Time trends in osteoporosis prevalence and cross-sectional associations with parental family history: The Tromsø Study

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This study aimed to examine trends in the prevalence of osteoporosis and the association between a parental family history of osteoporosis and osteoporosis. Methods Self-reported data from the population-based Tromsø Study, conducted in 1994–1995 (Tromsø4), 2001 (Tromsø5), and 2007–2008 (Tromsø6), were utilized in this cross-sectional study, with analyses performed using generalized estimating equations and logistic regression. Results The prevalences of osteoporosis increased over time in both women and men. Women had a higher prevalence of osteoporosis than men in both age groups (≤ 50 and > 50 years old). Among women, the highest prevalence of osteoporosis (9.9% [95% CI 9-10.8]) was found in Tromsø6 for the > 50 age group, while the lowest (0.1% [0.1–0.2]) was observed in the ≤ 50 age group in Tromsø4. Among men, the highest prevalence (1.2% [0.8–1.6]) was found in Tromsø5 for the > 50 age group, whereas the lowest (0.1% [0.05–0.2]) was observed in the ≤ 50 age group in Tromsø4. A parental history of osteoporosis independently increased the odds of osteoporosis with an odds ratio of 2.4 [95% CI 1.9–3.2]. The association remained independent, across both sexes and all levels of adjustment (age and osteoporosis-related factors). Conclusion Utilizing this knowledge to develop a more personalized approach may enhance osteoporosis prevention and control. Osteoporosis Prevalence Family History Epidemiology Sex-specific Figures Figure 1 Figure 2 Background Osteoporosis is a growing public health concern, significantly impacting morbidity, mortality, and healthcare costs 1–5 . With an aging population and various contributing risk factors, understanding the prevalence and determinants of osteoporosis is crucial for developing effective prevention strategies. Risk factors include advanced age, female sex, certain ethnic backgrounds, lifestyle habits, chronic conditions, and a family history of fractures 6 etc. Despite its widespread impact, osteoporosis often remains undiagnosed until fractures occur, leading to serious health consequences and substantial economic burdens. Norway, like many other countries, faces an osteoporosis burden. The prevalence of osteoporosis globally is estimated at approximately 19% 7–8 . Norwegian data suggest that between 240,000 and 300,000 individuals are affected 9 . Considering that the total population of Norway in 2016 was 5,213,985 10 , this corresponds to a prevalence between 4.6% and 5.7%. The Tromsø Study data demonstrated higher prevalences in men (10.8%) and women (20.9%) 11 compared to the national total estimates. One well-established risk factor for developing osteoporosis is a family history of fractures, particularly on the maternal side 6 . However, whether a family history of osteoporosis itself increases the likelihood of developing the condition remains uncertain, as studies have reported conflicting findings 7,12–14 . This study aims to examine trends in osteoporosis prevalence in the Tromsø Study and assess the role of parental history of osteoporosis. Methods Study design The Tromsø Study is a population-based longitudinal cohort study comprising seven consecutive surveys conducted in the municipality of Tromsø, Norway between 1974 and 2016. Both complete birth cohorts and random samples of women and men were invited to participate 15 . This cross-sectional study used data from three surveys—Tromsø4 (1994–1995), Tromsø5 (2001), and Tromsø6 (2007–2008) —all of which followed standardized protocols and collected relevant information on osteoporosis. Tromsø4 was the first survey to include osteoporosis data and enabled prevalence estimates over time. Tromsø6 was additionally used to examine associations with parental history of osteoporosis due to the availability of relevant covariates. Study population A total of 30,288 individuals who participated in at least one of the three surveys were included (Figure 1). For osteoporosis prevalence analyses, participants were required to have complete data on osteoporosis status, age, and sex, resulting in inclusion rates of 83.1% (Tromsø4), 96.7% (Tromsø5), and 97.3% (Tromsø6). Analyses of parental history and osteoporosis were restricted to Tromsø6 participants with complete data on family history, osteoporosis status, and covariates (Figure 2); 91.2% met the inclusion criteria after excluding outliers. Data Collection The Tromsø Study surveys have followed the same general design and have been described in detail previously 15-16 . In Tromsø4–6, osteoporosis status (yes/no) was assessed through self-administered questionnaires. In Tromsø6, we additionally used questionnaire data on family history of osteoporosis (parents, children, siblings; yes/no), use of osteoporosis medication (yes/no), education level (primary school/ vocational school/ upper secondary school/ university < 4 years/ university ≥ 4 years), physical activity frequency (never/ less than once a week/ once a week/ 2-3 times a week/ approximately every day), alcohol consumption frequency (never/ monthly or less frequently/ 2-4 times a month/ 2-3 times a week/ 4 or more times a week), daily smoking (current/ previous/ never), daily coffee and tea consumption (cups per day). Further details on the questionnaires are available on the Tromsø Study website (https://uit.no/research/tromsostudy). Body height and weight were measured with participants wearing light clothing and no shoes. Height was recorded to the nearest 0.1 cm and weight to the nearest 100 g. Body mass index (BMI) was calculated as weight (kg) divided by height (m²). According to the WHO classification, BMI was categorized as underweight (<18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), and obesity (≥30.0 kg/m²). Statistical Analysis Osteoporosis prevalence was estimated with 95% confidence intervals (CIs) and stratified by survey, sex, and age group (≤50 vs. >50 years). Prevalence across surveys was compared using generalized estimating equations (GEE) to account for repeated participation. Odds ratios (ORs), CIs, and p-values are reported. Associations between parental history of osteoporosis and osteoporosis prevalence were examined using binomial logistic regression. Potential confounders were identified using directed acyclic graphs (DAGs) and included sex, age, education, smoking, alcohol use, tea and coffee consumption, physical activity, and BMI. Interaction between sex and family history was assessed but was not statistically significant; nevertheless, sex-stratified analyses were presented due to clinical relevance. The interaction between age and family history was not tested, as genetic risk factors remain constant over life. Results The total prevalences suggest an increase in osteoporosis over time, with the most significant jump observed from Tromsø4 to Tromsø5 (Table 1). This trend was more pronounced in women. Men displayed the highest total prevalence in Tromsø5. In both women and men regardless of the age, the proportion of individuals with osteoporosis significantly differed in Tromsø5 and Tromsø6 compared to Tromsø4. Specifically, in Tromsø5, the odds of developing osteoporosis were higher compared to Tromsø4, with an OR of 1.9 [95% CI 1.7-2.2] in women and 3.8 [95% CI 2.3-6.2] in men. Similarly, in Tromsø6, the OR were 3.0 [95% CI 2.7-3.3] in women and 4.1 [95% CI 2.7-6.5] in men. In women, the prevalence of osteoporosis increased with age. In women aged ≤50 years, the prevalence of osteoporosis remained low in Tromsø4 (0.1%) and Tromsø5 (0.2%), with an increase in Tromsø6 (1.0%) (Table 1). Compared to Tromsø4, the prevalence in Tromsø5 was stable [p = 0.95, OR = 1.1, 95% CI (0.2–5.0)], while in Tromsø6, the odds of having osteoporosis were higher [OR = 6.8, 95% CI (3.4–13.6)]. Among women aged >50 years, the prevalence of osteoporosis gradually increased over time, reaching its highest level in Tromsø6 (9.9%). Compared to Tromsø4, the odds of osteoporosis were elevated in both Tromsø5 [OR = 1.3, 95% CI (1.1–1.4)] and Tromsø6 [OR = 1.7, 95% CI (1.5–2.0)]. In men, the prevalence of osteoporosis was lower compared to women in the older age group and was the same in the younger age group, except in Tromsø6. In men aged ≤50 years, the prevalence of osteoporosis was relatively low across all three