Skip to main content

Advertisement

SpringerLink
Log in

Socioeconomic status in relation to incident fracture risk in the Study of Women’s Health Across the Nation

  • Original Article
  • Published:
Osteoporosis International Aims and scope Submit manuscript

Abstract

Summary

We examined baseline and annual follow-up data (through annual follow-up visit 9) from a cohort of 2,234 women aged 42 to 52 years at baseline. Independent of financial status, higher educational level was associated with lower fracture incidence among non-Caucasian women but not among Caucasian women.

Introduction

This study was conducted to determine the associations of education and income with fracture incidence among midlife women over 9 years of follow-up.

Methods

We examined baseline and annual follow-up data (through annual follow-up visit 9) from 2,234 participants of the Study of Women’s Health Across the Nation, a cohort of women aged 42 to 52 years at baseline. We used Cox proportional hazards regression models to examine the associations of socioeconomic predictors (education, family-adjusted poverty-to-income ratio, and difficulty paying for basics) with time to first incident nontraumatic, nondigital, noncraniofacial fracture.

Results

Independent of family-adjusted poverty-to-income ratio, higher educational level was associated with decreased time to first incident fracture among non-Caucasian women but not among Caucasian women (p interaction 0.02). Compared with non-Caucasian women who completed no more than high school education, non-Caucasian women who attained at least some postgraduate education had 87 % lower rates of incident nontraumatic fracture (adjusted hazard ratio 0.13, 95 % confidence interval [CI] 0.03–0.60). Among non-Caucasian women, each additional year of education was associated with a 16 % lower odds of nontraumatic fracture (adjusted odds ratio 0.84, 95 % CI 0.73–0.97). Income, family-adjusted poverty-to-income ratio, and degree of difficulty paying for basic needs were not associated with time to first fracture in Caucasian or non-Caucasian women.

Conclusions

Among non-Caucasian midlife women, higher education, but not higher income, was associated with lower fracture incidence. Elucidation of the mechanisms underlying the possible protective effects of higher educational level on nontraumatic fracture incidence may allow us to better target individuals at risk of future fracture.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Adler NE, Boyce T, Chesney MA, Cohen S, Folkman S, Kahn RL, Syme SL (1994) Socioeconomic status and health. The challenge of the gradient. Am Psychol 49:15–24

    Article  CAS  PubMed  Google Scholar 

  2. Kaplan GA, Keil JE (1993) Socioeconomic factors and cardiovascular disease: a review of the literature. Circulation 88:1973–1998

    Article  CAS  PubMed  Google Scholar 

  3. Strike PC, Steptoe A (2004) Psychosocial factors in the development of coronary artery disease. Prog Cardiovasc Dis 46:337–347

    Article  PubMed  Google Scholar 

  4. Tamayo T, Christian H, Rathmann W (2010) Impact of early psychosocial factors (childhood socioeconomic factors and adversities) on future risk of type 2 diabetes, metabolic disturbances and obesity: a systematic review. BMC Public Health 10:525

    Article  PubMed Central  PubMed  Google Scholar 

  5. Seeman T, Epel E, Gruenewald T, Karlamangla A, McEwen BS (2010) Socio-economic differentials in peripheral biology: cumulative allostatic load. Ann N Y Acad Sci 1186:223–239

    Article  PubMed  Google Scholar 

  6. Gruenewald TL, Karlamangla AS, Hu P, Stein-Merkin S, Crandall C, Koretz B, Seeman TE (2012) History of socioeconomic disadvantage and allostatic load in later life. Soc Sci Med 74:75–83

    Article  PubMed Central  PubMed  Google Scholar 

  7. Elefteriou F (2008) Regulation of bone remodeling by the central and peripheral nervous system. Arch Biochem Biophys 473:231–236

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Isidro ML, Ruano B (2010) Bone disease in diabetes. Curr Diabetes Rev 6:144–155

