41 research outputs found
Study protocol: the impact of growth charts and nutritional supplements on child growth in Zambia (ZamCharts): a cluster randomized controlled trial
https://www.researchsquare.com/article/rs-2816403/v1First author draf
Predictors of low birth weight and preterm birth in rural Uganda: findings from a birth cohort study
BACKGROUND: Approximately 20.5 million infants were born weighing <2500 g (defined as low birthweight or LBW) in 2015, primarily in low- and middle-income countries (LMICs). Infants born LBW, including those born preterm (<37 weeks gestation), are at increased risk for numerous consequences, including neonatal mortality and morbidity as well as suboptimal health and nutritional status later in life. The objective of this study was to identify predictors of LBW and preterm birth among infants in rural Uganda.
METHODS: Data were derived from a prospective birth cohort study conducted from 2014–2016 in 12 districts across northern and southwestern Uganda. Birth weights were measured in triplicate to the nearest 0.1 kg by trained enumerators within 72 hours of delivery. Gestational age was calculated from the first day of last menstrual period (LMP). Associations between household, maternal, and infant characteristics and birth outcomes (LBW and preterm birth) were assessed using bivariate and multivariable logistic regression with stepwise, backward selection analyses.
RESULTS: Among infants in the study, 4.3% were born LBW (143/3,337), and 19.4% were born preterm (744/3,841). In multivariable analysis, mothers who were taller (>150 cm) (adjusted Odds Ratio (aOR) = 0.42 (95% CI = 0.24, 0.72)), multigravida (aOR = 0.62 (95% CI = 0.39, 0.97)), or with adequate birth spacing (>24 months) (aOR = 0.60 (95% CI = 0.39, 0.92)) had lower odds of delivering a LBW infant Mothers with severe household food insecurity (aOR = 1.84 (95% CI = 1.22, 2.79)) or who tested positive for malaria during pregnancy (aOR = 2.06 (95% CI = 1.10, 3.85)) had higher odds of delivering a LBW infant. In addition, in multivariable analysis, mothers who resided in the Southwest (aOR = 0.64 (95% CI = 0.54, 0.76)), were ≥20 years old (aOR = 0.76 (95% CI = 0.61, 0.94)), with adequate birth spacing (aOR = 0.76 (95% CI = 0.63, 0.93)), or attended ≥4 antenatal care (ANC) visits (aOR = 0.56 (95% CI = 0.47, 0.67)) had lower odds of delivering a preterm infant; mothers who were neither married nor cohabitating (aOR = 1.42 (95% CI = 1.00, 2.00)) or delivered at home (aOR = 1.25 (95% CI = 1.04, 1.51)) had higher odds.
CONCLUSIONS: In rural Uganda, severe household food insecurity, adolescent pregnancy, inadequate birth spacing, malaria infection, suboptimal ANC attendance, and home delivery represent modifiable risk factors associated with higher rates of LBW and/or preterm birth. Future studies on interventions to address these risk factors may be warranted.Published versio
Risk factors for mortality among Tanzanian infants and children
BACKGROUND: During the era of the Millennium Development Goals, under 5 mortality rates decreased significantly worldwide; however, reductions were not equally distributed. Children in sub-Saharan Africa still account for more than 50% of the world’s annual childhood deaths among children under 5 years of age. Understanding upstream risk factors for mortality among children may reduce the large burden of childhood mortality in sub-Saharan Africa. Our objective was to identify risk factors for mortality among infants and children in Tanzania.
METHODS: We conducted a secondary analysis of data pooled from two randomized-controlled micronutrient supplementation trials. A total of 4787 infants were enrolled in the two trials (n = 2387 HIV-exposed and n = 2400 HIV-unexposed). Predictors of mortality were assessed using unadjusted and adjusted hazard ratios (aHRs).
RESULTS: There were 307 total deaths, 262 (11%) among children who were HIV-exposed and 45 (2%) among children who were HIV-unexposed (P < 0.001). The most common cause of death was respiratory diseases (n = 109, 35.5%). Causes of death did not significantly differ between HIV-exposed and HIV-unexposed children. In adjusted regression analyses, children with birth weight < 2500 g (aHR 1.75, 95% CI 1.21–2.54), Apgar score of ≤7 at 5 min (aHR 2.16, 95% CI 1.29–3.62), or who were HIV-exposed but not infected (aHR 3.35, 95% CI 2.12–5.28) or HIV-infected (aHR 27.56, 95% CI 17.43–43.58) had greater risk of mortality.
