AnthropoAge, a novel approach to integrate body composition into the estimation of biological age

Aging is believed to occur across multiple domains, one of which is body composition; however, attempts to integrate it into biological age (BA) have been limited. Here, we consider the sex-dependent role of anthropometry for the prediction of 10-year all-cause mortality using data from 18,794 NHANES participants to generate and validate a new BA metric. Our data-driven approach pointed to sex-specific contributors for BA estimation: WHtR, arm and thigh circumferences for men; weight, WHtR, thigh circumference, subscapular and triceps skinfolds for women. We used these measurements to generate AnthropoAge, which predicted all-cause mortality (AUROC 0.876, 95%CI 0.864-0.887) and cause-specific mortality independently of ethnicity, sex, and comorbidities; AnthropoAge was a better predictor than PhenoAge for cerebrovascular, Alzheimer, and COPD mortality. A metric of age acceleration was also derived and used to assess sexual dimorphisms linked to accelerated aging, where women had an increase in overall body mass plus an important subcutaneous to visceral fat redistribution, and men displayed a marked decrease in fat and muscle mass. Finally, we showed that consideration of multiple BA metrics may identify unique aging trajectories with increased mortality (HR for multidomain acceleration 2.43, 95%CI 2.25-2.62) and comorbidity profiles. A simplified version of AnthropoAge (S-AnthropoAge) was generated using only BMI and WHtR, all results were preserved using this metric. In conclusion, AnthropoAge is a useful proxy of BA that captures cause-specific mortality and sex dimorphisms in body composition, and it could be used for future multidomain assessments of aging to better characterize the heterogeneity of this phenomenon.

Association of estimated glucose disposal rate and chronic diabetic complications in patients with type 1 diabetes

Introduction

The role of insulin resistance in diabetic chronic complications among individuals with type 1 diabetes (T1D) has not been clearly defined. The aim of this study was to examine the performance of insulin resistance, evaluated using the estimated glucose disposal rate (eGDR) for the identification of metabolic syndrome (MS) and diabetic chronic complications.

Methods

Cross‐sectional study in a tertiary care centre. We included patients of 18 years and older, with at least 6 months of T1D duration. Anthropometric, clinical and biochemical data were collected.

Results

Seventy patients, 41 (58.6%) women, with a median age of 36.6 years (range 18–65). Mean age of onset and duration of diabetes was 13.5 ± 6.5 and 23.6 ± 12.2 years, respectively. Twenty‐one (30%) patients met the metabolic syndrome (MS) criteria. Patients with MS had lower eGDR compared to patients without (5.17 [3.10–8.65] vs. 8.86 [6.82–9.85] mg/kg/min, respectively, p = .003). Median eGDR in patients with nephropathy, retinopathy and neuropathy compared with those without was 6.75 (4.60–8.20) versus 9.53 (8.57–10.3); p < .001, 6.45 (4.60–7.09) versus 9.50 (8.60–10.14); p < .001, 5.56 (4.51–6.81) versus 9.49 [8.19–10.26] mg/kg/min; p < .001, respectively. The eGDR showed an area under the curve of 0.909, 0.879, 0.897 and 0.836 for the discrimination of MS, retinopathy, neuropathy and nephropathy, respectively.

Conclusions

Patients with T1D diabetic complications have higher insulin resistance. The eGDR discriminates patients with chronic diabetic complications and MS. While more ethnic‐specific studies are required, this study suggests the possibility to incorporate eGDR into routine diabetes care.

Mapping the Spatial Distribution of Conotrachelus psidii (Coleoptera: Curculionidae): Factors Associated with the Aggregation of Damage

The guava weevil, Conotrachelus psidii Marshall, is one of the key pest species of Psidium guajava L. fruit in Colombia. Adults that emerge after completing development on the ground attack the guava fruits in some areas of the crop more than in others. During development, the weevil spends 3-6 months in the soil, suggesting that edaphoclimatic factors may influence its biology, and hence, the spatial distribution and damage pattern caused by weevils within the guava orchard. Understanding this pattern allows specific control practices to be used at crop sites. The trials were performed in a commercial orchard of 3.5 ha. Samples of damaged fruits were taken from each tree, and edaphoclimatic variables such as soil moisture, mechanical resistance, apparent density, texture, precipitation, solar radiation, temperature, and relative humidity were recorded. The data were analyzed using the basic stages of a geostatistical analysis. The findings indicate that the highest numbers of damaged fruits were correlated with areas within the surveyed field where the soil moisture ranged between 27 and 34% in rainy seasons and where the clay content was less than 30% and the silt content was 42% of the surveyed field. A linear model of the infestation was obtained, associated with the climatic variables that determine the environmental conditions and can favor the development of the weevil populations. With the information obtained, localized and efficient management of the guava weevil can be established.