Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros








Base de dados
Assunto principal
Intervalo de ano de publicação
1.
Influenza Other Respir Viruses ; 17(12): e13234, 2023 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-38149926

RESUMO

Few seroprevalence studies have been conducted on coronavirus disease (COVID-19) in Nepal. Here, we aimed to estimate seroprevalence and assess risk factors for infection in the general population of Nepal by conducting two rounds of sampling. The first round was in October 2020, at the peak of the first generalized wave of COVID-19, and the second round in July-August 2021, following the peak of the wave caused by the delta variant of SARS-CoV-2. We used cross-sectional probability-to-size (PPS)-based multistage cluster sampling to estimate the seroprevalence in the general population of Nepal at the national and provincial levels. We tested for anti-SARS-CoV-2 total antibody using the WANTAI SARS-CoV-2 Ab ELISA kit. In Round 1, the overall national seroprevalence was 14.4%, with provincial estimates ranging from 5.3% in Sudurpaschim to 27.3% in Madhesh Province. In Round 2, the estimated national seroprevalence was 70.7%, with the highest in the Madhesh Province (84.8%) and the lowest in the Gandaki Province (62.9%). Seroprevalence was comparable between males and females (Round 1, 15.8% vs. 12.2% and Round 2, 72.3% vs. 68.7%). The seroprevalence in the ecozones-Terai, hills, and mountains-was 76.3%, 65.3%, and 60.5% in Round 2 and 17.7%, 11.7%, and 4.6% in Round 1, respectively. In Nepal, COVID-19 vaccination was introduced in January 2021. At the peak of the first generalized wave of COVID-19, most of the population of Nepal remained unexposed to SARS-CoV-2. Towards the end of the second generalized wave in April 2021, two thirds of the population was exposed.


Assuntos
COVID-19 , Feminino , Masculino , Humanos , COVID-19/epidemiologia , Nepal/epidemiologia , Vacinas contra COVID-19 , Estudos Transversais , Pandemias , Estudos Soroepidemiológicos , SARS-CoV-2 , Anticorpos Antivirais
2.
Curr Dev Nutr ; 7(5): 100063, 2023 May.
Artigo em Inglês | MEDLINE | ID: mdl-37180849

RESUMO

Background: Analyses of predictors of anemia or malnutrition often pool national or regional data, which may hide variability at subnational levels. Objectives: We sought to identify the risk factors for anemia in young Nepali children aged 6-23 mo in 2 districts: Kapilvastu and Achham. Methods: This is an analysis of two cross-sectional surveys that were conducted as part of a program evaluation of an infant and young child feeding and micronutrient powder intervention that included anemia as a primary outcome. Baseline and endline surveys in each district (in 2013 and 2016) included hemoglobin assessments in n = 4709 children who were representative of children 6-23 mo in each district. Log-binomial regression models accounting for the survey design were used to estimate univariable and multivariable prevalence ratios for risk factors at multiple levels-underlying, direct, and biological causes. Average attributable fractions (AFs) for the population were calculated for significant predictor biomarkers of anemia in multivariable models. Results: In Accham, the prevalence of anemia was 31.4%; significant predictors included child's age, household asset ownership, length-for-age z-score, inflammation (CRP concentration > 0.5 mg/L; α-1 acid glycoprotein concentration > 1 mg/mL), and iron deficiency (serum ferritin concentration < 12 µg/L with BRINDA-inflammation adjustment). In Kapilvastu, the prevalence of anemia was 48.1%; significant predictors included child's sex and ethnicity, wasting and weight-for-length z-score, any morbidity in the previous 2 wk, consumption of fortified foods, receipt of multiple micronutrient powder distributions, iron deficiency, zinc deficiency (nonfasting serum zinc concentration of <65 µg/dL in the morning and that of <57 µg/dL in the afternoon), and inflammation. In Achham, average AFs were 28.2% and 19.8% for iron deficiency and inflammation, respectively. Average AFs for anemia in Kapilvastu were 32.1%, 4.2%, and 4.9% for iron deficiency, zinc deficiency, and inflammation, respectively. Conclusions: The prevalence of anemia and its risk factors varied between districts, with inflammation contributing to a greater share of anemia in Achham than in Kapilvastu. The estimated AF for iron deficiency was around 30% in both districts; iron-delivering interventions and multisectoral approaches to anemia are warranted.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA