Spatial distribution and determinants of health care access barriers among female Pakistan youths: spatial and multilevel regression analysis
Bibliographic record
Abstract
INTRODUCTION: Ensuring universal access to high-quality healthcare services including services free from financial barriers, is a global priority. However, accessing healthcare services remains challenging for youth in low- and middle-income countries (LMICs), including Pakistan. This study investigates the spatial distribution and determinants of healthcare access barriers among female youths in Pakistan. METHODS: We used the 2017/18 Pakistan Demographic and Health Survey (PDHS) dataset, including 2,924 female youth aged 15-24, to examine healthcare access barriers. These barriers were considered as an outcome variable and were regarded where a respondent reported encountering any of the following impediments to accessing healthcare services during illness: (i) difficulty obtaining permission to visit a health facility; (ii) financial constraints in meeting healthcare expenses or treatment costs; (iii) significant travel distance to access a health facility; and (iv) reluctance to visit health facilities alone. To analyse multi-level determinants and geographical disparities in healthcare access barriers among youths, we employed multilevel logistic regression and spatial analysis techniques, respectively. The analysis accounted for sample weights to ensure the robustness and representativeness of the findings. RESULTS: Almost four-fifths (79.4%) of female youth in Pakistan (95% CI: 77.9 to 80.9) have reported having perceived barriers to accessing healthcare services. Barriers to accessing healthcare among female youth were associated with not having employment (AOR = 1.96; 95% CI; 1.39, 2.76), living in a household where the head was a male (AOR = 1.97; 95% CI; 1.40, 2.77), having low and middle household wealth status (low: AOR = 3.22; 95% CI; 2.18, 4.75; middle: AOR = 1.89; 95% CI; 1.36, 2.63), being unempowered (AOR = 2.08; 95% CI; 1.55, 2.80), and residing in areas with low community female youth literacy rates (AOR = 1.48; 95% CI: 1.02, 2.15) and living in federally administered tribal areas (FATA), Balochistan, and Azad Jammu and Kashmir (AJK) regions. CONCLUSION: A substantial proportion of female youth in Pakistan have major perceived barriers to accessing healthcare services. Several individual- and community-level factors were associated with perceived barriers to accessing healthcare services among female youth. Significant geographic variation was observed in the perceived barriers to healthcare services among Pakistan's female youth. Policymakers had better take measures to improve access to healthcare services through the formulation of youth-responsive policies and strategies.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".