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The adult body: how age, gender, and body mass index are related to body image.

https://arctichealth.org/en/permalink/ahliterature147507
Source
J Aging Health. 2009 Dec;21(8):1112-32
Publication Type
Article
Date
Dec-2009
Author
Monica Algars
Pekka Santtila
Markus Varjonen
Katarina Witting
Ada Johansson
Patrick Jern
N Kenneth Sandnabba
Author Affiliation
Department of Psychology, Abo Akademi University, 20500 Turku, Finland. malgars@abo.fi
Source
J Aging Health. 2009 Dec;21(8):1112-32
Date
Dec-2009
Language
English
Publication Type
Article
Keywords
Adult
Age Factors
Aging
Body Image
Body mass index
Female
Finland
Humans
Male
Middle Aged
Personal Satisfaction
Questionnaires
Sex Factors
Twin Studies as Topic
Abstract
OBJECTIVE. Body image and perceived attractiveness were examined, and the impact of age, gender, and body mass index (BMI) was analyzed and discussed from an evolutionary and a sociocultural perspective. METHOD. The population-based sample consisted of 11,468 Finnish men and women aged 18 to 49 years. RESULTS. Both age-related decrease and increase in body satisfaction was detected as well as interactions between age and gender. Some effects were nonlinear. Women were generally less satisfied with their bodies than men. BMI had a stronger influence on women's body image than men's. DISCUSSION. It was proposed that it is insufficient to merely study how age affects general body image because adults might become more satisfied with some aspects of their bodies as a function of age and less satisfied with other aspects. Body satisfaction might also fluctuate during different phases of the adult life, and the patterns possibly differ between men and women.
PubMed ID
19897779 View in PubMed
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An estimate of amyotrophic lateral sclerosis heritability using twin data.

https://arctichealth.org/en/permalink/ahliterature140579
Source
J Neurol Neurosurg Psychiatry. 2010 Dec;81(12):1324-6
Publication Type
Article
Date
Dec-2010
Author
A. Al-Chalabi
F. Fang
M F Hanby
P N Leigh
C E Shaw
W. Ye
F. Rijsdijk
Author Affiliation
King's College London, MRC Centre for Neurodegeneration Research, Institute of Psychiatry, London, UK. ammar.al-chalabi@kcl.ac.uk
Source
J Neurol Neurosurg Psychiatry. 2010 Dec;81(12):1324-6
Date
Dec-2010
Language
English
Publication Type
Article
Keywords
Amyotrophic Lateral Sclerosis - diagnosis - genetics
Diseases in Twins - diagnosis - genetics
Genetic Predisposition to Disease - genetics
Great Britain
Humans
Models, Genetic
Registries
Sweden
Twin Studies as Topic
Twins, Dizygotic
Twins, Monozygotic
Abstract
Causative gene mutations have been identified in about 2% of those with amyotrophic lateral sclerosis (ALS), often, but not always, when there is a strong family history. There is an assumption that there is a genetic component to all ALS, but genome-wide association studies have yet to produce a robustly replicated result. A definitive estimate of ALS heritability is therefore required to determine whether ongoing efforts to find susceptibility genes are worth while.
The authors performed two twin studies, one population- and one clinic-based. The authors used structural equation modelling to perform a meta-analysis of data from these studies and an existing twin study to estimate ALS heritability, and identified 171 twin pairs in which at least one twin had ALS.
Five monozygotic twin pairs were concordant-affected, and 44 discordant-affected. No dizygotic twin pairs were concordant-affected, and 122 discordant-affected. The heritability of sporadic ALS was estimated as 0.61 (0.38 to 0.78) with the unshared environmental component 0.39 (0.22 to 0.62). ALS has a high heritability, and efforts to find causative genes should continue.
