Skip to main content
Dryad logo

Tsimane physiological dysregulation data

Citation

Kraft, Thomas et al. (2020), Tsimane physiological dysregulation data, Dryad, Dataset, https://doi.org/10.25349/D9NS4W

Abstract

Humans have the longest post-reproductive lifespans and lowest rates of actuarial aging among primates. Understanding the links between slow actuarial aging and physiological change is critical for improving the human “healthspan”. Physiological dysregulation may be a key feature of aging in industrialized populations with high burdens of chronic “diseases of civilization”, but little is known about age trajectories of physiological condition in subsistence populations with limited access to public health infrastructure. To better characterize human physiological dysregulation, we examined age trajectories of 40 biomarkers spanning the immune (n=13 biomarkers), cardiometabolic (n=14), musculoskeletal (n=6), and other (n=7) systems among Tsimane forager-horticulturalists of the Bolivian Amazon using mixed cross-sectional and longitudinal data (n=22,115 observations). We characterized age-related changes using a multi-system statistical index of physiological dysregulation (Mahalanobis distance; Dm) that increases with age in both humans and other primates. Although individual biomarkers showed varied age-profiles, we found a robust increase in age-related dysregulation for Tsimane (β=0.17-0.18) that was marginally faster than that reported for an industrialized Western sample (β=0.14-0.16), but slower than that of other non-human primates. We found minimal sex differences in the pace or average level of dysregulation for Tsimane. Our findings highlight some conserved patterns of physiological dysregulation in humans, consistent with the notion that somatic aging exhibits species-typical patterns, despite cross-cultural variation in environmental exposures, lifestyles and mortality.

Methods

Data collection methods are detailed in the associated paper. The data here are pre-processed analysis data that can be used to reproduce the main analyses of the paper.

Usage Notes

For details, see the metadata file "Metadata_for_Dm_dat.docx".

Funding

NIH/NIA, Award: RF1AG054442; R01AG024119

NSF, Award: BCS0136274, BCS0422690