, care, and sex-specific interventions. A cross-sectional study conducted at Herat Regional Hospital examined hepatitis B patients above 18 years old, between October 2020 and February 2021. The control group consisted of age and sex-matched individuals without a history of hepatitis B. Data were collected through a structured questionnaire covering socio-demographic characteristics, signs and symptoms of hepatitis B, and the SF-36 questionnaire for measuring the quality of life of study participants. Statistical analysis was performed using multivariate General Linear Models, and logistic regression. We identified several potential risk factors for hepatitis B infection, including male sex, younger age groups, tobacco use, lower education levels, rural residence, family history, weak social networks, specific family structures and underlying chronic diseases (p < .05). The study found that hepatitis B cases had significantly lower mean scores across all SF-36 components, indicating an overall reduced quality of life (p < .05). These differences were more pronounced in males, although females had lower scores in most components. Role limitations due to physical and emotional health were particularly affected. These findings highlight the urgent need for targeted interventions, sex-specific strategies, improved healthcare access and comprehensive policies. These findings can inform prevention efforts to improve the overall quality of life of people with hepatitis B in Afghanistan.
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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 | 0.002 | 0.002 |
| 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) | 0.000 | 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".