Structural inequality linked to brain volume and network dynamics in aging and dementia across the Americas
Open accessAbstract
Structural inequality, the uneven distribution of resources and opportunities, influences health outcomes. However, the biological embedding of structural inequality in aging and dementia, especially among underrepresented populations, is unclear. We examined the association between structural inequality (country-level and state-level Gini indices) and brain volume and connectivity in 2,135 healthy controls, and individuals with Alzheimer's disease and frontotemporal lobe degeneration from Latin America and the United States. Greater structural inequality was linked to reduced brain volume and connectivity, with stronger effects in Latin America, especially in the temporo-cerebellar, fronto-thalamic and hippocampal regions. In the United States, milder effects were observed in the insular-cingular and temporal areas. Results were more pronounced in Alzheimer's disease and were independent of age, sex, education, cognition and other confounding factors. The findings highlight the critical role of structural inequality in aging and dementia, emphasizing the biological embedding of macrosocial factors and the need for targeted interventions in underserved populations.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Resilience is understudied in the majority world, including low-, middle-, and upper-middle-income countries, where socioeconomic inequities, environmental stressors, high disease burdens, and limited healthcare access create distinct health trajectories.
“While extensively studied in high-income countries, resilience remains underexplored in the majority world, including low-, middleand upper-middle-income countries—where socioeconomic inequities, environmental stressors, large burdens of infectious and noncommunicable diseases and limited healthcare access shape unique health trajectories6–15.”
From Resilience and brain health in global populations (2025) · cites this paper as [14]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredWhen multiple disparity-related measures are included as predictors, smaller sex differences are observed.
“When multiple disparity-related measures are included as predictors, smaller sex differences are observed20,34.”
From The exposome of healthy and accelerated aging across 40 countries (2025) · cites this paper as [20]
Structural and environmental determinants have a substantial influence on aging beyond individual conditions.
“suggesting that structural and environmental determinants have a substantial influence on aging beyond individual conditions20,34.”
From The exposome of healthy and accelerated aging across 40 countries (2025) · cites this paper as [20]
Classical exposomal factors, including air pollution, structural socioeconomic inequality, gender inequalities, and migration, are associated with accelerated aging.
“Classical exposomal factors, including physical(air pollution) and social factors (structural socioeconomic inequality20,26,34, gender inequalities27, and migration33) are known to impact brain health and aging, which we demonstrate to also be associated with accelerated aging.”
From The exposome of healthy and accelerated aging across 40 countries (2025) · cites this paper as [20]
Aggregate-level metrics are not without bias from data sources, especially those of national relevance.
“As in other works2,20, aggregate-level metrics are not without bias from data sources, especially those of national relevance.”
From The exposome of healthy and accelerated aging across 40 countries (2025) · cites this paper as [20]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657 · see citing works
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319 · see citing works
Methods to detect, characterize, and remove motion artifact in resting state fMRI
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748 · see citing works
Noise contributions to the fMRI signal: An overview
Liu, T. T. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.008 · Cited by 279 · see citing works
Determinants of accelerated metabolomic and epigenetic aging in a UK cohort
Robinson, O., Chadeau Hyam, M., Karaman, I., Climaco Pinto, R., Ala-Korpela, M., Handakas, E., Fiorito, G., Gao, H., Heard, A., Jarvelin, M., et al. (2020) · Aging Cell · doi:10.1111/acel.13149 · Cited by 205 · see citing works
García-Cordero, I., Sedeño, L., de la Fuente, L., Slachevsky, A., Forno, G., Klein, F., Lillo, P., Ferrari, J., Rodriguez, C., Bustin, J., et al. (2016) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2016.0006 · Cited by 199 · see citing works
Self-citationImpaired insulin signalling and allostatic load in Alzheimer disease
Felice, F. G. D., Gonçalves, R. A., & Ferreira, S. T. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00558-9 · Cited by 180 · see citing works
Frontotemporal lobar degeneration
Grossman, M., Seeley, W. W., Boxer, A. L., Hillis, A. E., Knopman, D. S., Ljubenov, P. A., Miller, B., Piguet, O., Rademakers, R., Whitwell, J. L., et al. (2023) · Nature Reviews Disease Primers · doi:10.1038/s41572-023-00447-0 · Cited by 178 · cited 1× · see citing works
“Clinical diagnoses were performed by multidisciplinary expert teams according to established clinical criteria for FTLD 45 , including behavioral-variant frontotemporal dementia, primary progressive aphasia, corticobasal degeneration and others, as well as for AD 46 .”