Notes
Cites: Genet Epidemiol. 1995;12(1):27-357713398
Cites: Psychol Med. 1995 Jan;25(1):63-777792363
Cites: J Neurol Neurosurg Psychiatry. 1997 Jun;62(6):562-99219739
Cites: Nat Genet. 2006 Apr;38(4):411-316501576
Cites: Biochim Biophys Acta. 2006 Nov-Dec;1762(11-12):1150-717071060
Cites: J Neurol. 2006 Dec;253(12):1642-317219036
Cites: Neurogenetics. 2007 Aug;8(3):235-617549529
Cites: Science. 2008 Mar 21;319(5870):1668-7218309045
Cites: Nat Genet. 2008 May;40(5):572-418372902
Cites: Neurology. 2009 Feb 24;72(8):725-3119237701
Cites: Science. 2009 Feb 27;323(5918):1205-819251627
Cites: Science. 2009 Feb 27;323(5918):1208-1119251628
Cites: Neurology. 2009 Mar 24;72(12):1087-9419307543
Cites: Ann Neurol. 2009 Jul;66(1):94-919670447
Cites: Nat Genet. 2009 Oct;41(10):1083-719734901
Cites: Nat Rev Genet. 2009 Nov;10(11):769-8219823194
Cites: Nature. 2010 May 13;465(7295):223-620428114
Cites: Nature. 1993 Mar 4;362(6415):59-628446170
Cites: J Intern Med. 2002 Sep;252(3):184-20512270000
Cites: Am J Hum Genet. 2004 Nov;75(5):822-3115372378
Cites: Am J Hum Genet. 1983 Jul;35(4):695-7326349335
Comment In: J Neurol Neurosurg Psychiatry. 2010 Dec;81(12):1299-30021087924
PubMed ID
20861059 View in PubMed
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Anxiety trajectories in the second half of life: Genetic and environmental contributions over age.

https://arctichealth.org/en/permalink/ahliterature278402
Source
Psychol Aging. 2016 Feb;31(1):101-13
Publication Type
Article
Date
Feb-2016
Author
Lewina O Lee
Margaret Gatz
Nancy L Pedersen
Carol A Prescott
Source
Psychol Aging. 2016 Feb;31(1):101-13
Date
Feb-2016
Language
English
Publication Type
Article
Keywords
Age Factors
Aged
Aged, 80 and over
Aging - genetics - psychology
Anxiety - epidemiology - etiology - genetics
Anxiety Disorders - epidemiology - etiology - genetics
Biometry
Cohort Studies
Death
Environment
Female
Gene-Environment Interaction
Humans
Individuality
Life Change Events
Male
Middle Aged
Social Environment
Sweden - epidemiology
Twin Studies as Topic
Twins - genetics - psychology - statistics & numerical data
Abstract
Clinically significant anxiety symptoms are prevalent among the elderly, yet knowledge about the longitudinal course of anxiety symptoms in later life remains scarce. The goals of this study were to (a) characterize age trajectories of state anxiety symptoms in the second half of life, and (b) estimate genetic and environmental contributions to individual differences in the age trajectory of state anxiety. This study was based on data from 1,482 participants in the Swedish Adoption/Twin Study of Aging who were aged 50 and older at their first occasion (512 complete twin pairs, 458 singletons) and had up to 6 measurement occasions spanning 11 years. Consistent with life span developmental theories of age-related emotional change, anxiety symptom levels declined during the transition from midlife to the mid-60s, followed by a mild increase that gradually plateaued in the 80s. There were substantial individual differences in the age trajectory of anxiety. After accounting for effects of sex, cohort, mode of testing, and proximity to death, this longitudinal variation was partitioned into biometric sources. Nonshared environmental variance was highest in the late 60s and declined thereafter, whereas genetic variance increased at an accelerated pace from approximately age 60 onward. There was no evidence for effects of rearing or other shared environment on anxiety symptoms in later life. These findings highlight how the etiology of anxiety symptoms changes from midlife to old age.
