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The Decomposition of Shared Environmental Influences on Externalizing Syndromes in the Swedish Population: A Multivariate Study.

https://arctichealth.org/en/permalink/ahliterature289628
Source
Twin Res Hum Genet. 2017 08; 20(4):298-309
Publication Type
Clinical Trial
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Date
08-2017
Author
Henrik Ohlsson
Kenneth S Kendler
Paul Lichtenstein
Jan Sundquist
Kristina Sundquist
Author Affiliation
Center for Primary Health Care Research,Lund University,Malmö,Sweden.
Source
Twin Res Hum Genet. 2017 08; 20(4):298-309
Date
08-2017
Language
English
Publication Type
Clinical Trial
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Keywords
Adult
Alcoholism - genetics
Criminal Behavior
Environment
Family
Female
Humans
Male
Middle Aged
Models, Genetic
Registries
Substance-Related Disorders - genetics
Sweden
Syndrome
Abstract
Using information from Swedish population registries, we attempt to decompose the shared environment (C) into four subcomponents: close family, family, household, and community. Among pairs differing in their genetic and geographical/household relationships, we examine three externalizing syndromes: drug abuse (DA), criminal behavior (CB), and alcohol use disorders (AUD). The best-fitting common pathway model suggested that total estimates for C were higher for DA (21% for males and 18% for females) than for AUD (16% and 14%) and CB (17% and 10%). Concerning syndrome-specific influences in males, close family effects were stronger for CB and AUD, while community effects were stronger for DA. The two C components in between community experiences and close family experiences (family and household) were estimated to almost entirely derive from the common latent factor. In females, among the four components of C, the community experiences were just slightly above zero, while the C components referred to as the household effect were almost zero. The total close family experiences were similar and most important across syndromes were also divided into common and specific components. For all syndromes, for both males and females, the effects of additive genetic factors were 2-4 times the size of the total effect of the shared environment. Applying standard methods to novel relationships, we expand our understanding of how the shared environment contributes to individual differences in three externalizing syndromes.
Notes
Cites: Psychol Med. 2015 Aug;45(11):2253-62 PMID 25936380
Cites: Psychol Bull. 2009 Jul;135(4):608-37 PMID 19586164
Cites: Behav Genet. 2016 Mar;46(2):183-92 PMID 26494460
Cites: Psychol Med. 2015 Apr;45(5):1061-72 PMID 25171596
Cites: Am J Psychiatry. 2014 Feb;171(2):209-17 PMID 24077613
Cites: Psychol Med. 2014 Jul;44(9):1913-25 PMID 24180693
Cites: Soc Psychiatry Psychiatr Epidemiol. 2015 Aug;50(8):1277-84 PMID 25708193
Cites: Nat Genet. 2012 Feb 19;44(3):247-50 PMID 22344220
Cites: Psychol Med. 2014 Nov;44(15):3181-7 PMID 24766797
Cites: Psychol Med. 2015 Oct;45(13):2897-907 PMID 26040779
Cites: J Abnorm Psychol. 1992 Feb;101(1):3-17 PMID 1537970
Cites: J Adolesc. 2012 Aug;35(4):823-31 PMID 22240325
Cites: J Subst Abuse. 2001;13(4):391-424 PMID 11775073
Cites: Psychol Sci. 2003 May;14(3):273-7 PMID 12741753
Cites: J Child Psychol Psychiatry. 2014 Apr;55(4):304-12 PMID 24261560
Cites: Am J Psychiatry. 2003 Apr;160(4):687-95 PMID 12668357
Cites: Psychometrika. 2016 Jun;81(2):535-49 PMID 25622929
Cites: Behav Genet. 2002 May;32(3):221-7 PMID 12141783
Cites: Psychol Bull. 2002 May;128(3):490-529 PMID 12002699
Cites: JAMA Psychiatry. 2015 Mar;72(3):211-8 PMID 25565339
Cites: Arch Gen Psychiatry. 2012 Jul;69(7):690-7 PMID 22393206
Cites: Soc Psychiatry Psychiatr Epidemiol. 2013 Nov;48(11):1841-9 PMID 23344783
Cites: Psychol Med. 2000 Mar;30(2):281-94 PMID 10824649
Cites: JAMA Psychiatry. 2013 Feb;70(2):235-42 PMID 23229904
Cites: Psychol Med. 2016 Jun;46(8):1639-50 PMID 26996079
Cites: Nature. 2014 Feb 13;506(7487):185-90 PMID 24463508
Cites: Arch Gen Psychiatry. 1997 Feb;54(2):178-84 PMID 9040286
Cites: Nature. 2009 Aug 6;460(7256):748-52 PMID 19571811
Cites: Behav Genet. 1994 Jan;24(1):35-49 PMID 8192619
PubMed ID
28578747 View in PubMed
Less detail

