Dataset Information

The clinical biochemistry of obesity.

ABSTRACT: Obesity is essentially an excessive accumulation of triacylglycerols in fatty tissue that is the net result of excessive energy intake compared to energy usage. Severe forms of the disease are most likely to have a predominantly genetic basis and this is probably polygenic. The 'thrifty gene' hypothesis also describes the disturbance that a modern environment, including higher energy intake and decreased physical activity, has on otherwise advantageous genetic variations. While the physical consequences of obesity, such as arthritis, are debilitating and costly, the metabolic consequences are the drivers behind the modern epidemics of insulin resistance, diabetes, fatty liver disease, coronary artery disease, hypertension and polycystic ovary syndrome. The pathophysiological mechanisms behind these diseases are probably a combination of the toxic metabolic effects of free fatty acids and adipokines - the numerous messengers that adipose tissue has been discovered to produce.

SUBMITTER: Sikaris KA

PROVIDER: S-EPMC1880830 | biostudies-literature | 2004 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The clinical biochemistry of obesity.

Sikaris Ken A KA

The Clinical biochemist. Reviews 20040801 3

Obesity is essentially an excessive accumulation of triacylglycerols in fatty tissue that is the net result of excessive energy intake compared to energy usage. Severe forms of the disease are most likely to have a predominantly genetic basis and this is probably polygenic. The 'thrifty gene' hypothesis also describes the disturbance that a modern environment, including higher energy intake and decreased physical activity, has on otherwise advantageous genetic variations. While the physical cons ...[more]

PMID: 18458706

Similar Datasets

Project description:BackgroundReference intervals are assessment tools for interpretation of clinical test results. These intervals describe the dispersion of test parameter values of apparently healthy persons in defined populations as health status indicators. Using reference intervals obtained and validated in populations outside the geographical region of derivation for medical decision-making may impact negatively on clinical interpretation and patient management. Many countries have established their reference values, current studies on these data for Nigeria are however scarce. Determination of clinical biochemistry reference intervals for young Nigerian adults which is of particular importance in routine clinical management and conduct of clinical trials in response to existing and emerging diseases will add significantly to the existing body of knowledge.ObjectiveThe objective was to establish reference intervals for 24biochemistry analytes among Nigerians aged 18 to 26 years.MethodsThis was a cross-sectional study among 7,797 consenting male and female military applicants aged 18 to 26 years from 37 States of Nigeria. It was a total study among volunteers for military service. Blood samples were collected and subjected to serological testing for HIV-1 and 2, hepatitis-B, malaria, pregnancy and haematuria to restrict our study population to apparently healthy participants. Biochemical assays were performed on 6,169 participant samples that met the inclusion criteria. Generated data was entered into MS Excel® and exported into SPSS® software version 16 for analysis. Statistical tools used were frequencies, median, mid 95th percentile range with 2.5th and 97.5th percentiles as limits. Reference intervals were estimated using nonparametric methods. No intergender statistical comparison was made.ResultsComplete records were obtained for 6,169 eligible participants. Median values and associated reference intervals were similar in both genders.ConclusionThe findings from this study will help in clinical decision-making and play a significant role in supporting the current global rapid expansion of clinical trials in response to the urgent need for preventive and therapeutic solutions to existing and emerging diseases.

Dataset Information

The clinical biochemistry of obesity.

Publications

The clinical biochemistry of obesity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets