Volume 6, Issue 1

  • 2019, August

    systematic review

    The Role of Genetics in the Pathophysiology of Obesity: A Systematic ReviewOpen Access

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    Abstract [+]

    Aim

    The obesity epidemic has been largely attributed to changes in lifestyle habits established over the past three decades. These changes are mainly attributed to excessive nutrition and decline in physical activity as well as additional factors such as reduced intestinal microbiota diversity, sleep duration, endocrine disruptors, and reduced variability of the ambient temperature. However, the obesogenic environment is not sufficient to determine the presence of obesity, it is necessary that the lifestyle becomes associated with a personal predisposition for the phenotype to emerge. In this article, we review the main forms of monogenic and syndromic obesity, as well as a historical summary of the search for the genes that add up to confer greater risk for the development of polygenic obesity.

    Methods

    We carried out a PubMed search, along with ExcerptaMedica database (EMBASE)/Cochrane library, Web Sciences for the Medical Subject Headings (MeSH) terms “obesity’’ AND “genetics” for the past 5-years.

    Results

    We found a total of 14057 articles pertaining to obesity and genetics together of which we selected 92 articles for this review after getting articles after searching cross references.

    Conclusion

    Studies with twins and adopted children show that 55 to 80% of the variation of body mass index (BMI) is attributed to genetic factors. According to the genetic criteria, obesity can be classified as A) Monogenic – when a mutated gene is responsible for the phenotype; B) Syndromic – when a set of specific symptoms are present and a small group of genes is involved; usually the term is used to describe obese patients with cognitive delay, dysmorphic features, organ-specific abnormalities, hyperphagia, and/or other signs of hypothalamic dysfunction; C) Polygenic – also called “common” obesity, present in up to 95% of cases. Many genes add up to give a greater risk to the individual, and if associated with some habits culminates in obesity. In spite of its great relevance, the search for the genes that raise the risk of obesity has not been easy. It is still a challenge for the scientific community to separate the genetic element from the environmental component in the etiology of this disease. Individuals more susceptible to excessive adiposity may carry risk variants in the genes that influence appetite control, the regulation of cellular machinery, lipid metabolism and adipogenesis, the energy expenditure, insulin signaling, and inflammation.

    Keywords

    Obesity; Genetics; Polygenic; Monogenic; Syndromic; Polymorphism.


  • 2019, September

    original research

    Relationships between Sleep, Sedentary Behavior, and Physical Activity in Young AdultsOpen Access

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    Abstract [+]

    Purpose

    While there are some studies on sleep and physical activity, little is known regarding the associations between sleep and sedentary behavior. This study investigated the associations between sleep, sedentary behavior, and physical activity among young adults.

    Methods

    Cross-sectional data from 124 undergraduate students were included in the analysis (age=21±1 years). Both accelerometer-based and self-report assessments of sleep were included; physical activity and sedentary behavior were assessed by accelerometers. Participants were asked to fill out sleep questionnaires and wear accelerometers for 7 days. Pearson correlations, partial correlations, and analysis of covariance (ANCOVA) analyses were performed to investigate the relationships between sleep, sedentary behavior, and physical activity.

    Results

    After adjusting for age, gender, percent body fat, educational level, and monthly allowance, prolonged sedentary time was correlated with a shorter sleep onset latency (r=-0.19, p=0.04), shorter time in bed (r=-0.43, p<0.001), and shorter sleep duration (r=-0.38, p<0.001). Moderate-to-vigorous physical activity (MVPA) was positively correlated with sleep onset latency (r=0.43, p<0.001). Sedentary behavior and MVPA were not correlated with sleep quality or daytime sleepiness. After further categorizing sleep duration into three subgroups, individuals with ≤6 hours (p<0.001) of sleep spent more time being sedentary than did those with 6-7 hours (p<0.001) and ≥7 hours (p=0.007) of sleep. Individuals with 6-7 hours of sleep had a higher level of MVPA than did those with ≥7 hours of sleep.

    Conclusion

    Improving the duration of sleep may be a viable approach to help reduce sedentary behavior among young adults. Future studies with longitudinal designs are needed to further investigate the directionality of these associations and their potential mediators and moderators.

    Keywords

    Accelerometer; Sleep; Sedentary; Physical activity.