Developing a risk assessment tool for identifying individuals at high risk for developing insulin resistance in European adolescents: the HELENA-IR score.

OBJECTIVES: To develop and validate an easy-to-use screening tool for identifying adolescents at high-risk for insulin resistance (IR). METHODS: Α total of 1,053 adolescents (554 females), aged 12.5 to 17.5 years with complete data on glucose and insulin levels were included. Body mass index (BMI), fat mass index (FMI) and the homeostasis model assessment for insulin resistance (HOMA-IR) were calculated. VO2max was predicted using 20 m multi-stage fitness test. The population was randomly separated into two cohorts for the development (n=702) and validation (n=351) of the index, respectively. Factors associated with high HOMA-IR were identified by Spearman correlation in the development cohort; multiple logistic regression was performed for all identified independent factors to develop a score index. Finally, receiver operating characteristic (ROC) analysis was performed in the validation cohort and was used to define the cut-off values that could identify adolescents above the 75th and the 95th percentile for HOMA-IR. RESULTS: BMI and VO2max significantly identified high HOMA-IR in males; and FMI, TV watching and VO2max in females. The HELENA-IR index scores range from 0 to 29 for males and 0 to 43 for females. The Area Under the Curve, sensitivity and specificity for identifying males above the 75th and 95th of HOMA-IR percentiles were 0.635 (95%CI: 0.542-0.725), 0.513 and 0.735, and 0.714 (95%CI: 0.499-0.728), 0.625 and 0.905, respectively. For females, the corresponding values were 0.632 (95%CI: 0.538-0.725), 0.568 and 0.652, and 0.708 (95%CI: 0.559-0.725), 0.667 and 0.617, respectively. Simple algorithms were created using the index cut-off scores. CONCLUSIONS: Paediatricians or physical education teachers can use easy-to-obtain and non-invasive measures to apply the HELENA-IR score and identify adolescents at high risk for IR, who should be referred for further tests.

Towards a Semi-Automatic Early Warning System for Vector-Borne Diseases.

The emergence and spread of vector-borne diseases (VBDs) is a function of biotic, abiotic and socio-economic drivers of disease while their economic and societal burden depends upon a number of time-varying factors. This work is concerned with the development of an early warning system that can act as a predictive tool for public health preparedness and response. We employ a host-vector model that combines entomological (mosquito data), social (immigration rate, demographic data), environmental (temperature) and geographical data (risk areas). The output consists of appropriate maps depicting suitable risk measures such as the basic reproduction number, R0, and the probability of getting infected by the disease. These tools consist of the backbone of a semi-automatic early warning system tool which can potentially aid the monitoring and control of VBDs in different settings. In addition, it can be used for optimizing the cost-effectiveness of distinct control measures and the integration of open geospatial and climatological data. The R code used to generate the risk indicators and the corresponding spatial maps along with the data is made available.

Cardiorespiratory fitness is associated with body composition and insulin resistance in European adolescents: HELENA study.

BACKGROUND: The present study aimed to examine the independent association between cardiorespiratory fitness, sedentary time and insulin resistance in European adolescents. METHODS: A subset (N.=1097) of a large multicenter European study (HELENA-CSS study) was used in the present study. Serum concentrations of glucose (GF) and insulin (IF) were measured after overnight fast and homeostasis model assessment (HOMA-IR) was calculated. Sedentary time and time spent on moderate-to-vigorous physical activity (MVPA) was objectively measured by accelerometers. Moreover, sedentary activities were self-reported via questionnaires. RESULTS: Multilevel linear regression analysis revealed that adolescents watching TV≥2 h/day had higher HOMA-IR (P=0.007). Further adjustment for MVPA, showed that watching TV≥2 h/day remained significantly associated with IR (P=0.002). In this model, MVPA was inversely associated with HOMA-IR (P=0.001). Further controlling for waist circumference showed that adolescents watching TV≥2 h/day continued to have higher HOMA-IR levels (P=0.002). Stratified analysis by weight status, revealed that watching TV≥2 h/day was independently associated with HOMA-IR only in normal weight adolescents, while MVPA was inversely associated with HOMA-IR in both overweight/obese and normal weight adolescents. Only the volume of maximum oxygen consumption (VO2max) over body fat mass ratio was inversely associated with HOMA-IR after controlling for several confounders. CONCLUSIONS: The present study showed that watching TV≥2 h/day and MVPA were associated with HOMA-IR. However, after controlling for several confounders, only VO2max/body fat mass ratio remained negatively associated with HOMA-IR. Future interventions should aim both to promote physical activity and reduce sedentary time in adolescents to improve their cardiorespiratory fitness and postpone the onset of diabetes in adulthood.

Elucidating fitness components of the invasive dermestid beetle Trogoderma granarium combining deterministic and stochastic demography.

The invasive dermestid khapra beetle, Trogoderma granarium, is an important pest of stored products that is subject to strict phytosanitary measures. In this study, we conducted a demographic analysis of this species at 30, 35 and 40°C, combining deterministic and stochastic approaches. The net reproductive rate, the intrinsic rate of increase, the finite rate of increase and the doubling time did not differ significantly between 30 and 35°C, while at 40°C we detected negative values of the intrinsic rate of increase and the doubling time. The Briere model fit the data well with respect to the intrinsic rate of increase. Females of roughly 63, 42 and 21 days old reached their maximum reproductive potential at 30, 35 and 40°C, respectively. The stochastic models of this study allowed for checking model fit and the characterization of the most suitable distribution for each component of the process. We expect these results to have bearing on the management of T. granarium since they could be combined with models related to international trade and climatic change, alerting specialists towards early detection strategies against this species.