CONCLUSIONS: Infection with HIV, low birthweight, or low Apgar scores were associated with higher mortality risk. Early identification and modification of determinants of mortality among infants and children may be the first step to reducing such deaths.http://10.0.4.162/s41182-020-00233-8Published versio
Biomarkers of maternal environmental enteric dysfunction are associated with shorter gestation and reduced length in newborn infants in Uganda
https://pubmed.ncbi.nlm.nih.gov/30247538/Published versio
Markers of environmental enteric dysfunction are associated with poor growth and iron status in rural Ugandan infants
https://pubmed.ncbi.nlm.nih.gov/32455424/Published versio
Maternal aflatoxin exposure during pregnancy and adverse birth outcomes in Uganda
Aflatoxins are toxic metabolites of Aspergillus moulds and are widespread in the food supply, particularly in low- and middle-income countries. Both in utero and infant exposure to aflatoxin B1 (AFB1 ) have been linked to poor child growth and development. The objective of this prospective cohort study was to investigate the association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, primarily lower birth weight, in a sample of 220 mother-infant pairs in Mukono district, Uganda. Maternal aflatoxin exposure was assessed by measuring the serum concentration of AFB1 -lysine (AFB-Lys) adduct at 17.8 ± 3.5 (mean ± SD)-week gestation using high-performance liquid chromatography. Anthropometry and birth outcome characteristics were obtained within 48 hr of delivery. Associations between maternal aflatoxin exposure and birth outcomes were assessed using multivariable linear regression models adjusted for confounding factors. Median maternal AFB-Lys level was 5.83 pg/mg albumin (range: 0.71-95.60 pg/mg albumin, interquartile range: 3.53-9.62 pg/mg albumin). In adjusted linear regression models, elevations in maternal AFB-Lys levels were significantly associated with lower weight (adj-β: 0.07; 95% CI: -0.13, -0.003; p = 0.040), lower weight-for-age z-score (adj-β: -0.16; 95% CI: -0.30, -0.01; p = 0.037), smaller head circumference (adj-β: -0.26; 95% CI: -0.49, -0.02; p = 0.035), and lower head circumference-for-age z-score (adj-β: -0.23; 95% CI: -0.43, -0.03; p = 0.023) in infants at birth. Overall, our data suggest an association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, particularly lower birth weight and smaller head circumference, but further research is warranted.K24 DK104676 - NIDDK NIH HHS; P30 DK040561 - NIDDK NIH HHS; AID-OAA-L-10-00006 - U.S. Agency for International Development; K24DK104676 and 2P30 DK040561 - National Institutes of Health (NIH)https://pubmed.ncbi.nlm.nih.gov/30242967/Published versio
Markers of systemic inflammation and environmental enteric dysfunction are not reduced by zinc or multivitamins in Tanzanian infants: a randomized, placebo-controlled trial
https://pubmed.ncbi.nlm.nih.gov/30952509/Published versio
Global diversity and antimicrobial resistance of typhoid fever pathogens : insights from a meta-analysis of 13,000 Salmonella Typhi genomes
DATA AVAILABILITY : All data analysed during this study are publicly accessible. Raw Illumina sequence reads have been submitted to the European Nucleotide Archive (ENA), and individual sequence accession numbers are listed in Supplementary file 2. The full set of n=13,000 genome assemblies generated for this study are available for download from FigShare: https://doi.org/10.26180/21431883. All assemblies of suitable quality (n=12,849) are included as public data in the online platform Pathogenwatch (https://pathogen.watch). The data are organised into collections, which each comprise a neighbour-joining phylogeny annotated with metadata, genotype, AMR determinants, and a linked map. Each contributing study has its own collection, browsable at https://pathogen.watch/collections/all?organismId= 90370. In addition, we have provided three large collections, each representing roughly a third of the total dataset presented in this study: Typhi 4.3.1.1 (https://pathogen.watch/collection/ 2b7mp173dd57-clade-4311), Typhi lineage 4 (excluding 4.3.1.1) (https://pathogen.watch/collection/ wgn6bp1c8bh6-clade-4-excluding-4311), and Typhi lineages 0-3 (https://pathogen.watch/collection/ 9o4bpn0418n3-clades-0-1-2-and-3). In addition, users can browse the full set of Typhi genomes in Pathogenwatch and select subsets of interest (e.g. by country, genotype, and/or resistance) to generate a collection including neighbour-joining tree for