Self-citationAssociation of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume
Hunt, J. F. V., Buckingham, W. J., Kim, A. J., Oh, J. M., Vogt, N. M., Jonaitis, E. M., Hunt, T. K. A., Zuelsdorff, M. L., Powell, W. R., Norton, D., et al. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2019.4501 · Cited by 166 · see citing works
Factors associated with healthy aging in Latin American populations
Santamaria-Garcia, H., Sainz-Ballesteros, A., Hernandez, H., Moguilner, S., Maito, M., Ochoa-Rosales, C., Corley, M., Valcour, V., Miranda, J. J., Lawlor, B., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02495-1 · Cited by 141 · see citing works
Self-citationMoguilner, S., Baez, S., Hernandez, H., Migeot, J., Legaz, A., Gonzalez-Gomez, R., Farina, F. R., Prado, P., Cuadros, J., Tagliazucchi, E., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03209-x · Cited by 128 · see citing works
Self-citationIbáñez, A. M., Yokoyama, J. S., Possin, K. L., Matallana, D., Lopera, F. J., Nitríni, R., Takada, L. T., Custodio, N., Sosa, A. L., Ávila‐Funes, J. A., et al. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.631722 · Cited by 114 · see citing works
Self-citationWeissman, D. G., Hatzenbuehler, M. L., Cikara, M., Barch, D. M., & McLaughlin, K. A. (2023) · Nature Communications · doi:10.1038/s41467-023-37778-1 · Cited by 107 · see citing works
Interoception primes emotional processing: multimodal evidence from neurodegeneration
Salamone, P. C., Legaz, A., Sedeño, L., Moguilner, S., Fraile-Vazquez, M., Campo, C. G., Fittipaldi, S., Yoris, A., Miranda, M., Birba, A., et al. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.2578-20.2021 · Cited by 103 · see citing works
Self-citationJiang, L., & Probst, T. M. (2016) · Journal of Applied Psychology · doi:10.1037/apl0000179 · Cited by 91 · see citing works
Functional and Structural Brain Correlates of Socioeconomic Status.
Yaple, Z., & Yu, R. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz080 · Cited by 88 · see citing works
Walhovd, K. B., Fjell, A. M., Wang, Y., Amlien, I. K., Mowinckel, A. M., Lindenberger, U., Düzel, S., David Bartrés-faz, A., Ebmeier, K. P., Drevon, C. A., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab248 · Cited by 79 · see citing works
Neuroecological links of the exposome and One Health
Ibanez, A., Melloni, L., Świeboda, P., Hynes, W., Ikiz, B., Ayadi, R., Thioye, M., Walss-Bass, C., Güntekin, B., Mishra, J., et al. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.016 · Cited by 79 · see citing works
A predictive coding framework of allostatic–interoceptive overload in frontotemporal dementia
Migeot, J. A., Duran-Aniotz, C. A., Signorelli, C. M., Piguet, O., & Ibáñez, A. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.08.005 · Cited by 76 · see citing works
Self-citationSocioeconomic status impacts cognitive and socioemotional processes in healthy ageing
Migeot, J., Calivar, M., Granchetti, H. N., Ibáñez, A. M., & Fittipaldi, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-09580-4 · Cited by 66 · see citing works
Self-citationDementia caregiving across Latin America and the Caribbean and brain health diplomacy
Ibáñez, A., Pina-Escudero, S. D., Possin, K. L., Quiroz, Y. T., Peres, F. A., Slachevsky, A., Sosa, A. L., Brucki, S. M. D., & Miller, B. L. (2021) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(21)00031-3 · Cited by 65 · see citing works
Self-citationZugman, A., Alliende, L. M., Medel, V., Bethlehem, R. A. I., Seidlitz, J., Ringlein, G., Arango, C., Arnatkevičiūtė, A., Asmal, L., Bellgrove, M., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2218782120 · Cited by 65 · see citing works
