Evidence map›Paper›PMID 37739326›Full record

ReviewNeuroscience and biobehavioral reviews2023

Advancing methods for the biodemography of aging within social contexts.

Raisa Hernández-Pacheco, Ulrich K Steiner, Alexandra G Rosati, Shripad Tuljapurkar

Abstract readReview
In one paragraph

Review in Neuroscience and biobehavioral reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Raisa Hernández-PachecoDepartment of Biological Sciences, California State University, Long Beach, 1250 N Bellflower Blvd, Long Beach, CA 90840-0004, USA. Electronic address: rai.hernandezpacheco@csulb.edu.
Ulrich K SteinerFreie Universität Berlin, Biological Institute, Königin-Luise Str. 1-3, 14195 Berlin, Germany.
Alexandra G RosatiDepartments of Psychology and Anthropology, University of Michigan, 530 Church St, Ann Arbor, MI 48109, USA.
Shripad TuljapurkarStanford University, 327 Campus Dr., Rm 233, Stanford, CA 94305, USA.

Funding

Translational Science InitiativeP40OD012217 · OD · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI CARLOS A SARIOL · 2012 to 2026
$40.4M
Cumulative Life Course Effects on Aging and Health in a Long-Lived Primate ModelR37AG049395 · NIA · UNIVERSITY OF NEW MEXICO · PI Elizabeth Vinson Lonsdorf, Melissa Emery Thompson · 2022 to 2026
$3.2M
Research Network on Animal Models to Understand Social Dimensions of AgingR24AG065172 · NIA · UNIVERSITY OF MINNESOTA · PI Susan C. Alberts, Alessandro Bartolomucci · 2020 to 2026
$2.6M
Modeling Health Histories and the Dynamics of Social Inequality in a Nonhuman Primate PopulationR21AG072285 · NIA · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI HERNANDEZ PACHECO, RAISA, ROSATI, ALEXANDRA G · 2022 to 2023
$391k
NIA NIH HHS R21 AG072285NIA NIH HHS R24 AG065172NIA NIH HHS R37 AG049395NIH HHS P40 OD012217
6 · The paper itself

Abstract

Several social dimensions including social integration, status, early-life adversity, and their interactions across the life course can predict health, reproduction, and mortality in humans. Accordingly, the social environment plays a fundamental role in the emergence of phenotypes driving the evolution of aging. Recent work placing human social gradients on a biological continuum with other species provides a useful evolutionary context for aging questions, but there is still a need for a unified evolutionary framework linking health and aging within social contexts. Here, we summarize current challenges to understand the role of the social environment in human life courses. Next, we review recent advances in comparative biodemography and propose a biodemographic perspective to address socially driven health phenotype distributions and their evolutionary consequences using a nonhuman primate population. This new comparative approach uses evolutionary demography to address the joint dynamics of populations, social dimensions, phenotypes, and life history parameters. The long-term goal is to advance our understanding of the link between individual social environments, population-level outcomes, and the evolution of aging.

Indexed as

AgingSocial EnvironmentAnimalsHumansAnimal modelsBiodemographyCayo SantiagoIntegral projection modelsMulti-state modelsNonhuman primatesRhesus macaquesSocial dimensions

Identifiers

PMID37739326
PMCPMC10591901

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.