Statistical analysis

Spss data analysis
Student’s name
Institution
Date

Set A
The frequency of hypertension in the United States of America and its association with gender and race
Introduction
High blood pressure also called hypertension is a health condition in which the force of blood against the artery walls is high. It is defined as a blood pressure of systolic values above 140mm mercury and diastolic values of above 90mm mercury. Hypertension is one of the major risk factors associated cardiovascular diseases, and is also a component of the metabolic syndrome. It is caused by various factors such as consumption of a high salt, fat and cholesterol diet and leading a sedentary lifestyle.
Aside from the above mentioned high blood pressure may however be brought about by other uncontrollable factors such as family genetics or genetic factors influenced by race or gender.
Several studies have shown that there is a significant relationship between systemic blood pressures to race and gender with many stating that there is an association between blood pressures to both. Studies have shown the black race and female gender is associated with higher blood pressures and hypertension. There is however scarce evidence from a sufficient sample size to prove this and thus the observation remains highly theoretical.
1.1Background information
For a long time researchers have argued the association between skin pigmentation and blood pressure. One argument states that pigmentation alters calcium, vitamin D and parathyroid hormone levels thus influencing blood pressure.(Stephen R, 2014). Crystal C et al, 2018 evaluated whether albuminuria or black race modulates ambulatory blood pressure among adults enrolled in a DASH diet or control diet for 8 weeks, reductions measured in 24 hours night and daytime. The study suggested there was a significant interaction between diet and on change of ambulatory blood pressure per day. (Crystal C et al, 2018)
Gender has also been associated greatly with hypertension. A study on blood pressure and its association with gender, body mass index (BMI), smoking and family history among students in the university of Jordan revealed a significant gender difference regarding hypertension with males having more hypertension compared to females.(Husssein h et al, 2018)
2. Methods
2.1Data collection
Data was obtained from the National Household Survey on Drug abuse (NHSDA) data collected by the United States Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. Office of Applied Studies.
2.2Statistical analysis
The data was analyzed using the IBM SPSS statistical package version 20. Descriptive statistics were used to describe the study population using modes medians and frequency counts and percentages for categorical variables. Comparisons between gender and diagnosis for high blood pressure and race and diagnosis for high blood pressure were done to assess the association between them using the Pearson’s correlation coefficient. The Independent sample t test was then used to determine the mean difference in occurrence of high blood pressure in both genders.

The analysis was reported using tables and discussed.
Results
Among our sample 12955(45%) of the population was male and 15805(55%) female. Of a total sample of 28760, 3498(12.2%) said they had ever been diagnosed as having high blood pressure. Of this 1448(41.4%) an 11.2% representation of the gender were male and 2050(58.6%) a 13% representation of the gender were female.
25248(87.8%) said they had never been diagnosed as having high blood pressure. Of this 11503 (45.6%) an 88% representation of the gender were male and 13745(54.4%) an 87 % representation of the gender was female.
Looking at the data according to race, 4 races were represented in the data (ie American Indian, Asian, Black and White). 406(1.4%) represented the America Indian race, 1028(3.6%) the Asian 6757(23.5%) the black race and 20569(71.5%) the White race. Of this 48(1.4%) American Indians an 11.8% representation of their population,59(1.7%) of the Asians a 5.7% representation of their population, 988(28.2%) blacks a 14.6% representation of their population and 2403(68.7%) whites admitted to ever being diagnosed with high blood pressure. 87.7% of American Indians, 94.2% of Asians, 85.3% of blacks and 88.3% of whites had never been diagnosed with high blood pressure.
A Pearson’s correlational coefficient for the variables race, gender and ever diagnosed with high blood pressure were as follows; for race and ever diagnosis of high blood pressure the Pearson coefficient was r(28754)=.004, p<.001 thus no statistically significant relationship between the two variable. Sex/gender with ever diagnosed with high blood pressure the correlation was r(28758)= -0.27**, p<.001.
An independent samples t test to determine whether the occurrence of high blood pressure was significantly different between males and females revealed that the groups differed significantly t=(28758)=4.535 p<0.001 d=0.061 95Cl(.010,.025)(table 3).

