The Effect of Physical, Social, and Health Variables on Diabetes

Introduction This paper analyzes data of three hundred individuals’ health records. The data summarizes the diabetes status of the sample and presents their medical, social, physical and economic characteristics. Previous public-health studies have investigated and identified the relationship between variables and the prevalence of diabetes. The results will be compared with the findings of previous research on diabetes.Advertising We will write a custom report sample on The Effect of Physical, Social, and Health Variables on Diabetes specifically for you for only $16.05 $11/page Learn More Ten variables used to analyze the results were gender, race, salary, education, height, weight, Body Mass Index (BMI), allergies, family history of diabetes, and family history of allergies. Subsequent sections analyze the relationships between the variables. Analysis The relationship between each variable and diabetes may be observed by comparing the mean valu es for the two groups. Table 1 summarizes the mean values of the numerical variables for participants in the two groups. Table 1: Descriptive Statistics of Numerical Variables Diabetes N Mean Age Yes 109 70.47 No 191 38.95 Salary Yes 109 $70,226.45 No 191 $45,522.11 Height Yes 109 70.42 No 191 65.02 Weight Yes 109 187.87 No 191 142.70 BMI Yes 109 26.524 No 191 23.563 Two findings are deducible from the results presented in the table. The average age of those with diabetes was 70.47. However, those without diabetes had an average age of 38.95 years. This finding is supported by a previous study which reported that the decline in protein synthesis in aging tissues increased the risks of diabetes in older people (Yamamoto, et al., 2014). The effect of income on diabetes is observed in the table. The average salary of those with diabetes is $45,522 and for those without diabetes is $70,226.45. These findings can be compared with previous research that suggeste d low-income earners were more likely to have diabetes than their wealthier counterparts (Lysy, et al., 2013). Although discrepancies can be observed in the mean scores between the two groups, it is important to test the level of significance of these variations. Chi-Square tests and t-tests were used to investigate the significance of the difference in mean values.  Table 2 summarizes the results of the Chi-square test. The p-values for salary (0.001), height (0.000), weight (0.000), BMI (0.000), family history of diabetes (0.000), and family history of allergies (0.000) showed the variables were related to diabetes.Advertising Looking for report on health medicine? Let's see if we can help you! Get your first paper with 15% OFF Learn More The results are similar to previous studies, which suggest that income (Lipscombe, Austin Manuel, 2010), physical characteristics (Narayan Boyle, 2007), and family history (Uusitupa, Stancakova, Peltonen, Eriksson, 2011) are r elated to diabetes. Table 2: Chi-square values and p-values Chi-Square value p-value Gender .181 .670 Race 2.074 .839 Age 284.542 .152 Salary 289.193 .001 Education 2.897 .408 Height 175.981 .000 Weight 175.981 .000 BMI 163.689 .000 Allergies .010 .922 Family history diabetes 143.728 .000 Family history allergies 166.699 .000 Table 3 summarizes the p-values derived from the t-test. The findings are similar to the p-values derived from the chi-square tests however the p-value for age (0.000) derived from the t-test suggests a significant relationship between age and diabetes (Creatore, Moineddin Booth, 2010). Table 3: t-test values and p-values t-test value p-value Gender -.424 .672 Race -1.44 .885 Age 20.091 .000 Salary 7.794 .000 Education -.336 .737 Height 16.633 .000 Weight 16.331 .000 BMI 14.352 .000 Allergies .098 .922 Family history diabetes -16.555 .000 Family history allergies 19.304 .000 References Creatore, M. I., Moineddin, R., Booth, G. (2010). Age- and sex-related prevalence of diabetes mellitus among immigrants to Ontario, Canada. CMAJ, 182(8), 781-789. Lipscombe, L. L., Austin, P. C., Manuel, D. G. (2010). Income-related differences in mortality among people with diabetes mellitus. CMAJ, 182(1), E1-E17. Lysy, Z., Booth, G., Shah, B., Austin, P., Luo, J., Lipscombe, L. (2013). The impact of income on the incidence of diabetes: a population-based study. Diabetes Research for Clinical Practice, 99(3), 372-379.Advertising We will write a custom report sample on The Effect of Physical, Social, and Health Variables on Diabetes specifically for you for only $16.05 $11/page Learn More Narayan, K. M., Boyle, J. P. (2007). Effect of BMI on lifetime risk for diabetes in the U.S. Diabetes Care, 30(6), 1562-1562. Uusitupa, M. I., Stancakova, A., Peltonen, M., Eriksson, J. G. (2011). Impact of Positive Family History and Genetic Risk Variants on the Incidence of Diabet es. Diabetes Care, 34(2), 418–423. Yamamoto, K., Kitano, Y., Shuang, E., Hatakeyama, Y., Sakamoto, Y., Honma, T., Tsuduki, T. (2014). Decreased lipid absorption due to reduced pancreatic lipase activity in aging male mice. Biogerontology, 15(5), 463-473. This report on The Effect of Physical, Social, and Health Variables on Diabetes was written and submitted by user Kailynn Salas to help you with your own studies. 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