Notes
Cites: Twin Res Hum Genet. 2007 Jun;10(3):423-3317564500
Cites: Acta Genet Med Gemellol (Roma). 1991;40(1):7-201950353
Cites: Soc Sci Med. 2008 Jun;66(12):2391-40018339465
Cites: Arch Gen Psychiatry. 1987 Jun;44(6):573-883579504
Cites: Genet Epidemiol. 1984;1(2):89-1076544237
Cites: J Gerontol. 1992 May;47(3):P213-201573207
Cites: Nebr Symp Motiv. 1992;40:209-541340521
Cites: Psychol Aging. 1994 Jun;9(2):315-248054179
Cites: Am Psychol. 1997 Apr;52(4):366-809109347
Cites: J Anxiety Disord. 1997 Jan-Feb;11(1):33-479131880
Cites: Psychol Med. 1998 Nov;28(6):1321-89854273
Cites: J Gerontol B Psychol Sci Soc Sci. 2005 Jan;60(1):P27-3315643035
Cites: Br J Psychiatry. 2005 Mar;186:190-615738498
Cites: Behav Genet. 2005 Sep;35(5):631-5216184490
Cites: Psychol Aging. 2005 Sep;20(3):447-5916248704
Cites: Psychol Aging. 2005 Sep;20(3):493-50616248708
Cites: Psychol Aging. 2006 Mar;21(1):201-716594806
Cites: Dev Psychol. 2008 Jul;44(4):1148-5918605841
Cites: Psychol Aging. 2009 Jun;24(2):349-6219485653
Cites: J Gerontol B Psychol Sci Soc Sci. 2010 Mar;65B(2):135-4420054013
Cites: J Gerontol B Psychol Sci Soc Sci. 2010 Mar;65B(2):154-6220054015
Cites: Behav Ther. 2010 Sep;41(3):277-8420569777
Cites: Neurosci Biobehav Rev. 2010 Sep;35(1):58-6819963006
Cites: Psychol Bull. 2010 Nov;136(6):1068-9121038939
Cites: Arch Gerontol Geriatr. 2011 Jan-Feb;52(1):33-920207429
Cites: Am J Geriatr Psychiatry. 2011 Apr;19(4):316-2621427640
Cites: Nat Rev Genet. 2012 Sep;13(9):640-5322847273
Cites: Circulation. 2013 Jan 1;127(1):e6-e24523239837
Cites: PLoS One. 2013;8(10):e7682524098566
Cites: Psychol Aging. 2015 Mar;30(1):106-1925528065
Cites: Psychol Med. 2000 May;30(3):515-2710883708
Cites: J Pers Soc Psychol. 2001 Jan;80(1):136-5111195886
Cites: Psychol Aging. 2001 Jun;16(2):187-9511405307
Cites: Am J Psychiatry. 2001 Oct;158(10):1568-7811578982
Cites: J Gerontol B Psychol Sci Soc Sci. 2002 May;57(3):P246-5511983736
Cites: J Intern Med. 2002 Sep;252(3):184-20512270000
Cites: Gerontology. 2003 Mar-Apr;49(2):123-3512574672
Cites: J Gerontol B Psychol Sci Soc Sci. 2003 May;58(3):P153-6512730308
Cites: Psychol Med. 2003 Jul;33(5):793-80112877394
Cites: Twin Res. 2004 Feb;7(1):39-5315053853
Cites: Death Stud. 2004 May;28(4):309-4015129688
Cites: Psychoneuroendocrinology. 2005 Jan;30(1):80-9115358445
Cites: Br J Soc Clin Psychol. 1976 Nov;15(4):387-941000147
Cites: Acta Psychiatr Scand. 1983 Jun;67(6):361-706880820
Cites: Br J Clin Psychol. 1983 Nov;22 (Pt 4):245-96640176
Cites: Psychol Aging. 2008 Mar;23(1):154-6818361663
PubMed ID
26751006 View in PubMed
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Apolipoprotein E genotype frequency patterns in aged Danes as revealed by logistic regression models.

