. Given that well-being and BMI can be explained only by multiple factors, the interaction of several nutritional and lifestylefactors had to be considered for significant effects. The variables included nutrition, physical activity, social contacts and sleeping behavior. Therefore a general linear model (multifactorial univariate analysis of variance) for “well-being” and “BMI” was used. The significance level for all analyses was set at p<0.05. Analyses were performed with SPSS ver. 20 (IBM). Results The questionnaire was completed by 500 adolescents and young adults
, 270–286 http://dx.doi.org/10.1089/met.2006.4.270  Wilsgaard T., Jacobsen B.K., Lifestylefactors and incident metabolic syndrome The Tromso Study 1979–2001, Diabetes Research and Clinical Practice, 2007, 78, 217–224 http://dx.doi.org/10.1016/j.diabres.2007.03.006  Buckland G., Salas-Salvadó J., Roure E., Bulló M., Serra-Majem L., Sociodemographic risk factors associated with metabolic syndrome in a Mediterranean population, Public Health Nutr., 2008, 11, 1372–1378 http://dx.doi.org/10.1017/S1368980008003492  Qader S.S., Shakir Y.A., Nyberg P., Samsioe G
socio-economic conditions and lifestylefactors – a population-based study in Sweden. BMC Public Health. doi: 10.1186/1471-2458-9-302. 35. MOTA, J., F. FIDALGO, R. SILVA, R. C. RIBEIRO, R. SANTOS, J. CARVALHO & M. P. SANTOS, 2008. Relationship between physical activity, obesity and meal frequency in adolescents. Ann. Hum. Biol. 35 , 1-10. 36. NOVAK, D., E. SUZUKI & I. KAWACHI, 2015. Are family, neighbourhood and school social capital associated with higher self-rated health among Croatian high-school students? A popualtion-based study. BMJ Open . doi: 10
, Green J, Allen NE, Key TJ, et al. Characteristics of the Million Women Study participants who have and have not worked at night. Scand J Work Environ Health. 2012;38(6):590–599.  Saksvik-Lehouillier I, Bjorvatn B, Hetland H, Sandal GM, Moen BE, Mageroy N, et al. Individual, situational and lifestylefactors related to shift work tolerance among nurses who are new to and experienced in night work. J Adv Nurs. 2013;69(5): 1136–1146.  Zhao I, Bogossian F, Turner C. Does maintaining or changing shift types affect BMI? A longitudinal study. J Occup Environ Med
The aim of our study was to evaluate the association between variant genotype of angiotensinogen (AGT) c.-58A>C, lifestyle factors and clinical factors and corporeal extension of gastric inflammatory and preneoplastic lesions.
Methods: Our study included 209 subjects who underwent a complete set of gastric biopsies, followed by genotyping. They were included to study inflammatory gastric changes and preneoplastic lesions and were grouped according to the localization of changes.
Results: No significant statistical associations were noticed between AGT c.-58A>C genotypes and the corporeal extension of the inflammation or preneoplastic injury groups. Extending preneoplastic lesions to the gastric body was associated with smoking habits (p=0.01) and additionally, there was a significant association between nicotine consumption and the body extension of preneoplastic lesions (p=0.01). The use of acenocoumarol was frequently associated with the progression of histological lesions to preneoplastic lesions (p=0.01). Compared with the wild-type AA genotype, the combined genotypes AA+CC of AGT c.-58A>C were significantly associated with the progression of inflammatory gastric lesions’ according to the regular ingested doses of nonsteroidal anti-inflammatory drugs (NSAIDs).
Conclusion: The AGT c.-58A>C polymorphism is not associated with extension of the gastric lesions. In accordance with nicotine and alcohol consumption, the acenocoumarol co-treatment and multiple cardiac pathologies are associated with the corporeal progression of these injuries. The age below 70 years and NSAIDs treatment for the patients with heterozygous AC genotype and variant homozygous CC genotype for the mentioned SNP have been associated with the corporeal extension of gastric inflammation.