    Article  PubMed  Google Scholar 

  9. McLean RR (2009) Proinflammatory cytokines and osteoporosis. Curr Osteoporos Rep 7:134–139

    Article  PubMed  Google Scholar 

  10. Merlotti D, Gennari L, Dotta F, Lauro D, Nuti R (2010) Mechanisms of impaired bone strength in type 1 and 2 diabetes. Nutr Metab Cardiovasc Dis 20:683–690

    Article  CAS  PubMed  Google Scholar 

  11. Brennan SL, Pasco JA, Urquhart DM, Oldenburg B, Wang Y, Wluka AE (2011) Association between socioeconomic status and bone mineral density in adults: a systematic review. Osteoporos Int 22:517–527

    Article  CAS  PubMed  Google Scholar 

  12. Crandall CJ, Merkin SS, Seeman TE, Greendale GA, Binkley N, Karlamangla AS (2012) Socioeconomic status over the life-course and adult bone mineral density: the Midlife in the U.S. Study. Bone 51:107–113

    Article  PubMed Central  PubMed  Google Scholar 

  13. Brennan SL, Pasco JA, Urquhart DM, Oldenburg B, Hanna F, Wluka AE (2009) The association between socioeconomic status and osteoporotic fracture in population-based adults: a systematic review. Osteoporos Int 20:1487–1497

    Article  CAS  PubMed  Google Scholar 

  14. Cauley JA, Wu L, Wampler NS, Barnhart JM, Allison M, Chen Z, Jackson R, Robbins J (2007) Clinical risk factors for fractures in multi-ethnic women: the Women’s Health Initiative. J Bone Miner Res 22:1816–1826

    Article  PubMed  Google Scholar 

  15. Wilson RT, Chase GA, Chrischilles EA, Wallace RB (2006) Hip fracture risk among community-dwelling elderly people in the United States: a prospective study of physical, cognitive, and socioeconomic indicators. Am J Public Health 96:1210–1218

    Article  PubMed Central  PubMed  Google Scholar 

  16. Espino DV, Palmer RF, Miles TP, Mouton CP, Wood RC, Bayne NS, Markides KP (2000) Prevalence, incidence, and risk factors associated with hip fractures in community-dwelling older Mexican Americans: results of the Hispanic EPESE study. Establish Population for the Epidemiologic Study for the Elderly. J Am Geriatr Soc 48:1252–1260

    CAS  PubMed  Google Scholar 

  17. Zingmond DS, Soohoo NF, Silverman SL (2006) The role of socioeconomic status on hip fracture. Osteoporos Int 17:1562–1568

    Article  CAS  PubMed  Google Scholar 

  18. Rosen CJ, American Society for Bone and Mineral Research (2013) Primer on the metabolic bone diseases and disorders of mineral metabolism, 8th edn. Wiley-Blackwell, Ames, p 349

    Book  Google Scholar 

  19. Marshall D, Johnell O, Wedel H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 312:1254–1259

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Blackburn TD, Howard DB, Leib ES (2013) Utility of spine bone mineral density in fracture prediction within FRAX. J Clin Densitom 16:81–86

    Article  PubMed  Google Scholar 

  21. Kumar A, Mittal S, Orito S, Ishitani K, Ohta H (2010) Impact of dietary intake, education, and physical activity on bone mineral density among North Indian women. J Bone Miner Metab 28:192–201

    Article  CAS  PubMed  Google Scholar 

  22. Varenna M, Binelli L, Zucchi F, Ghiringhelli D, Gallazzi M, Sinigaglia L (1999) Prevalence of osteoporosis by educational level in a cohort of postmenopausal women. Osteoporos Int 9:236–241

    Article  CAS  PubMed  Google Scholar 

  23. Sowers M, Crawford S, Morgenstein D et al (2000) Design, survey sampling and recruitment methods of SWAN: a multi-center, multi-ethnic, community-based cohort study of women and the menopausal transition. In: Lobos R, Marcus R, Kelsey JL (eds) Menopause. Academic, New York, pp 175–188