Self-citationMaito, M., Santamaría-García, H., Moguilner, S., Possin, K., Godoy, M. E., Ávila-Funes, J., Behrens, M. I., Brusco, I., Bruno, M., Cardona, J., et al. (2022) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2022.100387 · Cited by 63 · see citing works
Self-citationAddressing the gaps between socioeconomic disparities and biological models of dementia
Ibáñez, A. M., Legaz, A., & Ruiz-Adame, M. (2023) · Brain · doi:10.1093/brain/awad236 · Cited by 60 · see citing works
Self-citationEducational disparities in brain health and dementia across Latin America and the United States
Gonzalez‐Gomez, R., Legaz, A., Moguilner, S., Cruzat, J., Hernández, H., Baez, S., Cocchi, R., Coronel‐Olivero, C., Medel, V., Tagliazuchi, E., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.14085 · Cited by 55 · see citing works
Self-citationHealth and Socioeconomic Inequities as Contributors to Brain Health
Resende, E. D. P. F., Guerra, J. J. L., & Miller, B. L. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2019.0362 · Cited by 52 · see citing works
Self-citationGlobal South research is critical for understanding brain health, ageing and dementia
Baez, S., Alladi, S., & Ibanez, A. (2023) · Clinical and Translational Medicine · doi:10.1002/ctm2.1486 · Cited by 47 · see citing works
Self-citationState inequality, socioeconomic position and subjective cognitive decline in the United States
Peterson, R. L., Carvajal, S. C., McGuire, L. C., Fain, M. J., & Bell, M. L. (2019) · SSM - Population Health · doi:10.1016/j.ssmph.2019.100357 · Cited by 46 · see citing works
Donnelly-Kehoe, P. A., Pascariello, G. O., García, A. M., Hodges, J. R., Miller, B. L., Rosen, H. J., Manes, F. F., Landín-Romero, R., Matallana, D., Serrano, C. M., et al. (2019) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2019.06.002 · Cited by 44 · see citing works
Self-citationBrain health in diverse settings: How age, demographics and cognition shape brain function
Hernandez, H., Báez, S., Medel, V., Moguilner, S., Cuadros, J., Santamaría‐García, H. A., Tagliazucchi, E., Valdes-Sosa, P. A., Lopera, F. J., Ochoa-Gómez, J. F., et al. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120636 · Cited by 42 · see citing works
Self-citationFittipaldi, S., Legaz, A., Maito, M. A., Hernandez, H., Altschuler, F., Canziani, V., Moguilner, S., Gillan, C. M., Castillo, J., Lillo, P., et al. (2024) · Nature Mental Health · doi:10.1038/s44220-023-00164-3 · Cited by 41 · see citing works
Self-citationMoguilner, S., Whelan, R., Adams, H., Valcour, V., Tagliazucchi, E., & Ibáñez, A. (2023) · eBioMedicine · doi:10.1016/j.ebiom.2023.104540 · Cited by 39 · see citing works
Self-citationHuman brain anatomy reflects separable genetic and environmental components of socioeconomic status
Kweon, H., Aydogan, G., Dagher, A., Bzdok, D., Ruff, C. C., Nave, G., Farah, M. J., & Koellinger, P. D. (2022) · Science Advances · doi:10.1126/sciadv.abm2923 · Cited by 36 · see citing works
Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases
Legaz, A., Abrevaya, S., Dottori, M., González Campo, C., Birba, A., Martorell Caro, M., Aguirre, J., Slachevsky, A., Aranguiz, R., Serrano, C., et al. (2022) · Brain · doi:10.1093/brain/awab345 · Cited by 34 · see citing works
Self-citationBiomarkers of neurodegeneration across the Global South
McGlinchey, E., Duran-Aniotz, C., Akinyemi, R., Arshad, F., Zimmer, E. R., Cho, H., Adewale, B. A., & Ibanez, A. (2024) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(24)00132-6 · Cited by 32 · see citing works
Lotze, M., Domín, M., Schmidt, C. O., Hosten, N., Grabe, H. J., & Neumann, N. (2020) · Scientific Reports · doi:10.1038/s41598-020-75809-9 · Cited by 31 · see citing works
A research agenda for understanding how social inequality is linked to brain structure and function
Hatzenbuehler, M. L., McLaughlin, K. A., Weissman, D. G., & Cikara, M. (2024) · Nature Human Behaviour · doi:10.1038/s41562-023-01774-8 · Cited by 31 · see citing works