surveys—0.1% in Tromsø4, 0.2% in Tromsø5, and 0.4% in Tromsø6. Compared to Tromsø4, the prevalence in Tromsø5 remained stable [OR = 1.3, 95% CI (0.3–6.1)], while in Tromsø6, the odds of developing osteoporosis were higher [OR = 2.8, 95% CI (1.2–6.7)]. Among men aged >50 years, the prevalence increased from 0.4% in Tromsø4 to 1.2% in Tromsø5, followed by a slight decrease to 1.1% in Tromsø6. The odds of developing osteoporosis were higher in both Tromsø5 [OR = 3.1, 95% CI (1.7–5.7)] and Tromsø6 [OR = 3.3, 95% CI (1.9–5.9)] compared to Tromsø4. Table 1 Prevalence of osteoporosis stratified by sex and age group in Tromsø4, Tromsø5, and Tromsø6 Women (n=22,894) Men (n=20,179) Age (years) Tromsø4 Tromsø5 Tromsø6 Tromsø4 Tromsø5 Tromsø6 ≤50 cases/total % (95% CI) OR (95% CI) p-value 11/7938 0.1 (0.1-0.2) - - 2/1164 0.2 (0.02-0.6) 1.1 (0.2-5.0) 0.95 22/2306 (0.6-1.4) 6.8 (3.4-13.6) 50 cases/total % (95% CI) OR (95% CI) p-value 313/3805 8.2 (7.4-9.1) - - 292/3265 8.9 (8.0 -9.9) 1.3 (1.1-1.4) 0.001 437/4416 9.9 (9.0-10.8) 1.7 (1.5-2.0) <0.001 15/3729 0.4 (0.2-0.6) - - 31/2541 1.2 (0.8-1.6) 3.1 (1.7-5.7) <0.001 45/3954 1.1 (0.8-1.5) 3.3 (1.9-5.9) <0.001 Total cases/total % (95% CI) OR (95% CI) p-value 324/11743 2.8 (2.5-3.1) - - 294/4429 6.6 (5.9-7.4) 1.9 (1.7-2.2) <0.001 459/6722 6.8 (6.2-7.4) 3.0 (2.7-3.3) <0.001 25/10837 0.2 (0.1-0.3) - - 33/3432 1.0 (0.6-1.3) 3.8 (2.3-6.2) <0.001 52/5910 0.9 (0.6-1.1) 4.1 (2.7-6.5) <0.001 OR = Odds Ratio, CI = Confidence Interval. Descriptive characteristics of participants in Tromsø6 are presented in Table 2. Most participants were over 50 years of age. Across sexes and family history groups, vocational education, physical activity 2–3 times per week, overweight, and alcohol consumption 2–4 times per month were most common. Coffee/tea intake was lowest among women without a family history of osteoporosis and highest among men with a positive family history, while former smoking predominated, particularly among men. Table 2 Descriptive characteristics of women and men with and without family history of osteoporosis; Tromsø6 Women Men Family history of osteoporosis No family history of osteoporosis Family history of osteoporosis No family history of osteoporosis Age, years 55.35 (10.64) 56.78 (12.84) 54.85 (9.36) 57.02 (12.25) Age, groups ≤50 years 267 (36%) 1967 (36%) 134 (35%) 1788 (34%) >50 years 474 (64%) 3521 (64%) 254 (65%) 3442 (66%) Education Primary school 170 (23%) 1688 (31%) 93 (24%) 1245 (24%) Vocational school 194 (26%) 1326 (24%) 97 (25%) 1490 (28%) Upper secondary school 53 (7%) 435 (8%) 29 (7%) 383 (7%) University < 4 years 133 (18%) 841 (15%) 77 (20%) 1102 (21%) University ≥ 4 years 191 (26%) 1198 (22%) 92 (24%) 1010 (19%) Physical activity Never 29 (4%) 270 (5%) 25 (6%) 335 (6%) Less than once a week 85 (11%) 734 (13%) 77 (20%) 1047 (20%) Once a week 140 (19%) 1010 (18%) 90 (23%) 1115 (21%) 2-3 times a week 328 (44%) 2238 (41%) 139 (36%) 1914 (37%) Approximately every day 159 (21%) 1236 (23%) 57 (15%) 819 (16%) BMI Underweight 5 (1%) 44 (1%) 0 (0%) 13 (0%) Normal weight 326 (44 %) 2229 (41%) 128 (33%) 1416 (27%) Overweight 272 (37%) 2122 (39%) 190 (49%) 2714 (52%) Obesity 138 (19%) 1093 (20%) 70 (18%) 1087 (21%) Never 75 (10%) 7373 (13%) 22 (6%) 383 (7%) Monthly or less frequently 203 (27%) 1723 (31%) 92 (24%) 1334 (26%) Alcohol 2-4 times a month 272 (37%) 1956 (36%) 88 (23%) 994 (19%) 2-3 times a week 148 (20%) 835 (15%) 88 (23%) 994 (19%) 4 or more times a week 43 (6%) 237 (4%) 26 (7%) 300 (6%) Coffee/tea Cups per day 5.12 (2.65) 5.00 (2.51) 6.04 (3.08) 5.61 (3.11) Daily smoking Current 147 (20%) 1176 (21%) 68 (18%) 1002 (19%) Previous 313 (42%) 2083 (38%) 169 (44%) 2444 (47%) Never 281 (38%) 2229 (41%) 151 (39%) 1784 (34%) BMI=body mass index. Data in the table presented as absolute number (%) or mean (standard deviation). Having a parental family history of osteoporosis independently increased the odds of having osteoporosis (Table 3). For the overall population the crude OR was 2.5 [95% CI 2.0-3.2], the age-adjusted OR was 2.6 [95% CI 2.0-3.3], and the fully-adjusted OR was 2.4 [95% CI 1.9-3.2]. Individuals with a parental history of osteoporosis were more than twice as likely to be diagnosed with the condition themselves compared to those without a family history of osteoporosis. The increase in risk remained consistent across different levels of adjustment, reinforcing the robustness of the association. When stratifying by sex the association was stronger in men. However, the interaction term was not statistically significant (p=0.2). Table 3 Odds ratios with 95% confidence intervals, for developing a family history of osteoporosis, at different levels of adjustment in the overall population, and separately for women and men Crude OR (95% CI) p-value Age-adjusted OR (95% CI) p-value Fully-adjusted OR a (95% CI) p-value Parental family history of osteoporosis 2.5 (2.0-3.2) <0.001 2.6 (2.0-3-3) <0.001 2.4 (1.9-3.2) <0.001 Parental family history of osteoporosis in women 1.97 (1.5-2.6) <0.001 2 (1.5-2.6) <0.001 2.3 (1.7-3.0) <0.001 Parental family history of osteoporosis in men 3.2 (1.6-6.8) 0.002 3.3 (1.6-6.8) 0.002 3.9 (1.8-8.2) <0.001 OR= Odds Ratio, CI= Confidence Interval. a Adjusted for age, sex (for non-sex-specific models), education, physical activity, body mass index, alcohol consumption, coffee/tea consumption, daily smoking. Discussion Summary of main findings Overall, osteoporosis prevalence is increasing over time in both sexes. Women showed higher osteoporosis prevalence than men in the older age group, while rates were similar between sexes in the younger group. Among women, the highest prevalence was observed in Tromsø6 and the lowest in Tromsø4. Among men, the highest prevalences occurred in Tromsø5 and Tromsø6 for those over 50 years, and in Tromsø6 for those aged 50 years or younger. An independent association between parental family history of osteoporosis and increased odds of developing the condition was found, with an OR of 2.63 [95% CI 2.02-3.43]. The association remains significant when stratified by sex and across different levels of adjustment. Scientific discussion Osteoporosis prevalence data from Norway are scarce, and this study provides novel population-based estimates from Tromsø using self-reported data. Compared with earlier DXA-based studies 11 , this study shows slightly different osteoporosis prevalence estimates. Prior DXA research suggests 17 higher prevalence in Tromsø4 than Tromsø5, with no available comparisons for Tromsø6. Research results on trends in osteoporosis prevalence over time in a population are inconsistent. While some studies report fluctuations 18-19 , others suggest stability 20-22 . The upward trend may reflect aging and other characteristic variations 23 of the population, changes in diagnostic practices 24 and awareness, lifestyle changes such as diet, exercise and smoking, and advances in medical care. The decline in bone mineral density (BMD) from Tromsø5 to Tromsø6 25 further supports the increasing prevalence observed in this study. Consistent with existing literature, osteoporosis prevalence was higher in women 6 . Earlier research and classic orthopedic texts 14-15,26 highlight a family history of osteoporosis as a risk factor, while more recent studies and WHO guidelines 6,27 focus on family history of fractures. In this study, parental history of osteoporosis remained a relevant risk factor, potentially more predictive in men, highlighting the importance of familial, genetic 28 environmental and epigenetic 29 contributions to osteoporosis risk. Strengths and limitations The main strengths of this study include its large, population-based sample, high participation, and comprehensive data collection, which enhance statistical power, representativeness, and the ability to adjust for key confounders. However, limitations include reliance on self-reported data and potential selection and information bias related to healthy participant effect and recall bias. However, studies have found only minor differences between participants and non-participants in the Tromsø Study surveys, supporting the overall generalizability of the results in the general population 30 . Risk of residual confounding from unmeasured factors such as race cannot be excluded. Some variables, like smoking, may be affected by measurement errors inherent in self-reported data. Conclusions The findings indicate a rising trend in