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Adolescent body composition and associations with body size and growth from birth to late adolescence. The Tromsø study: Fit Futures-A Norwegian longitudinal cohort study.

https://arctichealth.org/en/permalink/ahliterature300460
Source
Pediatr Obes. 2019 05; 14(5):e12492
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
05-2019
Author
Elin Evensen
Nina Emaus
Anne-Sofie Furberg
Ane Kokkvoll
Jonathan Wells
Tom Wilsgaard
Anne Winther
Guri Skeie
Author Affiliation
Department of Clinical Research, University Hospital of North Norway, Tromsø, Norway.
Source
Pediatr Obes. 2019 05; 14(5):e12492
Date
05-2019
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Absorptiometry, Photon - methods
Adolescent
Adult
Birth Weight - physiology
Body Composition
Body mass index
Child
Child Development - physiology
Cohort Studies
Female
Humans
Longitudinal Studies
Male
Norway
Pediatric Obesity - epidemiology - physiopathology
Risk factors
Young Adult
Abstract
Fat and fat-free masses and fat distribution are related to cardiometabolic risk.
to explore how birth weight, childhood body mass index (BMI) and BMI gain were related to adolescent body composition and central obesity.
In a population-based longitudinal study, body composition was measured by dual-energy X-ray absorptiometry in 907 Norwegian adolescents (48% girls). Associations between birth weight, BMI categories, and BMI gain were evaluated by fitting linear mixed models and conditional growth models with fat mass index (FMI, kg/m2 ), fat-free mass index (FFMI, kg/m2 ) standard deviation scores (SDS), and central obesity at 15 to 20 years, as well as change in FMI SDS and FFMI SDS between ages 15 to 17 and 18 to 20 as outcomes.
Birth weight was associated with FFMI in adolescence. Greater BMI gain in childhood, conditioned on prior body size, was associated with higher FMI, FFMI, and central overweight/obesity with the strongest associations seen at age 6 to 16.5 years: FMI SDS: ß = 0.67, 95% CI (0.63-0.71), FFMI SDS: 0.46 (0.39, 0.52), in girls, FMI SDS: 0.80 (0.75, 0.86), FFMI SDS: 0.49 (0.43, 0.55), in boys.
Compared with birth and early childhood, high BMI and greater BMI gain at later ages are strong predictors of higher fat mass and central overweight/obesity at 15 to 20 years of age.
PubMed ID
30590874 View in PubMed
Less detail

Adolescent body composition and associations with body size and growth from birth to late adolescence. The Tromsø study: Fit Futures-A Norwegian longitudinal cohort study.

https://arctichealth.org/en/permalink/ahliterature296939
Source
Pediatr Obes. 2018 Dec 27; :e12492
Publication Type
Journal Article
Date
Dec-27-2018
Author
Elin Evensen
Nina Emaus
Anne-Sofie Furberg
Ane Kokkvoll
Jonathan Wells
Tom Wilsgaard
Anne Winther
Guri Skeie
Author Affiliation
Department of Clinical Research, University Hospital of North Norway, Tromsø, Norway.
Source
Pediatr Obes. 2018 Dec 27; :e12492
Date
Dec-27-2018
Language
English
Publication Type
Journal Article
Abstract
Fat and fat-free masses and fat distribution are related to cardiometabolic risk.
to explore how birth weight, childhood body mass index (BMI) and BMI gain were related to adolescent body composition and central obesity.
In a population-based longitudinal study, body composition was measured by dual-energy X-ray absorptiometry in 907 Norwegian adolescents (48% girls). Associations between birth weight, BMI categories, and BMI gain were evaluated by fitting linear mixed models and conditional growth models with fat mass index (FMI, kg/m2 ), fat-free mass index (FFMI, kg/m2 ) standard deviation scores (SDS), and central obesity at 15 to 20 years, as well as change in FMI SDS and FFMI SDS between ages 15 to 17 and 18 to 20 as outcomes.
Birth weight was associated with FFMI in adolescence. Greater BMI gain in childhood, conditioned on prior body size, was associated with higher FMI, FFMI, and central overweight/obesity with the strongest associations seen at age 6 to 16.5 years: FMI SDS: ß = 0.67, 95% CI (0.63-0.71), FFMI SDS: 0.46 (0.39, 0.52), in girls, FMI SDS: 0.80 (0.75, 0.86), FFMI SDS: 0.49 (0.43, 0.55), in boys.
Compared with birth and early childhood, high BMI and greater BMI gain at later ages are strong predictors of higher fat mass and central overweight/obesity at 15 to 20 years of age.
PubMed ID
30590874 View in PubMed
Less detail

