This paper will address the relationship between healthcare, gender and race in the central valley. My classmate and I have been conducting the study through the telephone surveys for a period of the four weeks. I gathered both qualitative and quantitative data from the target respondents. I spent five hours in each session carrying out the surveys. The study was a combination of surveys conducted during last semester and this semester during the community survey. My target population was 1,100 respondents from Central Valley. I conducted this survey using random sampling technique. I derived my data from respondents with the published telephone numbers. The respondents were from Fresno, Kings, Madera and Tulare counties. Data analysis was done using chi-squire to show the correlation between gender, race and several other variables related to healthcare.
The first data was analyzed to show the relationship between people’s opinions and their government in providing healthcare to the poverty-stricken. The responses were rated on the scale rates of strongly disagree, disagree, agree, and strongly agree. Out of 812 respondents, there were only 551 valid responses. From the 551 total counts, 69.3% were white, 21.2% Hispanic and 9.4% of other races, who agreed to answer the survey. From the analyses, 83.3% of the white respondents strongly disagreed, 84.0% disagreed, 76.6% neither agreed nor disagreed, and 58.9% strongly agreed. Of the Hispanic respondents, 9.0% strongly disagreed, 10.6% disagreed, 19.1% were neither, 26.8% agreed, and 21.2% strongly agreed. Analysis of respondents from other races showed that 7.7% strongly disagreed, 5.3% disagreed, 13.2% neither agreed nor disagreed, 18.0% agreed, and 9.4% strongly agreed. The chi-square statistic test showed .000, with 99.9% accuracy. Therefore, it can be stated that there is a significant correlation between race and respondents’ opinion on whether the government should provide healthcare for the poor. Looking at the three categories of race, it can be noted that more respondents either strongly agreed, or agreed. Whites were prevalent in all scales, as we can see there were many, who strongly disagreed and strongly agreed. I was expecting that Hispanics and other races would strongly agree rather than just agree. From the study, the majority of the white respondents either strongly disagreed or strongly agreed. Therefore, we do not conclude that neither all whites have adequate healthcare nor are they rich but rather struggling to make the ends meet.
The second analysis that I conducted was developed to determine whether there was any (significantly strong) relationship between people’s race and the availability/unavailability of the insurance during the last five years (Table 2). Similarly, a total of 812 respondents were contacted; only 583 of them or 71.8% provided valid responses. After grouping these 583 respondents into their respective races, it was found that 70.8% percent of all respondents were white, 20.4% of respondents were Hispanic, and the remaining 8.7% comprised of other races. Upon tabulating the respondents’ answers to the question of whether they had been able to access insurance (at any given point) for the past five years, it was found that a total of 125 respondents answered in the affirmative way. In other words, it was found that a total of 125 individuals had no access to insurance at least at one point within the last five years (Dwyer, 1994). Upon further analysis of these results, it was found that 51.2% of the respondents were white, 37.6% were Hispanic, and 11.2% were members of other races. Conversely, it was found that a total of 458 participants responded negatively; they had not been able to access an insurance cover at any point within the last five years. Of these 458 respondents 76.2% were whites, 15.7% were Hispanics, and 8.1% were the members of other races. From the analysis, it is clear that the majority of whites (76.2%) have had insurance cover, while the majority of respondents from other races did not have insurance cover in the last five years. The percentage of whites, who had insurance cover for the last five years, is also high as compared to that of Hispanics. Respondents from other races had the least number among those who had an insurance cover within the last five years.
Furthermore, the results indicate that a lower portion of white Americans (compared to what was initially expected) had at some point been without insurance. Conversely, the estimate was overshadowed by the actual results for both Hispanics and members of other races. Based on this, it becomes clear that insurance is more readily available for whites than it is for either Hispanics or members of other races. Finally, it should be noted that upon calculating the chi-square statistic test, the result for asymptotic significance (2 sided) was also .000. This result indicates that with 99.9% accuracy, there is a relatively strong correlation between race and the availability/unavailability of insurance within any point of time during the last five years. As already mentioned, whites appear to have more access to insurance relative to other races being considered in the analysis. These results, therefore, have significant (public) health implications. Additionally, programs that promote insurance to all people regardless of their race should be developed.
The third and final analysis that I conducted was meant to determine the respondent’s opinion on the quality of the current healthcare services provided by the government (Table 2). In this research, 812 initial respondents were available, although only 589, or 72.5% of them, provided valid responses. In breaking down these 589 respondents by their respective races, it was found that 70.5% percent of all respondents were white, 20.4% of respondents were Hispanic, and the remaining 9.2% comprised of other races. Upon tabulating the respondents’ answers to the question of how they reviewed the quality of currently available healthcare services, it was found that a total of 125 respondents answered in the affirmative way. In other words, it was found that a total of 162 individuals reviewed them as being fair to very poor. Upon further analysis of these results, it was found that 113 of the 162 respondents (69.8%) were whites; the remaining 49 were divided as follows: 28 (33%) were Hispanics; 21 (14.9%) were members of other races. Conversely, it was found that a total of 427 respondents reviewed the current healthcare services as being good to excellent in terms of quality. Upon further analysis of these results, it was found that 302 of the 427 respondents (70.7%) were whites; the remaining 125 were divided as follows: 92 (21.5%) were Hispanics; 33 (7.7%) were members of other races.
Upon analyzing the results obtained from the last question that the respondents were asked, it becomes clear that the vast majority of them review the existing healthcare services (provided by government) as having a good to excellent quality. This is surely a positive result, at least in principle, because it points to the fact that the majority of the people living in the communities under study are satisfied with the quality of the healthcare available to them. Furthermore, the results indicate that a lower portion of white Americans (compared to what was initially expected) reviewed the quality of healthcare as fair to very poor; it was the same for Hispanics. In fact, the only group that reviewed the quality of healthcare as being fair to very poor (in a greater measure than was originally expected) was that comprised by other races. Finally, it should be noted that upon calculating the chi-square statistic test, the result for asymptotic significance (2 sided) was also .102. This result indicates that with 99.9% accuracy, there is also strong correlation between race and the opinion of quality of existing healthcare programs. Whites and Hispanics have a generally more positive opinion of the quality of existing healthcare. Given that this is not the case for the other races group; the results may potentially have serious implications in terms of the future improvements of healthcare programs and built-in provisions for equality and universal access.
The paper data concluded in the paper describes how the healthcare programs assist the world and the community. It further describes the way the health programs help in ensuring that equality is accessed universally. The data tables of the survey conducted act as the exhibits on the variance of the programs.