osteoporosis prevalence over time. Tromsø4 recorded the lowest rates for both men and women across all age groups. Among women and younger men, Tromsø6 showed the highest prevalence, while older men had the highest rates in Tromsø5. A parental family history of osteoporosis independently increased the odds of developing the condition in both the overall population and sex-specific groups across all levels of adjustment. This study enhances the epidemiological understanding of osteoporosis and underscores the importance of personalized prevention and management strategies based on individual risk factors. Declarations Ethics approval and consent to participate The Tromsø Study has been performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. All participants provided prior voluntary informed consent before participating in the Tromsø Study surveys. This study has been approved by Regional committees for medical and health research ethics (REC, reference 696648). Consent for publication Not applicable. Availability of data and materials Upon request, data may be made available to researchers who have obtained approval from the Data and Publication Committee of the Tromsø Study. Information for applicants is available at: https://uit.no/research/tromsostudy Competing interests The authors declare that they have no competing interests. Funding This study was conducted as part of a Master’s thesis in Public Health at UiT The Arctic University of Norway. Open access funding was provided by UiT The Arctic University of Norway. Authors' contributions MA, ML, and ES conceptualized the study and formulated the research questions. MA conducted all statistical analyses and drafted the manuscript. ML and ES revised the manuscript. All authors read and approved the final version of the paper. Acknowledgements We thank the participants of the Tromsø Study for their invaluable contributions. Authors' information (optional) Not applicable. References Adami G, Fassio A, Gatti D, Viapiana O, Benini C, Danila MI, et al. Osteoporosis in 10 years time: a glimpse into the future of osteoporosis. Ther Adv Musculoskelet Dis . 2022;14:1759720X221083541. Harvey N, Dennison E, Cooper C. Osteoporosis: impact on health and economics. Nat Rev Rheumatol . 2010;6(2):99–105. Becker DJ, Kilgore ML, Morrisey MA. The societal burden of osteoporosis. Curr Rheumatol Rep . 2010;12:186–191. Dennison E, Mohamed MA, Cooper C. Epidemiology of osteoporosis. Rheum Dis Clin North Am . 2006;32(4):617–629. Kemmak AR, Rezapour A, Jahangiri R, Nikjoo S, Farabi H, Soleimanpour S. Economic burden of osteoporosis in the world: a systematic review. Med J Islam Repub Iran . 2020;34:154. World Health Organization. World Osteoporosis Day: simple ways to prevent osteoporosis. Geneva: World Health Organization; 2019 Oct 20. Available from: https://www.who.int/westernpacific/articles/item/simple-ways-to-prevent-osteoporosis Xiao PL, Cui AY, Hsu CJ, Peng R, Jiang N, Xu XH, et al. Global, regional prevalence, and risk factors of osteoporosis according to the World Health Organization diagnostic criteria: a systematic review and meta-analysis. Osteoporos Int . 2022;33(10):2137–2153. Salari N, Ghasemi H, Mohammadi L, Rabieenia E, Shohaimi S, Mohammadi M. The global prevalence of osteoporosis in the world: a comprehensive systematic review and meta-analysis. J Orthop Surg Res . 2021;16(1):1–20. Meyer HE. Osteoporosis and fractures in Norway: fact sheet. Oslo: Norwegian Institute of Public Health; 2016 Nov 9. Statistik Sentralbyrå (Statistics Norway). Population [Internet]. Oslo: Statistics Norway; n.d. Available from: https://www.ssb.no/en/statbank/table/06913/ Emaus N, Omsland TK, Ahmed LA, Grimnes G, Sneve M, Berntsen GK. Bone mineral density at the hip in Norwegian women and men—prevalence of osteoporosis depends on chosen references: the Tromsø Study. Eur J Epidemiol . 2009;24:321–328. Robitaille J, Yoon PW, Moore CA, Liu T, Irizarry-Delacruz M, Looker AC, Khoury MJ. Prevalence, family history, and prevention of reported osteoporosis in US women. Am J Prev Med . 2008;35(1):47–54. Soroko SB, Barrett-Connor E, Edelstein SL, Kritz-Silverstein D. Family history of osteoporosis and bone mineral density at the axial skeleton: the Rancho Bernardo Study. J Bone Miner Res . 1994;9(6):761–769. Gasparik A, Szőcs T, Pascanu I, Csata Z, Poiana C. Family history BMD independently influences fracture risk. Acta Endocrinol (Buchar) . 2021;17(4):498. Jacobsen BK, Eggen AE, Mathiesen EB, Wilsgaard T, Njølstad I. Cohort profile: the Tromsø Study. Int J Epidemiol . 2012;41(4):961–967. UiT The Arctic University of Norway. The Tromsø Study [Internet]. Tromsø: UiT; n.d. Available from: https://uit.no/research/tromsostudy Hauger AV, Bergland A, Holvik K, Ståhle A, Emaus N, Strand BH. Osteoporosis and osteopenia in the distal forearm predict all-cause mortality independent of grip strength: 22-year follow-up in the population-based Tromsø Study. Osteoporos Int . 2018;29(11):2447–2456. Looker AC, Sarafrazi Isfahani N, Fan B, Shepherd JA. Trends in osteoporosis and low bone mass in older US adults, 2005–2006 through 2013–2014. Osteoporos Int . 2017;28(6):1979–1988. Smith L, Wilson S. Trends in osteoporosis diagnosis and management in Australia. Arch Osteoporos . 2022;17(1):97. Ahlborg HG, Rosengren BE, Järvinen TLN, Rogmark C, Nilsson JÅ, Sernbo I, Karlsson MK. Prevalence of osteoporosis and incidence of hip fracture in women—secular trends over 30 years. BMC Musculoskelet Disord . 2010;11:48. Rosengren BE, Ahlborg HG, Gärdsell P, Sernbo I, Daly RM, Nilsson JÅ, Karlsson MK. Bone mineral density and incidence of hip fracture in Swedish urban and rural women 1987–2002. Acta Orthop . 2010;81(4):453–459. Zhang X, Wang Z, Zhang D, Ye D, Zhou Y, Qin J, Zhang Y. The prevalence and treatment rate trends of osteoporosis in postmenopausal women. PLoS One . 2023;18(9):e0290289. Du P, Coles FB, O’Campo P, McNutt LA. Changes in population characteristics and their implication on public health research. Epidemiol Perspect Innov . 2007;4:6. Lorentzon M, Cummings SR. Osteoporosis: the evolution of a diagnosis. J Intern Med . 2015;277(6):650–661. Emaus N, Wilsgaard T, Ahmed LA. Impacts of body mass index, physical activity, and smoking on femoral bone loss: the Tromsø Study. J Bone Miner Res . 2014;29(9):2080–2089. Miller MD, Thompson SR. Miller’s Review of Orthopaedics . 8th ed. Philadelphia: Elsevier; 2019. Kanis JA, Johansson H, Oden A, Johnell O, De Laet C, Eisman JA, et al. A family history of fracture and fracture risk: a meta-analysis. Bone . 2004;35(5):1029–1037. Stewart T, Ralston S. Role of genetic factors in the pathogenesis of osteoporosis. J Endocrinol . 2000;166(2):235–245. Chen Y, Sun Y, Xue X, Ma H. Comprehensive analysis of epigenetics mechanisms in osteoporosis. Front Genet . 2023;14:1153585. Jacobsen BK, Thelle DS. The Tromsø Heart Study: responders and non-responders to a health questionnaire—do they differ? Scand J Soc Med . 1988;16(2):101–104. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8910562","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600905191,"identity":"69a8d4e9-84c2-439f-a7dc-bf2fead1c9ae","order_by":0,"name":"Maria Andreadou","email":"","orcid":"","institution":"General Hospital of Kavala","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Andreadou","suffix":""},{"id":600905192,"identity":"a1641f74-fa37-46fa-80e7-7e7277a94540","order_by":1,"name":"Marko Lukic","email":"","orcid":"","institution":"UiT The Arctic University of Norway","correspondingAuthor":false,"prefix":"","firstName":"Marko","middleName":"","lastName":"Lukic","suffix":""},{"id":600905193,"identity":"54c3b4ef-915a-4388-948c-3b40164a0d9c","order_by":2,"name":"Ekaterina Sharashova","email":"data:image/png;base64,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","orcid":"","institution":"UiT The Arctic University of Norway","correspondingAuthor":true,"prefix":"","firstName":"Ekaterina","middleName":"","lastName":"Sharashova","suffix":""}],"badges":[],"createdAt":"2026-02-18 15:09:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8910562/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8910562/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104402610,"identity":"5e82c168-ca64-4282-903f-b53f904a3cd4","added_by":"auto","created_at":"2026-03-11 12:15:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103742,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of study participants – Tromsø osteoporosis prevalence trends\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8910562/v1/59c3db27948eb5f4abb4ffef.png"},{"id":104024097,"identity":"93ddbafe-ce4f-426c-84fa-e0581f4e7a79","added_by":"auto","created_at":"2026-03-05 19:43:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64663,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of study participants – parental history and its role in osteoporosis development\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8910562/v1/54e9f95dcc541875f327f20b.png"},{"id":105260063,"identity":"fb7ca239-a5e9-4953-b41c-13dc618cc50c","added_by":"auto","created_at":"2026-03-24 05:56:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":751589,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8910562/v1/779e244f-0853-44bc-b926-4d6cf49a9445.