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Keywords = Smoking

  • Open Access Mini Review
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    Trends Journal of Sciences Research 2018, 3(2), 75-81. http://doi.org/10.31586/Nursing.0302.03
    144 Views 48 Downloads PDF Full-text (2.583 MB)  HTML Full-text
    Abstract
    Genotype and lifestyle factors have been implicated as the causes of non-communicable diseases including diabetes, cardiovascular diseases, cancer and chronic respiratory disease. Lifestyle factors constitute physical activity, smoking, alcohol intake and dietary habits. These factors alongside genetic factors have been studied over the past years on their relationships with non-communicable
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    Genotype and lifestyle factors have been implicated as the causes of non-communicable diseases including diabetes, cardiovascular diseases, cancer and chronic respiratory disease. Lifestyle factors constitute physical activity, smoking, alcohol intake and dietary habits. These factors alongside genetic factors have been studied over the past years on their relationships with non-communicable diseases. This review examined and compared the strengths of the two factors, lifestyle and genotype, in causing non-communicable diseases. A search was done online, predominantly with PubMed, to identify articles that contained the keywords, lifestyle, diet, exercise, genotype, gene, non-communicable diseases, cardiovascular diseases, cancer, chronic respiratory disease, diabetes. For diabetes, the results of this review showed that management of lifestyle factors can be used to prevent type 2 diabetes among genetically predisposed persons. Cancers studies have suggested that a Mediterranean diet is associated with lower cancer risk for both genetically susceptible people and non-susceptible individuals. Similar findings were gotten for cardiovascular diseases and chronic respiratory diseases. The results suggest a strong impact of lifestyle-related factors as a cause of non-communicable diseases though genetic factors cannot be underestimated. With good management of lifestyle factors, non-communicable diseases can be prevented and the risks reduced even among genetically high-risk individuals.  Full article
    References
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    World Health Organisation, Global action plan for the prevention and control of non-communicable diseases 2013-2020. Available at: who.int/iris/bitstream/10665/94384/1/9789241506236_eng.pdf. 2013. Accessed March 22, 2017.
    [2]
    Melaku YA, Temesgen AM, Deribew A, Tessema GA, Deribe K, Sahle BW, et al. The impact of dietary risk factors on the burden of non-communicable diseases in Ethiopia: findings from the Global Burden of Disease study 2013. International Journal of Behavioral Nutrition and Physical Activity 13 (2016) 122-134.
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    Hosseini-Esfahani F, Mirmiran P, Daneshpour MS, Mottaghi A, Aziz F. The effect of interactions of Single Nucleotide Polymorphisms of APOA1/APOC3 with food group intakes on the risk of metabolic syndrome. Avicenna J Med Biotech 9 (2017) 94-103.
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    Chikwere P, Annan RA. Dietary habit and other lifestyles and serum lipid profile of type 2 diabetes patients: a systematic review. Nutrition & Food Science 46 (2016) 161-170.
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    Chikwere P, Nsiah K, Tandoh MA. Relation of unsupported and unsupervised exercise with anthropometric and biochemical indices among type 2 diabetic patients. Turk J Med Sci 47 (2017) 85-90.
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    Naicker A, Venter CS, MacIntyre, UE, Ellis S. Dietary quality and patterns and non-communicable disease risk of an Indian community in KwaZulu-Natal. South Africa Journal of Health, Population and Nutrition 33 (2015) 12-20.
    [7]
    Chikwere P, Nsiah K, Tandoh MA, Agyenim-Boateng K. The relation of dietary pattern to serum lipid profile and uric acid among type 2 diabetes patients. J. Nutr. Ecol. Food Res 2 (2014) 207-213.
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    Langenberg C, Sharp S, Forouhi NG, Franks P, Schulze MB, Kerrison N, et al. The InterAct Project: An Examination of the Interaction of Genetic and Lifestyle Factors on the Incidence of Type 2 Diabetes in the EPIC Study. Diabetologia 54 (2011) 2272-2282.
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    Langenberg C, Sharp SJ, Franks PW, Scott RA, Deloukas P, Forouhi NG, et al. Gene-lifestyle interaction and type 2 diabetes: The EPIC InterAct case-cohort study. PLoS Med 11 (2014) e1001647.
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    Walker CG, Solis-Trapala I, Holzapfe C, Ambrosini GL, Fuller NR, Loos RJF, et al. Modelling the interplay between lifestyle factors and genetic predisposition on markers of type2 diabetes mellitus risk. PLoS ONE 10 (2015) e0131681.
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    Chikwere P. Functional foods and nutraceuticals, wonders in cancer risks - a review. World Scientific News 64 (2017) 18-33.