The Decomposition of Shared Environmental Influences on Externalizing Syndromes in the Swedish Population: A Multivariate Study.

https://arctichealth.org/en/permalink/ahliterature289470
Source
Twin Res Hum Genet. 2017 08; 20(4):298-309
Publication Type
Clinical Trial
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Date
08-2017
Author
Henrik Ohlsson
Kenneth S Kendler
Paul Lichtenstein
Jan Sundquist
Kristina Sundquist
Author Affiliation
Center for Primary Health Care Research,Lund University,Malmö,Sweden.
Source
Twin Res Hum Genet. 2017 08; 20(4):298-309
Date
08-2017
Language
English
Publication Type
Clinical Trial
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Keywords
Adult
Alcoholism - genetics
Criminal Behavior
Environment
Family
Female
Humans
Male
Middle Aged
Models, Genetic
Registries
Substance-Related Disorders - genetics
Sweden
Syndrome
Abstract
Using information from Swedish population registries, we attempt to decompose the shared environment (C) into four subcomponents: close family, family, household, and community. Among pairs differing in their genetic and geographical/household relationships, we examine three externalizing syndromes: drug abuse (DA), criminal behavior (CB), and alcohol use disorders (AUD). The best-fitting common pathway model suggested that total estimates for C were higher for DA (21% for males and 18% for females) than for AUD (16% and 14%) and CB (17% and 10%). Concerning syndrome-specific influences in males, close family effects were stronger for CB and AUD, while community effects were stronger for DA. The two C components in between community experiences and close family experiences (family and household) were estimated to almost entirely derive from the common latent factor. In females, among the four components of C, the community experiences were just slightly above zero, while the C components referred to as the household effect were almost zero. The total close family experiences were similar and most important across syndromes were also divided into common and specific components. For all syndromes, for both males and females, the effects of additive genetic factors were 2-4 times the size of the total effect of the shared environment. Applying standard methods to novel relationships, we expand our understanding of how the shared environment contributes to individual differences in three externalizing syndromes.
Notes
Cites: Psychol Med. 2015 Aug;45(11):2253-62 PMID 25936380
Cites: Psychol Bull. 2009 Jul;135(4):608-37 PMID 19586164
Cites: Behav Genet. 2016 Mar;46(2):183-92 PMID 26494460
Cites: Psychol Med. 2015 Apr;45(5):1061-72 PMID 25171596
Cites: Am J Psychiatry. 2014 Feb;171(2):209-17 PMID 24077613
Cites: Psychol Med. 2014 Jul;44(9):1913-25 PMID 24180693
Cites: Soc Psychiatry Psychiatr Epidemiol. 2015 Aug;50(8):1277-84 PMID 25708193
Cites: Nat Genet. 2012 Feb 19;44(3):247-50 PMID 22344220
Cites: Psychol Med. 2014 Nov;44(15):3181-7 PMID 24766797
Cites: Psychol Med. 2015 Oct;45(13):2897-907 PMID 26040779
Cites: J Abnorm Psychol. 1992 Feb;101(1):3-17 PMID 1537970
Cites: J Adolesc. 2012 Aug;35(4):823-31 PMID 22240325
Cites: J Subst Abuse. 2001;13(4):391-424 PMID 11775073
Cites: Psychol Sci. 2003 May;14(3):273-7 PMID 12741753
Cites: J Child Psychol Psychiatry. 2014 Apr;55(4):304-12 PMID 24261560
Cites: Am J Psychiatry. 2003 Apr;160(4):687-95 PMID 12668357
Cites: Psychometrika. 2016 Jun;81(2):535-49 PMID 25622929
Cites: Behav Genet. 2002 May;32(3):221-7 PMID 12141783
Cites: Psychol Bull. 2002 May;128(3):490-529 PMID 12002699
Cites: JAMA Psychiatry. 2015 Mar;72(3):211-8 PMID 25565339
Cites: Arch Gen Psychiatry. 2012 Jul;69(7):690-7 PMID 22393206
Cites: Soc Psychiatry Psychiatr Epidemiol. 2013 Nov;48(11):1841-9 PMID 23344783
Cites: Psychol Med. 2000 Mar;30(2):281-94 PMID 10824649
Cites: JAMA Psychiatry. 2013 Feb;70(2):235-42 PMID 23229904
Cites: Psychol Med. 2016 Jun;46(8):1639-50 PMID 26996079
Cites: Nature. 2014 Feb 13;506(7487):185-90 PMID 24463508
Cites: Arch Gen Psychiatry. 1997 Feb;54(2):178-84 PMID 9040286
Cites: Nature. 2009 Aug 6;460(7256):748-52 PMID 19571811
Cites: Behav Genet. 1994 Jan;24(1):35-49 PMID 8192619
PubMed ID
28578747 View in PubMed
Less detail