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Time trends in osteoporosis prevalence and cross-sectional associations with parental family history: The Tromsø Study","fulltext":[{"header":"Background","content":"\u003cp\u003eOsteoporosis is a growing public health concern, significantly impacting morbidity, mortality, and healthcare costs\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. With an aging population and various contributing risk factors, understanding the prevalence and determinants of osteoporosis is crucial for developing effective prevention strategies. Risk factors include advanced age, female sex, certain ethnic backgrounds, lifestyle habits, chronic conditions, and a family history of fractures\u003csup\u003e6\u003c/sup\u003e etc. Despite its widespread impact, osteoporosis often remains undiagnosed until fractures occur, leading to serious health consequences and substantial economic burdens.\u003c/p\u003e \u003cp\u003eNorway, like many other countries, faces an osteoporosis burden. The prevalence of osteoporosis globally is estimated at approximately 19%\u003csup\u003e7\u0026ndash;8\u003c/sup\u003e. Norwegian data suggest that between 240,000 and 300,000 individuals are affected\u003csup\u003e9\u003c/sup\u003e. Considering that the total population of Norway in 2016 was 5,213,985\u003csup\u003e10\u003c/sup\u003e, this corresponds to a prevalence between 4.6% and 5.7%. The Troms\u0026oslash; Study data demonstrated higher prevalences in men (10.8%) and women (20.9%)\u003csup\u003e11\u003c/sup\u003e compared to the national total estimates.\u003c/p\u003e \u003cp\u003eOne well-established risk factor for developing osteoporosis is a family history of fractures, particularly on the maternal side\u003csup\u003e6\u003c/sup\u003e. However, whether a family history of osteoporosis itself increases the likelihood of developing the condition remains uncertain, as studies have reported conflicting findings\u003csup\u003e7,12\u0026ndash;14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study aims to examine trends in osteoporosis prevalence in the Troms\u0026oslash; Study and assess the role of parental history of osteoporosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Troms\u0026oslash; Study is a population-based longitudinal cohort study comprising seven consecutive surveys conducted in the municipality of Troms\u0026oslash;, Norway between 1974 and 2016. Both complete birth cohorts and random samples of women and men were invited to participate\u003csup\u003e15\u003c/sup\u003e. This cross-sectional study used data from three surveys\u0026mdash;Troms\u0026oslash;4 (1994\u0026ndash;1995), Troms\u0026oslash;5 (2001), and Troms\u0026oslash;6 (2007\u0026ndash;2008) \u0026mdash;all of which followed standardized protocols and collected relevant information on osteoporosis. Troms\u0026oslash;4 was the first survey to include osteoporosis data and enabled prevalence estimates over time. Troms\u0026oslash;6 was additionally used to examine associations with parental history of osteoporosis due to the availability of relevant covariates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 30,288 individuals who participated in at least one of the three surveys were included (Figure 1). For osteoporosis prevalence analyses, participants were required to have complete data on osteoporosis status, age, and sex, resulting in inclusion rates of 83.1% (Troms\u0026oslash;4), 96.7% (Troms\u0026oslash;5), and 97.3% (Troms\u0026oslash;6). Analyses of parental history and osteoporosis were restricted to Troms\u0026oslash;6 participants with complete data on family history, osteoporosis status, and covariates (Figure 2); 91.2% met the inclusion criteria after excluding outliers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Troms\u0026oslash; Study surveys have followed the same general design and have been described in detail previously\u003csup\u003e15-16\u003c/sup\u003e. In Troms\u0026oslash;4\u0026ndash;6, osteoporosis status (yes/no) was assessed through self-administered questionnaires. In Troms\u0026oslash;6, we additionally used questionnaire data on family history of osteoporosis (parents, children, siblings; yes/no), use of osteoporosis medication (yes/no), education level (primary school/ vocational school/ upper secondary school/ university \u0026lt; 4 years/ university \u0026ge; 4 years), physical activity frequency (never/ less than once a week/ once a week/ 2-3 times a week/ approximately every day), alcohol consumption frequency (never/ monthly or less frequently/ 2-4 times a month/ 2-3 times a week/ 4 or more times a week), daily smoking (current/ previous/ never), daily coffee and tea consumption (cups per day). Further details on the questionnaires are available on the Troms\u0026oslash; Study website (https://uit.no/research/tromsostudy).\u003c/p\u003e\n\u003cp\u003eBody height and weight were measured with participants wearing light clothing and no shoes. Height was recorded to the nearest 0.1 cm and weight to the nearest 100 g. Body mass index (BMI) was calculated as weight (kg) divided by height (m\u0026sup2;). According to the WHO classification, BMI was categorized as underweight (\u0026lt;18.5 kg/m\u0026sup2;), normal weight (18.5\u0026ndash;24.9 kg/m\u0026sup2;), overweight (25.0\u0026ndash;29.9 kg/m\u0026sup2;), and obesity (\u0026ge;30.0 kg/m\u0026sup2;).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOsteoporosis prevalence was estimated with 95% confidence intervals (CIs) and stratified by survey, sex, and age group (\u0026le;50 vs. \u0026gt;50 years). Prevalence across surveys was compared using generalized estimating equations (GEE) to account for repeated participation. Odds ratios (ORs), CIs, and p-values are reported.\u003c/p\u003e\n\u003cp\u003eAssociations between parental history of osteoporosis and osteoporosis prevalence were examined using binomial logistic regression. Potential confounders were identified using directed acyclic graphs (DAGs) and included sex, age, education, smoking, alcohol use, tea and coffee consumption, physical activity, and BMI. Interaction between sex and family history was assessed but was not statistically significant; nevertheless, sex-stratified analyses were presented due to clinical relevance. The interaction between age and family history was not tested, as genetic risk factors remain constant over life.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe total prevalences suggest an increase in osteoporosis over time, with the most significant jump observed from Troms\u0026oslash;4 to Troms\u0026oslash;5 (Table 1). This trend was more pronounced in women. Men displayed the highest total prevalence in Troms\u0026oslash;5. In both women and men regardless of the age, the proportion of individuals with osteoporosis significantly differed in Troms\u0026oslash;5 and Troms\u0026oslash;6 compared to Troms\u0026oslash;4. Specifically, in Troms\u0026oslash;5, the odds of developing osteoporosis were higher compared to Troms\u0026oslash;4, with an OR of 1.9 [95% CI 1.7-2.2] in women and 3.8 [95% CI 2.3-6.2] in men. Similarly, in Troms\u0026oslash;6, the OR were 3.0 [95% CI 2.7-3.3] in women and 4.1 [95% CI 2.7-6.5] in men.