Exploring the Variables Affecting Life Satisfaction
Part 1: Data
The BRFSS (Behavioral Risk Factor Surveillance System) is a body of research which collects and manages the data related to the non-institutionalized population aged 18 or more from all the 50 states of United States of America including the District of Columbia (DC) and unincorporated territories: Guam, Puerto Rico, American Samoa, Federated States of Micronesia and Palau. This is maintained by the Centers for Disease Control (CDC), with the focused target of prevention of chronic diseases by adopting preventive health practices and behavioral risks associated with chronic disease and other related disorders.
Generalizability and Causality of Data No experiments have been done to record the data therefore this is purely an observational study of US residents, which has its own bias. The collection of data from the population is done by agents appointed for the purpose who may rationally add additional questions to a subset of the original sample. Though the sample is sufficiently large but it may not be random, hence again is biased to some extent. Regarding generalizability, as the data has been collected from all the 50 states of US, it may be considered generalizable for US population and residents residing therein.
Part 2: Research questions
Research quesion 1: The review of literature has identified various variables which may affect the general health like smoking habit, drinking tendency etc, I would like to study the relationship between the two. “How does Emotional Support affects the General Health?”
Research quesion 2: There is one thing which is being searched and looked for by Human Beings is happiness which is directly associated with Satisfaction of Life. Fortunately, on this variable, data has been collected. I would like to study the impact of Income Leve and Education Level on Satisfaction with Life. The analysis of this research question will tell us whether Life satisfaction is associated with Income and Education? This may give a clue about achieving something different than these for better satisfaction. “How does Income and Education Level is associated with Satisfaction of Life?” Or Does more education lead to more income which in turn leads to higher Life Satisfation?
Research quesion 3: It is well said that a person will gain high satisfaction in life if he is healthy and employed. With this context, I would like to study whether there is a relationship between General Health and Employment Status with Satisfaction of Life?
Part 3: Exploratory data analysis
Research quesion 1: (Two Variables) The first research questions studies the relatonship between Emotional Support and General Health. For this purpose I would like to see the levels in both the variables.
## [1] "Excellent" "Very good" "Good" "Fair" "Poor"## [1] "Always" "Usually" "Sometimes" "Rarely" "Never"Now let us prepare a cross tabulation of relationship between the two variables i.e. Emotional Support and General Health
##
## Excellent Very good Good Fair Poor
## Always 1012 2041 2022 951 501
## Usually 280 751 709 345 171
## Sometimes 95 281 531 448 301
## Rarely 34 84 145 136 108
## Never 48 96 179 155 147
Analysis of Research Question 1 From the above table and graph it can be concluded that there is a direct relationship between Emotional Support and Good Helath. Those who have always been getting Emotional Support were found good in health. Those who have achieved Excellent, Very Good and Good health, the proportion of “Always” and “Ususlly” getting emotional support is very high as compared to those having Fair and Poor health. Hence it can be conculded that Emotional Support plays a very important role in being Healthy
Research quesion 2: (Three Variables) The second research question comprising of Three Variables proposes to study, how Income and Education Level is Associated with Satisfaction of Life
Starting with understanding the three variables, first of all, I would like to know the levels of the variables i.e. Income, Eduation and Satisfaction of life.
