Psychological Disorders Linked to Osteoporosis Diagnoses in a Population-Based Cohort Study of Middle and Older Age United States Adults.

BACKGROUND AND OBJECTIVES: Although it is well established that psychological disorders and osteoporosis risk are linked, how the relationship manifests is not. This study examines depressive symptoms and a history of psychological problems as potential risk factors for osteoporosis diagnosis, adjudicating between 4 theoretical models rarely tested together. We analyze these models across multiple domains (i.e., demographic, socioeconomic, and health-related), while accounting for bone mineral density (BMD) scans, which have been shown to improve health equity across sex and racial/ethnic identities. RESEARCH DESIGN AND METHODS: Data from the 2012-2016, nationally representative, population-based, cohort Health and Retirement Study (N = 18,224-18,359) were used to estimate 4 logistic regression models with the outcome of osteoporosis diagnosis. Approximately 50% of the sample identified as female and 50% as male, while about 81% identified as White/European American, 11% as Black/African American, and 8% as another race/ethnicity. The key independent variables were depressive symptoms-measured using two common scales-and a history of psychological problems. RESULTS: A history of psychological problems and one depressive symptoms measure were associated with the odds of osteoporosis diagnosis in the presence of other known risk factors for osteoporosis. DISCUSSION AND IMPLICATIONS: Support for the theoretical models was limited. Evidence suggests possible directionality; a history of psychological distress may be a risk factor for osteoporosis, though we cannot rule out the other direction. Public health professionals and healthcare providers should consider a history of psychological problems as a risk factor for osteoporosis when deciding whether to recommend a BMD scan.

Development of a diverse osteoporosis screening tool for older US adults from the health and retirement study.

Existing osteoporosis screening tools have limitations, including using race as a predictor, and development on homogeneous samples. This biases risk assessment of osteoporosis in diverse populations and increases health inequities. We develop a tool that relies on variables easily learned during point-of-care, known by individuals, and with negligible racial bias. Data from the 2012-2016 waves of the population-based cohort Health and Retirement Study (HRS) were used to build a predictive model of osteoporosis diagnosis on a 75 % training sample of adults ages 50-90. The model was validated on a 25 % holdout sample and a cross-sectional sample of American individuals ages 50-80 from the National Health and Nutrition Examination Survey (NHANES). Sensitivity and specificity were compared across sex and race/ethnicity. The model has high sensitivity in the HRS holdout sample (89.9 %), which holds for those identifying as female and across racial/ethnic groups. Specificity is 57.9 %, and area under the curve (AUC) is approximately 0.81. Validation in the NHANES sample using empirically measured osteoporosis produced relatively good values of sensitivity, specificity, and consistency across groups. The model was used to create a publicly-available, open-source tool called the Osteoporosis Health Equality (& Equity) Evaluation (OsteoHEE). The model provided high sensitivity for osteoporosis diagnosis, with consistently high results for those identifying as female, and across racial/ethnic groups. Use of this tool is expected to improve equity in screening and increase access to bone density scans for those at risk of osteoporosis. Validation on alternative samples is encouraged.

Childhood Family Environment and Osteoporosis in a Population-Based Cohort Study of Middle-to Older-Age Americans.

Demographic and early-life socioeconomic and parental investment factors may influence later-life health and development of chronic and progressive diseases, including osteoporosis, a costly condition common among women. The "long arm of childhood" literature links negative early-life exposures to lower socioeconomic attainment and worse adult health. We build on a small literature linking childhood socioeconomic status (SES) and bone health, providing evidence of whether associations exist between lower childhood SES and maternal investment and higher risk of osteoporosis diagnosis. We further examine whether persons identifying with non-White racial/ethnic groups experience underdiagnosis. Data from the nationally representative, population-based cohort Health and Retirement Study (N = 5,490-11,819) were analyzed for participants ages 50-90 to assess these relationships. Using a machine learning algorithm, we estimated seven survey-weighted logit models. Greater maternal investment was linked to lower odds of osteoporosis diagnosis (odds ratio [OR] = 0.80, 95% confidence interval [CI] = 0.69, 0.92), but childhood SES was not (OR = 1.03, 95% CI = 0.94, 1.13). Identifying as Black/African American (OR = 0.56, 95% CI = 0.40, 0.80) was associated with lower odds, and identifying as female (OR = 7.22, 95% CI = 5.54, 9.40) produced higher odds of diagnosis. There were differences in diagnosis across intersectional racial/ethnic and sex identities, after accounting for having a bone density scan, and a model predicting bone density scan receipt demonstrated unequal screening across groups. Greater maternal investment was linked to lower odds of osteoporosis diagnosis, likely reflecting links to life-course accumulation of human capital and childhood nutrition. There is some evidence of underdiagnosis related to bone density scan access. Yet results demonstrated a limited role for the long arm of childhood in later-life osteoporosis diagnosis. Findings suggest that (1) clinicians should consider life-course context when assessing osteoporosis risk and (2) diversity, equity, and inclusivity training for clinicians could improve health equity. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Structural Inequity and Socioeconomic Status Link to Osteoporosis Diagnosis in a Population-Based Cohort of Middle-Older-Age Americans.