https://arctichealth.org/en/permalink/ahliterature178107
Source
Eur J Epidemiol. 2004;19(7):651-6
Publication Type
Article
Date
2004
Author
Qihua Tan
Lene Christiansen
Kaare Christensen
Torben A Kruse
Lise Bathum
Author Affiliation
Department of Clinical Biochemistry and Genetics, KKA, Odense University Hospital, Odense, Denmark. qihua.tan@ouh.fyns-amt.dk
Source
Eur J Epidemiol. 2004;19(7):651-6
Date
2004
Language
English
Publication Type
Article
Keywords
Aged
Aged, 80 and over
Apolipoproteins E - genetics
Cohort Studies
DNA - genetics
Denmark
Gene Frequency
Genotype
Humans
Logistic Models
Polymerase Chain Reaction
Twin Studies as Topic
Abstract
Although the ApoE gene has been intensively studied in aging research, most of the studies conducted so far have been based on the traditional case-control design with subjects consisting of young controls and long-lived cases. The genotype frequency pattern in and between the two age-groups has been rarely investigated due to limitations in either research design or data analytical method. In this study, we genotyped 748 individuals (including both twin pairs and unrelated individuals) aged from 73 to 95 with aim at examining the genotype frequency trajectory of ApoE gene at high ages. Binomial and multinomial logistic regression models have been applied to model the gene frequency as a function of age and to investigate the modes of gene function (dominant, recessive, additive). The generalized estimation equations (GEEs) are introduced to account for the intra-pair genotype correlation in the twin pairs included in the data. Both the observed and the fitted frequencies show a constantly declining pattern of ApoE epsilon4 allele as age advances indicating a significant and steadily deleterious effect of the dominant allele that increases the hazard of death at high ages.
PubMed ID
15461196 View in PubMed
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Association of smoking in adolescence with abdominal obesity in adulthood: a follow-up study of 5 birth cohorts of Finnish twins.

https://arctichealth.org/en/permalink/ahliterature153863
Source
Am J Public Health. 2009 Feb;99(2):348-54
Publication Type
Article
Date
Feb-2009
Author
Suoma E Saarni
Kirsi Pietiläinen
Suvi Kantonen
Aila Rissanen
Jaakko Kaprio
Author Affiliation
Department of Public Health, University of Helsinki, Helsinki, Finland. suoma.saarni@helsinki.fi
Source
Am J Public Health. 2009 Feb;99(2):348-54
Date
Feb-2009
Language
English
Publication Type
Article
Keywords
Abdominal Fat
Adolescent
Adult
Cohort Studies
Female
Finland - epidemiology
Humans
Male
Obesity
Odds Ratio
Overweight - epidemiology
Questionnaires
Smoking - epidemiology
Twin Studies as Topic
Young Adult
Abstract
We studied the association of adolescent smoking with overweight and abdominal obesity in adulthood.
We used the FinnTwin16, a prospective, population-based questionnaire study of 5 consecutive and complete birth cohorts of Finnish twins born between 1975 and 1979 (N = 4296) and studied at four points between the ages of 16 and 27 years to analyze the effect of adolescent smoking on abdominal obesity and overweight in early adulthood.
Smoking at least 10 cigarettes daily when aged 16 to 18 years increased the risk of adult abdominal obesity (odds ratio [OR]=1.77; 95% confidence interval [CI] = 1.39, 2.26). After we adjusted for confounders, the OR was 1.44 (95% CI = 1.11, 1.88), and after further adjustment for current body mass index (BMI), the OR was 1.34 (95% CI = 0.95, 1.88). Adolescent smoking significantly increased the risk of becoming overweight among women even after adjustment for possible confounders, including baseline BMI (OR = 1.74; 95% CI = 1.06, 2.88).
Smoking is a risk factor for abdominal obesity among both genders and for overweight in women. The prevention of smoking during adolescence may play an important role in promoting healthy weight and in decreasing the morbidity related to abdominal obesity.