Table 1;EVER DIAGNOSED AS HAVING HIGH BLOOD PRES * SEX – IMPUTATION REVISED Crosstabulation

SEX – IMPUTATION REVISED
Total

Male
Female

EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
Yes
Count
1448
2050
3498

% within EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
41.4%
58.6%
100.0%

% within SEX – IMPUTATION REVISED
11.2%
13.0%
12.2%

No
Count
11503
13745
25248

% within EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
45.6%
54.4%
100.0%

% within SEX – IMPUTATION REVISED
88.8%
87.0%
87.8%

Yes LOGICALLY IMPUTED
Count
4
10
14

% within EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
28.6%
71.4%
100.0%

% within SEX – IMPUTATION REVISED
0.0%
0.1%
0.0%

Total
Count
12955
15805
28760

% within EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
45.0%
55.0%
100.0%

% within SEX – IMPUTATION REVISED
100.0%
100.0%
100.0%

Table 2;EVER DIAGNOSED AS HAVING HIGH BLOOD PRES by IMPUTATION-REVISED RACE OF RESPONDENT

RACE
Total

American indian or Alaskan native
Asian or Pacific islander
Black
White

EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
Yes
Count
48
59
988
2403
3498

% within HIGH BLOOD PRES
1.4%
1.7%
28.2%
68.7%
100.0%

% within RACE
11.8%
5.7%
14.6%
11.7%
12.2%

No
Count
356
968
5766
18158
25248

% within HIGH BLOOD PRES
1.4%
3.8%
22.8%
71.9%
100.0%

% within RACE
87.7%
94.2%
85.3%
88.3%
87.8%

Yes LOGICALLY IMPUTED
Count
2
1
3
8
14

% within HIGH BLOOD PRES
14.3%
7.1%
21.4%
57.1%
100.0%

% within RACE
0.5%
0.1%
0.0%
0.0%
0.0%

Total
Count
406
1028
6757
20569
28760

% within HIGH BLOOD PRES
1.4%
3.6%
23.5%
71.5%
100.0%

% within RACE
100.0%
100.0%
100.0%
100.0%
100.0%

a. Data obtained from National Household Survey on Drug Abuse, 1992

Table 3.Independent Samples Test

Levene's Test for Equality of Variances
t-test for Equality of Means

F
Sig.
t
df
Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the Difference

Lower
Upper

EVER DIAGNOSED AS HAVING HIGH BLOOD PRES
Equal variances assumed
86.229
.000
4.535
28758
.000
.018
.004
.010
.025

Equal variances not assumed

4.564
28255.539
.000
.018
.004
.010
.025

Table 4; correlations of ever diagnosed as having high blood pressure

Sex
Race

Ever dx of high BPs
-0.27**
.004

Sex

-0.001

Race

3.1Discussion
From the frequency counts and percentage representations we can see that a bigger percentage of the females had ever been diagnosed for high blood pressure. Thus more females were predisposed to hypertension. The data also indicates a larger proportion of the black race had ever been diagnosed for high blood pressure thus associating the black race more to hypertension. A statistically significant correlation between sex and ever diagnosis was also proven. The correlational coefficient however dismissed the hypothesis that race is associated with hypertension as no statistically significant relation was found.
Independent samples test proved presence of the genders male and female differed significantly. Its findings suggest the prevalence of high blood pressure is significantly higher in females than male.
Conclusion
The results of this study suggest a higher predisposition of the female gender to hypertension. Efforts should thus be put in place to prevent hypertension such as health promotions. Encourage women to exercise regularly, eat a healthy diet and avoid stressful environments to avoid hypertension. There is no statistically significant association of the black race to hypertension.

Set b
An assessment of the relationship between age and total annual income
Introduction
Studies have shown that the generally the productivity of individuals peak between 35 and 45 years thus annual incomes are higher at this age categories. This research study aims to assess the relationship between age total individual income.
Methods
Data for this research study was obtained from the National Household Survey on Drug abuse (NHSDA) data collected by the United States Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. Office of Applied Studies.
Analysis was done using IBM SPSS statistics software version 20.The variables used were Annual personal total income inc recode 13(INDCAT) and age category 5 levels Record (CATAG3). The study is a quantitative study and seeks to assess the level of income in the population USA. Descriptive statistics were used to describe the sample characteristics using mean median and mode. A comparison between age category and total annual income was done using descriptive analysis and presented in an annual total income vs age category cross tabulation table.This being categorical variable correlational tests were done using the chi square tests.