Do weather changes influence physical activity level among older adults? - The Generation 100 study.

https://arctichealth.org/en/permalink/ahliterature297393
Source
PLoS One. 2018; 13(7):e0199463
Publication Type
Clinical Trial
Journal Article
Randomized Controlled Trial
Research Support, Non-U.S. Gov't
Date
2018
Author
Nils Petter Aspvik
Hallgeir Viken
Jan Erik Ingebrigtsen
Nina Zisko
Ingar Mehus
Ulrik Wisløff
Dorthe Stensvold
Author Affiliation
Department of Sociology and Political Science, Faculty of Social and Educational Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Source
PLoS One. 2018; 13(7):e0199463
Date
2018
Language
English
Publication Type
Clinical Trial
Journal Article
Randomized Controlled Trial
Research Support, Non-U.S. Gov't
Keywords
Age Factors
Aged
Aged, 80 and over
Body mass index
Cardiorespiratory fitness
Exercise
Female
Geriatric Assessment
Humans
Male
Norway
Public Health Surveillance
Seasons
Temperature
Weather
Abstract
Understanding how individual and environmental factors impact physical activity (PA) level is important when building strategies to improve PA of older adults. No studies have examined how hour-to-hour weather changes influence PA in older adults or how the association between weather and PA eventually is related to cardiorespiratory fitness (CRF) measured as peak oxygen uptake. The aim of this study was therefore to examine how hour-to-hour changes in weather effects hour-to-hour PA in a cohort of Norwegian older adults across CRF levels, gender and seasons.
PA was assessed objectively in 1219 older adults (70-77 years, 51% females) using the Actigraph GT3X+ accelerometer, and quantified as counts·min-1 (CPM). Weather (Norwegian meteorological Institute) and CRF (MetaMax II) were measured objectively. Panel data analysis added a longitudinal dimension when 110.888 hours of weather- and PA data were analyzed.
Older adults had a higher PA level in warmer (597 CPM) than colder months (556 CPM) (p
PubMed ID
29979711 View in PubMed
Less detail