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    Ib??ez-Sanz G, D?ez-Villanueva A, Henar Alonso M, Rodr?guez-Moranta F, P?rez-G?mez B, Bustamante M, et al. Risk Model for Colorectal Cancer in Spanish Population Using Environmental and Genetic Factors: Results from the MCC-Spain study. Scientific Reports 7 (2017) 43263.
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    Stein B, Anderson JC, Rajapakse R, Alpern ZA, Messina CR, Walker G. Body mass index as a predictor of colorectal neoplasia in ethnically diverse screening population. Dig Dis Sci 55 (2010) 2945-2952.
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    Abul? A, Fern?ndez-Rozadilla C, Alonso-Espinaco V, Mu?oz J, Gonzalo V, Bessa X, et al. Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins. BMC Cancer 11 (2011) 339-346.
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    Huo D, Zheng Y, Ogundiran TO, Adebamowo C, Nathanson KL, Domchek SM, et al. Evaluation of 19 susceptibility loci of breast cancer in women of African ancestry. Carcinogenesis 33 (2012) 835?840.
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    Ko K-P, Kim S-W, Ma SH, Park B, Ahn Y, Lee JW, et al. Dietary intake and breast cancer among carriers and noncarriers of BRCA mutations in the Korean Hereditary Breast Cancer Study. Am J Clin Nutr 98 (2013) 1493-1501.
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    Toledo E, Salas-Salvad? J, Donat-Vargas C, Buil-Cosiales P, Estruch R, Ros E, et al. Mediterranean Diet and Invasive Breast Cancer Risk Among Women at High Cardiovascular Risk in the PREDIMED Trial: A Randomized Clinical Trial. JAMA Intern Med 175 (2015) 1752-1760.
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    Sanchez NF, Stierman B, Saab S, Mahajan D, Yeung H, Francois F. Physical activity reduces risk for polyps in a multiethnic colorectal cancer screening population. BMC Research Notes 5 (2012) 312-319.
    [23]
    Folkersen L, van?t Hooft F, Chernogubova E, Agardh HE, Hansson GK, Hedin U. Association of genetic risk variants with expression of proximal genes identifies novel susceptibility genes for cardiovascular disease. Circ Cardiovasc Genet 3 (2010) 365-373.
    [24]
    Sotos-Prieto M, Baylin A, Campos H, Qi L, Mattei J. Lifestyle Cardiovascular Risk Score, Genetic Risk Score, and Myocardial Infarction in Hispanic/Latino Adults Living in Costa Rica. J Am Heart Assoc 5 (2016) e004067.
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    Corella D, Asensio EM, Coltell O, Sorl?, J. V., Estruch, R., Martinez-Gonz?lez, M.A, et al. CLOCK gene variation is associated with incidence of type 2 diabetes and cardiovascular diseases in type 2 diabetic subjects: dietary modulation in the PREDIMED randomized trial. Cardiovascular Diabetology 15 (2016) 4-15.
    [26]
    Garg V, Muth AN, Ransom JF, Schluterman MK, Barnes R, King IN, et al. Mutation in NOTCH1 cause aortic valve disease. Nature 437 (2005) 270-274.
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    Khera AV, Emdin CA, Drake I. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med 375 (2016) 2349-2358.
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    Micha R, Pe?alvo JL, Cudhea F, Imamura F, Rehm CD, Mozaffarian D. Association between dietary factors and mortality from heart disease, stroke, and type 2 diabetes in the United States. JAMA 317 (2017) 912-924.
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    Estruch R, Ros E, Salas-Salvad? J. Primary Prevention of Cardiovascular Disease with a Mediterranean Diet. N Engl J Med 368 (2013) 1279-1290.
    [30]
    McKeever TM, Lewis SA, Cassano PA, Ock? M, Burney P, Britton J, Smit HA, et al. Patterns of dietary intake and relation to respiratory disease, forced expiratory volume in 1 s, and decline in 5-y forced expiratory volume. Am J Clin Nutr 92 (2010) 408-415.
    [31]
    Powell R, Davidson D, Divers J, Manichaikul A, Jeffrey Carr J, Detrano R, et al. Genetic ancestry and the relationship of cigarette smoking to lung function and per cent emphysema in four race/ethnic groups: a cross-sectional study. Thorax 68 (2013) 634-642.
    [32]
    Sorli-Aguilar M, Martin-Lujan F, Flores-Mateo G, Arija-Val V, Basora-Gallisa J, Sola-Alberich R. Dietary patterns are associated with lung function among Spanish smokers without respiratory disease. BMC Pulmonary Medicine 16 (2016) 162-173.
    [33]
    Sabater-Lleal M, M?larstig A, Folkersen L, Artigas MS, Baldassarre D, Kavousi M, Almgren P, et al. Common Genetic Determinants of Lung Function, Subclinical Atherosclerosis and Risk of Coronary Artery Disease. PLoS ONE 9 (2014) e104082.
