In Mexico, the increase in childhood obesity is alarming. Thus, improving the precision of its diagnosis is expected to impact on disease prevention. We estimated obesity prevalence by bioimpedance–based percent body fat (%BF) and body mass index (BMI) in 1061 girls and 1121 boys, from 3 to 17 years old. Multiple regressions and area under receiver operating curves (AUC) were used to determine the predictive value of BMI on %BF and percentile curves were constructed. Overall obesity prevalence estimated by %BF was 43.7%, and by BMI it was 20.1%; it means that the diagnosis by BMI underestimated around 50% of children diagnosed with obesity by %BF (≥30% for girls, ≥25% for boys). The fat mass excess is further underestimated in boys than in girls when using the standard BMI classification. The relationship between %BF and BMI was strong in school children and adolescents (all cases R²>0.70), but not in preschool children (girls R² = 0.57, boys R² = 0.23). AUCs showed greater discriminative power of BMI to detect %BF obesity in school children and adolescents (all cases AUC≥0.90) than in preschool children (girls AUC = 0.86; boys AUC = 0.70). Growth percentile charts showed that girls aged 9–17 years and boys aged 8–17 years presented fat excess from the 50^th percentile and above. We suggested to change the BMI cut-off for them, considering values at the 75^th percentile as overweight, and values at the 85^th percentile as obesity, as previously recommended for Mexican children. Improving obesity diagnosis will allow greater efficiency when searching for comorbidities in clinical practice.

We investigated population and social structure of the franciscana dolphin, Pontoporia blainvillei, an endemic and the most endangered cetacean of the southwestern Atlantic Ocean. We analyzed samples from the Rio de la Plata estuary obtained in Uruguayan waters and from the Atlantic Ocean obtained in both Uruguayan and Brazilian waters. Mitochondrial and microsatellite DNA markers were used to study differentiation between the estuary and the ocean and the association between kinship and social group structure. Although multilocus analyses suggested that franciscanas are structured into 2 subpopulations (K = 2, divergence among clusters: F_ST = 0.06, P = 0.002; R_ST = 0.3, P = 0.001), mitochondrial markers did not support such divergence (F_ST = 0.02, P = 0.12; Ф_ST = 0.06, P =0.06). However, these units are not entirely segregated geographically. Regarding social structure, some groups are composed by first-order related individuals (R ≥ 0.5, P < 0.5). Overall, the data suggest that matrilines could be the social unit in this species. We argue that the divergence found could be associated to local adaptation and social structure, resulting from either feature leading to a recent divergence or reflecting equilibrium between local differentiation and gene flow. This evidence supports considering franciscanas from the Rio de la Plata estuary a discrete management unit.

Population differentiation in environments without well-defined geographical barriers represents a challenge for wildlife management. Based on a comprehensive database of individual sighting records (1988–2009) of blue whales from the winter/calving Gulf of California, we assessed the fine-scale genetic and spatial structure of the population using individual-based approaches. Skin samples of 187 individuals were analyzed for nine microsatellite loci. A single population with no divergence among years and months and no isolation by distance (Rxy = 0.1–0.001, p>0.05) were found. We ran two Bayesian clustering methods using Structure and Geneland softwares in two different ways: 1) a general analysis including all individuals in which a single cluster was identified with both softwares; 2) a specific analysis of females only in which two main clusters (Loreto Bay and northern areas, and San Jose-La Paz Bay area) were revealed by Geneland program. This study provides information indicating that blue whales wintering in the Gulf of California are part of a single population unit and showed a fine-scale structure among females, possibly associated with their high site fidelity, particularly when attending calves. It is likely that the loss of genetic variation is minimized by male mediated gene flow, which may reduce the genetic drift effect. Opportunities for kin selection may also influence calf survival and, in consequence, have a positive impact on population demography in this small and endangered population.

Background: Childhood obesity is a major health problem in Mexico. Obesity prevalence estimated by body mass index (BMI) is almost half than that estimated by percent body fat (%BF) in the Childhood Obesity pediatric cohort (COIPIS). Objective. We performed a genome-wide association study (GWAS) of BMI and %BF in 828 children from the COIPIS to identify markers of predisposition to high values for both phenotypes used for obesity classification. Methods: For the GWAS we used the LAT Axiom 1, Affymetrix and 2.5 million single loci from the 1000 Genomes Phase 3 imputation panel. We used a linear model, adjusted by age, sex, and Amerindian ancestry assuming an additive inheritance model. Results. Genome-wide significance (p ≤ 5.0 × 10⁻⁸) and 80% of statistical power was reached for associations of two loci in two genes (CERS3 and CYP2E1) to BMI. Also, 11 loci in six genes (ANKS1B, ARNTL2, KCNS3, LMNB1, SRGAP3, TRPC7) reached genome-wide significance for associations to %BF, though not 80% of statistical power. Discussion: None of the SNPs were previously reported as being associated to BMI or %BF. In addition, different loci were found for BMI and %BF. These results highlight the importance of gaining deeper understanding of genetic markers of predisposition to high values for the phenotypes used for obesity diagnosis.

In Mexico, the genetic mechanisms underlying childhood obesity are poorly known. We evaluated the effect of loci, known to be associated with childhood body mass index (BMI) in Europeans, in Mexican children from different ethnic groups. We performed linear and logistic analyses of BMI and obesity, respectively, in Mestizos and Amerindians (Seris, Yaquis and Nahuatl speakers) from Northern (n = 369) and Central Mexico (n = 8545). We used linear models to understand the effect of degree of Amerindian ancestry (AMA) and genetic risk score (GRS) on BMI z-score. Northern Mexican Mestizos showed the highest overweight-obesity prevalence (47.4%), followed by Seri (36.2%) and Central Mexican (31.5%) children. Eleven loci (SEC16B/rs543874, OLFM4/rs12429545/rs9568856, FTO/rs9939609, MC4R/rs6567160, GNPDA2/rs13130484, FAIM2/rs7132908, FAM120AOS/rs944990, LMX1B/rs3829849, ADAM23/rs13387838, HOXB5/rs9299) were associated with BMI and seven (SEC16B/rs543874, OLFM4/rs12429545/rs9568856, FTO/rs9939609, MC4R/rs6567160, GNPDA2 rs13130484, LMX1B/rs3829849) were associated with obesity in Central Mexican children. One SNP was associated with obesity in Northern Mexicans and Yaquis (SEC16B/rs543874). We found higher BMI z-score at higher GRS (β = 0.11, p = 0.2 × 10⁻¹⁶) and at lower AMA (β = −0.05, p = 6.8 × 10⁻⁷). The GRS interacts with AMA to increase BMI (β = 0.03, p = 6.08 × 10⁻³). High genetic BMI susceptibility increase the risk of higher BMI, including in Amerindian children.