Ageing and mental health: changes in self-reported health due to physical illness and mental health status with consecutive cross-sectional analyses.

https://arctichealth.org/en/permalink/ahliterature279278
Source
BMJ Open. 2017 Jan 18;7(1):e013629
Publication Type
Article
Date
Jan-18-2017
Author
Geir Fagerjord Lorem
Henrik Schirmer
Catharina E A Wang
Nina Emaus
Source
BMJ Open. 2017 Jan 18;7(1):e013629
Date
Jan-18-2017
Language
English
Publication Type
Article
Abstract
It is known that self-reported health (SRH) declines with increasing age and that comorbidity increases with age. We wished to examine how age transfers its effect to SRH through comorbid disease and mental illness and whether these processes remained stable from 1994 until 2008. The hypothesis is that ageing and/or the increased age-related burden of pathology explains the declining SRH.
The Tromsø Study (TS) is a cohort study using a survey approach with repeated physical examinations. It was conducted in the municipality of Tromsø, Norway, from 1974 to 2008.
A total of 21 199 women and 19 229 men participated.
SRH is the outcome of interest. We calculated and compared the effect sizes of age, comorbidity and mental health symptoms using multimediator analysis based on OLS regression.
Ageing had a negative impact on SRH, but the total effect of age decreased from 1994 to 2007. We assessed the direct effect of age and then the proportion of indirect age-related effects through physical illness and mental health symptoms on the total effect. The direct effect of age represented 79.3% of the total effect in 1994 and decreased to 58.8% in 2007. Physical illness emerged as an increasingly important factor and increased its influence from 15.7% to 41.2% of the total effect. Age alone had a protective effect on mental health symptoms and this increased (2.5% to 17.3%), but we found a stronger association between mental health symptoms and physical disease in the later waves of the study (increasing from 3.7% to 14.8%).
The results suggest that the effect on SRH of mental health symptoms caused by physical illness is an increasing public health problem. Treatment and care for specific medical conditions must therefore focus more strongly on how these conditions affect the patient's mental health and address these concerns accordingly.
PubMed ID
28100564 View in PubMed
Less detail

Association between objectively measured physical activity and longitudinal changes in body composition in adolescents: the Tromsø study fit futures cohort.

https://arctichealth.org/en/permalink/ahliterature304521
Source
BMJ Open. 2020 10 07; 10(10):e036991
Publication Type
Journal Article
Date
10-07-2020
Author
Nils Abel Aars
Sigurd Beldo
Bjarne Koster Jacobsen
Alexander Horsch
Bente Morseth
Nina Emaus
Anne-Sofie Furberg
Sameline Grimsgaard
Author Affiliation
Department of Community Medicine, UiT The Arctic University of Norway, Tromso, Troms, Norway nils.a.aars@uit.no.
Source
BMJ Open. 2020 10 07; 10(10):e036991
Date
10-07-2020
Language
English
Publication Type
Journal Article
Abstract
Physical activity may be important in deterring the obesity epidemic. This study aimed to determine whether objectively measured physical activity in first year of upper secondary high school predicted changes in body composition over 2 years of follow-up in a cohort of Norwegian adolescents (n=431).
A longitudinal study of adolescents (mean age of 16 (SD 0.4) at baseline, 60.3% girls) participating in the Fit Futures studies 1 (2010-2011) and 2 (2012-2013).
All eight upper secondary high schools in two municipalities in Northern Norway.
Students participating in both studies and under the age of 18 at baseline and with valid measurement of physical activity at baseline and body composition in both surveys.
Change in objectively measured body mass index and waist circumference and change in dual-energy X-ray absorptiometry measured fat mass index, lean mass index (LMI) and appendicular LMI (aLMI) between baseline and follow-up.
At baseline, boys had significantly higher physical activity volume (p=0.01) and spent on average of 6.4 (95% CI 2.1 to 10.6) more minutes in moderate-to-vigorous physical activity (MVPA) than girls (p
PubMed ID
33033016 View in PubMed
Less detail