Socioeconomic status (SES) is an important social determinant of health inequities that has been linked to chronic conditions, including osteoporosis, but research tends to focus on socioeconomic disadvantage rather than how socioeconomic advantage may facilitate these inequities. This study accounts for structural inequities and assesses the relationship between early-life and later-life SES, and risk of osteoporosis diagnosis. Data come from the nationally representative, population-based cohort Health and Retirement Study and include individuals ages 50 to 90. The outcome variable is osteoporosis diagnosis. Logistic regression models of the relationship between SES and osteoporosis diagnosis are estimated, accounting for demographic, health, and childhood variables. Higher levels of childhood and adult SES link to lower odds of osteoporosis diagnosis. Structural inequities in income and underdiagnosis of osteoporosis among persons identifying as Black/African American were detected. Accounting for bone density scan access, inequities in osteoporosis diagnosis appear to stem from barriers to accessing health care due to financial constraints. The important role of SES and evidence of structural inequities leading to underdiagnosis suggest the critical importance of clinicians receiving Diversity, Equity, and Inclusion training to reduce health inequities.

Health Insurance Coverage as a Social Determinant of Osteoporosis Diagnosis in a Population-Based Cohort Study of Older American Adults.

Social determinants of health theoretical frameworks identify health insurance coverage as a determinant of older adults' osteoporosis diagnoses, which results in health inequities. In this research, we used the longitudinal Health and Retirement Study dataset of older United States adults, sampled biennially from 2012 to 2016. Logistic regressions estimated odds of osteoporosis diagnosis with and without a bone scan and/or hip fracture, holding insurance type, and health and demographic factors constant. Results were validated using the National Health and Nutrition Examination Survey. Probable underdiagnosing is present in older adults identifying as Black/African American and as males without a bone scan, regardless of fracture status, potentially as products of structural racism and sexism. Models including a bone scan show a reduction in disparities. These findings suggest having a bone scan is still crucial for addressing health inequities in older adults, and remedying barriers to accessing a scan is paramount.

How social/environmental determinants and inflammation affect salivary telomere length among middle-older adults in the health and retirement study.

Social epidemiology posits that chronic stress from social determinants will lead to a prolonged inflammatory response that may induce accelerated aging as measured, for example, through telomere length (TL). In this paper, we hypothesize variables across demographic, health-related, and contextual/environmental domains influence the body's stress response, increase inflammation (as measured through high-sensitivity C-reactive protein (hs-CRP)), and thereby lead to shortening of telomeres. This population-based research uses data from the 2008 Health and Retirement Study on participants ages ≤ 54-95 + years, estimating logistic regression and Cox proportional hazards models of variables (with and without confounders) across the domains on shortened TL. A mediation analysis is also conducted. Contrary to expectations, hs-CRP is not associated with risk of shortened TL. Rather, factors related to accessing health care, underlying conditions of frailty, and social inequality appear to predict risk of shorter TL, and models demonstrate considerable confounding. Further, hs-CRP is not a mediator for TL. Therefore, the social determinants of health examined do not appear to follow an inflammatory pathway for shortened TL. The finding of a relationship to social determinants affecting access to health care and medical conditions underscores the need to address social determinants alongside primary care when examining health inequities.