These tables are crosstabs analysis for A chi-square test of the assoc.pdf

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These tables are crosstabs analysis for A chi-square test of the association between the predictor variable and the outcome variable (mortality) Predictor variable : Socio-Demographic Characteristics and chronic disease presence among COVID-19 patients and the outcome = mortality, Interpret the results?? REFERENCE Age: in Years Race: white, black, Other races Sex: Female / Male Marital status: single / Married Tobacco use: never smoke, Ex-smoker, Missing Alcohol use: Drinking, Not Drinking, Missing Comorbidity: 0 = no chronic disease, 1 = patient have one chronic disease, 2 = patient have two chronic diseases, 3= patient has three or more Diabetes: Yes/No Hypertension: Yes/No Chronic Lung Disease: Yes/No Chronic Heart Disease: Yes/No \begin{tabular}{lcc} \hline variables ( n = 276 ) & Mortality (fireq) & P-Value \\ \hline Comorbidity & 1 & .193 \\ 0 & 10 & \\ 1 & 15 & \\ 2 & 26 & \\ 3 & & 137 \\ Diabetes Mellitus & 67 & \\ Yes & 44 & \\ No & & \\ Hypertension & 101 & \\ Yes & 13 & \\ No & & \\ Chronic Lung Disease(y/n) & 24 & \\ Yes & 89 & \\ No & 921 \\ Chronic Lung Disease type & 9 & \\ Asthma & 4 & \\ COPD & 88 & \\ Lung cancer & 40 & \\ Missing & 73 & \end{tabular}.

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The study was conducted to identify some socioeconomic variables responsible for the prevalence of hypertensive kidney disease among Bangladeshi adults of 18 years and above. For this, 498 males and 497 females, totalling 995 adults of both urban and rural localities were investigated. In the sample there were 17.6% hypertensive adults and 18.9% of them were suffering from hypertension and kidney disease simultaneously. Beside other percentages of respondents, there were 19.6% elderly people of ages 50 years and above, 30.2% obese adults, 67.0% diabetic patients, 44.4% involved in sedentary activity and 33.1% smokers. The overall percentage of hypertensive kidney patients was 3.3. These group of patients were discriminated from the remaining 96.7% adults. During discrimination duration of diabetes was identified as most responsible variable followed by age, body mass index, sedentary activity, smoking habit, etc. The risk of prevalence of hypertensive kidney disease was 12.25 times in diabetic patients suffering for 15 years and above compared to the risk of prevalence in other adults. The risk was 8.43 times in elderly people, 16.80 times in obese adults, 2.50 times in adults involved in sedentary activity, and 1.91 times in smoker adults. Higher risk rate was also observed in adults of lower economic group of families.

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In this study, 140 patients were collected, and they were divided into two groups (120 patients and 30 control groups). The average age in this study ranged from 25 to 65 years. This paper aims to know the role of genetic factors in hypertension among Iraqi citizens and. This study was designed through cooperation with the hospital for the purpose of withdrawing the information found in the electronic record to patients, which includes primary information from demographic data (age - gender - body mass index - blood samples - smoking - alcohol - clinical history - genetic history and blood pressure. The data and demographic information related to the patients were analysed by relying on the statistical analysis program IBM soft SPSS 22. The results that were found were a collection of 140 patients (no positive result for 30 patients) (and 120 patients with a positive result), and the statistical value and the mean for the age of the patients was 45.2±15.3 as was done. Proportion of Family History with Hypertension patients and patient distribution (parents for 90 patients with 64.2% - siblings for 28 patients with 20% - offspring for 32 patients with 22.8%. Through the statistical analysis, a statistically significant relationship was found between genetic factors and their effect on arterial hypertension, with a p-value of 0.001.

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© 2014 Laureate Education, Inc. Page 1 of 2 Module 2 Application Data Set This data set on the following page does not contain actual patient information. However, relationships have been built into the measures that may reflect actual associations found in health. The invented background for this data is that of a sample of blood pressures and BMIs measured for clinic patients who were then followed for up to a 20-year period. These patients were followed until their deaths, and their final age was recorded. A data dictionary describing the measures follows the data. Data ID Num Age BP sex Systolic BP Diastolic BP BMI Death age diabetic Place 1 68 0 139 81 25 84 0 1 2 57 1 170 110 41 64 1 3 3 41 1 151 109 36 59 1 3 4 79 0 140 85 30 81 0 2 5 49 0 165 100 39 69 1 2 6 68 0 141 82 29 86 0 1 7 69 0 138 81 25 89 0 1 8 70 1 149 85 32 78 0 2 9 39 1 189 100 48 47 1 3 10 42 1 152 88 35 60 1 3 11 51 1 150 90 38 70 1 3 12 66 0 153 89 36 73 0 2 13 70 1 145 85 30 81 0 2 14 75 0 139 79 23 92 0 1 15 72 0 144 86 29 91 0 1 16 42 1 171 91 44 61 1 3 17 71 1 150 90 35 74 0 2 18 58 0 141 87 30 75 0 1 19 40 0 175 93 44 60 1 2 20 25 1 180 90 45 40 1 3 21 48 0 146 85 29 67 0 1 22 29 1 160 97 39 49 1 3 23 73 0 137 81 25 92 0 1 24 66 1 167 95 40 68 1 3 25 55 0 190 99 50 65 1 2 © 2014 Laureate Education, Inc. Page 2 of 2 Data Dictionary Name Type Label Values Missing Measure ID_Num Numeric A unique and encrypted ID number for a patient None Nominal Age_BP Numeric Initial visit age in years when a patient’s blood pressure was recorded None Scale sex Numeric Sex of patient 0 = female, 1 = male None Nominal Systolic_BP Numeric Systolic blood pressure at initial visit None Scale Diastolic_BP Numeric Diastolic blood pressure at initial visit None Scale BMI Numeric Body Mass Index None Scale Death_age Numeric Follow-up age at death in whole years None Scale diabetic Numeric Diabetic status of patient 0 = nondiabetic, 1 = diabetes None Nominal Place Numeric Census designation for patient’s residence 1 = rural, 2 = suburban, 3 = urban None Ordinal W A L D E N U N I V E R S I T Y P U B H 6 0 3 2 / 8 0 3 2 S P S S R E V E A L E D P U B H 6 0 3 3 / 8 0 3 3 I N T E R P R E T A T I O N & A P P O F D A T A T yp es of V ariables & L evels of M easu rem en t T yp es of V ariables y A variable is an y factor, trait, con d ition , or d isease th .

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