The association of grip strength from midlife onwards with all-cause and cause-specific mortality over 17 years of follow-up in the Tromsø Study.

https://arctichealth.org/en/permalink/ahliterature273326
Source
J Epidemiol Community Health. 2016 May 26;
Publication Type
Article
Date
May-26-2016
Author
Bjørn Heine Strand
Rachel Cooper
Astrid Bergland
Lone Jørgensen
Henrik Schirmer
Vegard Skirbekk
Nina Emaus
Source
J Epidemiol Community Health. 2016 May 26;
Date
May-26-2016
Language
English
Publication Type
Article
Abstract
Grip strength has consistently been found to predict all-cause mortality rates. However, few studies have examined cause-specific mortality or tested age differences in these associations.
In 1994, grip strength was measured in the population-based Tromsø Study, covering the ages 50-80 years (N=6850). Grip strength was categorised into fifths, and as z-scores. In this cohort study, models with all-cause mortality and deaths from specific causes as the outcome were performed, stratified by sex and age using Cox regression, adjusting for lifestyle-related and health-related factors.
During 17 years of follow-up, 2338 participants died. A 1 SD reduction in grip strength was associated with HR=1.17 (95% CI 1.12 to 1.22) for all-cause mortality in a model adjusted for age, gender and body size. This association was similar across all age groups, in men and women, and robust to adjustment for a range of lifestyle-related and health-related factors. Results for deaths due to cardiovascular disease (CVD), respiratory diseases and external causes resembled those for all-cause mortality, while for cancer, the association was much weaker and not significant after adjustment for lifestyle-related and health-related factors.
Weaker grip strength was associated with increased all-cause mortality rates, with similar effects on deaths due to CVD, respiratory disease and external causes, while a much weaker association was observed for cancer-related deaths. These associations were similar in both genders and across age groups, which supports the hypothesis that grip strength might be a biomarker of ageing over the lifespan.
PubMed ID
27229009 View in PubMed
Less detail

Body Weight and Body Mass Index Influence Bone Mineral Density in Late Adolescence in a Two-Year Follow-Up Study. The Tromsø Study: Fit Futures.

https://arctichealth.org/en/permalink/ahliterature308417
Source
JBMR Plus. 2019 Sep; 3(9):e10195
Publication Type
Journal Article
Date
Sep-2019
Author
Ole Andreas Nilsen
Luai Awad Ahmed
Anne Winther
Tore Christoffersen
Gyrd Thrane
Elin Evensen
Anne-Sofie Furberg
Guri Grimnes
Elaine Dennison
Nina Emaus
Author Affiliation
Department of Health and Care Sciences The Arctic University of Norway Tromsø Norway.
Source
JBMR Plus. 2019 Sep; 3(9):e10195
Date
Sep-2019
Language
English
Publication Type
Journal Article
Abstract
Determinants of bone acquisition in late adolescence and early adulthood are not well-described. This 2-year follow-up study explored the associations of body weight (BW), body mass index (BMI), and changes in weight status with adolescent bone accretion in a sample of 651 adolescents (355 girls and 296 boys) between 15 and 19 years of age from The Tromsø Study: Fit Futures. This Norwegian population-based cohort study was conducted from 2010 to 2011 and was repeated from 2012 to 2013. We measured femoral neck, total hip, and total body bone mineral content and areal bone mineral density (aBMD) by dual-energy X-ray absorptiometry. We measured height, BW, calculated BMI (kg/m 2), and collected information on lifestyle at both surveys. Mean BMI (SD) at baseline was 22.17 (3.76) and 22.18 (3.93) in girls and boys, respectively. Through multiple linear regression, baseline BW and BMI were positively associated with ?aBMD over 2 years of follow-up at all skeletal sites in boys ( p
PubMed ID
31667452 View in PubMed
Less detail

Bone mineral density at the hip and its relation to fat mass and lean mass in adolescents: the Tromsø Study, Fit Futures.

