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- Pesce, G., et al.
(författare)
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Low serum DHEA-S is associated with impaired lung function in women
- 2020
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Ingår i: EClinicalMedicine. - : Elsevier BV. - 2589-5370. ; 23
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Tidskriftsartikel (refereegranskat)abstract
- Background: Emerging evidence suggests that androgens and estrogens have a role in respiratory health, but it is largely unknown whether levels of these hormones can affect lung function in adults from the general population. This study investigated whether serum dehydroepiandrosterone sulfate (DHEA-S), a key precursor of both androgens and estrogens in peripheral tissues, was related to lung function in adult women participating in the European Community Respiratory Health Survey (ECRHS). Methods: Lung function and serum DHEA-S concentrations were measured in n = 2,045 and n = 1,725 women in 1999–2002 and in 2010–2013, respectively. Cross-sectional associations of DHEA-S levels (expressed as age-adjusted z-score) with spirometric outcomes were investigated, adjusting for smoking habits, body mass index, menopausal status, and use of corticosteroids. Longitudinal associations of DHEA-S levels in 1999–2002 with incidence of restrictive pattern and airflow limitation in 2010–2013 were also assessed. Findings: Women with low DHEA-S (z-score<-1) had lower FEV1 (% of predicted, adjusted difference: -2.2; 95%CI: -3.5 to -0.9) and FVC (-1.7; 95%CI: -2.9 to -0.5) and were at a greater risk of having airflow limitation and restrictive pattern on spirometry than women with higher DHEA-S levels. In longitudinal analyses, low DHEA-S at baseline was associated with a greater incidence of airflow limitation after an 11-years follow-up (incidence rate ratio, 3.43; 95%CI: 1.91 to 6.14). Interpretation: Low DHEA-S levels in women were associated with impaired lung function and a greater risk of developing airflow limitation later in adult life. Our findings provide new evidence supporting a role of DHEA-S in respiratory health. Funding: EU H2020, grant agreement no.633212 © 2020 The Authors
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| 2. |
- Triebner, K., et al.
(författare)
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Describing the status of reproductive ageing simply and precisely: A reproductive ageing score based on three questions and validated with hormone levels
- 2020
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:6
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Tidskriftsartikel (refereegranskat)abstract
- Equation 6. Quadratic logistic function approximating the function mu(B)(with age in years). Equation 1. Proportion of women who have regular menstruation for each number of reported menstruations in the last year(with period = number of periods per year, x = number of women answering "Yes" to the question: "Do you have regular periods?", y = number of women answering "No, they have been irregular for a few months" and z = number of women answering "No, my periods have stopped", e.g. x(11) = number of women reporting regular menstruation among those who report 11 menstruations in the last 12 months). Equation 5. Biquadratic exponential function mu(A)depending of the number of periods. Equation 3. Age modification by smoking and oophorectomy. Equation 2. Proportion of women whose menstruations have already stopped, for each reported year of age(with age = age in years, x = number of women answering "Yes" to the question: "Do you have regular periods?", y = number of women answering "No, they have been irregular for a few months", z = number of women answering "No, my periods have stopped", e.g. x(40) = number of women reporting regular menstruations among those who are 40 years old). Equation 7. Final formula to calculate the reproductive ageing score (RAS)(with period being the number of periods per year and age as the age in years, modified according to smoking status and oophorectomy). Objective Most women live to experience menopause and will spend 4-8 years transitioning from fertile age to full menstrual stop. Biologically, reproductive ageing is a continuous process, but by convention, it is defined categorically as pre-, peri- and postmenopause; categories that are sometimes supported by measurements of sex hormones in blood samples. We aimed to develop and validate a new tool, a reproductive ageing score (RAS), that could give a simple and yet precise description of the status of reproductive ageing, without hormone measurements, to be used by health professionals and researchers. Methods Questionnaire data on age, menstrual regularity and menstrual frequency was provided by the large multicentre population-based RHINE cohort. A continuous reproductive ageing score was developed from these variables, using techniques of fuzzy mathematics, to generate a decimal number ranging from 0.00 (nonmenopausal) to 1.00 (postmenopausal). The RAS was then validated with sex hormone measurements (follicle stimulating hormone and 17 beta-estradiol) and interview-data provided by the large population-based ECRHS cohort, using receiver-operating characteristics (ROC). Results The RAS, developed from questionnaire data of the RHINE cohort, defined with high precision and accuracy the menopausal status as confirmed by interview and hormone data in the ECRHS cohort. The area under the ROC curve was 0.91 (95% Confidence interval (CI): 0.90-0.93) to distinguish nonmenopausal women from peri- and postmenopausal women, and 0.85 (95% CI: 0.83-0.88) to distinguish postmenopausal women from nonmenopausal and perimenopausal women. Conclusions The RAS provides a useful and valid tool for describing the status of reproductive ageing accurately, on a continuous scale from 0.00 to 1.00, based on simple questions and without requiring blood sampling. The score allows for a more precise differentiation than the conventional categorisation in pre-, peri- and postmenopause. This is useful for epidemiological research and clinical trials. Equation 4. The reproductive ageing score as an aggregation function of mu(A)and mu(B).
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