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1.
BMC Public Health ; 23(1): 2055, 2023 10 20.
Artigo em Inglês | MEDLINE | ID: mdl-37858163

RESUMO

BACKGROUND: Despite the close relationship between pre-pregnancy body mass index (BMI), gestational weight gain (GWG) and postpartum weight (PPW), these factors are often studied separately. There are no data characterising longitudinal weight trajectories among pregnant and postpartum women in urban African populations. We examined maternal weight trajectories from pregnancy through to 12 months postpartum, factors associated with higher weight trajectory class membership and associations of weight trajectories with infant growth at 12 months. METHODS: Data from 989 women were examined for weight trajectories from first antenatal care visit in pregnancy to 12 months postpartum using latent-class growth models. Baseline factors associated with class membership were assessed using multinomial logistic regression. Of the enrolled women, 613 of their infants were assessed for growth at 12 months. Anthropometry measurements for mothers and infants were conducted by a trained study nurse. Associations between maternal weight trajectory class and infant weight-for-age (WAZ), length-for-age (LAZ), weight-for-length (WLZ) at 12 months of age were analysed using linear regression. RESULTS: Four distinct classes of maternal weight trajectories were identified. The classes included consistent low (29%), consistent medium (37%), medium-high (24%) and consistent high (10%) trajectories. Similar to trends observed with medium-high trajectory, baseline factors positively associated with consistent high class membership included age (OR 1.05, 95% CI 1.01-1.09), pre-pregnancy BMI (OR 2.24, 95% CI 1.97-2.56), stage 1 hypertension (OR 3.28, 95% CI 1.68-6.41), haemoglobin levels (OR 1.39, 95% CI 1.11-1.74) and parity (OR 1.39, 95% CI 1.15-1.67); living with HIV (OR 0.47, 95% CI 0.30-0.74) was inversely associated. In adjusted analyses, compared to consistent medium weight trajectory, consistent low weight trajectory (mean difference -0.41, 95% CI -0.71;-0.12) was associated with decreased, and consistent high weight trajectory (mean difference 1.21, 95% CI 0.59-1.83) with increased infant WAZ at 12 months of age. CONCLUSION: Identification of unique longitudinal weight trajectory groupings might inform comprehensive efforts targeted at improving healthy maternal weight and infant outcomes.


Assuntos
Trajetória do Peso do Corpo , Gravidez , Lactente , Feminino , Humanos , África do Sul/epidemiologia , Cuidado Pré-Natal , Período Pós-Parto , Índice de Massa Corporal , Mães
2.
Res Sq ; 2024 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-39070658

RESUMO

Background: Lower respiratory tract infection (LRTI) is a leading cause of infant morbidity and mortality globally. LRTI may be caused by viral or bacterial infections, individually or in combination. We investigated associations between LRTI and infant nasopharyngeal (NP) viruses and bacteria in a South African birth cohort. Methods: In a case-control study of infants enrolled in the Drakenstein Child Health Study (DCHS), LRTI cases were identified prospectively and age-matched with controls from the cohort. NP swabs were tested using quantitative real-time polymerase chain reaction (qPCR) and 16S rRNA gene amplicon sequencing. We calculated adjusted Conditional Odds Ratios (aORs) for qPCR targets and used mixed effects models to identify differentially abundant taxa between LRTI cases and controls and explore viral-bacterial interactions. Results: Respiratory Syncytial Virus (RSV) [aOR: 5.69, 95% CI: 3.03-10.69], human rhinovirus (HRV) [1.47, 1.03-2.09], parainfluenza virus [3.46, 1.64-7.26], adenovirus [1.99, 1.08-3.68], enterovirus [2.32, 1.20-4.46], Haemophilus influenzae [1.72, 1.25-2.37], Klebsiella pneumoniae [2.66, 1.59-4.46], or high-density (> 6.9 log10 copies/mL) Streptococcus pneumoniae [1.53, 1.01-2.32] were associated with LRTI. Using 16S sequencing, LRTI was associated with increased relative abundance of Haemophilus (q = 0.0003) and decreased relative abundance of Dolosigranulum (q = 0.001), Corynebacterium (q = 0.091) and Neisseria (q = 0.004). In samples positive for RSV, Staphylococcus and Alloprevotella were present at lower relative abundance in cases than controls. In samples positive for parainfluenza virus or HRV, Haemophilus was present at higher relative abundance in cases. Conclusions: The associations between bacterial taxa and LRTI are strikingly similar to those identified in high-income countries, suggesting a conserved phenotype. RSV was the major virus associated with LRTI. H. influenzae appears to be the major bacterial driver of LRTI, acting synergistically with viruses. The Gram-positive bacteria Dolosigranulum and Corynebacteria may protect against LRTI, while Staphylococcus was associated with reduced risk of RSV-related LRTI. Funding: National Institutes of Health of the USA, Bill and Melinda Gates Foundation, National Research Foundation South Africa, South African Medical Research Council, L'Oréal-UNESCO For Women in Science South Africa, Australian National Health and Medical Research Council.

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