https://arctichealth.org/en/permalink/ahliterature294684
Source
BMC Musculoskelet Disord. 2018 01 19; 19(1):21
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
01-19-2018
Author
Anne Winther
Lone Jørgensen
Luai Awad Ahmed
Tore Christoffersen
Anne-Sofie Furberg
Guri Grimnes
Rolf Jorde
Ole Andreas Nilsen
Elaine Dennison
Nina Emaus
Author Affiliation
Division of Neurosciences, Orthopedics and Rehabilitation Services, University Hospital of North Norway, Tromsø, Norway. anne.winther@unn.no.
Source
BMC Musculoskelet Disord. 2018 01 19; 19(1):21
Date
01-19-2018
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Absorptiometry, Photon - methods
Adipose Tissue - diagnostic imaging - physiology
Adolescent
Body mass index
Body Weight - physiology
Bone Density - physiology
Cross-Sectional Studies
Exercise - physiology
Female
Forecasting
Humans
Life Style
Male
Norway - epidemiology
Pelvic Bones - diagnostic imaging - physiology
Abstract
Positive association between body weight and bone mass is well established, and the concept of body mass index (BMI) is associated with higher areal bone mineral density (aBMD) and reduced fracture risk. BMI, that comprises both fat mass (FM) and lean mass (LM) may contribute to peak bone mass achievement in different ways. This study explored the influence of body composition in terms of total body LM and FM on hip aBMD-values in adolescence.
In 2010/2011, 93% of the region's first-year upper-secondary school students (15-17 years old) in Tromsø, Norway attended the Tromsø Study, Fit Futures. Areal BMD at femoral neck (aBMDFN) and total hip (aBMDTH) (g/cm2), total body LM and FM (g) were measured by dual energy X-ray absorptiometry (DXA). Height and weight were measured, and BMI calculated. Lifestyle variables were collected by self-administered questionnaires and interviews, including questions on time spent on leisure time physical activity. Stratified analyses of covariance and regression models included 395 girls and 363 boys. Crude results were adjusted for age, height, sexual maturation, physical activity levels, vitamin D levels, calcium intake, alcohol consumption and smoking habits.
Unadjusted distribution indicated higher aBMD-levels at higher LM-levels in both genders (p?
Notes
Cites: Osteoporos Int. 2016 Apr;27(4):1281-386 PMID 26856587
Cites: Obesity (Silver Spring). 2006 May;14(5):819-25 PMID 16855191
Cites: J Youth Adolesc. 1988 Apr;17(2):117-33 PMID 24277579