    Chapter  Google Scholar 

  24. Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L (1986) A data-based approach to diet questionnaire design and testing. Am J Epidemiol 124:453–469

    CAS  PubMed  Google Scholar 

  25. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S (2001) Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America’s Table Study. Am J Epidemiol 154:1089–1099

    Article  CAS  PubMed  Google Scholar 

  26. Block G, Thompson FE, Hartman AM, Larkin FA, Guire KE (1992) Comparison of two dietary questionnaires validated against multiple dietary records collected during a 1-year period. J Am Diet Assoc 92:686–693

    CAS  PubMed  Google Scholar 

  27. Sternfeld B, Wang H, Quesenberry CP Jr, Abrams B, Everson-Rose SA, Greendale GA, Matthews KA, Torrens JI, Sowers M (2004) Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Women’s Health Across the Nation. Am J Epidemiol 160:912–922

    Article  PubMed  Google Scholar 

  28. Wolinsky FD, Fitzgerald JF (1994) The risk of hip fracture among noninstitutionalized older adults. J Gerontol 49:S165–S175

    Article  CAS  PubMed  Google Scholar 

  29. Ahlborg HG, Johnell O, Nilsson BE, Jeppsson S, Rannevik G, Karlsson MK (2001) Bone loss in relation to menopause: a prospective study during 16 years. Bone 28:327–331

    Article  CAS  PubMed  Google Scholar 

  30. Chapurlat RD, Garnero P, Sornay-Rendu E, Arlot ME, Claustrat B, Delmas PD (2000) Longitudinal study of bone loss in pre- and perimenopausal women: evidence for bone loss in perimenopausal women. Osteoporos Int 11:493–498

    Article  CAS  PubMed  Google Scholar 

  31. Ebeling PR, Atley LM, Guthrie JR, Burger HG, Dennerstein L, Hopper JL, Wark JD (1996) Bone turnover markers and bone density across the menopausal transition. J Clin Endocrinol Metab 81:3366–3371

    CAS  PubMed  Google Scholar 

  32. Finkelstein JS, Brockwell SE, Mehta V et al (2008) Bone mineral density changes during the menopause transition in a multiethnic cohort of women. J Clin Endocrinol Metab 93:861–868

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  33. Guthrie JR, Ebeling PR, Hopper JL, Barrett-Connor E, Dennerstein L, Dudley EC, Burger HG, Wark JD (1998) A prospective study of bone loss in menopausal Australian-born women. Osteoporos Int 8:282–290

    Article  CAS  PubMed  Google Scholar 

  34. Khosla S, Melton LJ 3rd, Riggs BL (2011) The unitary model for estrogen deficiency and the pathogenesis of osteoporosis: is a revision needed? J Bone Miner Res 26:441–451

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. Komukai S, Ohta H, Makita K, Yanamoto S, Takamatsu K, Okano H, Yajima M, Nozawa S (2003) One-year spinal bone change in pre- and perimenopausal Japanese women. A prospective observational study. Horm Res 59:79–84

    Article  CAS  PubMed  Google Scholar 

  36. Pouilles JM, Tremollieres F, Ribot C (1993) The effects of menopause on longitudinal bone loss from the spine. Calcif Tissue Int 52:340–343

    Article  CAS  PubMed  Google Scholar 

  37. Riggs BL, Khosla S, Melton LJ 3rd (1998) A unitary model for involutional osteoporosis: estrogen deficiency causes both type I and type II osteoporosis in postmenopausal women and contributes to bone loss in aging men. J Bone Miner Res 13:763–773

    Article  CAS  PubMed  Google Scholar 

  38. Riggs BL, Melton LJ, Robb RA, Camp JJ, Atkinson EJ, McDaniel L, Amin S, Rouleau PA, Khosla S (2008) A population-based assessment of rates of bone loss at multiple skeletal sites: evidence for substantial trabecular bone loss in young adult women and men. J Bone Miner Res 23:205–214

