Variations in human body water isotope composition across the United States

Accurate human provenancing using stable isotopes depends directly on solid understandings of the geographic and individual factors affecting isotope variability and incorporation into human tissues. Transfer of isotopic, and therefore spatial, information between environmental water and biological tissues is mediated by the isotopic composition of body water. Thus, there is a need to study body water isotope ratios at a population level and over a large isotopic and geographic range. We evaluated oxygen (δ¹⁸O_bw) and hydrogen (δ²H_bw) isotope values of body water from 72 volunteers in 10 different cities across the US, and over a 5-10-day period. We analyzed covariates (e.g., water intake, physical activity, biometrics, gender) that might explain individual stable isotope ratio variations and tested a predictive model that incorporates the δ-values of drinking water, food, and O₂ as well as individual variables to predict the δ-values of body water. The individual variability in body water isotope values overtime (mean 0.3‰ for δ¹⁸O_bw and 2.3‰ for δ²H_bw) was lower than the intra-city variability (mean 0.9‰ for δ¹⁸O_bw and 6.9‰ for δ²H_bw). Body water isotope values differed among cities (ANOVA: δ¹⁸O_bwF = 97.2, p < 0.001; δ²H_bwF = 176.2, p < 0.001). However, significant overlap among some cities with different drinking water was discovered. We detected significant covariation of measured drinking water and human body water isotope values (both isotope systems R² ≥ 0.89, p < 0.001) and small but significant effects of the average daily exercise and amount of fluid intake. The differences between measured and model-predicted body water values (mean 0.12 ± 1.2‰ for Δδ¹⁸O and -1.2 ± 8.2‰ for Δδ²H) were statistically indistinguishable from zero (Δδ¹⁸O t = -0.751, p = 0.45; Δδ²H t = 1.133, p = 0.26). Here we show that community level variation exists in the δ¹⁸O_bw and δ²H_bw values and the primary drivers are the regional differences in drinking water isotopes. Consistency of the body water isotope composition over the study period suggests that tissues would incorporate a stable isotope signal over time. The amount of drinking water and physical activity influence body water values, while the variation in the isotopic values of food may contribute to regional level variability, but that still remains to be assessed further. The human body water model provides accurate estimates for measured values, capturing and reproducing the main features of the body water isotope variation across space.

Bioimpedance Guided Fluid Management in Peritoneal Dialysis: A Randomized Controlled Trial

BACKGROUND AND OBJECTIVES

Bioelectrical impedance analysis (BIA) devices can help assess volume overload in patients receiving maintenance peritoneal dialysis. However, the effects of BIA on the short-term hard end points of peritoneal dialysis lack consistency. This study aimed to test whether BIA-guided fluid management could improve short-term outcomes in patients on peritoneal dialysis.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A single-center, open-labeled, randomized, controlled trial was conducted. Patients on prevalent peritoneal dialysis with volume overload were recruited from July 1, 2013 to March 30, 2014 and followed for 1 year in the initial protocol. All participants with volume overload were 1:1 randomized to the BIA-guided arm (BIA and traditional clinical methods) and control arm (only traditional clinical methods). The primary end point was all-cause mortality and secondary end points were cardiovascular disease mortality and technique survival.

RESULTS

A total of 240 patients (mean age, 49 years; men, 51%; diabetic, 21%, 120 per group) were enrolled. After 1-year follow-up, 11(5%) patients died (three in BIA versus eight in control) and 21 patients were permanently transferred to hemodialysis (eight in BIA versus 13 in control). The rate of extracellular water/total body water decline in the BIA group was significantly higher than that in the control group. The 1-year patient survival rates were 96% and 92% in BIA and control groups, respectively. No significant statistical differences were found between patients randomized to the BIA-guided or control arm in terms of patient survival, cardiovascular disease mortality, and technique survival (P>0.05).

CONCLUSIONS

Although BIA-guided fluid management improved the fluid overload status better than the traditional clinical method, no significant effect was found on 1-year patient survival and technique survival in patients on peritoneal dialysis.