\u003c/p\u003e\n\u003cp\u003eIn women, the prevalence of osteoporosis increased with age. \u0026nbsp; In women aged \u0026le;50 years, the prevalence of osteoporosis remained low in Troms\u0026oslash;4 (0.1%) and Troms\u0026oslash;5 (0.2%), with an increase in Troms\u0026oslash;6 (1.0%) (Table 1). Compared to Troms\u0026oslash;4, the prevalence in Troms\u0026oslash;5 was stable [p = 0.95, OR = 1.1, 95% CI (0.2\u0026ndash;5.0)], while in Troms\u0026oslash;6, the odds of having osteoporosis were higher [OR = 6.8, 95% CI (3.4\u0026ndash;13.6)]. Among women aged \u0026gt;50 years, the prevalence of osteoporosis gradually increased over time, reaching its highest level in Troms\u0026oslash;6 (9.9%). Compared to Troms\u0026oslash;4, the odds of osteoporosis were elevated in both Troms\u0026oslash;5 [OR = 1.3, 95% CI (1.1\u0026ndash;1.4)] and Troms\u0026oslash;6 [OR = 1.7, 95% CI (1.5\u0026ndash;2.0)].\u003c/p\u003e\n\u003cp\u003eIn men, the prevalence of osteoporosis was lower compared to women in the older age group and was the same in the younger age group, except in Troms\u0026oslash;6. In men aged \u0026le;50 years, the prevalence of osteoporosis was relatively low across all three surveys\u0026mdash;0.1% in Troms\u0026oslash;4, 0.2% in Troms\u0026oslash;5, and 0.4% in Troms\u0026oslash;6. Compared to Troms\u0026oslash;4, the prevalence in Troms\u0026oslash;5 remained stable [OR = 1.3, 95% CI (0.3\u0026ndash;6.1)], while in Troms\u0026oslash;6, the odds of developing osteoporosis were higher [OR = 2.8, 95% CI (1.2\u0026ndash;6.7)]. Among men aged \u0026gt;50 years, the prevalence increased from 0.4% in Troms\u0026oslash;4 to 1.2% in Troms\u0026oslash;5, followed by a slight decrease to 1.1% in Troms\u0026oslash;6. The odds of developing osteoporosis were higher in both Troms\u0026oslash;5 [OR = 3.1, 95% CI (1.7\u0026ndash;5.7)] and Troms\u0026oslash;6 [OR = 3.3, 95% CI (1.9\u0026ndash;5.9)] compared to Troms\u0026oslash;4.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Prevalence of osteoporosis stratified by sex and age group in Troms\u0026oslash;4, Troms\u0026oslash;5, and Troms\u0026oslash;6\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"814\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4626%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.6952%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWomen (n=22,894)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5719%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.0789%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3455%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMen (n=20,179)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5859%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4626%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.6952%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5719%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.0789%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8167%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTroms\u0026oslash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4626%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026le;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.6952%;\"\u003e\n \u003cp\u003ecases/total\u003c/p\u003e\n \u003cp\u003e% (95% CI)\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7231%;\"\u003e\n \u003cp\u003e11/7938\u003c/p\u003e\n \u003cp\u003e0.1 (0.1-0.2)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e2/1164\u003c/p\u003e\n \u003cp\u003e0.2 (0.02-0.6)\u003c/p\u003e\n \u003cp\u003e1.1 (0.2-5.0)\u003c/p\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5719%;\"\u003e\n \u003cp\u003e22/2306\u003c/p\u003e\n \u003col\u003e\n \u003cli\u003e(0.6-1.4)\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e6.8 (3.4-13.6)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.0789%;\"\u003e\n \u003cp\u003e10/7108\u003c/p\u003e\n \u003cp\u003e0.1 (0.05-0.2)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e2/891\u003c/p\u003e\n \u003cp\u003e0.2 (0.03-0.8)\u003c/p\u003e\n \u003cp\u003e1.3 (0.3-6.1)\u003c/p\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8167%;\"\u003e\n \u003cp\u003e7/1956\u003c/p\u003e\n \u003cp\u003e0.4 (0.1-0.6)\u003c/p\u003e\n \u003cp\u003e2.8 (1.2-6.7)\u003c/p\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4626%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026gt;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.6952%;\"\u003e\n \u003cp\u003ecases/total\u003c/p\u003e\n \u003cp\u003e% (95% CI)\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7231%;\"\u003e\n \u003cp\u003e313/3805\u003c/p\u003e\n \u003cp\u003e8.2 (7.4-9.1)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e292/3265\u003c/p\u003e\n \u003cp\u003e8.9 (8.0 -9.9)\u003c/p\u003e\n \u003cp\u003e1.3 (1.1-1.4)\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5719%;\"\u003e\n \u003cp\u003e437/4416\u003c/p\u003e\n \u003cp\u003e9.9 (9.0-10.8)\u003c/p\u003e\n \u003cp\u003e1.7 (1.5-2.0)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.0789%;\"\u003e\n \u003cp\u003e15/3729\u003c/p\u003e\n \u003cp\u003e0.4 (0.2-0.6)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e31/2541\u003c/p\u003e\n \u003cp\u003e1.2 (0.8-1.6)\u003c/p\u003e\n \u003cp\u003e3.1 (1.7-5.7)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8167%;\"\u003e\n \u003cp\u003e45/3954\u003c/p\u003e\n \u003cp\u003e1.1 (0.8-1.5)\u003c/p\u003e\n \u003cp\u003e3.3 (1.9-5.9)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4626%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.6952%;\"\u003e\n \u003cp\u003ecases/total\u003c/p\u003e\n \u003cp\u003e% (95% CI)\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.7231%;\"\u003e\n \u003cp\u003e324/11743\u003c/p\u003e\n \u003cp\u003e2.8 (2.5-3.1)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e294/4429\u003c/p\u003e\n \u003cp\u003e6.6 (5.9-7.4)\u003c/p\u003e\n \u003cp\u003e1.9 (1.7-2.2)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.5719%;\"\u003e\n \u003cp\u003e459/6722\u003c/p\u003e\n \u003cp\u003e6.8 (6.2-7.4)\u003c/p\u003e\n \u003cp\u003e3.0 (2.7-3.3)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.0789%;\"\u003e\n \u003cp\u003e25/10837\u003c/p\u003e\n \u003cp\u003e0.2 (0.1-0.3)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6812%;\"\u003e\n \u003cp\u003e33/3432\u003c/p\u003e\n \u003cp\u003e1.0 (0.6-1.3)\u003c/p\u003e\n \u003cp\u003e3.8 (2.3-6.2)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8167%;\"\u003e\n \u003cp\u003e52/5910\u003c/p\u003e\n \u003cp\u003e0.9 (0.6-1.1)\u003c/p\u003e\n \u003cp\u003e4.1 (2.7-6.5)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eOR = Odds Ratio, CI = Confidence Interval.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive characteristics of participants in Troms\u0026oslash;6 are presented in Table 2. Most participants were over 50 years of age. Across sexes and family history groups, vocational education, physical activity 2\u0026ndash;3 times per week, overweight, and alcohol consumption 2\u0026ndash;4 times per month were most common. Coffee/tea intake was lowest among women without a family history of osteoporosis and highest among men with a positive family history, while former smoking predominated, particularly among men.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Descriptive characteristics of women and men with and without family history of osteoporosis; Troms\u0026oslash;6\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 28.1921%;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 31.072%;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003eFamily history of osteoporosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003eNo family history of osteoporosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003eFamily history of osteoporosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003eNo family history of osteoporosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e55.35 (10.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e56.78 (12.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e54.85 (9.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e57.02 (12.