Notes
Cites: Am J Public Health. 1989 Feb;79(2):152-72913832
Cites: Am J Epidemiol. 1982 Nov;116(5):765-757148802
Cites: Ann Intern Med. 1989 Nov 15;111(10):783-72817625
Cites: JAMA. 1993 Mar 17;269(11):1391-58441214
Cites: BMJ. 1995 Nov 25;311(7017):1401-58520275
Cites: Int J Obes Relat Metab Disord. 1997 Mar;21(3):189-969080257
Cites: J Epidemiol Community Health. 1997 Jun;51(3):252-609229053
Cites: Am J Clin Nutr. 1998 May;67(5):846-529583840
Cites: Int J Obes Relat Metab Disord. 1998 Sep;22(9):915-229756252
Cites: Health Psychol. 1998 Sep;17(5):454-89776004
Cites: J Consult Clin Psychol. 1998 Dec;66(6):987-939874912
Cites: Int J Obes Relat Metab Disord. 1999 Feb;23(2):107-1510078843
Cites: Acta Paediatr. 1999 Apr;88(4):431-710342544
Cites: Int J Obes (Lond). 2005 Feb;29(2):236-4315505632
Cites: Int J Obes (Lond). 2005 Jun;29(6):697-70215782226
Cites: Int J Obes (Lond). 2005 Jul;29(7):778-8415917857
Cites: Eur J Public Health. 2005 Jun;15(3):262-915755781
Cites: Circulation. 2005 Aug 9;112(6):862-916061737
Cites: Obes Res. 2005 Aug;13(8):1466-7516129730
Cites: J Clin Epidemiol. 2005 Nov;58(11):1165-7116223660
Cites: Int J Psychophysiol. 2006 Mar;59(3):236-4316325948
Cites: Nutr Rev. 2006 Feb;64(2 Pt 1):53-6616536182
Cites: Psychosom Med. 2006 May-Jun;68(3):414-2016738073
Cites: Am J Clin Nutr. 2006 Aug;84(2):274-8816895873
Cites: Clin Res Cardiol. 2007 Jun;96(6):365-7417453138
Cites: Am J Public Health. 2007 Aug;97(8):1427-3317600242
Cites: Am J Epidemiol. 2008 Jan 15;167(2):188-9218079134
Cites: Behav Neurosci. 2008 Feb;122(1):161-7318298259
Cites: BMJ. 1989 May 13;298(6683):1287-902500198
Cites: BMJ. 2000 May 6;320(7244):1240-310797032
Cites: Nutrition. 2000 Oct;16(10):924-3611054598
Cites: Am J Med. 2000 Nov;109(7):538-4211063954
Cites: J Epidemiol Community Health. 2002 Mar;56(3):167-7011854334
Cites: Obes Rev. 2001 May;2(2):73-8612119665
Cites: Scand J Med Sci Sports. 2002 Jun;12(3):179-8512135451
Cites: Nat Rev Genet. 2002 Nov;3(11):872-8212415317
Cites: Int J Obes Relat Metab Disord. 2002 Dec;26(12):1570-812461673
Cites: Ann Intern Med. 2003 Jan 7;138(1):24-3212513041
Cites: Twin Res. 2002 Oct;5(5):366-7112537860
Cites: Addict Behav. 2003 Apr;28(3):501-1212628622
Cites: J Adolesc Health. 2003 Apr;32(4):306-1312667735
Cites: Eur J Clin Nutr. 2003 Jul;57(7):842-5312821884
Cites: Twin Res. 2003 Oct;6(5):409-2114624725
Cites: Arch Pediatr Adolesc Med. 2003 Dec;157(12):1212-814662578
Cites: Eur J Clin Nutr. 2004 Jan;58(1):180-9014679384
Cites: JAMA. 2004 Mar 10;291(10):1238-4515010446
Cites: Int J Obes Relat Metab Disord. 2004 Jun;28(6):796-80215024402
Cites: Nicotine Tob Res. 2004 Jun;6(3):397-42515203775
Cites: Int J Obes Relat Metab Disord. 2004 Aug;28(8):1091-615197410
Cites: Am J Clin Nutr. 2004 Sep;80(3):569-7515321794
Cites: Hum Hered. 1978;28(4):241-54566252
Comment In: Am J Public Health. 2009 Aug;99(8):135019542028
PubMed ID
19059868 View in PubMed
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Beyond the tip of the iceberg: Adolescent weight development of women and men with features of binge eating disorder.