    Article  PubMed Central  PubMed  Google Scholar 

  39. Riggs BL, Wahner HW, Melton LJ 3rd, Richelson LS, Judd HL, Offord KP (1986) Rates of bone loss in the appendicular and axial skeletons of women. Evidence of substantial vertebral bone loss before menopause. J Clin Invest 77:1487–1491

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Seifert-Klauss V, Link T, Heumann C, Luppa P, Haseitl M, Laakmann J, Rattenhuber J, Kiechle M (2006) Influence of pattern of menopausal transition on the amount of trabecular bone loss. Results from a 6-year prospective longitudinal study. Maturitas 55:317–324

    Article  CAS  PubMed  Google Scholar 

  41. Slemenda C, Hui SL, Longcope C, Johnston CC (1987) Sex steroids and bone mass. A study of changes about the time of menopause. J Clin Invest 80:1261–1269

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Sowers M, Crutchfield M, Bandekar R, Randolph JF, Shapiro B, Schork MA, Jannausch M (1998) Bone mineral density and its change in pre-and perimenopausal white women: the Michigan Bone Health Study. J Bone Miner Res 13:1134–1140

    Article  CAS  PubMed  Google Scholar 

  43. Sowers MR, Zheng H, Jannausch ML, McConnell D, Nan B, Harlow S, Randolph JF Jr (2010) Amount of bone loss in relation to time around the final menstrual period and follicle-stimulating hormone staging of the transmenopause. J Clin Endocrinol Metab 95:2155–2162

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  44. Greendale GA, Sowers M, Han W, Huang MH, Finkelstein JS, Crandall CJ, Lee JS, Karlamangla AS (2012) Bone mineral density loss in relation to the final menstrual period in a multiethnic cohort: results from the Study of Women’s Health Across the Nation (SWAN). J Bone Miner Res 27:111–118

    Article  PubMed Central  PubMed  Google Scholar 

  45. Ishii S, Cauley JA, Greendale GA, Crandall CJ, Huang MH, Danielson ME, Karlamangla AS (2013) Trajectories of femoral neck strength in relation to the final menstrual period in a multi-ethnic cohort. Osteoporos Int 24(9):2471–2481

    Article  CAS  PubMed  Google Scholar 

  46. Dorn LD, Beal SJ, Kalkwarf HJ, Pabst S, Noll JG, Susman EJ (2013) Longitudinal impact of substance use and depressive symptoms on bone accrual among girls aged 11–19 years. J Adolesc Health 52(4):393–399

    Article  PubMed  Google Scholar 

  47. Shaw NJ, Mughal MZ (2013) Vitamin D and child health Part 1 (skeletal aspects). Arch Dis Child 98(5):363–367

    Article  PubMed  Google Scholar 

  48. Ross AC, Institute of Medicine (U. S.). Committee to Review Dietary Reference Intakes for Vitamin D and Calcium (2011) Dietary reference intakes : calcium, vitamin D. National Academies Press, Washington

    Google Scholar 

  49. Kant AK, Graubard BI (2007) Ethnicity is an independent correlate of biomarkers of micronutrient intake and status in American adults. J Nutr 137:2456–2463

    CAS  PubMed  Google Scholar 

  50. Winkleby MA, Cubbin C, Ahn DK, Kraemer HC (1999) Pathways by which SES and ethnicity influence cardiovascular disease risk factors. Ann N Y Acad Sci 896:191–209

    Article  CAS  PubMed  Google Scholar 

  51. Winkleby MA, Robinson TN, Sundquist J, Kraemer HC (1999) Ethnic variation in cardiovascular disease risk factors among children and young adults: findings from the Third National Health and Nutrition Examination Survey, 1988–1994. JAMA 281:1006–1013

    Article  CAS  PubMed  Google Scholar 

  52. Kahn RS, Wise PH, Kennedy BP, Kawachi I (2000) State income inequality, household income, and maternal mental and physical health: cross sectional national survey. BMJ 321:1311–1315

