547 research outputs found

    A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education

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    <p>Abstract</p> <p>Background</p> <p>Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity.</p> <p>Methods</p> <p>Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures.</p> <p>Results</p> <p>The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group.</p> <p>Conclusions</p> <p>Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.</p

    Multi-level modeling of social factors and preterm delivery in Santiago de Chile

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    <p>Abstract</p> <p>Background</p> <p>Birth before the 37th week of gestation (preterm birth) is an important cause of infant and neonatal mortality, but has been little studied outside of wealthy nations. Chile is an urbanized Latin American nation classified as "middle-income" based on its annual income per capita of about $6000.</p> <p>Methods</p> <p>We studied the relations between maternal social status and neighborhood social status on risk of preterm delivery in this setting using multilevel regression analyses of vital statistics data linked to geocoded decennial census data. The analytic data set included 56,970 births from 2004 in the metropolitan region of Santiago, which constitutes about 70% of all births in the study area and about 25% of all births in Chile that year. Dimensionality of census data was reduced using principal components analysis, with regression scoring to create a single index of community socioeconomic advantage. This was modeled along with years of maternal education in order to predict preterm birth and preterm low birthweight.</p> <p>Results</p> <p>Births in Santiago displayed an advantaged pattern of preterm risk, with only 6.4% of births delivering before 37 weeks. Associations were observed between risk of outcomes and individual and neighborhood factors, but the magnitudes of these associations were much more modest than reported in North America.</p> <p>Conclusion</p> <p>While several potential explanations for this relatively flat social gradient might be considered, one possibility is that Chile's egalitarian approach to universal prenatal care may have reduced social inequalities in these reproductive outcomes.</p

    Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms

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    Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). Conclusion: The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended. Keywords: Clinical prediction model; Long COVID; Prognostic factors; Stratified medicin

    Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus

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    Objective To assess whether genetically determined Amerindian ancestry predicts increased presence of risk alleles of known susceptibility genes for systemic lupus erythematosus (SLE). Methods Single-nucleotide polymorphisms (SNPs) within 16 confirmed genetic susceptibility loci for SLE were genotyped in a set of 804 Mestizo lupus patients and 667 Mestizo healthy controls. In addition, 347 admixture informative markers were genotyped. Individual ancestry proportions were determined using STRUCTURE. Association analysis was performed using PLINK, and correlation between ancestry and the presence of risk alleles was analyzed using linear regression. Results A meta-analysis of the genetic association of the 16 SNPs across populations showed that TNFSF4 , STAT4 , ITGAM , and IRF5 were associated with lupus in a Hispanic Mestizo cohort enriched for European and Amerindian ancestry. In addition, 2 SNPs within the major histocompatibility complex region, previously shown to be associated in a genome-wide association study in Europeans, were also associated in Mestizos. Using linear regression, we predicted an average increase of 2.34 risk alleles when comparing an SLE patient with 100% Amerindian ancestry versus an SLE patient with 0% Amerindian ancestry ( P < 0.0001). SLE patients with 43% more Amerindian ancestry were predicted to carry 1 additional risk allele. Conclusion Our results demonstrate that Amerindian ancestry is associated with an increased number of risk alleles for SLE.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78480/1/27753_ftp.pd

    Bodyweight Perceptions among Texas Women: The Effects of Religion, Race/Ethnicity, and Citizenship Status

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    Despite previous work exploring linkages between religious participation and health, little research has looked at the role of religion in affecting bodyweight perceptions. Using the theoretical model developed by Levin et al. (Sociol Q 36(1):157–173, 1995) on the multidimensionality of religious participation, we develop several hypotheses and test them by using data from the 2004 Survey of Texas Adults. We estimate multinomial logistic regression models to determine the relative risk of women perceiving themselves as overweight. Results indicate that religious attendance lowers risk of women perceiving themselves as very overweight. Citizenship status was an important factor for Latinas, with noncitizens being less likely to see themselves as overweight. We also test interaction effects between religion and race. Religious attendance and prayer have a moderating effect among Latina non-citizens so that among these women, attendance and prayer intensify perceptions of feeling less overweight when compared to their white counterparts. Among African American women, the effect of increased church attendance leads to perceptions of being overweight. Prayer is also a correlate of overweight perceptions but only among African American women. We close with a discussion that highlights key implications from our findings, note study limitations, and several promising avenues for future research