  • Open Access Research Article
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    Trends Journal of Sciences Research 2018, 3(3), 104-115. http://doi.org/10.31586/PharmaceuticalHealth.0303.01
    67 Views 47 Downloads PDF Full-text (858.621 KB)  HTML Full-text
    Abstract
    Objective: To examine which medication could lead to a higher short and long term smoking abstinence in patients with schizophrenia.Methods: A retrospective cohort study was conducted using General Electric (GE) medical records database (1995 ? 2011). The cohort consisted of adult smokers with diagnosis of schizophrenia newly initiating cessation medication.
    [...] Read more.
    Objective: To examine which medication could lead to a higher short and long term smoking abstinence in patients with schizophrenia.Methods: A retrospective cohort study was conducted using General Electric (GE) medical records database (1995 ? 2011). The cohort consisted of adult smokers with diagnosis of schizophrenia newly initiating cessation medication. Short term and long term outcomes of cessation were measured at 3 weeks and 1 year. Descriptive and chi-square analyses were used to determine the frequencies and associations of patient characteristics with the abstinence outcomes. Logistic regression models were carried out to determine the predictors of short term and long term abstinence. Results: The cohort consisted of 3,976 patients. Abstinence rate was highest for Varenicline, followed by Bupropion, NRT, and lastly combination at week 12. At one year, abstinence rate was highest for Varenicline, followed by combination, NRT, and lastly Bupropion. Age, race, household locations and receiving counseling were associated with abstinence. No significant differences were found between cessation medications. Conclusions: There were no statistically significant differences in quitting with type of cessation medication. Predictors of better abstinence identified included older age, white race, western household location. These factors should be considered when designing future interventions for schizophrenic population as this minority population may need more tailored approaches to achieve a successful cessation outcome.  Full article
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    Tsoi, D.T., M. Porwal, and A.C. Webster, Efficacy and safety of bupropion for smoking cessation and reduction in schizophrenia: systematic review and meta-analysis. The British Journal of Psychiatry, 2010. 196(5): p. 346-353.
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  • Open Access Research Article
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    Trends Journal of Sciences Research 2019, 4(1), 21-28. http://doi.org/10.31586/Cardiology.0401.04
    58 Views 40 Downloads PDF Full-text (793.318 KB) PDF Full-text (794.026 KB) PDF Full-text (793.965 KB)  HTML Full-text
    Abstract
    At present, cardiovascular diseases are global health problems responsible for 17.3 million deaths per year and adding extra burden in developing countries like Nepal. Studies show that serum uric acid (SUA) can result in endothelial dysfunction which can lead to vascular disease like stroke. In this study, we determined serum
    [...] Read more.
    At present, cardiovascular diseases are global health problems responsible for 17.3 million deaths per year and adding extra burden in developing countries like Nepal. Studies show that serum uric acid (SUA) can result in endothelial dysfunction which can lead to vascular disease like stroke. In this study, we determined serum uric acid levels in patients with acute coronary syndrome (ACS) and assess its risk factors. A cross sectional study was conducted in 82 patients with ACS who fulfilled the inclusion criteria included in the study and their serum uric acid level were investigated. It was found that 51 (62.2%) were males and 31 (37.8%) were females. Mean age in study population was 60.26 ± 11.34 years. Majority of the population belongs to 56-65 years age group. The mean uric acid level of our study population was 6.03 ± 1.50 mg/dl (male = 5.92 ± 1.72, female = 6.64 ± 1.53). SUA ≥ 7 mg/dl was maximum in 56-65 years age group and there was no association between age and SUA (P value = 0.146). Over half of the study population were hypertensive i.e. 42 (51.21%) and smoker i.e. 43 (52.43%). It showed association between SUA and ACS (P value = 0.003). Among those having diabetes, maximum have SUA ≥ 7 mg/dl i.e. 17 (47.22%). Among those having high cholesterol level, male have higher incidence than female with no association between T. Cholesterol and gender (P value = 0.49). The mean value of T. Cholesterol was 189.83 ± 46.81 mg/dl (male = 198.78 ± 55.19 mg/dl, female = 202.30 ± 54.92 mg/dl) with (P value = 0.52). In conclusion, the mean age of ACS patients was 60.26 years, with the peak incidence at the age of 56-65 years. The ACS had male predominance. The potential risk factors of ACS were: Age >56 years (65.83%), male sex (62.2%), dyslipidemia (35.36%, hypertension (51.2%), diabetes mellitus (43.9%), smoking (52.4%) and alcohol consumption (39%). Among these SUA significantly associated with risk factors were- Sex, Diabetes Mellitus, T. Cholesterol. There was association between serum uric acid level and ACS patients. Hypertension and smoking constitutes one of the major risk factor for ACS in study population.  Full article
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