Results and Discussions
From the data in table 1 we can see that the younger age category groups are more represented in lower income categories compared to older ones. 58.1% of young individuals in the age category 12-17 years had a total personal income of 0$ representing 60.6% individuals in this level of income compared to the oldest age category of whom 5.1% fell in this level of income presenting the lowest representation in this category preceding the age category 35-49 years with 4.7%. The representation in the level of income 0$ evidently reduces with increasing age. A similar observation can be seen in the 1-4999$ level of total annual income for increasing age.
Fairly higher total annual income level have a higher representation of older age categories. For a total income of $75000+ earners the age category of 35-49years represents 53.6% of the individuals followed by the age category 26-34 years with 29.1%
From this frequencies we can tell that age is strongly related to the level of annual total personal income. The level of annual total personal income increases with an increase in age. The level of income seems to peek at the age category of which has a higher representation at higher total annual income levels. These results also suggest the peak productive age category to be 35-49 years.
Table 1;ANNUAL TOTAL PERSONAL INCOME by AGE CATEGORY

AGE CATEGORYa
Total

12-17 years
18-25 years
26-34 years
35-49 years
50+ years

ANNUAL TOTAL PERSONAL INCOME
$0
Count
4216
1505
809
329
94
6953

% within Annual Personal Income
60.6%
21.6%
11.6%
4.7%
1.4%
100.0%

% within Age Category
58.1%
19.5%
10.8%
7.3%
5.1%
24.1%

% of Total
14.6%
5.2%
2.8%
1.1%
0.3%
24.1%

$1-$4,999
Count
2481
1652
927
448
210
5718

% within Annual Personal Income
43.4%
28.9%
16.2%
7.8%
3.7%
100.0%

% within Age Category
34.2%
21.4%
12.3%
10.0%
11.4%
19.8%

% of Total
8.6%
5.7%
3.2%
1.6%
0.7%
19.8%

$5,000-$6,999
Count
210
632
396
232
261
1731

% within Annual Personal Income
12.1%
36.5%
22.9%
13.4%
15.1%
100.0%

% within Age Category
2.9%
8.2%
5.3%
5.2%
14.1%
6.0%

% of Total
0.7%
2.2%
1.4%
0.8%
0.9%
6.0%

$7,000-$8,999
Count
157
688
386
256
193
1680

% within Annual Personal Income
9.3%
41.0%
23.0%
15.2%
11.5%
100.0%

% within Age Category
2.2%
8.9%
5.1%
5.7%
10.4%
5.8%

% of Total
0.5%
2.4%
1.3%
0.9%
0.7%
5.8%

$9,000-$11,999
Count
81
788
575
271
197
1912

% within Annual Personal Income
4.2%
41.2%
30.1%
14.2%
10.3%
100.0%

% within Age Category
1.1%
10.2%
7.7%
6.0%
10.6%
6.6%

% of Total
0.3%
2.7%
2.0%
0.9%
0.7%
6.6%

$12,000-$14,999
Count
42
937
877
404
185
2445

% within Annual Personal Income
1.7%
38.3%
35.9%
16.5%
7.6%
100.0%

% within Age Category
0.6%
12.1%
11.7%
9.0%
10.0%
8.5%

% of Total
0.1%
3.2%
3.0%
1.4%
0.6%
8.5%

$15,000-$19,999
Count
24
642
900
457
192
2215

% within Annual Personal Income
1.1%
29.0%
40.6%
20.6%
8.7%
100.0%

% within Age Category
0.3%
8.3%
12.0%
10.2%
10.4%
7.7%

% of Total
0.1%
2.2%
3.1%
1.6%
0.7%
7.7%

$20,000-$24,999
Count
17
419
776
522
126
1860

% within Annual Personal Income
0.9%
22.5%
41.7%
28.1%
6.8%
100.0%

% within Age Category
0.2%
5.4%
10.3%
11.6%
6.8%
6.5%

% of Total
0.1%
1.5%
2.7%
1.8%
0.4%
6.5%

$25,000-$29,999
Count
7
166
473
287
74
1007

% within Annual Personal Income
0.7%
16.5%
47.0%
28.5%
7.3%
100.0%

% within Age Category
0.1%
2.1%
6.3%
6.4%
4.0%
3.5%

% of Total
0.0%
0.6%
1.6%
1.0%
0.3%
3.5%

$30,000-$39,999
Count
11
222
734
524
126
1617

% within Annual Personal Income
0.7%
13.7%
45.4%
32.4%
7.8%
100.0%

% within Age Category
0.2%
2.9%
9.8%
11.7%
6.8%
5.6%

% of Total
0.0%
0.8%
2.5%
1.8%
0.4%
5.6%

$40,000-$49,999
Count
3
42
392
330
80
847

% within Annual Personal Income
0.4%
5.0%
46.3%
39.0%
9.4%
100.0%

% within Age Category
0.0%
0.5%
5.2%
7.3%
4.3%
2.9%

% of Total
0.0%
0.1%
1.4%
1.1%
0.3%
2.9%

$50,000-$74,999
Count
5
25
220
339
83
672

% within Annual Personal Income
0.7%
3.7%
32.7%
50.4%
12.4%
100.0%

% within Age Category
0.1%
0.3%
2.9%
7.5%
4.5%
2.3%

% of Total
0.0%
0.1%
0.8%
1.2%
0.3%
2.3%

$75,000+
Count
0
3
51
92
29
175

% within Annual Personal Income
0.0%
1.7%
29.1%
52.6%
16.6%
100.0%

% within Age Category
0.0%
0.0%
0.7%
2.0%
1.6%
0.6%

% of Total
0.0%
0.0%
0.2%
0.3%
0.1%
0.6%

Total
Count
7254
7721
7516
4491
1850
28832

% within Annual Personal Income
25.2%
26.8%
26.1%
15.6%
6.4%
100.0%

% within Age Category
