Age-related variation in red blood cell stable isotope ratios (delta13C and delta15N) from two Yupik villages in southwest Alaska: a pilot study

Abstract

Objectives. A significant fraction of the Alaska Native population appears to be shifting from a primarily subsistence-based diet to a market-based diet; therefore, the ability to link diet pattern to disease risk has become increasingly important to predicting public health needs. Our research aims to develop the use of stable isotope ratios as diet pattern biomarkers, based on naturally-occurring isotopic differences in the elemental composition of subsistence and non-subsistence foods. These differences are reflected in human blood, hair and fingernail isotope signatures.Study Design. In this preliminary study, we investigate the potential for 13C and 15N to serve as dietary biomarkers for age-related dietary differences in a subset of participants involved with a long-term study initiated by the Center for Alaska Native Health Research (CANHR) at the University of Alaska Fairbanks (UAF).Methods. We measured delta13C and delta15N in red blood cells collected from 12 “elder” participants (age 60+ yrs) and 14 younger participants (age 14–19 yrs). Samples were evenly divided between males and females, and between two villages sampled in 2004. We also sampled market and subsistence foods in Fairbanks, AK, as an indicator of the isotopic differences likely to be observed in village foods.Results. Elders were significantly enriched in 15N, but depleted in 13C, relative to younger participants. These differences are consistent with increased intake of marine subsistence in elders, and of certain market foods in younger participants. However, elders were considerably more variable in delta15N, suggesting greater differences among individuals in their usual intake.Conclusions. Overall we find that RBC stable isotope signatures exhibit variation consistent with previously documented dietary patterns in Alaska Natives, and we describe future directions for developing these biomarkers for diet pattern monitoring.