Ibanez, A., Maito, M., Botero-Rodríguez, F., Fittipaldi, S., Coronel, C., Migeot, J., Lacroix, A., Lawlor, B., Duran-Aniotz, C., Baez, S., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00648-6 · Cited by 30 · see citing works
Self-citationMoguilner, S., García, A. M., Mikulan, E., Hesse, E., Cordero, I. R. G., Melloni, M., Cervetto, S., Serrano, C. M., Herrera, E., Reyes, P. A., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-29538-9 · Cited by 27 · see citing works
Self-citationStefler, D., Prina, M. A., Wu, Y., Niubo, A. S., Lu, W., Haro, J. M., Marmot, M. G., & Bobák, M. (2021) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2020-214714 · Cited by 27 · see citing works
Allostasis, health, and development in Latin America
Migeot, J., Panesso, C., Duran-Aniotz, C., Ávila-Rincón, C., Ochoa, C., Huepe, D., Santamaría-García, H., Miranda, J. J., Escobar, M. J., Pina-Escudero, S., et al. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105697 · Cited by 25 · see citing works
Self-citationLooze, C. D., Demnitz, N., Knight, S. P., Carey, D., Meaney, J., Kenny, R. A., & McCrory, C. (2023) · The Journals of Gerontology Series A · doi:10.1093/gerona/glad068 · Cited by 21 · see citing works
Structural inequality and temporal brain dynamics across diverse samples
Baez, S., Hernandez, H., Moguilner, S., Cuadros, J., Santamaria‐Garcia, H., Medel, V., Migeot, J., Cruzat, J., Valdes‐Sosa, P. A., Lopera, F., et al. (2024) · Clinical and Translational Medicine · doi:10.1002/ctm2.70032 · Cited by 21 · see citing works
Self-citationEnvironmental–genetic interactions in ageing and dementia across Latin America
Ibanez, A., & Slachevsky, A. (2024) · Nature Reviews Neurology · doi:10.1038/s41582-024-00998-0 · Cited by 15 · see citing works
Self-citationMeasuring the impact of structural inequality on the structure of the brain
Sheridan, M. A. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2306076120 · Cited by 14 · see citing works
Socioeconomic disparities harm social cognition
Fittipaldi, S., Migeot, J., & Ibáñez, A. M. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.12.005 · Cited by 12 · see citing works
Self-citationYu, S., Qian, L., & Ma, J. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14677 · Cited by 9 · see citing works
Social and non-social working memory in neurodegeneration
Legaz, A., Prado, P., Moguilner, S., Báez, S., Santamaría‐García, H. A., Birba, A., Barttfeld, P., García, A. M., Fittipaldi, S., & Ibáñez, A. M. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106171 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The exposome of healthy and accelerated aging across 40 countries
Hernandez, H., Santamaria-Garcia, H., Moguilner, S., Farina, F. R., Legaz, A., Prado, P., Cuadros, J., Gonzalez, L., Gonzalez-Gomez, R., Migeot, J., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03808-2 · Cited by 71 · see citing works
Self-citationMostert, C. M., Udeh-Momoh, C., Winkler, A. S., McLaughlin, C., Eyre, H., Salama, M., Ranchod, K., Trepel, D., Vradenburg, G., Hynes, W., et al. (2025) · eBioMedicine · doi:10.1016/j.ebiom.2025.105950 · Cited by 42 · see citing works
Resilience and brain health in global populations
Udeh-Momoh, C. T., Migeot, J., Blackmon, K., Mielke, M. M., Melloni, M., Cox, L., Yaffe, K., Santamaria-Garcia, H., Stern, Y., & Ibanez, A. (2025) · Nature Medicine · doi:10.1038/s41591-025-03846-w · Cited by 42 · see citing works
Self-citationStructural inequality and temporal brain dynamics across diverse samples
Baez, S., Hernandez, H., Moguilner, S., Cuadros, J., Santamaria‐Garcia, H., Medel, V., Migeot, J., Cruzat, J., Valdes‐Sosa, P. A., Lopera, F., et al. (2024) · Clinical and Translational Medicine · doi:10.1002/ctm2.70032 · Cited by 21 · see citing works