https://arctichealth.org/en/permalink/ahliterature296077
Source
Eat Behav. 2018 08; 30:83-87
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
08-2018
Author
Linda Mustelin
Jaakko Kaprio
Anna Keski-Rahkonen
Author Affiliation
Department of Public Health, University of Helsinki, Finland; Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland. Electronic address: linda.mustelin@helsinki.fi.
Source
Eat Behav. 2018 08; 30:83-87
Date
08-2018
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Adolescent
Binge-Eating Disorder - psychology
Body mass index
Female
Finland - epidemiology
Humans
Longitudinal Studies
Male
Obesity - epidemiology
Overweight - epidemiology
Twin Studies as Topic
Weight Gain
Young Adult
Abstract
Binge eating disorder (BED) is a clinical eating disorder that is strongly and bidirectionally related to overweight and obesity. Little is known about how subclinical features of BED relate to weight development in adolescence and young adulthood.
Women (n?=?2825) and men (n?=?2423) from the community-based longitudinal FinnTwin16 cohort participated. Seven eating-related cognitions and behaviors similar to the defining features of BED were extracted from the Eating Disorder Inventory-2 and were assessed at a mean age of 24. We used linear mixed models to assess the association of features of BED with BMI trajectories across four waves of data collection (mean ages 16, 17, 18, and 24).
The number of features of BED at wave 4 (age 24) was significantly associated with BMI from age 16?years onwards. Those reporting more features of BED had gained more weight throughout adolescence and into their twenties.
Features of BED in young adulthood were preceded by steeper BMI trajectories in adolescence. A higher number of features were consistently associated with higher BMI and more weight gain.
PubMed ID
29933124 View in PubMed
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Binge eating and menstrual dysfunction.

https://arctichealth.org/en/permalink/ahliterature258002
Source
J Psychosom Res. 2014 Jan;76(1):19-22
Publication Type
Article
Date
Jan-2014
Author
Monica Algars
Lu Huang
Ann F Von Holle
Christine M Peat
Laura M Thornton
Paul Lichtenstein
Cynthia M Bulik
Author Affiliation
Department of Psychology and Logopedics, Abo Akademi University, Turku, Finland.
Source
J Psychosom Res. 2014 Jan;76(1):19-22
Date
Jan-2014
Language
English
Publication Type
Article
Keywords
Adult
Aged
Amenorrhea - epidemiology
Bulimia - epidemiology
Bulimia Nervosa - epidemiology
Diuretics - administration & dosage
Female
Humans
Laxatives - administration & dosage
Linear Models
Logistic Models
Male
Middle Aged
Oligomenorrhea - epidemiology
Self Medication
Sweden - epidemiology
Twin Studies as Topic
Vomiting
Abstract
The relation between eating disorders and menstrual function has been widely studied, but it is unknown whether the behavior of binge eating itself is related to menstrual dysfunction.
The 11,503 women included in this study were from the Swedish Twin study of Adults: Genes and Environment. The associations between menstrual dysfunction and binge eating were analyzed using logistic regression or multiple linear regression models with generalized estimation equations.
Women who reported lifetime binge eating were more likely to report either amenorrhea or oligomenorrhea than women who reported no binge eating. These results persisted when controlling for compensatory behaviors including self-induced vomiting, laxative use, and diuretic use. No differences between women with and without a history of binge eating were observed for age at menarche.
Even when controlling for the effect of compensatory behaviors, the behavior of binge eating is associated with menstrual dysfunction. Metabolic and endocrinological factors could underlie this association. Careful evaluation of menstrual status is warranted for women with all eating disorders, not just anorexia nervosa.