interactive exploration.SUPPLEMENTARY FILES : Available at https://elifesciences.org/articles/85867/figures#content. SUPPLEMENTARY FILE 1. Details of local ethical approvals provided for studies that were unpublished at the time of contributing data to this consortium project. Most data are now published, and the citations for the original studies are provided here. National surveillance programs in Chile (Maes et al., 2022), Colombia (Guevara et al., 2021), France, New Zealand, and Nigeria (Ikhimiukor et al., 2022b) were exempt from local ethical approvals as these countries allow sharing of non-identifiable pathogen sequence data for surveillance purposes. The US CDC Internal Review Board confirmed their approval was not required for use in this project (#NCEZID-ARLT- 10/ 20/21-fa687). SUPPLEMENTARY FILE 2. Line list of 13,000 genomes included in the study. SUPPLEMENTARY FILE 3. Source information recorded for genomes included in the study. ^Indicates cases included in the definition of ‘assumed acute illness’. SUPPLEMENTARY FILE 4. Summary of genomes by country. SUPPLEMENTARY FILE 5. Genotype frequencies per region (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 6. Genotype frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 7. Antimicrobial resistance (AMR) frequencies per region (N, %, 95% confidence interval; aggregated 2010–2020). SUPPLEMENTARY FILE 8. Antimicrobial resistance (AMR) frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 9. Laboratory code master list. Three letter laboratory codes assigned by the consortium.BACKGROUND : The Global Typhoid Genomics Consortium was established to bring together the
typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi)
genomic data to inform public health action. This analysis, which marks 22 years since the publication
of the first Typhi genome, represents the largest Typhi genome sequence collection to date
(n=13,000).
METHODS : This is a meta-analysis
of global genotype and antimicrobial resistance (AMR) determinants
extracted from previously sequenced genome data and analysed using consistent methods
implemented in open analysis platforms GenoTyphi and Pathogenwatch.
RESULTS : Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58)
has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate
and have independently evolved AMR. Data gaps remain in many parts of the world, and we
show the potential of travel-associated
sequences to provide informal ‘sentinel’ surveillance for
such locations. The data indicate that ciprofloxacin non-susceptibility
(>1 resistance determinant) is
widespread across geographies and genotypes, with high-level
ciprofloxacin resistance (≥3 determinants)
reaching 20% prevalence in South Asia. Extensively drug-resistant
(XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone
resistance has emerged in eight non-XDR
genotypes, including a ciprofloxacin-resistant
lineage
(4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South
Asia, including in two common ciprofloxacin-resistant
genotypes.
CONCLUSIONS : The consortium’s aim is to encourage continued data sharing and collaboration to
monitor the emergence and global spread of AMR Typhi, and to inform decision-making
around the
introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies.Fellowships from the European Union (funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council.https://elifesciences.org/am2024Medical MicrobiologySDG-03:Good heatlh and well-bein
ChristopherMayes/Xopt: Xopt v2.2.3
<h2>What's Changed</h2>
<ul>
<li>add robustness and additional test to fixed features functionality in Bayesian generators by @roussel-ryan in https://github.com/ChristopherMayes/Xopt/pull/222</li>
<li>Modularize visualization by @t-bz in https://github.com/ChristopherMayes/Xopt/pull/221</li>
<li>Model construction example by @roussel-ryan in https://github.com/ChristopherMayes/Xopt/pull/223</li>
<li>Include requirement botorch<=0.10.0 for compatibility with python 3.9 by @dylanmkennedy in https://github.com/ChristopherMayes/Xopt/pull/225</li>
<li>Set weights bugfix that creates improper behavior for bayesian exploration by @roussel-ryan in https://github.com/ChristopherMayes/Xopt/pull/224</li>
<li>Update index.md by @roussel-ryan in https://github.com/ChristopherMayes/Xopt/pull/226</li>
<li>Error handling + test improvements by @roussel-ryan in https://github.com/ChristopherMayes/Xopt/pull/227</li>
</ul>
<p><strong>Full Changelog</strong>: https://github.com/ChristopherMayes/Xopt/compare/v2.2.2...v2.2.3</p>