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- Waagaard, Lovisa, et al.
(författare)
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Body mass index and weight gain in pregnancy and cardiovascular health in middle age: A cohort study
- 2023
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Ingår i: BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY. - : John Wiley & Sons. - 1470-0328 .- 1471-0528.
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To examine associations between body mass index (BMI) in early pregnancy and gestational weight gain (GWG) with cardiovascular health in middle age using the 'Life's Essential 8' (LE8) concept of the American Heart Association (AHA).Design: Population-based cohort study.Setting: Swedish CardioPulmonary bioImage Study (SCAPIS).Population: A total of 8871 women from SCAPIS were included.Methods: Information on cardiovascular health in middle age was collected from SCAPIS and linked to pregnancy weight data obtained from the Swedish Medical Birth Register, with an average follow-up time of 24.5 years. An LE8 score between 0 and 100 was determined, where a score under 60 points was defined as poor cardiovascular health. Binary logistic regression and restricted cubic splines were used.Main outcome measures: Cardiovascular health according to LE8 in middle age.Results: The odds of having poor cardiovascular health in middle age were significantly higher in women who had overweight (adjusted odds ratio, aOR 3.30, 95% CI 2.82-3.88) or obesity (aOR 7.63, 95% CI 5.86-9.94), compared with women classified as being of normal weight in pregnancy. Higher odds were also found for excessive GWG (aOR 1.31, 95% CI 1.09-1.57), compared with women who gained weight within the recommendations. Conclusions: A high BMI in early pregnancy and excessive GWG were associated with greater odds of poor cardiovascular health in middle age. Although further studies are needed, our results highlight pregnancy as an important period to support long-term cardiovascular health.
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| 2. |
- Altmejd, Adam, et al.
(författare)
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Nowcasting COVID-19 statistics reported with delay : A case-study of Sweden and the UK
- 2023
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 20:4
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Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic has demonstrated the importance of unbiased, real-time statistics of trends in disease events in order to achieve an effective response. Because of reporting delays, real-time statistics frequently underestimate the total number of infections, hospitalizations and deaths. When studied by event date, such delays also risk creating an illusion of a downward trend. Here, we describe a statistical methodology for predicting true daily quantities and their uncertainty, estimated using historical reporting delays. The methodology takes into account the observed distribution pattern of the lag. It is derived from the "removal method"-a well-established estimation framework in the field of ecology.
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