PubMed ID
24360136 View in PubMed
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A bivariate survival model with compound Poisson frailty.

https://arctichealth.org/en/permalink/ahliterature98811
Source
Stat Med. 2010 Jan 30;29(2):275-83
Publication Type
Article
Date
Jan-30-2010
Author
A. Wienke
S. Ripatti
J. Palmgren
A. Yashin
Author Affiliation
Institute of Medical Epidemiology, Biostatistics and Informatics, University Halle-Wittenberg, Germany. andreas.wienke@medizin.uni-halle.de
Source
Stat Med. 2010 Jan 30;29(2):275-83
Date
Jan-30-2010
Language
English
Publication Type
Article
Keywords
Adult
Age of Onset
Aged
Aged, 80 and over
Algorithms
Breast Neoplasms - epidemiology
Computer simulation
Epidemiologic Research Design
Female
Humans
Likelihood Functions
Middle Aged
Models, Statistical
Poisson Distribution
Proportional Hazards Models
Survival Analysis
Sweden - epidemiology
Twin Studies as Topic
Abstract
A correlated frailty model is suggested for analysis of bivariate time-to-event data. The model is an extension of the correlated power variance function (PVF) frailty model (correlated three-parameter frailty model) (J. Epidemiol. Biostat. 1999; 4:53-60). It is based on a bivariate extension of the compound Poisson frailty model in univariate survival analysis (Ann. Appl. Probab. 1992; 4:951-972). It allows for a non-susceptible fraction (of zero frailty) in the population, overcoming the common assumption in survival analysis that all individuals are susceptible to the event under study. The model contains the correlated gamma frailty model and the correlated inverse Gaussian frailty model as special cases. A maximum likelihood estimation procedure for the parameters is presented and its properties are studied in a small simulation study. This model is applied to breast cancer incidence data of Swedish twins. The proportion of women susceptible to breast cancer is estimated to be 15 per cent.
PubMed ID
19856276 View in PubMed
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Both the environment and genes are important for concentrations of cadmium and lead in blood.

https://arctichealth.org/en/permalink/ahliterature197411
Source
Environ Health Perspect. 2000 Aug;108(8):719-22
Publication Type
Article
Date
Aug-2000
Author
L. Björkman
M. Vahter
N L Pedersen
Author Affiliation
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Source
Environ Health Perspect. 2000 Aug;108(8):719-22
Date
Aug-2000
Language
English
Publication Type
Article
Keywords
Aged
Aged, 80 and over
Biological Markers - blood
Cadmium - blood
Cohort Studies
Environmental Exposure - statistics & numerical data
Female
Humans
Lead - blood
Male
Middle Aged
Phenotype
Spectrophotometry, Atomic
Sweden - epidemiology
Twin Studies as Topic
Abstract
Concentrations of cadmium and lead in blood (BCd and BPb, respectively) are traditionally used as biomarkers of environmental exposure. We estimated the influence of genetic factors on these markers in a cohort of 61 monozygotic and 103 dizygotic twin pairs (mean age = 68 years, range = 49-86). BCd and BPb were determined by graphite furnace atomic absorption spectrophotometry. Variations in both BCd and BPb were influenced by not only environmental but also genetic factors. Interestingly, the genetic influence was considerably greater for nonsmoking women (h(2) = 65% for BCd and 58% for BPb) than for nonsmoking men (13 and 0%, respectively). The shared familial environmental (c(2)) influence for BPb was 37% for men but only 3% for women. The association between BCd and BPb could be attributed entirely to environmental factors of mutual importance for levels of the two metals. Thus, blood metal concentrations in women reflect not only exposure, as previously believed, but to a considerable extent hereditary factors possibly related to uptake and storage. Further steps should focus on identification of these genetic factors and evaluation of whether women are more susceptible to exposure to toxic metals than men.