strengthen the evidence on the association of various lifestylefactors on academic performance to plan specific interventions. School health program shall necessarily incorporate compulsory periodic health talks regarding the lifestyle diseases as it is emerging risk among adolescents and parents sensitization regarding the factors influencing the academic behavior of students. Conclusion Academic performance of secondary school students was influenced by regularity of attendance, socio-economic status and education of the parents. Various other factors including skipping
the change needed between two serial test results from the same individual to be significantly different, considering the measurement error [ 18 ]. With these premises in mind, our study aimed to identify biological and lifestylefactors affecting GDF-15 to establish robust reference intervals for GDF-15 concentrations in serum, and to estimate GDF-15 within-subject biological variation and derived indices, using the Roche Diagnostics Elecsys GDF-15 assay. Materials and methods Evaluation of biological and lifestylefactors affecting GDF-15 and derivation of
Abdominal obesity is caused by several factors and the explanation of the level of its variability also depends on anthropometric indexes applied for its assessment. The aim was to determine the degree of explanation of the abdominal adiposity variation, presented by the aggregate fat distribution index (AFDI), through the socio-economic status and lifestyle. Subjects and methods: A cross-sectional population-based study was conducted on a sample of 259 healthy working males aged 20-30 from the city of Cracow, Poland. A full model was created using a stepwise backward regression with the social and lifestyle data as independent variables and the AFDI as a dependent variable. The AFDI was created by unitarization applied to selected characteristics of fat distribution which were transformed into [0,1] interval (without measurement unit) and then added and averaged to form a composite index. The highest autonomous influence on AFDI is ascribed to age (b = 0.2456 p = 0.000), level of motor fitness b=−0.2392 p=0.000), leisure time physical activity (b=−0.1353 p=0.000) and being born in a rural area (b=0.1300 p=0.000). The variables explain 17% (R2=0.1667) of the variation of the central fat distribution. Variation of the abdominal adiposity was explained with the use of AFDI at the level close to the commonly applied indexes.
In order to investigate the association between polymorphisms in genes encoding metabolizing enzymes (CYP1A1-MspI, EC-SOD (extracellular superoxide dismutase), GSTT1, GSTM1, ALDH2), cigarette and alcohol consumption, and the risk of oral squamous cell carcinoma, we conducted a prospective case-control study comprised of 750 individuals with oral squamous cell carcinoma (OSCC) and 750 healthy individuals. Data about smoking and drinking habits were collected along with other demographic and clinical information. Peripheral blood samples were collected for DNA extraction, and polymerase chain reaction (PCR) and PCR-RFLP (restriction fragment length polymorphism) were used to determine genotypes of CYP1A1, EC-SOD, GSTT1, GSTM1, ALDH2. The results showed that smoking and alcohol consumption were significantly more common among patients than controls (p <0.05). There were significant differences in the genotype distribution for each locus between groups, with the CYP1A1 (m2/ m2), EC-SOD (C/G), GSTT1 [–], GSTM1 [–] and ALDH2 (non G/G) genotypes being more common among patients (p <0.05). Furthermore, the majority of patients had at least two or more variant genotypes, while controls had one or no variant genotype (p <0.05). Finally, multiple variant genotypes combined with smoking, drinking, or both smoking and drinking significantly increased the risk of OSCC, with greater increase for heavier smoking/drinking. In brief, genetic polymorphism of CYP1A1, EC-SOD, GSTT1, GSTM1, and ALDH2 and smoking and drinking history are closely associated with susceptibility to OSCC.
Background: Genetic variations, such as those affecting DNA repair genes, could represent susceptibility factors for sporadic colorectal cancer (CRC) as a result of their interaction with environmental factors. Materials and
methods: 80 female and 70 males patients diagnosed with sporadic CRC in the Surgical Clinic III Cluj were genotyped for Arg399Gln-XRCC1, Lys751Gln-XPD and Met241Thr-XRCC3 using PCR-RFLP methods. We also genotyped 100 females and 62 males, who formed the control group. Genotyping results were related to environmental risk factors, smoking habit and diet. Results: Male patients carriers of the Arg399Gln, Lys751Gln, Met241Thr had a 4.09 (95%CI[0.96-19.98],p=0.05)-fold, 5.95(95%CI[1.08-43.22],p=0.03)-fold and 3.73(95%CI[0.86- 18.53],p=0.05)- fold significantly increased risk to develop sporadic CRC if they smoked. A significantly increased risk for CRC was observed in females and males with high daily fried red meat intake, carriers of the Arg399Gln (OR 2.77 95%CI [1.34-6.82],p=0.015 and OR 8.64 95%CI[2.67-29.14],p<0.001), Lys751Gln (OR 4.12 95%CI[1.37-12.74],p=0.007 and OR 5.06 95%CI[1.4-19.02],p=0.006), Met241Thr (OR5.92 95%CI[2.21- 16.23],p<0.001 and OR 5.64 95%CI[1.52-21.7],p=0.022). Female patients with high fried red meat intake had a significantly higher risk to develop early-onset sporadic CRC if they were carriers of the Arg399Gln-XRCC1 (OR 5.14 95%CI[0.99-28.3],p=0.047), Thr241Met-XRCC3 (OR 6.67 95%CI[1.05-46.67],p=0.025) and Lys- 751Gln-XPD (OR 4.7 95%CI[0.99-23.32],p=0.034). Conclusions: In Romanians, the association between the mutated genotypes and environmental risk factors modulates the risk for sporadic CRC. Smoking in association with the Arg399Gln-XRCC1 genetic variation influences the early onset of sporadic colorectal cancer in females. Diet rich in fried red meat intake associated with Arg399Gln-XRCC1, Lys751Gln-XPD and Thr241Met- XRCC3 genetic variations significantly influences the early onset of sporadic colorectal cancer in females.