Gender Analysis on Perception of Quality of Life
Regarding Urgent Needs and Limited Resources
 

Baomei Zhao
Victor Wilburn
University of Akron

Literature Review

     “Quality of life” denotes a set of wants, the satisfaction for which makes people happy. It reflects a combination of the subjective feelings and objective status of the “well-being” of people and the environment in which they live at a particular point in time.
     The search for quality of life indicators is an attempt to obtain new information that will be useful to evaluate the past, guide the actions of the present, and plan for future improvement. The empirical measures of various levels of quality of life used by Americans are aimed at the identification of strengths and weaknesses of the national health so that decision makers, public or private, can be assisted as they seek to evaluate, guide, and plan for a better quality of life.
     In relation to quality of life, there is little agreement about the meaning of the term itself. There are rival factions each strongly urging the adoption of a different approach and a lot of measures purporting to address quality of life. As a consequence, there are doubts about the wisdom of using quality of life as an outcome that could influence the lives of the general public (Andrews & Withey, 1976).      
     This situation has been perpetuated by two common and somewhat contradictory attitudes among researchers on the topic. The first attitude is exemplified by those who state categorically that there is general agreement on the components that make up quality of life. This statement is, however, never supported by information about who was involved in this general agreement, or where and when it was achieved (Campbell, Converse, & Rodgers, 1976). That such a consensus does not exist is evidenced by the fact that there are in existence a number of models of quality of life, that are by no means in agreement about the structure of the concept. In fact it is acknowledged that there is wide dissent about the meaning of the term -- quality of life, how to measure it, and whether it should be measured at all. Clinicians, economists, psychologists, sociologists, philosophers and health research scientists, all have different perspectives which, most often, reflect the preoccupations of their particular discipline. In addition, the stance adopted may be influenced by the requirements of funding bodies, both public and private that have their own agendas (Andrew & Withey, 1976). 
     The researchers who are of the second attitude justify a laissez faire use of measures by pointing out that there is no gold standard for quality of life. This statement apparently confers the freedom to measure in any way and or any means that the researcher fancies or finds convenient. Thus quality of life may appear as health status, physical functioning, perceived health status, subjective health, health perception, symptom, need satisfaction, individual cognition, functional disability, psychiatric disturbance, well-being, and often, several of these at the same time. “Thus indicators of quality of life have ranged from the purely physiological through functional capacity to complex series of questionnaires on social activities and psychological problems” (Hunt, 1997).
     Although the disagreement exists, currently there are two basic approaches to the measurement of quality of life. The so-called “objective” (Andrews & Withey, 1976) measures are selected and refined from the Census and other repositories of regularly collected statistical data. Examples for “objective” items are population, employment status, education level, health index, age, gender, housing, recreation, and income. The so-called “subjective” (Andrews & Withey, 1976) indicators are obtained through polls and surveys asking people about their quality of life as they experience it and/or perceive it from their environment. Examples are mental health and happiness, self-rated stress, financial well-being and satisfaction.
     Richard Easterlin (1974, 1995) was one of the first economists to study statistics over time on the reported level of happiness. His 1974 paper suggested that individual happiness appears to be the same across poor countries and rich countries. Researchers should think of people as obtaining utility from a comparison of themselves with others close to them, “Happiness is relative.” Because individuals are all moving up together, the benefit of higher total national income will mean less to an individual. He also found that economic growth does not raise well-being. By testing whether reported happiness rose as national income did, he concluded: “In the one time series studied, that for the United States since 1946, higher income was not systematically accompanied by greater happiness.”
     Andrew Oswald analyzed subjective well-being and estimated a well-being regression equation of the form “reported well-being = f (personal characteristics).” Oswald found that the equation held true “across different periods, different countries, and even different measures of well-being.”  This finding illustrates two points as follows: (1) “Reported happiness is high among those who are married, high income, women, whites, the well-educated, the self-employed, the retired, and those looking after the home” (p1795)(Oswald ,1997); and (2) “Unemployed people are very unhappy”  (Oswald, 1997). This is in accord with the Eurobarometer data (Warr et al, 1988).