## [1] "Less than $10,000" "Less than $15,000" "Less than $20,000"
## [4] "Less than $25,000" "Less than $35,000" "Less than $50,000"
## [7] "Less than $75,000" "$75,000 or more"## [1] "Never attended school or only kindergarten"
## [2] "Grades 1 through 8 (Elementary)"
## [3] "Grades 9 though 11 (Some high school)"
## [4] "Grade 12 or GED (High school graduate)"
## [5] "College 1 year to 3 years (Some college or technical school)"
## [6] "College 4 years or more (College graduate)"## [1] "Very satisfied" "Satisfied" "Dissatisfied"
## [4] "Very dissatisfied"Now let us prepare a cross tabulation of relationship between the variables i.e. Education Level and and Life Satisfaction
##
## Very satisfied
## Never attended school or only kindergarten 3
## Grades 1 through 8 (Elementary) 171
## Grades 9 though 11 (Some high school) 373
## Grade 12 or GED (High school graduate) 1585
## College 1 year to 3 years (Some college or technical school) 1379
## College 4 years or more (College graduate) 1868
##
## Satisfied
## Never attended school or only kindergarten 8
## Grades 1 through 8 (Elementary) 291
## Grades 9 though 11 (Some high school) 577
## Grade 12 or GED (High school graduate) 1853
## College 1 year to 3 years (Some college or technical school) 1467
## College 4 years or more (College graduate) 1310
##
## Dissatisfied
## Never attended school or only kindergarten 0
## Grades 1 through 8 (Elementary) 24
## Grades 9 though 11 (Some high school) 93
## Grade 12 or GED (High school graduate) 219
## College 1 year to 3 years (Some college or technical school) 166
## College 4 years or more (College graduate) 96
##
## Very dissatisfied
## Never attended school or only kindergarten 0
## Grades 1 through 8 (Elementary) 10
## Grades 9 though 11 (Some high school) 35
## Grade 12 or GED (High school graduate) 51
## College 1 year to 3 years (Some college or technical school) 43
## College 4 years or more (College graduate) 22
##
## Very satisfied Satisfied Dissatisfied Very dissatisfied
## Less than $10,000 238 461 113 52
## Less than $15,000 309 548 101 27
## Less than $20,000 374 594 52 19
## Less than $25,000 398 572 58 16
## Less than $35,000 517 587 67 8
## Less than $50,000 634 589 43 8
## Less than $75,000 708 504 28 1
## $75,000 or more 1112 563 28 3
##
## Less than $10,000
## Never attended school or only kindergarten 121
## Grades 1 through 8 (Elementary) 2600
## Grades 9 though 11 (Some high school) 4270
## Grade 12 or GED (High school graduate) 9413
## College 1 year to 3 years (Some college or technical school) 6104
## College 4 years or more (College graduate) 2873
##
## Less than $15,000
## Never attended school or only kindergarten 73
## Grades 1 through 8 (Elementary) 1993
## Grades 9 though 11 (Some high school) 3714
## Grade 12 or GED (High school graduate) 10837
## College 1 year to 3 years (Some college or technical school) 7087
## College 4 years or more (College graduate) 3037
##
## Less than $20,000
## Never attended school or only kindergarten 78
## Grades 1 through 8 (Elementary) 2015
## Grades 9 though 11 (Some high school) 4126
## Grade 12 or GED (High school graduate) 14513
## College 1 year to 3 years (Some college or technical school) 9606
## College 4 years or more (College graduate) 4455
##
## Less than $25,000
## Never attended school or only kindergarten 50
## Grades 1 through 8 (Elementary) 1420
## Grades 9 though 11 (Some high school) 3516
## Grade 12 or GED (High school graduate) 16999
## College 1 year to 3 years (Some college or technical school) 12510
## College 4 years or more (College graduate) 7165
##
## Less than $35,000
## Never attended school or only kindergarten 52
## Grades 1 through 8 (Elementary) 1131
## Grades 9 though 11 (Some high school) 2872
## Grade 12 or GED (High school graduate) 18153
## College 1 year to 3 years (Some college or technical school) 15396
## College 4 years or more (College graduate) 11191
##
## Less than $50,000
## Never attended school or only kindergarten 31
## Grades 1 through 8 (Elementary) 566
## Grades 9 though 11 (Some high school) 1954
## Grade 12 or GED (High school graduate) 18857
## College 1 year to 3 years (Some college or technical school) 19798
## College 4 years or more (College graduate) 20249
##
## Less than $75,000
## Never attended school or only kindergarten 23
## Grades 1 through 8 (Elementary) 243
## Grades 9 though 11 (Some high school) 1062
## Grade 12 or GED (High school graduate) 14848
## College 1 year to 3 years (Some college or technical school) 19865
## College 4 years or more (College graduate) 29145
##
## $75,000 or more
## Never attended school or only kindergarten 28
## Grades 1 through 8 (Elementary) 288
## Grades 9 though 11 (Some high school) 1003
## Grade 12 or GED (High school graduate) 15040
## College 1 year to 3 years (Some college or technical school) 25651
## College 4 years or more (College graduate) 73800
Analysis of Research Question 2
In research question 2, there are three variable. The association of each variable has been analysed with other in such a way that there are three combinations formed which are discussed as under:
1. Association of Education Level with Life Satisfaction : From the table and the bar chart shown in Fig 2 above, it can be clearly said that there is a positive association between the education level and life satisfaction. Those who are college graduates for 4 years and up to 3 years are mostly present in “Very Satisfied” category than those who are just 12th pass or below. Hence those who are well educated are having better satisfaction of life than those who have not studied well.
