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- Amid Hägg, Shadi, et al.
(author)
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Smokers with insomnia symptoms are less likely to stop smoking
- 2020
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In: Respiratory Medicine. - : Elsevier BV. - 0954-6111 .- 1532-3064. ; 170
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Journal article (peer-reviewed)abstract
- Objectives: Smoking is associated with sleep disturbances. The aim of this study was to analyze whether sleep disturbances are predictors of smoking cessation and whether continued smoking is associated with the development of sleep disturbances. Methods: A questionnaire was sent to randomly selected men and women in Northern Europe in 1999-2001 (RHINE II) and was followed up by a questionnaire in 2010-2012 (RHINE III). The study population consisted of 2568 participants who were smokers at baseline and provided data on smoking at follow-up. Insomnia symptoms were defined as having difficulty initiating and/or maintaining sleep and/or early morning awakening >= 3 nights/week. Multiple logistic regression analyses were performed to calculate odds ratios (OR). Results: Subjects with difficulty initiating sleep (adjusted odds ratio; 95% confidence interval: 0.6; 0.4-0.8), difficulty maintaining sleep (0.7; 0.5-0.9), early morning awakening (0.6; 0.4-0.8), any insomnia symptom (0.6; 0.5-0.8) or excessive daytime sleepiness (0.7; 0.5-0.8) were less likely to achieve long-term smoking cessation after adjustment for age, BMI, pack-years, hypertension, diabetes, chronic bronchitis, rhinitis, asthma, gender and BMI difference. There was no significant association between snoring and smoking cessation. In subjects without sleep disturbance at baseline, continued smoking increased the risk of developing difficulty initiating sleep during the follow-up period compared with those that had quit smoking (adj. OR 1.7, 95% CI 1.2-2.3). Conclusions: Insomnia symptoms and excessive daytime sleepiness negatively predict smoking cessation. Smoking is a risk factor for the development of difficulty initiating sleep. Treatment for sleep disturbances should be included in smoking-cessation programs.
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| 2. |
- Knudsen, G. T. M., et al.
(author)
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Parents' smoking onset before conception as related to body mass index and fat mass in adult offspring: Findings from the RHINESSA generation study
- 2020
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In: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 15:7
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Journal article (peer-reviewed)abstract
- Emerging evidence suggests that parents' preconception exposures may influence offspring health. We aimed to investigate maternal and paternal smoking onset in specific time windows in relation to offspring body mass index (BMI) and fat mass index (FMI). We investigated fathers (n = 2111) and mothers (n = 2569) aged 39-65 years, of the population based RHINE and ECRHS studies, and their offspring aged 18-49 years (n = 6487, mean age 29.6 years) who participated in the RHINESSA study. BMI was calculated from self-reported height and weight, and FMI was estimated from bioelectrical impedance measures in a subsample. Associations with parental smoking were analysed with generalized linear regression adjusting for parental education and clustering by study centre and family. Interactions between offspring sex were analysed, as was mediation by parental pack years, parental BMI, offspring smoking and offspring birthweight. Fathers' smoking onset before conception of the offspring (onset >= 15 years) was associated with higher BMI in the offspring when adult (beta 0.551, 95%CI: 0.174-0.929, p = 0.004). Mothers' preconception and postnatal smoking onset was associated with higher offspring BMI (onset <15 years: beta 1.161, 95%CI 0.378-1.944; onset >= 15 years: beta 0.720, 95%CI 0.293-1.147; onset after offspring birth: beta 2.257, 95%CI 1.220-3.294). However, mediation analysis indicated that these effects were fully mediated by parents' postnatal pack years, and partially mediated by parents' BMI and offspring smoking. Regarding FMI, sons of smoking fathers also had higher fat mass (onset <15 years beta 1.604, 95%CI 0.269-2.939; onset >= 15 years beta 2.590, 95%CI 0.544-4.636; and onset after birth beta 2.736, 95%CI 0.621-4.851). There was no association between maternal smoking and offspring fat mass. We found that parents' smoking before conception was associated with higher BMI in offspring when they reached adulthood, but that these effects were mediated through parents' pack years, suggesting that cumulative smoking exposure during offspring's childhood may elicit long lasting effects on offspring BMI.
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| 3. |
- Kuiper, I. N., et al.