Notes
Cites: Occup Environ Med. 1995 Nov;52(11):764-98535497
Cites: Mt Sinai J Med. 1995 Oct;62(5):343-557500964
Cites: Nature. 1997 Jul 31;388(6641):482-89242408
Cites: Arterioscler Thromb Vasc Biol. 1997 Nov;17(11):2776-829409255
Cites: Environ Health Perspect. 1998 Apr;106(4):175-89485480
Cites: Scand J Work Environ Health. 1998;24 Suppl 1:1-519569444
Cites: J Clin Endocrinol Metab. 1998 Jun;83(6):1875-809626112
Cites: Am J Clin Nutr. 1998 Dec;68(6):1241-69846853
Cites: Clin Biochem. 1998 Nov;31(8):657-659876899
Cites: Proc Natl Acad Sci U S A. 1999 Mar 16;96(6):3143-810077651
Cites: Environ Res. 1999 Apr;80(3):222-3010094806
Cites: Lancet. 1999 Apr 3;353(9159):1140-410209978
Cites: Acta Obstet Gynecol Scand. 1966;45(4):389-4105955252
Cites: Heredity (Edinb). 1977 Feb;38(1):79-95268313
Cites: Gastroenterology. 1978 May;74(5 Pt 1):841-6640339
Cites: Analyst. 1978 Jul;103(1228):714-22749560
Cites: Environ Health Perspect. 1984 Mar;54:111-56734550
Cites: Acta Genet Med Gemellol (Roma). 1984;33(2):243-506540957
Cites: Environ Res. 1988 Oct;47(1):79-943168967
Cites: Food Addit Contam. 1988 Oct-Dec;5(4):645-93192015
Cites: Scand J Work Environ Health. 1991 Feb;17(1):65-742047809
Cites: Acta Genet Med Gemellol (Roma). 1991;40(1):7-201950353
Cites: Int Arch Occup Environ Health. 1992;64(4):219-211468789
Cites: Am J Ind Med. 1993 May;23(5):763-778506854
Cites: Am J Hum Genet. 1994 Dec;55(6):1255-677977387
Cites: Hypertension. 1994 Dec;24(6):663-707995622
Cites: Environ Health Perspect. 1994 Dec;102(12):1058-667713018
Cites: Eur J Clin Nutr. 1995 Mar;49(3):200-77774536
Cites: Toxicol Appl Pharmacol. 1996 Feb;136(2):332-418619241
PubMed ID
10964791 View in PubMed
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A cautionary note on the use of attributable fractions in cohort studies.

https://arctichealth.org/en/permalink/ahliterature291785
Source
Stat Methods Med Res. 2016 Dec; 25(6):2434-2443
Publication Type
Journal Article
Date
Dec-2016
Author
Arvid Sjölander
Author Affiliation
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden arvid.sjolander@ki.se.
Source
Stat Methods Med Res. 2016 Dec; 25(6):2434-2443
Date
Dec-2016
Language
English
Publication Type
Journal Article
Keywords
Body mass index
Cohort Studies
Female
Humans
Male
Mortality
Proportional Hazards Models
Sweden
Twin Studies as Topic
Twins
Abstract
The attributable fraction is a widely used measure to quantify the public health impact of an exposure on an outcome. It was originally proposed for binary outcomes, but attributable fraction estimators have also been proposed for time-to-event outcomes. In this note, we consider an estimator which was proposed by Benichou (Stats Methods Med Res, 2001) and is supposed to estimate the cohort attributable fraction, i.e. the number of events that would have been prevented in the cohort during follow-up, if the exposure would hypothetically have been eliminated. We show that this estimator is only valid under certain assumptions, which are often likely to be violated in practice. We further argue that the cohort attributable fraction may not be of substantial scientific interest in the first place. We propose a potentially more relevant measure of attributable fraction in cohort studies; the baseline attributable fraction. We show how the baseline attributable fraction can be conveniently estimated in Cox proportional hazards models.
PubMed ID
24567439 View in PubMed
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