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Development and validation of a predictive nomogram for mild cognitive impairment in middle-aged and elderly populations: A multi-module analysis integrating air quality and sociodemographic factors
Jia Hui Yu, Yu Yang, Mengmeng Li, Zhanxue Liu, Fengjun Yang. Journal of Alzheimer s Disease, 2025-10-07
Topic: Risk, prevention and care in population studies
Background Growing evidence links air pollution to mild cognitive impairment (MCI), yet existing models often overlook environmental exposures. We developed a novel MCI nomogram integrating air pollution, sociodemographic, and clinical predictors for Chinese adults ≥ 45 years. Objective To develop and validate a personalized MCI risk assessment tool incorporating sociodemographic, clinical, and environmental factors. Methods Using the 2015 CHARLS cohort (n = 7702), we built two MCI prediction models with city- and county-level air pollution exposures. Model performance was assessed via discrimination (C-index, ROC), calibration, clinical utility (decision curves), predictive performance (net reclassification improvement, NRI and integrated discrimination improvement, IDI). Results This study analyzed 7702 participants, randomly split into training (n = 5391) and validation (n = 2311) groups. Uni-variate analysis identified MCI risk in age ≥75 years, private medical insurance, married individuals and males. Multivariate analysis in Model 2 identified 13 key factors associated with MCI, among them age ≥75 years (OR = 5.437, 95%CI: 3.524–8.388, p < 0.001), private medical insurance (OR = 4.994, 95%CI: 2.340–11.337, p = 0.002), being mental disorders (OR = 2.210, 95%CI: 1.217–4.014, p < 0.001), males (OR = 0.638, 95%CI: 0.493–0.824, p = 0.04), PM 10 (OR = 1.059, 95%CI: 1.051–1.067, p < 0.001) and PM 2.5 (OR = 1.025, 95%CI: 1.013 −1.038, p < 0.001) as strongest predictors. Model 2 outperformed Model 1 with higher discrimination, better calibration, greater clinical utility and improved accuracy. Conclusions The validated nomogram enables individualized MCI risk stratification, supporting targeted community prevention strategies.
Key findings
- Results This study analyzed 7702 participants, randomly split into training (n = 5391) and validation (n = 2311) groups.
- Multivariate analysis in Model 2 identified 13 key factors associated with MCI, among them age ≥75 years (OR = 5.437, 95%CI: 3.524–8.388, p < 0.001), private medical insurance (OR = 4.994, 95%CI: 2.340–11.337, p = 0.002), being mental disorders (OR = 2.210, 95%CI: 1.217–4.014, p < 0.001), males (OR = 0.638, 95%CI: 0.493–0.824, p = 0.04), PM 10 (OR = 1.059, 95%CI: 1.051–1.067, p < 0.001) and PM 2.5 (OR = 1.025, 95%CI: 1.013 −1.038, p < 0.001) as strongest predictors.
Why it matters
Using data from 7,702 Chinese adults aged 45 and older, researchers developed a model to predict mild cognitive impairment that includes air pollution, sociodemographic, and clinical factors. The model identified 13 factors associated with MCI, including age 75 and older, private medical insurance, mental disorders, male sex, and PM10 exposure.
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Study details
- Participants7,702
- Effect sizeOR = 5.437; OR = 4.994; OR = 2.210
- Evidence strengthModerate
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it. We have no data on senior author's track record, so that was left out: it earned 37 of the 96 points we could judge it on, which is 39 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of Alzheimer s Disease) |
| Journal's citation record | 2 / 4 | Journal of Alzheimer s Disease: journal h-index 218 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 3 / 4 | 7,702 participants |
| Effect reported | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 0 / 7 | Cited 0 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 0 / 6 | Cited 0.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 0 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | 0 / 3 | Chifeng University: institution h-index 80 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41055934) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 37 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 37 of the 96 points we could judge it on is 39 out of 100. |
| Total | 39 / 100 | — |
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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APA 7th
Yu, J. H., Yang, Y., Li, M., Liu, Z., & Yang, F. (2025). Development and validation of a predictive nomogram for mild cognitive impairment in middle-aged and elderly populations: A multi-module analysis integrating air quality and sociodemographic factors. Journal of Alzheimer s Disease. https://doi.org/10.1177/13872877251378520
Vancouver
Yu JH, Yang Y, Li M, Liu Z, Yang F. Development and validation of a predictive nomogram for mild cognitive impairment in middle-aged and elderly populations: A multi-module analysis integrating air quality and sociodemographic factors. Journal of Alzheimer s Disease. 2025. doi:10.1177/13872877251378520. PMID: 41055934.
BibTeX
@article{yu2025-41055934,
author = {Yu, Jia Hui and Yang, Yu and Li, Mengmeng and Liu, Zhanxue and Yang, Fengjun},
title = {{Development and validation of a predictive nomogram for mild cognitive impairment in middle-aged and elderly populations: A multi-module analysis integrating air quality and sociodemographic factors}},
journal = {Journal of Alzheimer s Disease},
year = {2025},
doi = {10.1177/13872877251378520},
pmid = {41055934},
url = {https://doi.org/10.1177/13872877251378520}
}
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