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  53. Bailey RK, Patel M, Barker NC, Ali S, Jabeen S (2011) Major depressive disorder in the African American population. J Natl Med Assoc 103:548–557

    PubMed  Google Scholar 

  54. Headen SW, Bauman KE, Deane GD, Koch GG (1991) Are the correlates of cigarette smoking initiation different for black and white adolescents? Am J Public Health 81:854–858

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  55. Goodman E, McEwen BS, Dolan LM, Schafer-Kalkhoff T, Adler NE (2005) Social disadvantage and adolescent stress. J Adolesc Health 37:484–492

    Article  PubMed  Google Scholar 

  56. Dennison E, Hindmarsh P, Fall C, Kellingray S, Barker D, Phillips D, Cooper C (1999) Profiles of endogenous circulating cortisol and bone mineral density in healthy elderly men. J Clin Endocrinol Metab 84:3058–3063

    CAS  PubMed  Google Scholar 

  57. Kann P, Laudes M, Piepkorn B, Heintz A, Beyer J (2001) Suppressed levels of serum cortisol following high-dose oral dexamethasone administration differ between healthy postmenopausal females and patients with established primary vertebral osteoporosis. Clin Rheumatol 20:25–29

    Article  CAS  PubMed  Google Scholar 

  58. Reynolds RM, Dennison EM, Walker BR, Syddall HE, Wood PJ, Andrew R, Phillips DI, Cooper C (2005) Cortisol secretion and rate of bone loss in a population-based cohort of elderly men and women. Calcif Tissue Int 77:134–138

    Article  CAS  PubMed  Google Scholar 

  59. Papanicolaou DA, Wilder RL, Manolagas SC, Chrousos GP (1998) The pathophysiologic roles of interleukin-6 in human disease. Ann Intern Med 128:127–137

    Article  CAS  PubMed  Google Scholar 

  60. Ganesan K, Teklehaimanot S, Tran TH, Asuncion M, Norris K (2005) Relationship of C-reactive protein and bone mineral density in community-dwelling elderly females. J Natl Med Assoc 97:329–333

    PubMed Central  PubMed  Google Scholar 

  61. Gold EB, Crawford SL, Avis NE, Crandall CJ, Matthews KA, Waetjen LE, Lee JS, Thurston R, Vuga M, Harlow SD (2013) Factors related to age at natural menopause: longitudinal analyses from SWAN. Am J Epidemiol 178:70–83

    Article  PubMed  Google Scholar 

  62. Luoto R, Kaprio J, Uutela A (1994) Age at natural menopause and sociodemographic status in Finland. Am J Epidemiol 139:64–76

    CAS  PubMed  Google Scholar 

  63. Stanford JL, Hartge P, Brinton LA, Hoover RN, Brookmeyer R (1987) Factors influencing the age at natural menopause. J Chronic Dis 40:995–1002

    Article  CAS  PubMed  Google Scholar 

  64. Torgerson DJ, Avenell A, Russell IT, Reid DM (1994) Factors associated with onset of menopause in women aged 45–49. Maturitas 19:83–92

    Article  CAS  PubMed  Google Scholar 

  65. Palmer JR, Rosenberg L, Wise LA, Horton NJ, Adams-Campbell LL (2003) Onset of natural menopause in African American women. Am J Public Health 93:299–306

    Article  PubMed Central  PubMed  Google Scholar 

  66. Castelo-Branco C, Blumel JE, Chedraui P et al (2006) Age at menopause in Latin America. Menopause 13:706–712

    Article  PubMed  Google Scholar 

  67. Lawlor DA, Ebrahim S, Smith GD (2003) The association of socio-economic position across the life course and age at menopause: the British Women’s Heart and Health Study. BJOG: Int J Obstet Gynaecol 110:1078–1087