     To explore the idea that money buys happiness, Humphry (1992) discussed the notion of and evidence for rational suicide. Oswald (1997) revealed the fact that “total suicide deaths reached their maximum in the Great Depression, which is consistent with the idea that economics may have some role to play in this area.” (p.1801) Charlton, Kelly, Evans, Jenkins, and Wallis (1992) showed that “the suicide death rate is largely independent of social class.” Thus generally speaking, people of different income levels treat their lives in the same way. But they also found the exception that “men unemployed and seeking work at census, were at 2-3 fold greater risk of suicide death than the average. … But married men commit suicide — holding age constant—only one third as often as other” (p.92) (Charlton, Kelly, Evans, Jenkins, & Wallis, 1992).
     Identified variables can include gender, race, age, marital status, education, etc. They are pervasive qualities that affect a person’s social standing so that all of them might be expected to have an important impact on one’s quality of life, but this has not been uniform. Most studies on the relationship between quality of life and gender have found no relationship or a relatively low correlation. But it would be meaningful to investigate the gender difference regarding urgent needs and use of the community-based human services, so that the actions to improve the quality of life can be designed properly.
     As mentioned above, quality of life is a subjective and a comparative notion. Perceptions of one’s financial situation can combine subjective and objective standards and reflect personal subjective perceptions, i.e., the comparison of one’s previous situation instead of comparison to someone else’s situation. This can be applied to all income levels. Examples of these kinds of variables are: sufficient money for monthly bills, emergencies in basic needs, or anyone in the family saving or investing for retirement? Housing (ownership of the residence) is highly correlated with well-being and quality of life. Income is also found highly correlated with health, and both variables affect the quality of life, especially for senior citizens (Liu, 1976).
     Community quality of life is also multi-dimensional; it is contingent on the social science field of interest and the specific focus of research. Proshansky and Fabian (1996) have suggested that a better understanding of community quality of life will be obtained from research questions that are more specific in their focus. For example, the research question is “What kind of quality, for what kinds of people, and in what kinds of places?”
     Researchers have examined and illustrated numerous resources in different communities that serve to impact the welfare of the individual (Shin, 1980). These resource indicators can be grouped under categories such as economic, social, political, health and education, and environmental conditions. Underwood (2000) suggested that community quality of life research should adhere to the policy-based nature, only those resources indicators subject to reasoned policy choice qualify as proper components of community quality of life measure. Since many resources affecting quality of life (e. g., climatic conditions, geography, etc.) are not subject to modification by government, business, and community service agents; they should not be included as part of the conceptualization and measurement of community quality of life (Shin, 1980). The resource indicators measured in the Shin study included public schools, medical care, housing, government services, and neighborhood safety.
     A predictive model of community quality of life was developed by Widgery (1982) and focused on both community and neighborhood. Wagner (1995) conducted a study with the Regional Plan Association and Quinnipiac College Polling Institute of Hamden Connecticut. “The survey covered five metropolitan areas in an attempt to pin down how community residents define quality of life.” (p.18) At the top of the list were low crime and safe streets, followed by important issues like “high-quality public schools, a good personal financial situation, strong family, and good health.” (p20)
     The research to date, however, has been relatively limited with regard to quality of life and community–based human services. The task of measuring quality of life is a difficult and relatively unconventional one.
     Based on a new hypothesis that absolute levels of community resources might explain the variations that are seen in perceptions of quality of life and that relative levels of access to community resources might also explain variations seen in perceptions of quality of life, this research investigates quality of life using individual characteristics, household characteristics, and community-based human services. It provides community leaders with a more refined tool to determine the specific perceptions of quality of life in the community by the residents, as well as to improve the quality and use of human service in the community.

