Household‐level predictors of maternal mental health and systemic inflammation among infants in Mwanza, Tanzania
Bibliographic record
Abstract
OBJECTIVES: Household conditions and culturally/socially variable childcare practices influence priming of the inflammatory response during infancy. Maternal mental health may partially mediate that effect. Among mother-infant dyads in Mwanza, Tanzania, we hypothesized that poorer maternal mental health would be associated with adverse household ecology, lower social capital, and greater inflammation among infants under the age of one; and that mental health would mediate any effects of household ecology/social capital on inflammation. METHODS: We collected dried blood spots from mother-infant dyads (N = 88) at health centers near Mwanza, Tanzania. To assess household ecology and social capital, we conducted interviews with mothers using the Household Food Insecurity Access Scale, the MacArthur Subjective Social Status Scale, and a household wealth inventory. We employed the Hopkins Symptom Checklist to assess maternal mental health. A high-sensitivity C-reactive protein (CRP) assay was used to quantify inflammation. RESULTS: Severe food insecurity (OR: 5.16), lower subjective social status (r = -0.32), and lower household wealth (r = -0.26) were associated with high symptoms of maternal depression. Lower household wealth (r = -0.21) and severe food insecurity (OR: 2.52) were associated with high anxiety. High depression symptoms (OR: 2.56) and severe food insecurity (OR: 2.77) each were associated with greater-than-median infant CRP. However, mediation was not supported. CONCLUSIONS: Maternal mental health should be considered alongside nutritional status, pathogen exposure, and education as a potential driver of very early innate immune system development. Proximal mechanisms warrant further investigation. Am. J. Hum. Biol. 28:461-470, 2016. © 2015 Wiley Periodicals, Inc.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".