Back

Reproductive history and cognitive aging: Interactive effects of children and grandchildren in a life history framework

Sanchez, O. R.; Salazar, A. M.; Pedraza, O. L.; Leongomez, J. D.

2026-05-28 evolutionary biology
10.64898/2026.05.26.727926 bioRxiv
Show abstract

Cognitive decline, particularly Alzheimers disease, represents a significant global health concern. While traditional risk factors are well documented, an evolutionary perspective grounded in life history theory offers critical insights into the intergenerational dynamics influencing cognitive aging. This study empirically analyzed the relationship between reproductive history and late-life cognitive performance in women, as measured by the Montreal Cognitive Assessment Colombian version (MOCA-Col). Specifically, we examined the moderating role of the number of grandchildren on the association between parity and cognitive performance. Using an observational, cross-sectional design with a sample of 145 women (mean age = 69.9 years), a cumulative ordinal logistic regression model was fitted to MOCA-Col scores, incorporating age and the interaction between the standardized number of children and grandchildren. A higher number of children was significantly associated with lower odds of being in a better cognitive category ({beta} = -0.869, SE = 0.305, p = 0.0104, OR = 0.42). Crucially, a significant positive interaction between number of children and number of grandchildren was observed ({beta} = 0.354, SE = 0.093, p < 0.001, OR = 1.42), indicating that the negative association between parity and cognition progressively attenuated as the number of grandchildren increased. This evidence supports human life history models and the grandmother hypothesis, suggesting that intergenerational investment may mitigate the cumulative biological costs of reproduction. The findings reflect an evolutionary trade-off between early reproductive effort and later somatic maintenance.

Matching journals

The top 13 journals account for 50% of the predicted probability mass.

1
PLOS ONE
4510 papers in training set
Top 14%
12.8%
2
Scientific Reports
3102 papers in training set
Top 13%
7.0%
3
Aging
69 papers in training set
Top 0.5%
4.1%
4
Epigenetics
43 papers in training set
Top 0.2%
3.7%
5
International Journal of Molecular Sciences
453 papers in training set
Top 2%
3.7%
6
npj Aging
15 papers in training set
Top 0.3%
3.2%
7
The Journals of Gerontology: Series A
25 papers in training set
Top 0.4%
3.2%
8
FEBS Open Bio
29 papers in training set
Top 0.1%
2.8%
9
eLife
5422 papers in training set
Top 32%
2.7%
10
Aging Cell
144 papers in training set
Top 2%
2.4%
11
GeroScience
97 papers in training set
Top 0.7%
2.2%
12
Frontiers in Aging Neuroscience
67 papers in training set
Top 1%
2.1%
13
Frontiers in Psychology
49 papers in training set
Top 0.4%
1.9%
50% of probability mass above
14
Frontiers in Genetics
197 papers in training set
Top 4%
1.8%
15
Frontiers in Ecology and Evolution
60 papers in training set
Top 2%
1.7%
16
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 4%
1.7%
17
Evolution, Medicine, and Public Health
14 papers in training set
Top 0.1%
1.5%
18
Antioxidants
25 papers in training set
Top 0.2%
1.5%
19
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 36%
1.4%
20
Translational Psychiatry
219 papers in training set
Top 3%
1.4%
21
Behavior Genetics
15 papers in training set
Top 0.1%
1.3%
22
Alzheimer's Research & Therapy
52 papers in training set
Top 1%
1.3%
23
Genes
126 papers in training set
Top 2%
1.3%
24
Cells
232 papers in training set
Top 4%
1.1%
25
PLOS Computational Biology
1633 papers in training set
Top 21%
1.0%
26
Journal of Alzheimer's Disease
43 papers in training set
Top 1.0%
1.0%
27
Gene
41 papers in training set
Top 1%
1.0%
28
Human Brain Mapping
295 papers in training set
Top 4%
1.0%
29
Frontiers in Public Health
140 papers in training set
Top 7%
0.9%
30
Biology
43 papers in training set
Top 2%
0.9%