Methodology

     This section explains the methodology applied to this research in two subjects: (a) sampling and data collection, and (b) operationalizing variables and analysis.
Sampling and Data Collection
     Heath (2003) at the University of Kentucky Research Center for Families and Children (RCFC) conducted a study to assess knowledge and use of human services in the Lexington-Fayette County area.  The Self-Assessment Study (Heath, 2003) was conducted by the Research Center for Families and Children with survey assistance by the University of Kentucky Survey Research Center. Both centers are located at the University of Kentucky. The study was funded by LexLinc--a nonprofit organization in Lexington, Kentucky.
     The sample was initially drawn using the Info Time Polk Directory distributed by Equifax (2002). This directory has listed information for all households in Lexington-Fayette County, Kentucky. A simple random sample of 11,500 households was drawn across all census tracts in Lexington-Fayette County to ensure that there would be enough households in the sample pool to complete both the telephone and mailed phases of the study. After the matching and cleaning process to obtain telephone numbers where none were originally listed, a smaller random sample of 4,700 was drawn resulting in 3,606 households for the telephone survey sample and the remaining 1,094 for the mailed survey sample. Calls were conducted by the University of Kentucky Survey Research Center from March 22-April 18, 2002. Up to 22 attempts were made by telephone per sample household at various times during the day and evening (Heath, 2003).
     Mailed surveys were used to reach households drawn in the sample who did not have telephone service or for which no number was found. Statements in Spanish inviting participation in the survey through either a phone interview in Spanish or a mailed survey in Spanish were included in a cover letter. The mailed portion of the study began May 10, 2002 and was completed June 25, 2002.
     The number of completed surveys was 1561 (1237 telephone surveys and 324 mailed surveys). “The margin-of-error for the survey is less than ± 2.5% at the 95% confidence level” (Heath, 2003). Individuals must have been 18 years old of age or older to participate in the interview. Randomly selected Lexington residents answered questions regarding their financial needs, income support, needs of the elderly, employment, childcare needs, physical and mental health needs, and characteristics such as ethnicity, last grade of school completed, martial status, and number of people in their household.
     The data for this research were organized into three vectors according to the family systems theoretical model: Vector 1: data on individual characteristics, Vector 2: data on household characteristics, and Vector 3: data on use of community-based human services. The questions addressed in the three vectors are shown in Figure 1. In Vector 1, the variables are gender, age, racial/ethnic background, education, marital status, and ownership of residence. In Vector 2, the variables are number of people in the household, household income, whether children in the household, whether senior citizens in the household, household financial situation, household income supports, and whether household experienced an urgent basic need. And in Vector 3, neighborhood safety, awareness of availability of social services, transportation services, childcare, financial emergency services, and overall needs are investigated.
     The dependent variable was assessed at the end of the overall assessment of needs questionnaire, the key question is “Thinking about the needs of you and your household and thinking about the issues in this survey, overall, how do you perceive your situation in life? Would you say you are: (1) thriving, (2) safe, (3) stable, (4) at-risk, or (5) in-crisis?”  This question with resulting response options was derived for use based on the development and use of this same scale by Community Action Council as the basis on which to judge clients’ needs.  The scale has also been adopted by the local Salvation Army for use in their assessment of clients.
Sample Description
This section reports the sample and characteristics using descriptive statistics in the order of the three vectors of individual, household, and community. When the respondent was asked to think, overall, about himself or herself, their household, and the issues of the survey, respondents report their perceived quality of life (n=1547): 6.0 percent reported in-crisis or at risk, 64.5 percent stable or safe, and 29.5 percent thriving (see Table 1).
Characteristics of Respondents’ Individual Characteristics
     Of the respondents, 61.5 percent were female. Respondents’ average age is within the range of 35-44 years, with a mode of 55 years old or above; 88.4 percent identified themselves as white.  Almost three out of five (58.4%) were currently married. About three quarters of respondents (77.1%) own their residence. Regarding education, 21.2 percent had a high school diploma, GED or less, 27.4 percent had some college but no degree/Vocational-technical degree; 51.4 percent had bachelor degree or more (see Table 2).
Characteristics of Respondents’ Household
     Regarding household, the average household size is 2.48 with 22.7 percent of the households with only one member, and 38.8 percent of households with two people; 64.9 percent of households reported no child under the age of 18 in the household (see Table 3). In the 35.1 percent of households with a child under the age of 18, the average number of children was 1.76. For 20.1 percent of households with someone 65 years of age or older, the average size of the household is 1.36 persons. 82.3 percent of households report overall physical health as good or excellent compared to 17.7 percent of households report overall physical health as poor or fair.  Regarding income, 17 percent reported income at $25,000 or below, 33 percent reported between the ranges of $25,001 - $50,000; and 50 percent reported $50,001 or above.
Characteristics of Respondents in Vector 3: Community-based Human Services
     Regarding community-based human services, the majority of respondents (92.5%) reported living in a safe neighborhood. At least 93 percent reported not using Lextran -- the public transportation service, 75.9 percent reported not having friends or family pick them up. Regarding financial assistance, approximately 50 percent reported turning to family or friends, 20 percent reported turning to church or clergy, 26 percent reported turning to banks, 5.6 percent reported turning to Lexington Housing Authority, 9 percent reported turning to utility companies, 9.4 percent reported turning to Community Action Council or Department of Community-based Services, 11 percent reported turning to food banks, 11 percent reported turning to the Salvation Army, 8.6 percent reported turning to Catholic Social Services, and about 6 percent report turning to other person or agency.  Regarding income support during the past twelve months, 21.8 percent of households reported support from social security/survivor income, and 19.3 percent reported support from Medicare (see Table 4).

