Aims: To investigate the relative contribution of genetic and environmental factors on smoking trajectory membership and to test whether individual smoking trajectories represent phenotypical thresholds of increasing genetic risk along a common genetic liability dimension.
Design: Prospective study of a birth cohort of female like-sex twin pairs.
Setting: Participants completed diagnostic interview surveys four times from adolescence (average age 16) to young adulthood (average age 25).
Participants: Female twins who had smoked ≥100 cigarettes life-time (n = 1466 regular smokers).
Measurements: Number of cigarettes smoked per day during the heaviest period of smoking (two waves) or during the past 12 months (two waves).
Findings: A four-trajectory class solution provided the best fit to cigarette consumption data and was characterized by low (n = 564, 38.47%), moderate (n = 366, 24.97%) and high-level smokers (n = 197, 13.44%), and smokers who increased their smoking from adolescence to young adulthood (n =339, 23.12%). The best genetic model fit was a three-category model that comprised the low, a combined increasing + moderate and high trajectories. This trajectory categorization was heritable (72.7%), with no evidence for significant contribution from shared environmental factors.
Conclusions: The way in which smoking patterns develop in adolescence has a high level of heritability.
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http://dx.doi.org/10.1111/j.1360-0443.2012.03871.x | DOI Listing |
PLoS One
January 2025
Department of Psychology, Crean College of Health and Behavioral Sciences, Chapman University, Orange, California, United States of America.
Background: Mobile sensing technology allows automated behavior shaping routines to be incorporated into health behavior interventions and other settings. In previous work, a computational model was built to investigate how to best arrange automatic behavior shaping procedures, but the degree to which this model reflects actual human behavior is not known.
Purpose: To translate a previously developed computational model of automatic behavior shaping into an experimental setting.
Alzheimers Dement (Amst)
January 2025
Health Care Research Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Greifswald Mecklenburg-Vorpommern Germany.
Introduction: This study investigated the association between modifiable factors and symptom progression in dementia over up to 8 years.
Methods: Multilevel growth curve models assessed the role of modifiable risk factors (low education, hearing impairment and its treatment, depression, physical inactivity, diabetes and its treatment, smoking, hypertension and its treatment, obesity, alcohol consumption, social isolation, and visual impairment) on cognitive and functional trajectories in 353 people with dementia.
Results: Higher education was associated with higher initial cognitive status but faster decline.
J Appl Gerontol
January 2025
Seoul National University, Seoul, Republic of Korea.
This study aims to examine the trajectory of older adults' cognitive function over time and identify its predictors. Based on the model of neuroplasticity and cognitive reserve, participants' general characteristics as well as their physical, mental, and social factors were included as predictors of cognitive function. A latent growth model analysis was used to examine the trajectory of cognitive function and its predictors.
View Article and Find Full Text PDFBMJ Open
December 2024
Department of Public Health, University of Helsinki, Helsinki, Finland.
Objectives: This study aimed to identify distinct trajectories of long-term sickness absence (LTSA, >10 consecutive working days) among young and early midlife Finnish employees who experienced pain at baseline. It also aimed to determine the pain characteristics and occupational and lifestyle factors associated with these LTSA patterns.
Design: Longitudinal occupational cohort study with register linkage.
Respirology
January 2025
Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Background: Some individuals never achieve normal peak FEV in early adulthood. It is unknown if this is due to airflow limitation and/or lung restriction.
Methods: To investigate this, we: (1) looked forward in 19,791 participants in the Dutch Lifelines general population cohort aged 25-35 years with 5-year follow-up; and (2) looked backwards in 2032 participants in the Swedish BAMSE birth cohort with spirometry at 24 years of age but also at 16 and/or 8 years.
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