Self-citationGonzalez-Gomez, R., Cruzat, J., Hernández, H., Migeot, J., Legaz, A., Santamaria-García, H., Fittipaldi, S., Maito, M. A., Medel, V., Tagliazucchi, E., et al. (2025) · eClinicalMedicine · doi:10.1016/j.eclinm.2025.103187 · Cited by 19 · see citing works
Self-citationInspired by struggle: A personal journey to global precision brain health
Ibanez, A. (2025) · iScience · doi:10.1016/j.isci.2025.111918 · Cited by 5 · see citing works
- Authors
- Legaz, A., Altschuler, F., Gonzalez-Gomez, R., Hernández, H., Baez, S., Migeot, J., Fittipaldi, S., Medel, V., Maito, M. A., Godoy, M. E., Moguilner, S., Cruzat, J., Coronel-Oliveros, C., Tagliazuchi, E., Santamaria Garcia, H., Farina, F. R., Reyes, P., Javandel, S., García, A. M., Deleglise, Á., Matallana, D. L., Avila-Funes, J. A., Slachevsky, A., Behrens, M. I., Custodio, N., Trujillo-Llano, C., Cardona, J. F., Barttfeld, P., Brusco, I. L., Bruno, M. A., Sosa Ortiz, A. L., Pina-Escudero, S. D., Takada, L. T., França Resende, E. D. P., Possin, K. L., Okada de Oliveira, M., Hu, K., Lopera, F., Lawlor, B., Valcour, V., Yokoyama, J. S., Miller, B., & Ibañez, A.
- Affiliations
- Adolfo Ibáñez University (CL)
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Trinity College Dublin (IE)
- University of California, San Francisco (US)
- University of San Andrés (AR)
- Harvard University (US)
- Pontificia Universidad Javeriana (CO)
- Universidad de Santiago de Chile (CL)
- Universidad del Desarrollo (CL)
- Instituto Peruano de Neurociencias (PE)
- Universidad del Valle (CO)
- Universidad de Buenos Aires (AR)
- Universidade de São Paulo (BR)
- Universidad de Antioquia (CO)
- ORCID
- Legaz, Agustina
- Altschuler, Florencia
- Gonzalez-Gomez, Raul
- Hernández, Hernán
- Migeot, Joaquín
- Fittipaldi, Sol
- Medel, Vicente
- Maito, Marcelo Adrián
- Moguilner, Sebastián
- Cruzat, Josephine
- Farina, Francesca R.
- Reyes, Pablo
- García, Adolfo M.
- Deleglise, Álvaro
- Matallana, Diana L.
- Slachevsky, Andrea
- Behrens, María I.
- Custodio, Nilton
- Cardona, Juan F.
- Barttfeld, Pablo
- Sosa Ortiz, Ana L.
- Pina-Escudero, Stefanie D.
- Takada, Leonel T.
- Possin, Katherine L.
- Hu, Kun
- Lopera, Francisco
- Lawlor, Brian
- Valcour, Victor
- Yokoyama, Jennifer S.
- Miller, Bruce
- Ibañez, Agustin
- Venue
- Nature Aging
- Published
- 2024-12-27
- Volume
- 5
- Issue
- 2
- Pages
- 259-274
- ISSN
- 2662-8465 (ISSN-L)
- PMC
- PMC12010405
- OpenAlex
- W4405829122
- Cited by
- 36
- References
- 48
- Citations by year
- 2026: 12 · 2025: 23 · 2024: 1
- FWCI
- 10.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Aging (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Conicet (submittedVersion, cc-by-nc-sa)
- Funders
- Alzheimer's Association (20-725707, SG-20- 725707)
- Agencia Nacional de Investigación y Desarrollo (15150012, ANID/FONDAP/15150012, 1210195, 1210176, 1220995)
- National Institutes of Health (15150012)
- National Institute on Aging (AG057234, R01 AG21051, 1210176, 1210195, R01AG057234, P01AG019724, R01AG082056, R01AG075775, R01AG083799)
- Fogarty International Center
- Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias (15150012)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Health › Health disparities and outcomes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- structural inequality, economic inequality, Gini coefficient, brain volume, brain connectivity, Alzheimer's disease, frontotemporal lobar degeneration, dementia, aging, hippocampus, Latin America, United States
- MeSH terms
- Aged, Aged, 80 and over, Aging, Alzheimer Disease, Brain, Dementia, Female, Humans, Latin America, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Socioeconomic Factors, United States
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