Gender Analyses

     In total sample of 1561 respondents, 957 (61.5%) were female, and 598 (38.5%) were male—with 6 missing.
     With regard to the correlation between perception of quality of life and the community-based human services (see Table 5), out of sixteen variables, nine were statistically significant for females and four for males. The nine variables statistically significant for females are: neighborhood safety (.10); transportation: whether use LexTran service (-.11), have family or friends to provide transportation (-.11); sufficient activities in Lexington for teenagers 14-17 (.09), who to turn to when financial assistance is needed: family or friends (-.15), Community Action Council or Department of Community-based Services (-.13), food banks (-.07); during the past 12 months received income from: social security/survivor income (-.09) and Medicare (-.13). The four variables statistically significant for males are: neighborhood safety (.16); transportation: whether use LexTran service (-.12), whether have family or friends to provide transportation (-.13); who to turn to when financial assistance is need: family or friends (-.10).
     Then urgent needs were also investigated (see Tables 6-7). Urgent needs were in six perspectives, whether worry that food will run out before getting money to buy more, whether worry about paying mortgage or rent, whether worry about being able to pay utility bills, whether the respondent has enough income to pay for prescription drugs the family needs, whether the respondent has enough income to pay for family’s medical needs, and whether the respondent has enough income to pay for family housing.
     As Table 6 shows, although there is no gender difference in perception of quality of life, females reported higher percentage of urgent needs in these four perspectives than the males; they worry that food will run out before getting money to buy more, worry about being able to pay utility bills, worry about prescription drugs the family needs, and worry about the family’s medical needs.
     With regard to the correlation between urgent needs and the community-based human services in the form of income support, results (see Table 7) are reported in the order of the six urgent needs perspectives.
     (1) Regarding whether the respondent worries that food will run out before getting money to buy more, six income support variables are statistically significant for females, they are financial assistance: turning to family and friends (.12), banks (-.07), Lexington Housing Authority (.11), utility companies (.12), Community Action Council or Department of Community-based Services (.19), and food banks (.18). Three income support variables are statistically significant for males, they are financial assistance: turning to family and friends (.15), Community Action Council or Department of Community-based Services (.10), and other persons and agencies (.09).
     (2) Regarding whether the respondent worries about being able to pay mortgage or rent, six income support variables are statistically significant for females, they are financial assistance: turning to family and friends (.15), church or clergy (.07), Lexington Housing Authority (.14), utility companies (.15), Community Action Council or Department of Community-based Services (.16), and food banks (.13). Two income support variables are statistically significant for males, they are financial assistance: turning to family and friends (.15), and the Salvation Army (-.09).
     (3) Regarding whether the respondent worries about being able to pay utility bills, five income support variables are statistically significant for females, they are financial assistance: turning to family and friends (.15), Lexington Housing Authority (.11), utility companies (.12), Community Action Council or Department of Community-based Services (.17), and Food Bank (.12). Only one income support variable is statistically significant for males, it is financial assistance: turning to family and friends (.18).
     (4) Regarding whether the respondent has enough income for prescription drugs the family needs, eight income support variables are statistically significant for females, they are financial assistance: turning to family and friends (-.09), Lexington Housing Authority (-.15), utility companies (-.14), Community Action Council or Department of Community-based Services (-.23), food banks (-.18), Catholic Social Services (-.08); during the past 12 months received income from: social security/survivor income (-.12), and Medicare (-.18). Four income support variables are statistically significant for males, they are financial assistance: turning to family and friends (-.16), utility companies (-.13), Community Action Council or Department of Community-based Services (-.18), and other persons and agencies (-.10).
     (5) Regarding whether the respondent has enough income for family’s medical needs, seven income support variables are statistically significant for females, they are financial assistance: turning to family and friends (-.16), Lexington Housing Authority (-.12), utility companies (-.09), Community Action Council or Department of Community based Services (-.22), food banks (-.15), Catholic Social Services (-.08), and during the past 12 months received income from Medicare (-.07). Only one income support variable is statistically significant for males, it is financial assistance: turning to family and friends (-.16).
     (6) Regarding whether the respondent has enough income for paying family housing, three income support variables are statistically significant for females, they are financial assistance: turning to family and friends (-.08), Community Action Council or Department of Community-based Services (-.11), and during the past 12 months received income from Medicare (-.07). Only one income support variable is statistically significant for males, it is financial assistance: turning to family and friends (-.12).
     The above results revealed the behavior similarity of females and males. Each group tended to turn to family and friends when financial assistance was needed. Although there were no gender differences in perception of quality of life, there were gender differences regarding urgent needs and the use of community human services. Community human services were very important resources for respondents with urgent needs, especially for female respondents.

