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

Abstract

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.

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

“…We include three measures related to physical activity and mobility: indicators of difficulty (1) walking one block (no/yes, a little/yes, a lot), (2) sitting for 2 hr (no/yes), and (3) getting up from a chair (no/yes). We account for having received a dual energy x-ray absorptiometry (DXA) scan (yes/no) because a BMD scan is a key element in receiving an osteoporosis diagnosis, and there are disparities in access to BMD scans (e.g., by race/ethnicity; Calikyan et al, 2023 ; Godde et al, 2022 ; Gough Courtney, Roberts, & Godde, 2023 ; Gough Courtney, Roberts, Quintero, et al, 2023 ). T-scores from BMD scans may still include bias as they were developed from persons identifying as non-Hispanic White ( Noel et al, 2021 ).…”

“…Evidence linking certain inflammatory biomarkers (e.g., high-sensitivity C-reactive protein) with osteoporosis is mixed ( Ganesan et al, 2005 ; Godde et al, 2022 ; Gough & Godde, 2019 ; Gough Courtney et al, 2021 ; Gough Courtney, Roberts, & Godde, 2023 ; Gough Courtney, Roberts, Quintero, et al, 2023 ; Koh et al, 2005 ; Lencel & Magne, 2011 ). However, significant associations between more upstream factors and osteoporosis (bone mineral density [BMD]) are observed, such as through difficulty accessing equitable, quality healthcare ( Calikyan et al, 2023 ; Godde et al, 2022 ; Gough Courtney et al, 2021 ; Mikuls et al, 2005 ), childhood adversity (e.g., socioeconomic disadvantage; Crandall et al, 2012 ; Gough Courtney, Roberts, Quintero, et al, 2023 ), educational attainment (i.e., degree of completion) and income ( Du et al, 2017 ; Gough Courtney, Roberts, & Godde, 2023 ; Tsai, 2019 ), body weight ( Mazocco & Chagas, 2017 ), diabetes ( Kurra & Siris, 2011 ), and thyroid disorders ( Apostu et al, 2020 ). Research suggests a link between hyperactivity of the HPA axis and osteoporosis through a cascading effect of high glucocorticoids, low growth hormones, and low sex hormones that stem from psychological stress ( Azuma et al, 2015 ) and lead to reduced osteoblastic activity ( Almeida & O’Brien, 2013 ).…”

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

“…Thus, in attempting to understand the disparities seen for osteoporosis diagnosis, it is necessary to consider the role of racism, along with the role of SES. Indeed, recent studies have provided strong evidence of inequities in osteoporosis diagnosis by race that appear to stem from systemic racism to a greater extent than economic resources [ 9 , 10 ].…”