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%

% of Total
25.2%
26.8%
26.1%
15.6%
6.4%
100.0%

a. (df)=13287.96a(48) p<0.001

Set c
Prevalence of use of marijuana in the USA and the effect of gender.
Introduction
Marijuana is the most abused drug worldwide by people of all ages. It is also known as cannabis and is a psychoactive drug from the plant cannabis. Cannabis can be used as a recreational drug and in some extend; it can be used for medical purposes. Cannabis has this component that is known as tetrahydrocannabinol which is the main psychoactive compound with other 65 cannabinoids. Cannabis also contains 483 compounds related to the plant. It can be consumed in food substance, it can be smoked, vaporized or can be used as an extract. When consume, it has a stoned feeling and other general feelings such as relaxation, increased appetite, impaired short term memory among other side effects (Volkow, 2014). The onset of the effects of cannabis can be felt after some minutes when smoked and about 30 to 50 minutes when consumed in food substance and the effect lasts for a maximum of six hour. It has some physical effects such as increased heart rate and blood pressure. When used for a long term, it can lead to addiction and psychological effects such as paranoia or anxiety; it is also associated with respiratory infections
Background information
Marijuana has a long history of human consumption; it was mainly used for medical use as herbal medicine and is assumed that it was used in Asia in the year 500 BC. In America, it was used for textile and rope but was criminalized as a result of political and racial factors but it is becoming legal in the modern world (Stoa, 2017). Today it is mostly used for recreational purpose than its medicinal value and is widely used in males more than in female (Schepis, 2011).
Methods
This research study studies data obtained from the National Household Survey on Drug Abuse (NHSDA) survey. A survey by the Department of Health and Human Services of the National Institute on Drug Abuse in USA. Two variables were used; Marijuana Ever Used(MRJFLAG) and SEX Imputation Revised(IRSEX).
Analysis was done using IBM SPSS Statistical version 20.Descriptive statistics were used to describe the study sample. Marijuana use in either genders was compared using frequencies and percentages in a cross table. Since both variables were categorical, correlation tests were done using the Chi Square test.

Results
Table 1;MARIJUANA USE by SEXa

SEX
Total

Male
Female

MARIJUANA – EVER USED
Never used
Count
7961
10855
18816

% within Ever used
42.3%
57.7%
100.0%

% within SEX
61.3%
68.5%
65.3%

% of Total
27.6%
37.6%
65.3%

Ever used
Count
5027
4989
10016

% within Ever used
50.2%
49.8%
100.0%

% within SEX
38.7%
31.5%
34.7%

% of Total
17.4%
17.3%
34.7%

Total
Count
12988
15844
28832

% within Ever used
45.0%
55.0%
100.0%

% within SEX
100.0%
100.0%
100.0%

% of Total
45.0%
55.0%
100.0%

a. x2=(1, N=28832=163.960a, p<.01)

Table 1 show that 34.7%of the population has ever used marijuana. Of this 50.2% were male while 49.8% were female. From the gender angle, 38.7% of males had used marijuana compared to the 31.8% of females who had ever used marijuana. 65.3 % of the population had never used marijuana, of this, 42.3% were male which represented 61.3% of the male gender while 57.7% were female representing 68.5% of the female gender.
The chi test (x2=(1, N=28832=163.960a, p<.01)) showed that there was a significant statistical relationship between marijuana use and sex/gender.
Discussion
Form the frequencies and percentages results above we can see that more males than females had ever used marijuana in their lifetime and an even larger fraction of males amongst the male sex had ever used marijuana compared to their female counterparts. This suggests a strong relationship between gender and marijuana use. From this frequencies and percentages we can say that the male gender has used or uses marijuana more than females. The correlation test also suggests a strong significant relationship between gender and marijuana use. This study thus concludes the rate of marijuana use in the United States of America is 34.7 percent and that marijuana use is more prevalent in males than females.

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