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eAge, groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e\u0026le;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e267 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1967 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e134 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1788 (34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e\u0026gt;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e474 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e3521 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e254 (65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e3442 (66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e170 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1688 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e93 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1245 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eVocational school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e194 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1326 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e97 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1490 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eUpper secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e53 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e435 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e29 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e383 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eUniversity \u0026lt; 4 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e133 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e841 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e77 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1102 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eUniversity \u0026ge; 4 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e191 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1198 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e92 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1010 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e29 (4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e270 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e25 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e335 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eLess than once a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e85 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e734 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e77 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1047 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eOnce a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e140 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1010 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e90 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1115 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e2-3 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e328 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e2238 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e139 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1914 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eApproximately every day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e159 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1236 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e57 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e819 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e5 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e44 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e13 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eNormal weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e326 (44 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e2229 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e128 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1416 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e272 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e2122 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e190 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e2714 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e138 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1093 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e70 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1087 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e75 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e7373 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e22 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e383 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eMonthly or less frequently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e203 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1723 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e92 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1334 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e2-4 times a month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e272 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1956 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e88 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e994 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e2-3 times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e148 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e835 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e88 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e994 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003e4 or more times a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e43 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e237 (4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e26 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e300 (6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eCoffee/tea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eCups per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e5.12 (2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e5.00 (2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e6.04 (3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e5.61 (3.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 14.7023%;\"\u003e\n \u003cp\u003eDaily smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e147 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e1176 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e68 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1002 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003ePrevious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e313 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e2083 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e169 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e2444 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20.462%;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e281 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5212%;\"\u003e\n \u003cp\u003e2229 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4602%;\"\u003e\n \u003cp\u003e151 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6118%;\"\u003e\n \u003cp\u003e1784 (34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eBMI=body mass index. Data in the table presented as absolute number (%) or mean (standard deviation).\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHaving a parental family history of osteoporosis independently increased the odds of having osteoporosis (Table 3). For the overall population the crude OR was 2.5 [95% CI 2.0-3.2], the age-adjusted OR was 2.6 [95% CI 2.0-3.3], and the fully-adjusted OR was 2.4 [95% CI 1.9-3.2]. Individuals with a parental history of osteoporosis were more than twice as likely to be diagnosed with the condition themselves compared to those without a family history of osteoporosis. The increase in risk remained consistent across different levels of adjustment, reinforcing the robustness of the association. When stratifying by sex the association was stronger in men. However, the interaction term was not statistically significant (p=0.2). \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Odds ratios with 95% confidence intervals, for developing a family history of osteoporosis, at different levels of adjustment in the overall population, and separately for women and men\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"582\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eCrude OR (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eAge-adjusted OR (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eFully-adjusted OR\u003csup\u003ea\u003c/sup\u003e (95% CI)\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eParental family history of osteoporosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e2.5 (2.0-3.2)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2.6 (2.0-3-3)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2.4 (1.9-3.2)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eParental family history of osteoporosis in \u003cu\u003ewomen\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e1.97 (1.5-2.6)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2 (1.5-2.6)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2.3 (1.7-3.0)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eParental family history of osteoporosis in \u003cu\u003emen\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e3.2 (1.6-6.8)\u003c/p\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e3.3 (1.6-6.8)\u003c/p\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.9 (1.8-8.2)\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eOR= Odds Ratio, CI= Confidence Interval.