Cites: Osteoporos Int. 2008 May;19(5):595-606 PMID 17965817
Cites: Bone. 2000 Aug;27(2):203-7 PMID 10913912
Cites: Obes Res. 2002 Jan;10(1):56-60 PMID 11786602
Cites: J Bone Miner Metab. 2007;25(6):423-30 PMID 17968496
Cites: J Pediatr Endocrinol Metab. 2000 Jun;13(6):571-90 PMID 10905381
Cites: Bone. 2004 Nov;35(5):1169-79 PMID 15542043
Cites: J Clin Endocrinol Metab. 2014 Jan;99(1):30-8 PMID 24384013
Cites: Bone. 2014 Jul;64:298-302 PMID 24792957
Cites: Osteoporos Int. 2014 Apr;25(4):1297-304 PMID 24326885
Cites: Arch Biochem Biophys. 2010 Nov 1;503(1):20-7 PMID 20599663
Cites: Scand J Public Health. 2014 Nov;42(7):593-602 PMID 25053469
Cites: Nutrients. 2013 Jun 06;5(6):2047-61 PMID 23743968
Cites: Circulation. 1968 Dec;38(6):1104-15 PMID 5721960
Cites: Arch Osteoporos. 2017 Dec;12 (1):37 PMID 28389986
Cites: Osteoporos Int. 2005 Nov;16(11):1330-8 PMID 15928804
Cites: BMJ. 1996 May 18;312(7041):1254-9 PMID 8634613
Cites: J Musculoskelet Neuronal Interact. 2005 Jul-Sep;5(3):239-54 PMID 16172515
Cites: Bone. 2015 May;74:146-52 PMID 25652209
Cites: Osteoporos Int. 2005 Jun;16(6):581-9 PMID 15616758
Cites: Arch Osteoporos. 2014;9:185 PMID 24893722
Cites: Rheumatol Int. 2012 Sep;32(9):2737-43 PMID 21809005
Cites: Calcif Tissue Int. 2017 May;100(5):500-513 PMID 28013362
Cites: Compr Physiol. 2013 Jul;3(3):1337-62 PMID 23897689
Cites: Bone. 2010 Feb;46(2):294-305 PMID 19840876
Cites: J Bone Miner Res. 2011 Aug;26(8):1729-39 PMID 21520276
Cites: J Clin Densitom. 2008 Apr-Jun;11(2):276-82 PMID 18158262
Cites: J Clin Endocrinol Metab. 2007 Jan;92(1):143-7 PMID 17047019
Cites: Am J Clin Nutr. 2004 Oct;80(4):966-72 PMID 15447907
Cites: J Clin Endocrinol Metab. 2006 Jul;91(7):2534-41 PMID 16621904
Cites: Osteoporos Int. 2000;11(12):985-1009 PMID 11256898
Cites: Bone. 2009 May;44(5):752-7 PMID 19103314
Cites: Hormones (Athens). 2013 Apr-Jun;12(2):214-23 PMID 23933690
Cites: Osteoporos Int. 2006;17(3):337-47 PMID 16331359
Cites: BMJ Open. 2015 Apr 22;5(6):e006665 PMID 26063563
Cites: Bone. 2012 Feb;50(2):457-66 PMID 21619952
Cites: Osteoporos Int. 2008 Jan;19(1):29-38 PMID 17660933
Cites: Sports Med. 2006;36(9):723-32 PMID 16937949
Cites: Pediatr Obes. 2013 Dec;8(6):418-27 PMID 23447431
Cites: Osteoporos Int. 2003 Jul;14(7):539-47 PMID 12844213
Cites: JAMA. 2002 Oct 16;288(15):1889-97 PMID 12377088
Cites: Eur J Appl Physiol. 2009 Mar;105(5):759-64 PMID 19096868
Cites: Maturitas. 2008 Feb 20;59(2):191-200 PMID 18221845
PubMed ID
29351755 View in PubMed
Less detail