2. Association of Income Level with Life Satisfaction : From the table and graph shown in Fig 3 above, it can be seen that income and money also plays significant role in life satisfaction. THose who are in “Very Satisfied” and “Satisfied” category of ‘Life Satisfaction’ variable are those who have higher income of Rs $35000 or more. Further, those who are earning higher say $75000 or more are in the “Very Satisfied” category.Conversly those who are earning less than $15000 are more in proportion in less satisfied categories. Further there are only 3 people who are earning more than $75000 but are very dissatisfied. Hence it can be concluded that earning/income plays a very important role in life satisfaction.
3. Association of Income Level and Education Level : As a part of Research Question 2, it would be interesting to see the relationship between Income and Education. It can be hypothesised as Income is dependent on Education as there is a direct relationship. More education lead to more income and therefore more satisfaction. In the table and Fig 4 abobe it can be clearly seen that the people who have studies up to college level (Up to 3 years and 4 years) are earning higher than $75000. Further the categories of income less than $15000 are those who have studeies less than 12th class. Hence it can be stated that in order to have higher income, higher education must be taken.
Research quesion 3: The Third research question comprising of Three Variables proposes to study, how Health and Employment Level is associated with Satisfaction of Life
Starting with understanding the three variables, first of all, I would like to know the levels of the variables i.e. Employment. I have already seen the the levels of Health and Satisfaction of Live, so I will aviod the duplicacy.
## [1] "Employed for wages" "Self-employed"
## [3] "Out of work for 1 year or more" "Out of work for less than 1 year"
## [5] "A homemaker" "A student"
## [7] "Retired" "Unable to work"Now let us prepare a cross tabulation of relationship between two variables i.e. Employment Level and and Life Satisfaction
##
## Less than $10,000
## Never attended school or only kindergarten 121
## Grades 1 through 8 (Elementary) 2600
## Grades 9 though 11 (Some high school) 4270
## Grade 12 or GED (High school graduate) 9413
## College 1 year to 3 years (Some college or technical school) 6104
## College 4 years or more (College graduate) 2873
##
## Less than $15,000
## Never attended school or only kindergarten 73
## Grades 1 through 8 (Elementary) 1993
## Grades 9 though 11 (Some high school) 3714
## Grade 12 or GED (High school graduate) 10837
## College 1 year to 3 years (Some college or technical school) 7087
## College 4 years or more (College graduate) 3037
##
## Less than $20,000
## Never attended school or only kindergarten 78
## Grades 1 through 8 (Elementary) 2015
## Grades 9 though 11 (Some high school) 4126
## Grade 12 or GED (High school graduate) 14513
## College 1 year to 3 years (Some college or technical school) 9606
## College 4 years or more (College graduate) 4455
##
## Less than $25,000
## Never attended school or only kindergarten 50
## Grades 1 through 8 (Elementary) 1420
## Grades 9 though 11 (Some high school) 3516
## Grade 12 or GED (High school graduate) 16999
## College 1 year to 3 years (Some college or technical school) 12510
## College 4 years or more (College graduate) 7165
##
## Less than $35,000
## Never attended school or only kindergarten 52
## Grades 1 through 8 (Elementary) 1131
## Grades 9 though 11 (Some high school) 2872
## Grade 12 or GED (High school graduate) 18153
## College 1 year to 3 years (Some college or technical school) 15396
## College 4 years or