Maternal Factors Contribute to Low Cranial Size among <i>Mam</i> ‐Mayan Infants in Guatemala
Notice bibliographique
Résumé
Background In Guatemala, emerging research reveals a diversity of stressors in pregnancy and lactation impact early infant growth. Most research has focused efforts on uncovering associations with infant stunting. In comparison, rates of low cranial size, as measured by infant head circumference for age z scores (HCZ) < −2SD, and its potential causes are largely unknown. It is also unclear if a premature birth contributes to retarded infant HCZ in this population. Objectives The objectives were to: (1) quantify the prevalence of low cranial size at early (0–6 wks) and later (4–6 mo) post‐partum in a cohort of Mam ‐Mayan infants; (2) investigate the ΔHCZ from 0–6 wks to 4–6 mo; and to (3) explore the relative contribution of infant prematurity and maternal anthropometric measures to infant HCZ at both 0–6wks and 4–6 mo. Methods This study followed a cohort of Mam ‐Mayan mothers (n=81 mother‐infant dyads) in the Western Highlands of Guatemala from pregnancy through 6 months postpartum. Anthropometric measures were collected from mothers and infants at early (< 6 wks) and later (4–6 mo) postpartum. Gestational age (GA) was based on last menstrual period; infant prematurity was defined as a delivery <37wks of gestation. Rate of change for infant HCZ was calculated based on Δ HCZ from 0–6 wks to 4–6 mo divided by days postpartum. Correlations between HCZ, GA and anthropometric variables were explored. Separate multiple linear regression models for HCZ at 0–6 wks and 4–6 mo were investigated and unstandardized coefficients (B) reported. All models included the variables of GA (wks) and prematurity (yes/no). Statistical significance was set at p<0.05. Results At 0–6 wks, the prevalence of low cranial size (HCZ <‐2SD) was 16%; the median HCZ was −0.30 (mean HCZ −0.48±1.57). At 4–6 mo, the prevalence of low cranial size was 13%; the median HCZ was −0.48 (mean HZC −0.63±1.49). The mean infant Δ HCZ was −0.04±0.42/day with a mean GA of 34.49±1.4 wks; 23% of infants were premature. GA was positively correlated with infant HCZ (r=0.29, p=0.01) only at 0–6 wks. In bivariate analyses, HCZ at 0–6 wks was lower for premature (−1.31±1.82) compared to non‐premature infants (−0.25±1.42), but in unadjusted odds ratios (OR), premature birth (OR=2.64, p=0.134) was not associated with low cranial size at 0–6 wks. At 0–6 wks, multiple linear regression showed that only maternal weight during pregnancy (B=0.06, p=0.016) was positively associated with HCZ in a model that captured 16.3% of the variance while controlling for maternal height, GA, and prematurity, which were not significant. At 4–6 mo, multiple linear regression showed that infant HCZ at 0–6 wks (B=0.26, p=0.029) was positively associated with HCZ at 4–6 mo in an adjusted model that captured 11.2% of the variance and that controlled for maternal weight during pregnancy, maternal height, GA and prematurity, none of which were significant. Conclusion In contrast to our expectation, prematurity did not contribute to low cranial size when adjusting for maternal variables during pregnancy. Our study showed that maternal weight during pregnancy was associated with infant HCZ at 0–6 wks and that growth at 0–6 wks is strongly associated with HCZ at 4–6 mo. Our findings strongly suggest that both in utero and postnatal conditions contribute to low cranial size. Support or Funding Information CeSSIAM
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».