Comment on “Association between the dietary index for gut microbiota and osteoporosis among middle-aged and older adults in the United States”

Abstract

The recent NHANES-based study by Zhan et al. (2025) investigated the association between the dietary index for gut microbiota (DI-GM) and osteoporosis, reporting that higher DI-GM scores were linked to lower osteoporosis prevalence. While the study provides valuable exploratory evidence, several limitations may affect its clinical and public health implications. First, residual confounding may remain, as weight-bearing exercise, vitamin D status, calcium/phosphate metabolism, sex hormones, and family history were not incorporated. Second, generalizability is constrained: the sample was predominantly White and higher-income, dietary cultures shape gut microbiota composition, and osteopenia—a key prevention target—was excluded. Third, the absence of subgroup analyses may obscure heterogeneity across high-risk groups, especially postmenopausal women, in whom pathophysiological drivers and intervention effects differ. Finally, the outcome definition (femoral neck DXA T-score ≤ −2.5) does not fully align with clinical decision-making, which primarily relies on fragility fractures and FRAX-estimated 10-year probabilities. Future research should integrate broader metabolic and behavioral determinants, validate DI-GM across diverse populations and dietary contexts, include osteopenic individuals, and align outcomes with fracture risk to enhance clinical and public health utility.

To the Editor,

We read with great interest the recent NHANES-based study examining the association between the dietary index for gut microbiota (DI-GM) and osteoporosis (Zhan et al., 2025). The authors should be commended for providing novel evidence on the potential role of diet in bone health. Nevertheless, several aspects of the study design and interpretation may limit its clinical and public health applicability.

First, residual confounding may remain despite multivariable adjustment. Although the authors controlled for demographic factors, BMI, and selected lifestyle variables, other determinants of bone metabolism were not incorporated. For example, weight-bearing and resistance exercise have been consistently demonstrated in meta-analyses to improve bone mineral density in postmenopausal women (Mohebbi et al., 2023), yet physical activity was captured only as sedentary time. Similarly, vitamin D status, calcium/phosphate balance, and sex hormone levels all central to bone metabolism were unavailable. Furthermore, genetic predisposition and family history were not considered. These omissions may have introduced residual confounding, which could attenuate or inflate the observed associations.Furthermore, a potential limitation lies in the data analysis approach. The study excluded individuals with missing DI-GM components or key demographic information (n = 504), effectively employing a complete-case analysis. This method assumes data are missing at random, and if this assumption does not hold, it could lead to selection bias and affect the accuracy of the effect estimates. In future research, conducting sensitivity analyses using methods for handling missing data, such as multiple imputation, would help verify the robustness of the current findings.

Second, the generalizability of the findings is constrained. The analytic sample was predominantly non-Hispanic White (71.9 %) and skewed toward higher income levels (53.2 % with PIR >3.5), limiting extrapolation to minority and socioeconomically disadvantaged populations. Moreover, dietary culture and habitual intake are closely linked to gut microbiota composition. Evidence shows that microbiome variation associated with race and ethnicity can emerge as early as infancy (Mallott et al., 2023), and experimental data highlight the context-dependent effects of the gut–bone axis (Lyu et al., 2023). Thus, whether a DI-GM derived from U.S. dietary patterns retains predictive validity in other cultural contexts remains uncertain. Importantly, individuals with osteopenia were excluded, despite being a much larger population at elevated risk. As Reid (2024) has emphasized, osteopenia represents a pivotal target for early prevention, and omission of this group reduces the public health relevance of the findings.

Third, the absence of subgroup analyses limits interpretability. Osteoporosis pathophysiology differs markedly between men and women, with hormonal changes after menopause being a dominant driver. Recent evidence confirms that interventions such as exercise confer clear benefits specifically in postmenopausal women (Mohebbi et al., 2023). Without stratification by sex, menopausal status, age, or ethnicity, the reported associations may obscure heterogeneity across high-risk groups and limit guidance for targeted prevention.

Finally, the choice of outcome does not fully align with real-world decision-making. The study defined osteoporosis solely by femoral neck DXA T-score ≤ −2.5. While this remains a diagnostic standard, clinical and policy decisions are based primarily on fragility fractures and FRAX 10-year fracture probabilities. FRAX has become integral to international guidelines and treatment thresholds (Schini et al., 2024). By focusing only on cross-sectional BMD, the study may overstate the translational potential of DI-GM. Incorporating fracture incidence, FRAX thresholds, or sensitivity analyses of prior fracture and fall history would improve clinical relevance.

In summary, this study provides valuable exploratory evidence linking a microbiota-oriented dietary index with osteoporosis prevalence, but residual confounding, limited external validity, absence of subgroup analyses, and reliance on BMD rather than fracture outcomes suggest that conclusions should be interpreted cautiously. Future research that integrates additional metabolic and behavioral determinants, validates DI-GM across diverse populations and dietary cultures, includes osteopenic individuals, and employs fracture-aligned outcomes will strengthen both clinical and public health translation.

CRediT authorship contribution statement

Xiaoling Xu: Writing – review & editing, Writing – original draft.

Ethics statement

As this is a Letter to the Editor providing a scholarly commentary on a previously published article, no original patient data were collected, analyzed, or reported. Therefore, ethical approval and patient consent were not required.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this manuscript, the author used ChatGPT to assist with language refinement and stylistic editing. All AI-assisted content was carefully reviewed and revised by the author, who assumes full responsibility for the final version of the manuscript.

Funding

None.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Not applicable