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003ea\u003c/sup\u003eAdjusted for age, sex (for non-sex-specific models), education, physical activity, body mass index, alcohol consumption, coffee/tea consumption, daily smoking.\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSummary of main findings\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, osteoporosis prevalence is increasing over time in both sexes. Women showed higher osteoporosis prevalence than men in the older age group, while rates were similar between sexes in the younger group. Among women, the highest prevalence was observed in Troms\u0026oslash;6 and the lowest in Troms\u0026oslash;4. Among men, the highest prevalences occurred in Troms\u0026oslash;5 and Troms\u0026oslash;6 for those over 50 years, and in Troms\u0026oslash;6 for those aged 50 years or younger.\u003c/p\u003e\n\u003cp\u003eAn independent association between parental family history of osteoporosis and increased odds of developing the condition was found, with an OR of 2.63 [95% CI 2.02-3.43]. The association remains significant when stratified by sex and across different levels of adjustment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eScientific discussion\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOsteoporosis prevalence data from Norway are scarce, and this study provides novel population-based estimates from Troms\u0026oslash; using self-reported data. Compared with earlier DXA-based studies\u003csup\u003e11\u003c/sup\u003e, this study shows slightly different osteoporosis prevalence estimates. Prior DXA research suggests\u003csup\u003e17\u003c/sup\u003e higher prevalence in Troms\u0026oslash;4 than Troms\u0026oslash;5, with no available comparisons for Troms\u0026oslash;6.\u003c/p\u003e\n\u003cp\u003eResearch results on trends in osteoporosis prevalence over time in a population are inconsistent. While some studies report fluctuations\u003csup\u003e18-19\u003c/sup\u003e, others suggest stability\u003csup\u003e20-22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe upward trend may reflect aging and other characteristic variations\u003csup\u003e23\u003c/sup\u003e of the population, changes in diagnostic practices\u003csup\u003e24\u003c/sup\u003e and awareness, lifestyle changes such as diet, exercise and smoking, and advances in medical care. The decline in bone mineral density (BMD) from Troms\u0026oslash;5 to Troms\u0026oslash;6\u003csup\u003e25\u003c/sup\u003e further supports the increasing prevalence observed in this study. Consistent with existing literature, osteoporosis prevalence was higher in women\u003csup\u003e6\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEarlier research and classic orthopedic texts\u003csup\u003e14-15,26\u003c/sup\u003e highlight a family history of osteoporosis as a risk factor, while more recent studies and WHO guidelines\u003csup\u003e6,27\u003c/sup\u003e focus on family history of fractures. In this study, parental history of osteoporosis remained a relevant risk factor, potentially more predictive in men, highlighting the importance of familial, genetic\u003csup\u003e28\u003c/sup\u003e environmental and epigenetic\u003csup\u003e29\u003c/sup\u003e contributions to osteoporosis risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main strengths of this study include its large, population-based sample, high participation, and comprehensive data collection, which enhance statistical power, representativeness, and the ability to adjust for key confounders.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;However, limitations include reliance on self-reported data and potential selection and information bias related to healthy participant effect and recall bias. However, studies have found only minor differences between participants and non-participants in the Troms\u0026oslash; Study surveys, supporting the overall generalizability of the results in the general population\u003csup\u003e30\u003c/sup\u003e. Risk of residual confounding from unmeasured factors such as race cannot be excluded. Some variables, like smoking, may be affected by measurement errors inherent in self-reported data.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings indicate a rising trend in osteoporosis prevalence over time. Troms\u0026oslash;4 recorded the lowest rates for both men and women across all age groups. Among women and younger men, Troms\u0026oslash;6 showed the highest prevalence, while older men had the highest rates in Troms\u0026oslash;5.\u003c/p\u003e \u003cp\u003eA parental family history of osteoporosis independently increased the odds of developing the condition in both the overall population and sex-specific groups across all levels of adjustment.\u003c/p\u003e \u003cp\u003eThis study enhances the epidemiological understanding of osteoporosis and underscores the importance of personalized prevention and management strategies based on individual risk factors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Troms\u0026oslash; Study has been performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. All participants provided prior voluntary informed consent before participating in the Troms\u0026oslash; Study surveys. This study has been approved by Regional committees for medical and health research ethics (REC, reference 696648).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUpon request, data may be made available to researchers who have obtained approval from the Data and Publication Committee of the Troms\u0026oslash; Study. Information for applicants is available at: https://uit.no/research/tromsostudy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted as part of a Master\u0026rsquo;s thesis in Public Health at UiT The Arctic University of Norway. Open access funding was provided by UiT The Arctic University of Norway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMA, ML, and ES conceptualized the study and formulated the research questions. MA conducted all statistical analyses and drafted the manuscript. ML and ES revised the manuscript. All authors read and approved the final version of the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the participants of the Troms\u0026oslash; Study for their invaluable contributions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information (optional)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdami G, Fassio A, Gatti D, Viapiana O, Benini C, Danila MI, et al. Osteoporosis in 10 years time: a glimpse into the future of osteoporosis. \u003cem\u003eTher Adv Musculoskelet Dis\u003c/em\u003e. 2022;14:1759720X221083541.\u003c/li\u003e\n\u003cli\u003eHarvey N, Dennison E, Cooper C. Osteoporosis: impact on health and economics. \u003cem\u003eNat Rev Rheumatol\u003c/em\u003e. 2010;6(2):99\u0026ndash;105.\u003c/li\u003e\n\u003cli\u003eBecker DJ, Kilgore ML, Morrisey MA. The societal burden of osteoporosis. \u003cem\u003eCurr Rheumatol Rep\u003c/em\u003e. 2010;12:186\u0026ndash;191. \u003c/li\u003e\n\u003cli\u003eDennison E, Mohamed MA, Cooper C. Epidemiology of osteoporosis. \u003cem\u003eRheum Dis Clin North Am\u003c/em\u003e. 2006;32(4):617\u0026ndash;629.\u003c/li\u003e\n\u003cli\u003eKemmak AR, Rezapour A, Jahangiri R, Nikjoo S, Farabi H, Soleimanpour S. Economic burden of osteoporosis in the world: a systematic review. \u003cem\u003eMed J Islam Repub Iran\u003c/em\u003e. 2020;34:154.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. World Osteoporosis Day: simple ways to prevent osteoporosis. Geneva: World Health Organization; 2019 Oct 20. Available from: https://www.who.int/westernpacific/articles/item/simple-ways-to-prevent-osteoporosis\u003c/li\u003e\n\u003cli\u003eXiao PL, Cui AY, Hsu CJ, Peng R, Jiang N, Xu XH, et al. Global, regional prevalence, and risk factors of osteoporosis according to the World Health Organization diagnostic criteria: a systematic review and meta-analysis. \u003cem\u003eOsteoporos Int\u003c/em\u003e. 2022;33(10):2137\u0026ndash;2153.