Household food and water insecurity are positively associated with high perceived stress during COVID-19 lockdown: Evidence from a low-middle income country
Bibliographic record
Abstract
The COVID-19 pandemic has increased the risk of global public health and has the potential to cause severe food and water insecurity due to economic recession during lockdown for people living in low-middle income countries like Bangladesh where capital resources are scarce.There is growing evidence that household food and water insecurity has been associated with poor psychological outcomes.The objective of this study was to determine the association between household food and water insecurity with mental health and whether these differed among urban-rural households.A cross-sectional online survey was conducted with 545 participants immediately after the COVID-19 lockdown period in Bangladesh (August 1-September 30, 2020).Household food and water security were determined using a 9-item Household Food Insecurity Access Scale (HFIAS) (score range 0-27) and a 12-item Household Water Insecurity Experiences (HWISE) scale (score range 0-36), respectively.The Perceived Stress Scale (PSS) was used to evaluate mental health.Multivariable logistic regression examined the association between household food and water insecurity with perceived stress, adjusting socioeconomic characteristics.An urban-rural stratified analysis was also performed.About 72.84% (397) respondents reported high stress and more than 70% of households suffered from food and water insecurity during the lockdown period.After adjusting covariates, logistic regression model results show that food insecurity was associated with a 1.07-point increase in high perceived stress (OR=1.07,95% CI=1.01-1.11,p<0.01) while water insecurity was associated with 1.03 times greater odds of high perceived stress (OR=1.03,95% CI=0.93-1.23,p<0.05).In stratified analysis, only food insecurity was associated with high perceived stress in the urban household (OR=1.08,95% CI=1.00-1.11,p<0.05).However, none of the household insecurity was associated with perceived stress in rural households.Interventions that promote equal access to resources for low-income individuals will likely to be more effective to alleviate economic burden of pandemic.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".