Suchergebnisse

AIM: To determine what proportion of the inter‐country variation in death rates can be explained in terms of obesity rates and other known risk factors for coronavirus disease 2019 (COVID‐19). MATERIALS AND METHODS: COVID‐19 death rates from 30 industrialized countries were analysed using linear regression models. Covariates modelled population density, the age structure of the population, obesity, population health, per capita gross domestic product (GDP), ethnic diversity, national temperature and the delay in the government imposing virus control measures. RESULTS: The multivariable regression model explained 63% of the inter‐country variation in COVID‐19 death rates. The initial model was optimized using stepwise selection. In descending order of absolute size of model coefficient, the covariates in the optimized model were the obesity rate, the hypertension rate, population density, life expectancy, the percentage of the population aged older than 65 years, the percentage of the population aged younger than 15 years, the diabetes rate, the delay in imposing national COVID‐19 control measures, per capita GDP and mean temperature (with a negative coefficient indicating an association between higher national temperatures and lower death rates). CONCLUSIONS: A large proportion of the inter‐country variation in COVID‐19 death rates can be explained by differences in obesity rates, population health, population densities, age demographics, delays in imposing national virus control measures, per capita GDP and climate. Some of the unexplained variation is probably attributable to inter‐country differences in the definition of a COVID‐19 death and in the completeness of the recording of COVID‐19 deaths.

ObjectiveTo establish a cohort of children consisting of those born after assisted reproductive technology (ART) in the UK between 1992 and 2009, their naturally conceived siblings (NCS) and matched naturally conceived population controls (NCP) and linking this to postnatal health records up to 2015.
MethodsDeterministic record linkage between the Human Fertilization & Embryology Authority (HFEA) register and Office for National Statistics (ONS) birth registration datasets was carried out to identify a cohort of children born after ART between 1992 and 2009, their NCS, and matched NCP controls (HFEA-ONS linkage). This cohort was linked to the UK Hospital Episode Statistics database to allow monitoring of the child's post-natal health outcomes up to 2015 (HFEA-ONS-HES linkage). Birthweight and health outcomes were compared between groups and by treatment type.
ResultsThe HFEA-ONS linkage consisted of 75348 children born after non-donor ART carried out in the UK between 1st April 1992 and 31st July 2009, 14763 NCS and 164823 matched NCP controls. Of these, 63877 ART, 11343 NCS, and 127544 matched NCP controls were linked to hospital admissions and outpatient data (HFEA-ONS-HES sub-cohort). The study had 1.6-million-person years of follow-up (mean: 12.9 years; range 0-19 years). Children born after fresh embryo transfers were lighter and those born after frozen embryo transfers were heavier than the NCP controls. The within-sibling analyses were directionally consistent with the NCP analyses, but attenuated for the fresh vs NC and increased for the frozen vs NC analyses. ART singletons had increased risk of hospital admission as well as higher admission rates compared to NCP but not NCS.
ConclusionBespoke record linkage was carried out to generate a new child cohort for use in exploring the relationship between conception via ART and short- and long-term health outcomes in offspring. Identification of NCS as well as matched NCP controls allows exploration of the association of ART with adverse offspring outcomes while accounting for parental factors related to sub-fertility which may confound these associations.