\u003c/li\u003e\n\u003cli\u003eSalari N, Ghasemi H, Mohammadi L, Rabieenia E, Shohaimi S, Mohammadi M. The global prevalence of osteoporosis in the world: a comprehensive systematic review and meta-analysis. \u003cem\u003eJ Orthop Surg Res\u003c/em\u003e. 2021;16(1):1\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eMeyer HE. Osteoporosis and fractures in Norway: fact sheet. Oslo: Norwegian Institute of Public Health; 2016 Nov 9.\u003c/li\u003e\n\u003cli\u003eStatistik Sentralbyr\u0026aring; (Statistics Norway). Population [Internet]. Oslo: Statistics Norway; n.d. Available from: https://www.ssb.no/en/statbank/table/06913/\u003c/li\u003e\n\u003cli\u003eEmaus N, Omsland TK, Ahmed LA, Grimnes G, Sneve M, Berntsen GK. Bone mineral density at the hip in Norwegian women and men\u0026mdash;prevalence of osteoporosis depends on chosen references: the Troms\u0026oslash; Study. \u003cem\u003eEur J Epidemiol\u003c/em\u003e. 2009;24:321\u0026ndash;328.\u003c/li\u003e\n\u003cli\u003eRobitaille J, Yoon PW, Moore CA, Liu T, Irizarry-Delacruz M, Looker AC, Khoury MJ. Prevalence, family history, and prevention of reported osteoporosis in US women. \u003cem\u003eAm J Prev Med\u003c/em\u003e. 2008;35(1):47\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eSoroko SB, Barrett-Connor E, Edelstein SL, Kritz-Silverstein D. Family history of osteoporosis and bone mineral density at the axial skeleton: the Rancho Bernardo Study. \u003cem\u003eJ Bone Miner Res\u003c/em\u003e. 1994;9(6):761\u0026ndash;769.\u003c/li\u003e\n\u003cli\u003eGasparik A, Szőcs T, Pascanu I, Csata Z, Poiana C. Family history BMD independently influences fracture risk. \u003cem\u003eActa Endocrinol (Buchar)\u003c/em\u003e. 2021;17(4):498. \u003c/li\u003e\n\u003cli\u003eJacobsen BK, Eggen AE, Mathiesen EB, Wilsgaard T, Nj\u0026oslash;lstad I. Cohort profile: the Troms\u0026oslash; Study. \u003cem\u003eInt J Epidemiol\u003c/em\u003e. 2012;41(4):961\u0026ndash;967.\u003c/li\u003e\n\u003cli\u003eUiT The Arctic University of Norway. The Troms\u0026oslash; Study [Internet]. Troms\u0026oslash;: UiT; n.d. Available from: https://uit.no/research/tromsostudy\u003c/li\u003e\n\u003cli\u003eHauger AV, Bergland A, Holvik K, St\u0026aring;hle A, Emaus N, Strand BH. Osteoporosis and osteopenia in the distal forearm predict all-cause mortality independent of grip strength: 22-year follow-up in the population-based Troms\u0026oslash; Study. \u003cem\u003eOsteoporos Int\u003c/em\u003e. 2018;29(11):2447\u0026ndash;2456.\u003c/li\u003e\n\u003cli\u003eLooker AC, Sarafrazi Isfahani N, Fan B, Shepherd JA. Trends in osteoporosis and low bone mass in older US adults, 2005\u0026ndash;2006 through 2013\u0026ndash;2014. \u003cem\u003eOsteoporos Int\u003c/em\u003e. 2017;28(6):1979\u0026ndash;1988.\u003c/li\u003e\n\u003cli\u003eSmith L, Wilson S. Trends in osteoporosis diagnosis and management in Australia. \u003cem\u003eArch Osteoporos\u003c/em\u003e. 2022;17(1):97.\u003c/li\u003e\n\u003cli\u003eAhlborg HG, Rosengren BE, J\u0026auml;rvinen TLN, Rogmark C, Nilsson J\u0026Aring;, Sernbo I, Karlsson MK. Prevalence of osteoporosis and incidence of hip fracture in women\u0026mdash;secular trends over 30 years. \u003cem\u003eBMC Musculoskelet Disord\u003c/em\u003e. 2010;11:48.\u003c/li\u003e\n\u003cli\u003eRosengren BE, Ahlborg HG, G\u0026auml;rdsell P, Sernbo I, Daly RM, Nilsson J\u0026Aring;, Karlsson MK. Bone mineral density and incidence of hip fracture in Swedish urban and rural women 1987\u0026ndash;2002. \u003cem\u003eActa Orthop\u003c/em\u003e. 2010;81(4):453\u0026ndash;459.\u003c/li\u003e\n\u003cli\u003eZhang X, Wang Z, Zhang D, Ye D, Zhou Y, Qin J, Zhang Y. The prevalence and treatment rate trends of osteoporosis in postmenopausal women. \u003cem\u003ePLoS One\u003c/em\u003e. 2023;18(9):e0290289.\u003c/li\u003e\n\u003cli\u003eDu P, Coles FB, O\u0026rsquo;Campo P, McNutt LA. Changes in population characteristics and their implication on public health research. \u003cem\u003eEpidemiol Perspect Innov\u003c/em\u003e. 2007;4:6.\u003c/li\u003e\n\u003cli\u003eLorentzon M, Cummings SR. Osteoporosis: the evolution of a diagnosis. \u003cem\u003eJ Intern Med\u003c/em\u003e. 2015;277(6):650\u0026ndash;661.\u003c/li\u003e\n\u003cli\u003eEmaus N, Wilsgaard T, Ahmed LA. Impacts of body mass index, physical activity, and smoking on femoral bone loss: the Troms\u0026oslash; Study. \u003cem\u003eJ Bone Miner Res\u003c/em\u003e. 2014;29(9):2080\u0026ndash;2089.\u003c/li\u003e\n\u003cli\u003eMiller MD, Thompson SR. \u003cem\u003eMiller\u0026rsquo;s Review of Orthopaedics\u003c/em\u003e. 8th ed. Philadelphia: Elsevier; 2019.\u003c/li\u003e\n\u003cli\u003eKanis JA, Johansson H, Oden A, Johnell O, De Laet C, Eisman JA, et al. A family history of fracture and fracture risk: a meta-analysis. \u003cem\u003eBone\u003c/em\u003e. 2004;35(5):1029\u0026ndash;1037.\u003c/li\u003e\n\u003cli\u003eStewart T, Ralston S. Role of genetic factors in the pathogenesis of osteoporosis. \u003cem\u003eJ Endocrinol\u003c/em\u003e. 2000;166(2):235\u0026ndash;245.\u003c/li\u003e\n\u003cli\u003eChen Y, Sun Y, Xue X, Ma H. Comprehensive analysis of epigenetics mechanisms in osteoporosis. \u003cem\u003eFront Genet\u003c/em\u003e. 2023;14:1153585.\u003c/li\u003e\n\u003cli\u003eJacobsen BK, Thelle DS. The Troms\u0026oslash; Heart Study: responders and non-responders to a health questionnaire\u0026mdash;do they differ? \u003cem\u003eScand J Soc Med\u003c/em\u003e. 1988;16(2):101\u0026ndash;104.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Osteoporosis, Prevalence, Family History, Epidemiology, Sex-specific","lastPublishedDoi":"10.21203/rs.3.rs-8910562/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8910562/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOsteoporosis is a growing public health concern yet research on its epidemiology remains limited. This study aimed to examine trends in the prevalence of osteoporosis and the association between a parental family history of osteoporosis and osteoporosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSelf-reported data from the population-based Troms\u0026oslash; Study, conducted in 1994\u0026ndash;1995 (Troms\u0026oslash;4), 2001 (Troms\u0026oslash;5), and 2007\u0026ndash;2008 (Troms\u0026oslash;6), were utilized in this cross-sectional study, with analyses performed using generalized estimating equations and logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalences of osteoporosis increased over time in both women and men. Women had a higher prevalence of osteoporosis than men in both age groups (\u0026le;\u0026thinsp;50 and \u0026gt;\u0026thinsp;50 years old). Among women, the highest prevalence of osteoporosis (9.9% [95% CI 9-10.8]) was found in Troms\u0026oslash;6 for the \u0026gt;\u0026thinsp;50 age group, while the lowest (0.1% [0.1\u0026ndash;0.2]) was observed in the \u0026le;\u0026thinsp;50 age group in Troms\u0026oslash;4. Among men, the highest prevalence (1.2% [0.8\u0026ndash;1.6]) was found in Troms\u0026oslash;5 for the \u0026gt;\u0026thinsp;50 age group, whereas the lowest (0.1% [0.05\u0026ndash;0.2]) was observed in the \u0026le;\u0026thinsp;50 age group in Troms\u0026oslash;4. A parental history of osteoporosis independently increased the odds of osteoporosis with an odds ratio of 2.4 [95% CI 1.9\u0026ndash;3.2]. The association remained independent, across both sexes and all levels of adjustment (age and osteoporosis-related factors).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eUtilizing this knowledge to develop a more personalized approach may enhance osteoporosis prevention and control.\u003c/p\u003e","manuscriptTitle":"Time trends in osteoporosis prevalence and cross-sectional associations with parental family history: The Tromsø Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-05 19:43:46","doi":"10.21203/rs.3.rs-8910562/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89412bf9-071e-45d9-b18a-15f46ad98c94","owner":[],"postedDate":"March 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-24T05:55:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-05 19:43:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8910562","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8910562","identity":"rs-8910562","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}