An alternative hypothesis to the obesity epidemic: Obesity is due to increased maternal body size, birth size, growth rate, and height

The artificial sweetener Splenda intake promotes changes in expression of c-Fos and NeuN in hypothalamus and hippocampus of rats

BACKGROUND

Obesity is the result of the interaction of multiple variables, including the excessive increase of sugar-sweetened beverages consumption. Diets aimed to treat obesity have suggested the use of artificial sweeteners. However, recent evidence has shown several health deficits after intake of artificial sweeteners, including effects in neuronal activity. Therefore, the influence of artificial sweeteners consumption such as Splenda, on the expression of c-Fos and neuronal nuclear protein (NeuN) in hypothalamus and hippocampus remains to be determined.

OBJECTIVES

We investigated the effects on c-Fos or NeuN expression in hypothalamus and hippocampus of Splenda-treated rats.

METHODS

Splenda was diluted in water (25, 75 or 250 mg/100 mL) and orally given to rats during 2 weeks ad libitum. Next, animals were sacrificed by decapitation and brains were collected for analysis of c-Fos or NeuN immunoreactivity.

RESULTS

Consumption of Splenda provoked an inverted U-shaped dose-effect in c-Fos expression in ventromedial hypothalamic nucleus while similar findings were observed in dentate gyrus of hippocampus. In addition, NeuN immunoreactivity was enhanced in ventromedial hypothalamic nucleus at 25 or 75 mg/100 mL of Splenda intake whereas an opposite effect was observed at 250 mg/100 mL of artificial sweetener consumption. Lastly, NeuN positive neurons were increased in CA2/CA3 fields of hippocampus from Splenda-treated rats (25, 75 or 250 mg/100 mL).

CONCLUSION

Consuming Splenda induced effects in neuronal biomarkers expression. To our knowledge, this study is the first description of the impact of intake Splenda on c-Fos and NeuN immunoreactivity in hypothalamus and hippocampus in rats.

Fighting obesity: Non-pharmacological interventions

The abnormal or excessive fat accumulation that impairs health is one of the criteria that fulfills obesity. According to epidemiological data, obesity has become a worldwide public health problem that in turn would trigger additional pathologies such as cardiorespiratory dysfunctions, cancer, gastrointestinal disturbances, depression, sleep disorders, just to mention a few. Then, the search for a therapeutical intervention aimed to prevent and manage obesity has been the focus of study during the last years. As one can assume, the increased prevalence of obesity has translated to search of efficient pharmaceuticals designed to manage this health issue. However, to further complicate the scenario, scientific literature has described that obesity is the result of interaction between multiple events. Therefore, pharmacological approaches have faced a serious challenge for develop the adequate treatment. Here, we argue that a wide range of non-pharmacological/invasive techniques can be used to manage obesity, such as diets, cognitive behavioral interventions, exercise and transcranial direct current stimulation. Combining these techniques may allow improving quality of life of obese patients.

The four-compartment model of body composition in obese Chilean schoolchildren, by pubertal stage: comparison with simpler models

OBJECTIVES

We assessed the agreement of body fat and fat-free mass measured by simpler methods against the four-compartment model (4C).

METHODS

In 60 obese schoolchildren (body mass index ≥95th percentile) between the ages of 8 and 13 y who were recruited from one school in Chile, multicompartmental body composition was estimated with the use of isotopic dilution, plethysmography (BodPod), radiographic absorptiometry (DEXA), and anthropometric equations. These results were compared to those of the 4C model, which is considered the gold standard.

RESULTS

For body fat, the 4C model showed the best agreement with DEXA for boys in Tanner stages I and II (r = 0.971) and with isotopic dilution for boys in Tanner stages III and IV (r = 0.984). The best agreement in girls occurred with isotopic dilution, regardless of pubertal stage (r = 0.948 for Tanner stages I and II; r = 0.978 for Tanner stages III and IV). Both isotopic dilution and the Huang, Ellis, and Deurenberg anthropometric equations underestimated body fat in boys; by contrast, DEXA, BodPod, and the Slaughter equation overestimated body fat in boys. All of the equations underestimated body fat in girls. For fat-free mass in both boys and girls, the 4C model showed the best agreement with isotopic dilution, regardless of pubertal stage. The Huang equation showed the best agreement for boys (r = 0.730 for Tanner stages I and II; r = 0.695 for Tanner stages III and IV) and for girls in Tanner stages I and II (r = 0.884). The Ellis equation had the best agreement for girls in Tanner stages III and IV (r = 0.917).

CONCLUSIONS

For obese Chilean children of both sexes, isotopic dilution and DEXA were the two-compartment methods that had the best agreement with the gold-standard 4C model for both body fat and fat-free mass; these were followed by the Huang and Ellis anthropometric equations.

Can weight-related health risk be more accurately assessed by BMI, or by gender specific calculations of Percentage Body Fatness?

The problem of obesity over the last 10 years has consistently been referred to as a 'global epidemic'. The Body Mass Index (BMI) is the currently accepted measure for classifying weight-related risk, but is a crude measure that has not changed in 150 years. It is recognised as having significant limitations, largely due to its lack of distinction between fat and muscle tissue. As the health risks of obesity are linked to the fat content of the body, a more accurate method of classifying would be Percentage Body Fatness (PBF). Although skinfold thickness analysis is recognised as a valid and accurate estimate of PBF in field studies, this method is not routinely used in clinical practice. Using data collected from young adults in the United Kingdom, we compared classifications (underweight, normal weight, overweight and obese) using BMI, with classifications using estimated PBF (from skinfold thickness analysis). We identified disparity between these two methods in approximately 1/3 of participants. BMI correctly classified 66.5% of females and 62.7% of males, with different gender profiles of incorrect classification. Regression analysis was conducted using estimated PBF (by skinfold thickness analysis) as the dependent variable, with explanatory variables of age, height, weight, systolic blood pressure, frequency of vigorous exercise and grip strength. The resulting gender-specific formulae derived from this regression analysis provides a regression R(2) of around 65%, and improved correct classifications to 74% for females and 76% for males. This represents an average improvement of roughly ten percentage points over BMI (male: 7.2% points; female: 13.4% points). We hypothesise that the presented formulae provide gender-specific calculations of PBF, which result in a more accurate indicator of weight-related health risk, compared with BMI in this population. This provides a new approach to an increasingly important clinical issue. These formulae use data that can be easily, quickly and cost-effectively measured in a practice setting. If shown to be repeatable with larger and more diverse populations, the PBF formulae could provide an alternative to the BMI as the major indicator of body-composition related health risk. This would ensure resources are targeted more appropriately and efficiently.