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Predicting low premorbid cognitive ability with social determinants: A machine learning approach
Lubnaa Badriyyah Abdullah, Ibshar Khandakar, Ashley Douglas, Robert Nance, Zhengyang Zhou, James W Hall III, Sid E. O’Bryant. Journal of Aging Research and Lifestyle, 2026-01-01
Topic: Risk, prevention and care in population studies
The model achieved and AUC of 0.72 [0.64, 0.81]. Top predictors included worry, ADI, income, high school completion, and tangible support. Low pIQ was associated with greater neighborhood deprivation, lower income, and reduced support resources. Low pIQ, when combined with SDoH factors reflects a vulnerable psychosocial-cognitive phenotype that may accelerate pathways to cognitive decline potentially through inflammatory mechanisms.
Key findings
- The model achieved and AUC of 0.72 [0.64, 0.81].
- Top predictors included worry, ADI, income, high school completion, and tangible support.
- Low pIQ was associated with greater neighborhood deprivation, lower income, and reduced support resources.
- Low pIQ, when combined with SDoH factors reflects a vulnerable psychosocial-cognitive phenotype that may accelerate pathways to cognitive decline potentially through inflammatory mechanisms.
Why it matters
This study used a machine learning model to predict low cognitive ability before symptoms from social factors like worry, neighborhood deprivation, income, and support. It is about predicting risk, not about treating, curing, or preventing Alzheimer's disease.
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Study details
- Evidence strengthLow
How this study scored 31/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of Aging Research and Lifestyle) |
| Journal's citation record | 0 / 4 | Journal of Aging Research and Lifestyle: journal h-index 13 (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 | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| 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 2 year(s) since 2026 |
| 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 | 3 / 4 | Last-listed author Sid E. O’Bryant: h-index 63 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | University of North Texas: institution h-index 431 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41704741) |
| Free to read | 2 / 2 | Free to read |
| Total | 31 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1016/j.jarlif.2026.100062
- PubMed: 41704741
- Original source →
- Free full text: Journal of Aging Research and Lifestyle →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Abdullah, L. B., Khandakar, I., Douglas, A., Nance, R., Zhou, Z., Hall, J. W., III., et al. (2026). Predicting low premorbid cognitive ability with social determinants: A machine learning approach. Journal of Aging Research and Lifestyle. https://doi.org/10.1016/j.jarlif.2026.100062
Vancouver
Abdullah LB, Khandakar I, Douglas A, Nance R, Zhou Z, Hall JW III, et al. Predicting low premorbid cognitive ability with social determinants: A machine learning approach. Journal of Aging Research and Lifestyle. 2026. doi:10.1016/j.jarlif.2026.100062. PMID: 41704741.
BibTeX
@article{abdullah2026-41704741,
author = {Abdullah, Lubnaa Badriyyah and Khandakar, Ibshar and Douglas, Ashley and Nance, Robert and Zhou, Zhengyang and Hall, III., James W and O’Bryant, Sid E.},
title = {{Predicting low premorbid cognitive ability with social determinants: A machine learning approach}},
journal = {Journal of Aging Research and Lifestyle},
year = {2026},
doi = {10.1016/j.jarlif.2026.100062},
pmid = {41704741},
url = {https://doi.org/10.1016/j.jarlif.2026.100062}
}
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