    A genome-wide identification and comparative analysis of the lentil MLO genes

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    Revista electrónica on linePowdery mildew is a widespread fungal plant disease that can cause significant losses in many crops. Some MLO genes (Mildew resistance locus O) have proved to confer a durable resistance to powdery mildew in several species. Resistance granted by the MLO gene family members has prompted an increasing interest in characterizing these genes and implementing their use in plant breeding. Lentil (Lens culinaris Medik.) is a widely grown food legume almost exclusively consumed as dry seed with an average world production of 4.5 million tons. Powdery mildew causes severe losses on certain lentil cultivars under particular environmental conditions. Data mining of the lentil CDC Redberry draft genome allowed to identify up to 15 gene sequences with homology to known MLO genes, designated as LcMLOs. Further characterization of these gene sequences and their deduced protein sequences demonstrated conformity with key MLO protein characteristics such as the presence of transmembrane and calmodulin binding domains, as well as that of other conserved motifs. Phylogenetic and other comparative analyses revealed that LcMLO1 and LcMLO3 are the most likely gene orthologs related to powdery mildew response in other species, sharing a high similarity with other known resistance genes of dicot species, such as pea PsMLO1 and Medicago truncatula MtMLO1 and MtMLO3. Sets of primers were designed as tools to PCR amplify the genomic sequences of LcMLO1 and LcMLO3, also to screen lentil germplasm in search of resistance mutants. Primers were used to obtain the complete sequences of these two genes in all of the six wild lentil relatives. Respective to each gene, all Lens sequences shared a high similarity. Likewise, we used these primers to screen a working collection of 58 cultivated and 23 wild lentil accessions in search of length polymorphisms present in these two genes. All these data widen the insights on this gene family and can be useful for breeding programs in lentil and close related species.S

    Does Time Since Immigration Modify Neighborhood Deprivation Gradients in Preterm Birth? A Multilevel Analysis

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    Immigrants’ health is jointly influenced by their pre- and post-migration exposures, but how these two influences operate with increasing duration of residence has not been well-researched. We aimed to examine how the influence of maternal country of birth and neighborhood deprivation effects, if any, change over time since migration and how neighborhood effects among immigrants compare with those observed in the Canadian-born population. Birth data from Ontario hospital records (2002–2007) were linked with an official Canadian immigration database (1985–2000). The outcome measure was preterm birth. Neighborhoods were ranked according to a neighborhood deprivation index developed for Canadian urban areas and collapsed into tertiles of approximately equal size. Time since immigration was measured from the date of arrival to Canada to the date of delivery, ranging from 1 to 22 years. We used cross-classified random effect models to simultaneously account for the membership of births (N = 83,233) to urban neighborhoods (N = 1,801) and maternal countries of birth (N = 168). There were no differences in preterm birth between neighborhood deprivation tertiles among immigrants with less than 15 years of residence. Among immigrants with 15 years of stay or more, the adjusted absolute risk difference (ARD%, 95% confidence interval) between high-deprived (tertile 3) and low-deprived (tertile 1) neighborhoods was 1.86 (0.68, 2.98), while the ARD% observed among the Canadian-born (N = 314,237) was 1.34 (1.11, 1.57). Time since migration modifies the neighborhood deprivation gradient in preterm birth among immigrants living in Ontario cities. Immigrants reached the level of inequalities in preterm birth observed at the neighborhood level among the Canadian-born after 14 years of stay, but neighborhoods did not influence preterm birth among more recent immigrants, for whom the maternal country of birth was more predictive of preterm birth

    Spatial abundance and clustering of Culicoides (Diptera: Ceratopogonidae) on a local scale

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    BACKGROUND: Biting midges, Culicoides, of the Obsoletus group and the Pulicaris group have been involved in recent outbreaks of bluetongue virus and the former was also involved in the Schmallenberg virus outbreak in northern Europe. METHODS: For the first time, here we investigate the local abundance pattern of these two species groups in the field by intensive sampling with a grid of light traps on 16 catch nights. Neighboring trap catches can be spatially dependent on each other, hence we developed a conditional autoregressive (CAR) model framework to test a number of spatial and non-spatial covariates expected to affect Culicoides abundance. RESULTS: The distance to sheep penned in the corner of the study field significantly increased the abundance level up to 200 meters away from the sheep. Spatial clustering was found to be significant but could not be explained by any known factors, and cluster locations shifted between catch nights. No significant temporal autocorrelation was detected. CAR models for both species groups identified a significant positive impact of humidity and significant negative impacts of precipitation and wind turbulence. Temperature was also found to be significant with a peak at just below 16 degrees Celcius. Surprisingly, there was a significant positive impact of wind speed. The CAR model for the Pulicaris group also identified a significant attraction to the smaller groups of sheep placed in the field. Furthermore, a large number of spatial covariates which were incorrectly found to be significant in ordinary regression models were not significant in the CAR models. The 95% C.I. on the prediction estimates ranged from 20.4% to 304.8%, underlining the difficulties of predicting the abundance of Culicoides. CONCLUSIONS: We found that significant spatial clusters of Culicoides moved around in a dynamic pattern varying between catch nights. This conforms with the modeling but was not explained by any of the tested covariates. The mean abundance within these clusters was up to 11 times higher for the Obsoletus group and 4 times higher for the Pulicaris group compared to the rest of the field
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