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General Practice Clinical Data Help Identify Dementia Hotspots: A Novel Geospatial Analysis Approach
Nasser Bagheri, Kinley Wangdi, Nicolas Cherbuin, Kaarin Jane Anstey. Journal of Alzheimer s Disease, 2017-11-10
Topic: Risk, prevention and care in population studies
We have a poor understanding of whether dementia clusters geographically, how this occurs, and how dementia may relate to socio-demographic factors. To shed light on these important questions, this study aimed to compute a dementia risk score for individuals to assess spatial variation of dementia risk, identify significant clusters (hotspots), and explore their association with socioeconomic status. We used clinical records from 16 general practices (468 Statistical Area level 1 s, N = 14,746) from the city of west Adelaide, Australia for the duration of 1 January 2012 to 31 December 2014. Dementia risk was estimated using The Australian National University-Alzheimer's Disease Risk Index. Hotspot analyses were applied to examine potential clusters in dementia risk at small area level. Significant hotspots were observed in eastern and southern areas while coldspots were observed in the western area within the study perimeter. Additionally, significant hotspots were observed in low socio-economic communities. We found dementia risk scores increased with age, sex (female), high cholesterol, no physical activity, living alone (widow, divorced, separated, or never married), and co-morbidities such as diabetes and depression. Similarly, smoking was associated with a lower dementia risk score. The identification of dementia risk clusters may provide insight into possible geographical variations in risk factors for dementia and quantify these risks at the community level. As such, this research may enable policy makers to tailor early prevention strategies to the correct individuals within their precise locations.
Key findings
- To shed light on these important questions, this study aimed to compute a dementia risk score for individuals to assess spatial variation of dementia risk, identify significant clusters (hotspots), and explore their association with socioeconomic status.
- Significant hotspots were observed in eastern and southern areas while coldspots were observed in the western area within the study perimeter.
- Additionally, significant hotspots were observed in low socio-economic communities.
- We found dementia risk scores increased with age, sex (female), high cholesterol, no physical activity, living alone (widow, divorced, separated, or never married), and co-morbidities such as diabetes and depression.
- Similarly, smoking was associated with a lower dementia risk score.
Why it matters
Using general practice records in west Adelaide, this study found clusters of higher dementia risk in some areas and lower risk in others, with hotspots in low socioeconomic communities. It identifies where risk clusters occur but does not test any treatment or prevention.
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Study details
- Participants14,746
- Evidence strengthLow
How this study scored 45/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| 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 | 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 | 2 / 5 | 2017 — within 10 year(s) of the newest study here |
| Sample size | 4 / 4 | 14,746 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| 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 | 3 / 7 | Cited 27 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.5 citations a year over 11 year(s) since 2017 |
| Impact for its field and year | 2 / 6 | Cited 1.6× 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 | 1 / 4 | Cited 6 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Kaarin Jane Anstey: h-index 103 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Australian National University: institution h-index 1,088 (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 29125484) |
| Free to read | 2 / 2 | Free to read |
| Total | 45 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.3233/jad-170079
- PubMed: 29125484
- Original source →
- Free full text: UNSWorks (University of New South Wales, Sydney, Australia) →
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. Check the citation against the original before you use it.
APA 7th
Bagheri, N., Wangdi, K., Cherbuin, N., & Anstey, K. J. (2017). General Practice Clinical Data Help Identify Dementia Hotspots: A Novel Geospatial Analysis Approach. Journal of Alzheimer s Disease. https://doi.org/10.3233/jad-170079
Vancouver
Bagheri N, Wangdi K, Cherbuin N, Anstey KJ. General Practice Clinical Data Help Identify Dementia Hotspots: A Novel Geospatial Analysis Approach. Journal of Alzheimer s Disease. 2017. doi:10.3233/jad-170079. PMID: 29125484.
BibTeX
@article{bagheri2017-29125484,
author = {Bagheri, Nasser and Wangdi, Kinley and Cherbuin, Nicolas and Anstey, Kaarin Jane},
title = {{General Practice Clinical Data Help Identify Dementia Hotspots: A Novel Geospatial Analysis Approach}},
journal = {Journal of Alzheimer s Disease},
year = {2017},
doi = {10.3233/jad-170079},
pmid = {29125484},
url = {https://doi.org/10.3233/jad-170079}
}
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Referenced by this study and also in the alzhub library, so you can read them here.