Summary

     Although there was no gender difference in perception of overall quality of life, there were gender differences in urgent needs and the use of community-based human service. Female’s and male’s association of perception of quality of life and use of human services were similar regarding neighborhood safety, public transportation service, transportation help from family or friends, and turning to family or friends for financial assistance. However, female respondents were more likely to indicate that sufficient activities for teenagers aged 14-17 affected their perceptions of quality of life positively. Females also used more services than the males, especially in Community Action Council or Department of Community-based Services, social security/survivor income, and Medicare. Females’ urgent needs were higher than males’ in percentage, and among the group of urgent needs, females were more likely to use community income support than males. Females were more likely to obtain services from housing authority, Community Action Council or Department of Community-based Services, food bank, the Salvation Army, Catholic Social Services, and Medicare.
Implications
     Based on the family systems theory, the investigation into perceptions of quality of life was addressed in three domains: individual characteristics, family situation, and community human services.  This approach is a contribution to the research on quality of life as it applies a new way of looking at the components of quality of life.  Specifically, the impact of community-based human services and urgent needs on perceptions of quality of life was addressed.  In addition, respondents were broken into sub-groups according to their gender. This made it possible to determine what the main variables influencing perception of quality of life, and what community-based human services meet urgent needs. 
     In addition, this study provides baseline information concerning perceptions of quality of life and community human services among households in Lexington-Fayette County, Kentucky. The findings provide insights into residents’ perceptions of quality of life with their individual characteristics, family situation, and community human services as components contributing to perceptions of quality of life. The gender comparison of quality of life with urgent needs and the use of community income support services provided a broader context for interpreting perception of quality of life. This study also provided a useful way of understanding research on perceptions of quality of life and improving community services for the general public and urgent needs at the community level.
     Policy makers, educators, and social service providers can benefit from the findings of this study. Specifically, their efforts to improve quality of life should focus on those variables that have been shown to predict enhanced quality of life.  
     In addition to improving the availability of community-based human services to the general population, community human service providers should also focus special programs for subpopulations with urgent needs. According to the gender analysis in this study, although there was no gender difference in perception of quality of life, females reported a higher percentage of urgent needs in these four perspectives than the males. They worry that food will run out before getting money to buy more, worry about being able to pay utility bills, worry about prescription drugs the family needs, and worry about the family’s medical needs. Community housing authority, utility companies, Community Action Council or Department of Community-based Services, food banks and Medicare should develop special programs for the female population with urgent needs and give support to females in dealing with their hardships and becoming independent themselves.
Limitations
     The findings of this study are limited by their focus on primarily the Lexington-Fayette County population. The sample reflected the perception of quality of life with urgent needs of lower income population. As a result these findings do not accurately describe what factors contribute to the perceptions of quality of life and the association of quality of life with urgent needs and the community-based human services. In addition, the urgent needs investigated in the study were limited to financial needs without considering the other perspectives.
     Although there are limitations in this study, there are several significant conclusions that can be drawn as mentioned above, and the methodology can be applied to future research.   
Future Research
     Regarding future research, three perspectives are worth considering. (1) Not only the use of community human services, but also the quality of the services should be paid attention. For example, the service may be available, but the satisfaction level for the users of the service may be low, which may even have worse effect on ones perceptions of quality of life than no service. (2) Perceptions of quality of life are highly associated with urgent needs like worry for food, worry for utility bills, etc. Future research can prioritize to urgent needs and investigate the cause of the urgent needs, thus helping to eliminate poverty and improve quality of life.   (3) The importance of the empirical demonstration of the impact of the use and quality of human services on perceptions of quality of life cannot be underestimated. This study made some initial inroads, however future research may require longitudinal research designs that monitor changes in variables over time. Future research with the above-mentioned factors will build a broader and deeper understanding of the quality of life construct, thus contributing to research and the improvement of quality of life. 

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