Bone mineral density at the hip and its relation to fat mass and lean mass in adolescents: the Tromsø Study, Fit Futures.

https://arctichealth.org/en/permalink/ahliterature289232
Source
BMC Musculoskelet Disord. 2018 01 19; 19(1):21
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
01-19-2018
Author
Anne Winther
Lone Jørgensen
Luai Awad Ahmed
Tore Christoffersen
Anne-Sofie Furberg
Guri Grimnes
Rolf Jorde
Ole Andreas Nilsen
Elaine Dennison
Nina Emaus
Author Affiliation
Division of Neurosciences, Orthopedics and Rehabilitation Services, University Hospital of North Norway, Tromsø, Norway. anne.winther@unn.no.
Source
BMC Musculoskelet Disord. 2018 01 19; 19(1):21
Date
01-19-2018
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Abstract
Positive association between body weight and bone mass is well established, and the concept of body mass index (BMI) is associated with higher areal bone mineral density (aBMD) and reduced fracture risk. BMI, that comprises both fat mass (FM) and lean mass (LM) may contribute to peak bone mass achievement in different ways. This study explored the influence of body composition in terms of total body LM and FM on hip aBMD-values in adolescence.
In 2010/2011, 93% of the region's first-year upper-secondary school students (15-17 years old) in Tromsø, Norway attended the Tromsø Study, Fit Futures. Areal BMD at femoral neck (aBMDFN) and total hip (aBMDTH) (g/cm2), total body LM and FM (g) were measured by dual energy X-ray absorptiometry (DXA). Height and weight were measured, and BMI calculated. Lifestyle variables were collected by self-administered questionnaires and interviews, including questions on time spent on leisure time physical activity. Stratified analyses of covariance and regression models included 395 girls and 363 boys. Crude results were adjusted for age, height, sexual maturation, physical activity levels, vitamin D levels, calcium intake, alcohol consumption and smoking habits.
Unadjusted distribution indicated higher aBMD-levels at higher LM-levels in both genders (p?
Notes
Cites: Osteoporos Int. 2016 Apr;27(4):1281-386 PMID 26856587
Cites: Obesity (Silver Spring). 2006 May;14(5):819-25 PMID 16855191
Cites: J Youth Adolesc. 1988 Apr;17(2):117-33 PMID 24277579
Cites: Osteoporos Int. 2008 May;19(5):595-606 PMID 17965817
Cites: Bone. 2000 Aug;27(2):203-7 PMID 10913912
Cites: Obes Res. 2002 Jan;10(1):56-60 PMID 11786602
Cites: J Bone Miner Metab. 2007;25(6):423-30 PMID 17968496
Cites: J Pediatr Endocrinol Metab. 2000 Jun;13(6):571-90 PMID 10905381
Cites: Bone. 2004 Nov;35(5):1169-79 PMID 15542043
Cites: J Clin Endocrinol Metab. 2014 Jan;99(1):30-8 PMID 24384013
Cites: Bone. 2014 Jul;64:298-302 PMID 24792957
Cites: Osteoporos Int. 2014 Apr;25(4):1297-304 PMID 24326885
Cites: Arch Biochem Biophys. 2010 Nov 1;503(1):20-7 PMID 20599663
Cites: Scand J Public Health. 2014 Nov;42(7):593-602 PMID 25053469
Cites: Nutrients. 2013 Jun 06;5(6):2047-61 PMID 23743968
Cites: Circulation. 1968 Dec;38(6):1104-15 PMID 5721960
Cites: Arch Osteoporos. 2017 Dec;12 (1):37 PMID 28389986
Cites: Osteoporos Int. 2005 Nov;16(11):1330-8 PMID 15928804
Cites: BMJ. 1996 May 18;312(7041):1254-9 PMID 8634613
Cites: J Musculoskelet Neuronal Interact. 2005 Jul-Sep;5(3):239-54 PMID 16172515
Cites: Bone. 2015 May;74:146-52 PMID 25652209
Cites: Osteoporos Int. 2005 Jun;16(6):581-9 PMID 15616758
Cites: Arch Osteoporos. 2014;9:185 PMID 24893722
Cites: Rheumatol Int. 2012 Sep;32(9):2737-43 PMID 21809005
Cites: Calcif Tissue Int. 2017 May;100(5):500-513 PMID 28013362
Cites: Compr Physiol. 2013 Jul;3(3):1337-62 PMID 23897689
Cites: Bone. 2010 Feb;46(2):294-305 PMID 19840876
Cites: J Bone Miner Res. 2011 Aug;26(8):1729-39 PMID 21520276
Cites: J Clin Densitom. 2008 Apr-Jun;11(2):276-82 PMID 18158262
Cites: J Clin Endocrinol Metab. 2007 Jan;92(1):143-7 PMID 17047019
Cites: Am J Clin Nutr. 2004 Oct;80(4):966-72 PMID 15447907
Cites: J Clin Endocrinol Metab. 2006 Jul;91(7):2534-41 PMID 16621904
Cites: Osteoporos Int. 2000;11(12):985-1009 PMID 11256898
Cites: Bone. 2009 May;44(5):752-7 PMID 19103314
Cites: Hormones (Athens). 2013 Apr-Jun;12(2):214-23 PMID 23933690
Cites: Osteoporos Int. 2006;17(3):337-47 PMID 16331359
Cites: BMJ Open. 2015 Apr 22;5(6):e006665 PMID 26063563
Cites: Bone. 2012 Feb;50(2):457-66 PMID 21619952
Cites: Osteoporos Int. 2008 Jan;19(1):29-38 PMID 17660933
Cites: Sports Med. 2006;36(9):723-32 PMID 16937949
Cites: Pediatr Obes. 2013 Dec;8(6):418-27 PMID 23447431
Cites: Osteoporos Int. 2003 Jul;14(7):539-47 PMID 12844213
Cites: JAMA. 2002 Oct 16;288(15):1889-97 PMID 12377088
Cites: Eur J Appl Physiol. 2009 Mar;105(5):759-64 PMID 19096868
Cites: Maturitas. 2008 Feb 20;59(2):191-200 PMID 18221845
PubMed ID
29351755 View in PubMed
Less detail

Bone mineral density at the hip in Norwegian women and men--prevalence of osteoporosis depends on chosen references: the Tromsø Study.