(author)
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Associations of Preconception Exposure to Air Pollution and Greenness with Offspring Asthma and Hay Fever
- 2020
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In: International Journal of Environmental Research and Public Health. - : MDPI AG. - 1660-4601 .- 1661-7827. ; 17:16
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Journal article (peer-reviewed)abstract
- We investigated if greenness and air pollution exposure in parents' childhood affect offspring asthma and hay fever, and if effects were mediated through parental asthma, pregnancy greenness/pollution exposure, and offspring exposure. We analysed 1106 parents with 1949 offspring (mean age 35 and 6) from the Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) generation study. Mean particulate matter (PM(2.5)and PM10), nitrogen dioxide (NO2), black carbon (BC), ozone (O-3) (mu g/m(3)) and greenness (normalized difference vegetation index (NDVI)) were calculated for parents 0-18 years old and offspring 0-10 years old, and were categorised in tertiles. We performed logistic regression and mediation analyses for two-pollutant models (clustered by family and centre, stratified by parental lines, and adjusted for grandparental asthma and education). Maternal medium PM(2.5)and PM(10)exposure was associated with higher offspring asthma risk (odds ratio (OR) 2.23, 95%CI 1.32-3.78, OR 2.27, 95%CI 1.36-3.80), and paternal high BC exposure with lower asthma risk (OR 0.31, 95%CI 0.11-0.87). Hay fever risk increased for offspring of fathers with medium O(3)exposure (OR 4.15, 95%CI 1.28-13.50) and mothers with high PM(10)exposure (OR 2.66, 95%CI 1.19-5.91). The effect of maternal PM(10)exposure on offspring asthma was direct, while for hay fever, it was mediated through exposures in pregnancy and offspring's own exposures. Paternal O(3)exposure had a direct effect on offspring hay fever. To conclude, parental exposure to air pollution appears to influence the risk of asthma and allergies in future offspring.
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| 4. |
- Timm, S., et al.
(author)
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Does parental farm upbringing influence the risk of asthma in offspring? A three-generation study
- 2020
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In: International journal of epidemiology. - : Oxford University Press (OUP). - 0300-5771 .- 1464-3685. ; 49:6, s. 1874-1882
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Journal article (peer-reviewed)abstract
- Background: A farm upbringing has been associated with lower risk of asthma and methylation of asthma-related genes. As such, a farm upbringing has the potential to transfer asthma risk across generations, but this has never been investigated. We aimed to study the generational effects from a parental farm upbringing on offspring asthma. Methods: Our study involved three generations: 5759 participants from the European Community Respiratory Health Survey (ECRHS) study (born 1945-1971, denoted G1), their 9991 parents (GO) and their 8260 offspring (G2) participating in RHINESSA (Respiratory Health In Northern Europe, Spain and Australia). Questionnaire data were collected on GO and G1 from G1 in 2010 and on G2 from themselves in 2013. The parental/grandparental place of upbringing was categorized: (i) both parents from farm; (ii) mother from farm, father from village/city; (iii) father from farm, mother from village/city; (iv) both parents from village or one parent from village and one from city; (v) both parents from city (reference group). Grandparental upbringing was equivalently categorized. Offspring asthma was self-reported and data were analysed using Cox-regression models with G2 age as the time scale. Results: A parental farm upbringing was not associated with offspring asthma when compared with city upbringing [hazard ratio (HR) 1.12, 95% confidence interval (CI) 0.74-1.69]. Findings remained similar when stratified by offspring upbringing and asthma phenotypes. Quantitative bias analyses showed similar estimates for alternative data sources. A grandparental farm upbringing was not associated with offspring asthma in either the maternal (HR 1.05, 95% CI 0.67-1.65) or paternal line (HR 1.02, 95% CI 0.62-1.68). Conclusions: This multigenerational analysis suggests no evidence of an association between parental/grandparental farm upbringing and offspring asthma.
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| 5. |
- Triebner, K., et al.
(author)
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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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In: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:6
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Journal article (peer-reviewed)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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| 6. |
- Wang, Juan, et al.
(author)
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Dampness and mold at home and at work and onset of insomnia symptoms, snoring and excessive daytime sleepiness
- 2020
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In: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 139
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Journal article (peer-reviewed)abstract
- Aim: To investigate whether exposure to dampness and mold at home and at work induce sleep disturbances and daytime sleepiness among adults. Materials and methods: Associations between onset of sleep disturbances and dampness, mold and mold odor at home and at work were investigated in a cohort of 11,318 adults from the population in Iceland, Norway, Sweden, Denmark and Estonia. The participants answered a questionnaire at baseline and 10 years later, with questions on sleep disturbances, including difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), early morning awakening (EMA), insomnia symptoms, snoring and excessive daytime sleepiness (EDS). Multiple logistic regression models were applied to estimate associations adjusting for potential confounders including gender, age, smoking habit at baseline, change of smoking habit from baseline to follow up, BMI at baseline, change of BMI from baseline to follow up, education level at follow up, allergic rhinitis at baseline, doctor diagnosed asthma at baseline and chronic bronchitis at baseline. Results: Baseline floor dampness, visible mold and mold odor at home increased onset of DIS, DMS, EMA, insomnia symptoms and snoring during follow up (OR 1.29–1.87). Any sign of dampness at baseline increased onset of DIS (OR 1.28, 95%CI 1.06–1.55), DMS (OR 1.17, 95%CI 1.02–1.34) and insomnia symptoms (OR 1.18, 95%CI 1.03–1.36). Dampness at home during follow up increased onset of DIS, DMS, EMA, insomnia symptoms and EDS (OR 1.17–1.36). Dampness at work during follow up increased onset of DIS, EMA, insomnia symptoms and EDS (OR 1.16–1.34). Combined dampness at home and at work during follow up increased the risk of onset of DIS, DMS, EMA, insomnia symptoms and EDS (OR 1.29–1.74). Conclusions: Dampness and mold at home and at work can increase the development of insomnia symptoms, snoring and EDS among adults. © 2020 The Authors
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