    Article  Google Scholar 

  68. Chen Z, Kooperberg C, Pettinger MB, Bassford T, Cauley JA, LaCroix AZ, Lewis CE, Kipersztok S, Borne C, Jackson RD (2004) Validity of self-report for fractures among a multiethnic cohort of postmenopausal women: results from the Women’s Health Initiative observational study and clinical trials. Menopause 11:264–274

    Article  PubMed  Google Scholar 

  69. U.S. Department of Health and Human Services (2004) Bone health and osteoporosis: a report of the Surgeon General Executive Summary. U.S. Department of Health and Human Services, Rockville

    Google Scholar 

Download references

Acknowledgments

Dr. Crandall received support from the Jonsson Comprehensive Cancer Center at the University of California, Los Angeles. The Study of Women’s Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the NIH Office of Research on Women’s Health (ORWH) (grants U01NR004061, U01AG012505, U01AG012535, U01AG012531, U01AG012539, AG012546, U01AG012553, U01AG012554, U01AG012495). The authors also received support from NIH Grant number 5R01AG033067. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NIA, NINR, ORWH, or the NIH. Funding from the National Institutes of Health Grant 5R01AG033067.

Clinical Centers: University of Michigan, Ann Arbor—Siobán Harlow, PI 2011–present; MaryFran Sowers, PI 1994–2011; Massachusetts General Hospital, Boston, MA—Joel Finkelstein, PI 1999–present; Robert Neer, PI 1994–1999; Rush University, Rush University Medical Center, Chicago, IL—Howard Kravitz, PI 2009–present; Lynda Powell, PI 1994–2009; University of California, Davis/Kaiser—Ellen Gold, PI; University of California, Los Angeles—Gail Greendale, PI; Albert Einstein College of Medicine, Bronx, NY—Carol Derby, PI 2011–present; Rachel Wildman, PI 2010–2011; Nanette Santoro, PI 2004–2010; University of Medicine and Dentistry—New Jersey Medical School, Newark—Gerson Weiss, PI 1994–2004; and the University of Pittsburgh, Pittsburgh, PA—Karen Matthews, PI.

NIH Program Office: National Institute on Aging, Bethesda, MD—Winifred Rossi, 2012–present; Sherry Sherman, 1994–2012; Marcia Ory, 1994–2001; National Institute of Nursing Research, Bethesda, MD—Program Officers.

Central Laboratory: University of Michigan, Ann Arbor—Daniel McConnell (Central Ligand Assay Satellite Services).

Coordinating Center: University of Pittsburgh, Pittsburgh, PA—Maria Mori Brooks, PI 2012–present; Kim Sutton-Tyrrell, PI 2001–2012; New England Research Institutes, Watertown, MA—Sonja McKinlay, PI 1995–2001.

Steering Committee: Susan Johnson, Current Chair

Chris Gallagher, Former Chair

We thank the study staff at each site and all the women who participated in SWAN.

Conflicts of interest

None.

Author information

Authors and Affiliations

  1. Division of General Internal Medicine, David Geffen School of Medicine at University of California, 911 Broxton Ave., 1st floor, Los Angeles, CA, 90024, USA

    C. J. Crandall

  2. Division of Geriatrics, David Geffen School of Medicine at University of California, Los Angeles, USA

    W. Han, G. A. Greendale, T. Seeman & A. S. Karlamangla

  3. Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA

    P. Tepper

  4. University of Pittsburgh School of Medicine & Graduate School of Public Health, Pittsburgh, PA, 15213, USA

    R. Thurston

  5. Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA

    C. Karvonen-Gutierrez

Authors
  1. C. J. Crandall
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. W. Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. A. Greendale
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. T. Seeman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. P. Tepper
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. R. Thurston
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. Karvonen-Gutierrez
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. A. S. Karlamangla
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. J. Crandall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Crandall, C.J., Han, W., Greendale, G.A. et al. Socioeconomic status in relation to incident fracture risk in the Study of Women’s Health Across the Nation. Osteoporos Int 25, 1379–1388 (2014). https://doi.org/10.1007/s00198-013-2616-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-013-2616-y

Keywords

Search

Navigation