more (College graduate) 11191
##
## Less than $50,000
## Never attended school or only kindergarten 31
## Grades 1 through 8 (Elementary) 566
## Grades 9 though 11 (Some high school) 1954
## Grade 12 or GED (High school graduate) 18857
## College 1 year to 3 years (Some college or technical school) 19798
## College 4 years or more (College graduate) 20249
##
## Less than $75,000
## Never attended school or only kindergarten 23
## Grades 1 through 8 (Elementary) 243
## Grades 9 though 11 (Some high school) 1062
## Grade 12 or GED (High school graduate) 14848
## College 1 year to 3 years (Some college or technical school) 19865
## College 4 years or more (College graduate) 29145
##
## $75,000 or more
## Never attended school or only kindergarten 28
## Grades 1 through 8 (Elementary) 288
## Grades 9 though 11 (Some high school) 1003
## Grade 12 or GED (High school graduate) 15040
## College 1 year to 3 years (Some college or technical school) 25651
## College 4 years or more (College graduate) 73800
##
## Very satisfied Satisfied Dissatisfied Very dissatisfied
## Excellent 997 456 22 5
## Very good 1914 1278 70 6
## Good 1550 1916 132 31
## Fair 647 1175 167 42
## Poor 265 670 202 76
##
## Excellent Very good Good Fair Poor
## Employed for wages 43990 78534 60875 15825 2476
## Self-employed 10232 14271 11283 3198 709
## Out of work for 1 year or more 1636 3332 4862 3006 1172
## Out of work for less than 1 year 1971 3588 4263 1859 501
## A homemaker 5663 9786 9937 4811 1318
## A student 3291 4978 3400 861 124
## Retired 17110 41216 46701 23602 8937
## Unable to work 955 2530 8090 13050 12510
Analysis of Research Question 3
The third research question attempts to discuss how health and employment level leads to Life Satisfaction, further discussing the relationship between health and employment. These are discussed as under:
1. Association of Employment Level with Life Satisfaction: From the table and Fig 5 above, it can be seen that those who are Very Satisfied have more proportions of Self Employed and Employed for Wages. This shows a direct relationship between having employment or being self dependent and Life Satisd=faction
2. Association of Health and Life Satisfaction: From the table and Fig 6 above it can be said that there is a direct relationship between good health and life satisfaction. Most of the healthy people are in either Very Satisfied of Satisfied category of Life Satisfaction. On observing table, only 5 and 6 people having Excellent and Good Heath respectively are in dissatisfied category of Life Satisfaction. Therefore it can be concluded that there is a positive and direct relationship between Health and Life Satisfaction
3. Association of Employment and Health: From the table and Fig 7 above, it can be seen that there is more proportion of people who are self dependent (Self Employed, Employed for Wages and Retired) in Health Category. Majorty of people who are having good health are working. In table it can be seen and concluded that the people those are having bad health are unable to work. It can also be said that the people are not able to work only because they are having health issues.
Final Conclusion
From the above study it can be concluded that the life satisfaction depends on a large number of factors such as Health, Education, Income and Employment Status. Health, is directly affected by Emptional Support, which in turn increases life satisfaction. Higher Education increases the income which in turn affects Life Satisfaction. Therefore in order to be satisfied in life, one must study well, work hard and earn more. This all will be possible only if Good Health is there which is supported by Emotions. Hence Be Happy and Be Healthy