https://arctichealth.org/en/permalink/ahliterature151994
Source
Eur J Epidemiol. 2009;24(6):321-8
Publication Type
Article
Date
2009
Author
Nina Emaus
Tone K Omsland
Luai Awad Ahmed
Guri Grimnes
Monica Sneve
Gro K Berntsen
Author Affiliation
Institute of Community Medicine, University of Tromsø, Tromso, Norway. nina.emaus@ism.uit.no
Source
Eur J Epidemiol. 2009;24(6):321-8
Date
2009
Language
English
Publication Type
Article
Keywords
Absorptiometry, Photon
Adult
Aged
Aged, 80 and over
Bone Density - physiology
Female
Hip - physiology
Humans
Male
Middle Aged
Norway - epidemiology
Osteoporosis - diagnosis - epidemiology
Questionnaires
Abstract
This study describes bone mineral density (BMD) and the prevalence of osteoporosis in women and men between 30-89 years in an unselected population. BMD was measured in g/cm(2) at total hip and femoral neck by dual-energy-X-ray absorptiometry in 3,094 women and 2,132 men in the 2001 Tromsø Study. BMD levels were significantly explained by age and declined progressively in both sexes from middle into old age, with highest decline in women. With osteoporosis defined as a T-score of two and a half standard deviation below the young adult mean BMD, the prevalence at the total hip in subjects above 70 years was 6.9% in men and 15.3% in women, respectively, using the Lunar reference material for T-score calculations. The prevalence increased significantly to 7.3% in men and 19.5% in women, when T-scores were calculated on basis of the young adult mean BMD (age group 30-39 years) in the study population. At the femoral neck, prevalence of osteoporosis increased from 13.5 to 18.5% in men, and from 20.4 to 35.2% in women above 70 years, respectively, depending on how T-scores were calculated. The study highlights the challenges with fixed diagnostic levels when measuring normally distributed physiologic parameters. Although BMD only partly explains fracture risk, future studies should evaluate which calculations give optimal fracture prediction.
PubMed ID
19296062 View in PubMed
Less detail

Bone mineral density is associated with vitamin D related rs6013897 and estrogen receptor polymorphism rs4870044: The Tromsø study.

https://arctichealth.org/en/permalink/ahliterature280495
Source
PLoS One. 2017;12(3):e0173045
Publication Type
Article
Date
2017
Author
Ieva Martinaityte
Rolf Jorde
Nina Emaus
Anne Elise Eggen
Ragnar Martin Joakimsen
Elena Kamycheva
Source
PLoS One. 2017;12(3):e0173045
Date
2017
Language
English
Publication Type
Article
Abstract
Bone mineral density (BMD) is determined by bone remodeling processes regulated by endocrine, autocrine and genetic mechanisms. Thus, some studies have reported that BMD is associated with single nucleotide polymorphisms (SNPs) associated with vitamin D receptor (VDR), serum 25(OH)D levels and estrogen receptor 1 (ESR1), but without consensus. Therefore, we aimed to map and compare the risk genotypes for forearm and total hip low BMD.
Data were derived from a population-based study in northern Norway; the Tromsø Study. Distal forearm BMD was measured with a single x-ray absorptiometric device, while total hip BMD was measured with a dual-energy x-ray absorptiometric device. There were 7,317 and 4,082 successful analyses of distal forearm and total hip BMD, respectively, and at least one SNP of interest. We evaluated plausible BMD modulating factors and associations of BMD and SNPs related to vitamin D metabolism (FokI, Cdx2, BsmI, rs2298850, rs10741657, rs3794060, rs6013897), ApaI-BsmI-TaqI haplotypes and ESR1 SNP rs4870044.
Age, BMI, physical activity and smoking were significantly associated with BMD. In a linear regression model with adjustment for age and gender and with the major homozygote as reference, rs6013897 had a standardized beta coefficient (ß) of -0.031 (P = 0.024) for total hip BMD. ß for ESR1 SNP rs4870044 was -0.016 (P = 0.036) for forearm BMD and -0.034 (P = 0.015) for total hip BMD. The other SNPs nor serum 25(OH)D were significantly associated with BMD.
Both forearm and total hip BMD were associated with ESR1 SNP rs4870044. Of the vitamin D-related genes, only CYP24A1 gene rs6013897 was associated with total hip BMD, but the association was weak and needs confirmation in other studies. Serum 25(OH)D was not associated with BMD in our population, probably due to the generally sufficient vitamin D levels in the population.
Notes
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