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Sökning: WFRF:(Haider Sadia)

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  • Huoman, Johanna, et al. (författare)
  • Childhood CCL18, CXCL10 and CXCL11 levels differentially relate to and predict allergy development
  • 2021
  • Ingår i: Pediatric Allergy and Immunology. - : Wiley. - 0905-6157 .- 1399-3038. ; 32:8, s. 1824-1832
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Chemokines are important mediators in immune cell recruitment, contributing to allergy development. However, extensive studies of chemokines in the circulation in relation to the presence and development of allergic diseases remain scarce. Our aim was to investigate associations of circulating allergy-related chemokines with the development of asthma and sensitization cross-sectionally and longitudinally in a population-based cohort. Methods The chemokines CCL17, CCL22, CXCL10, CXCL11 and CCL18 were measured in plasma samples from children in the Manchester Asthma and Allergy Study. Samples were available from cord blood at birth (n = 376), age 1 (n = 195) and age 8 (n = 334). Cross-sectional and longitudinal association analyses were performed in relation to asthma and allergic sensitization, as well as allergic phenotype clusters previously derived using machine learning in the same study population. Results In children with asthma and/or allergic sensitization, CCL18 levels were consistently elevated at 1 and/or 8 years of ages. In a longitudinal model including information on asthma from 4 time points (5, 8, 11 and 16 years of ages), we observed a significant association between increasing CCL18 levels at age 1 and a higher risk of asthma from early school age to adolescence (OR = 2.9, 95% CI 1.1-7.6, p = .028). We observed similar associations in longitudinal models for allergic sensitization. Asthma later in life was preceded by increased CXCL10 levels after birth and decreased CXCL11 levels at birth. Conclusion Elevated CCL18 levels throughout childhood precede the development of asthma and allergic sensitization. The Th1-associated chemokines CXCL10 and CXCL11 also associated with the development of both outcomes, with differential temporal effects.
  • Micah, Angela E., et al. (författare)
  • Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
  • 2021
  • Ingår i: The Lancet. - : Elsevier BV. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
  • Forskningsöversikt (refereegranskat)abstract
    • Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
  • Wang, Gang, et al. (författare)
  • Spirometric phenotypes from early childhood to young adulthood : a Chronic Airway Disease Early Stratification study
  • 2021
  • Ingår i: ERJ Open Research. - : ERS Publications. - 2312-0541. ; 7:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The prevalences of obstructive and restrictive spirometric phenotypes, and their relation to early-life risk factors from childhood to young adulthood remain poorly understood. The aim was to explore these phenotypes and associations with well-known respiratory risk factors across ages and populations in European cohorts.Methods: We studied 49334 participants from 14 population-based cohorts in different age groups (⩽10, >10–15, >15–20, >20–25 years, and overall, 5–25 years). The obstructive phenotype was defined as forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) z-score less than the lower limit of normal (LLN), whereas the restrictive phenotype was defined as FEV1/FVC z-score ⩾LLN, and FVC z-score Results: The prevalence of obstructive and restrictive phenotypes varied from 3.2–10.9% and 1.8–7.7%, respectively, without clear age trends. A diagnosis of asthma (adjusted odds ratio (aOR=2.55, 95% CI 2.14–3.04), preterm birth (aOR=1.84, 1.27–2.66), maternal smoking during pregnancy (aOR=1.16, 95% CI 1.01–1.35) and family history of asthma (aOR=1.44, 95% CI 1.25–1.66) were associated with a higher prevalence of obstructive, but not restrictive, phenotype across ages (5–25 years). A higher current body mass index (BMI was more often observed in those with the obstructive phenotype but less in those with the restrictive phenotype (aOR=1.05, 95% CI 1.03–1.06 and aOR=0.81, 95% CI 0.78–0.85, per kg·m−2 increase in BMI, respectively). Current smoking was associated with the obstructive phenotype in participants older than 10 years (aOR=1.24, 95% CI 1.05–1.46).Conclusion: Obstructive and restrictive phenotypes were found to be relatively prevalent during childhood, which supports the early origins concept. Several well-known respiratory risk factors were associated with the obstructive phenotype, whereas only low BMI was associated with the restrictive phenotype, suggesting different underlying pathobiology of these two phenotypes.
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