Quality of life of low-income adults

Abstract

BACKGROUND:

Quality of life is currently one of the basic conceptual categories in many research disciplines. The authors of the present study are convinced that measurement of quality of life in reference to people living on the poverty line deserves special attention.

OBJECTIVE:

The aim of the study was to identify relationships between the quality of life and sociodemographic variables in low-income Wrocław residents.

METHODS:

The research was conducted in Wrocław (Poland) and involved 1215 respondents aged 18–64 years, whose monthly gross income per capita in the household did not exceed 1043 PLN. The respondents’ quality of life was assessed with the World Health Organization Quality of Life Questionnaire with additional questions on the respondents’ social and demographic status.

RESULTS:

The Wrocław residents most often assessed their quality of life as average or below average. They rated their health-related quality of life in the social domain as the highest, and in the physical domain as the lowest. Age, household size, stable source of income, savings, and indebtedness were significantly correlated with the quality of life of Wrocław residents under study. Among the respondents, statistically significant relationships between perceived health condition assessment and age, professional status, stable source of income, and debt were also identified.

CONCLUSIONS:

The results of the study indicate that public health programs and other activities related to quality of life management should be directed to individuals and social groups particularly threatened by low quality of life, i.e., people living on the income poverty line.

Keywords

Quality of life income poverty socio-demographic factors

1 Introduction

Quality of life is currently one of the basic conceptual categories in many research disciplines as well as in socio-economic practice. The authors of the present study are convinced that measurement of health-related quality of life in reference to groups at risk of social exclusion deserves special attention. One of such groups are people living on the poverty line, i.e., those whose monthly household income does not exceed 60% of the median equivalent income for the whole country [1]. The importance of measuring the quality of life of low-income adults results from three premises. Firstly, the results of some studies indicate the prevalence of certain psychosomatic disorders in low-income individuals, such as obesity [2], arterial hypertension [3], or chronic obstructive pulmonary disease [4]. Secondly, many studies have documented the negative impact of low income on quality of life and perceived health conditions [5 –7]. Thirdly, people with low incomes are still quite numerous, even in economically developed countries. For example, in Poland about 14% of all households have experienced income poverty. It occurs most frequently in families with three and more dependent children (36%), and in single-parent families, where the mother or the father raises children alone (26%). Households living on social benefits other than pensions (72%), households of disability pensioners (36%), and households of the self-employed in agriculture (27%), are also in the worst situation [8].

In the opinion of the authors of this paper, the influence of socio-demographic status on the assessment of overall quality of life and health-related quality of life constitutes a rarely discussed research problem. Studies conducted so far on health-related quality of life determinants have examined gender, age, health behaviors, medical procedures, and social support. These studies have shown that male gender [9] and young age [10] may be predictors of a higher quality of life. Jalali-Farahani et al. [11], Bonaccio et al. [12], and Guallar-Castilloni et al. [13] documented a positive impact of some health behaviors, including a rational diet, proper body weight, and sleep length, on perceived quality of life. Behzadifar et al. [14] showed that respondents’ quality of life can be influenced by increasing social cooperation, improving health care, and providing counseling healthcare services. Greeson et al. [15] demonstrated significant links between spirituality and mindfulness and health status and overall quality of life.

The research on the relationships between quality of life and socio-demographic status has mainly focused on the general population [16, 17] and groups of patients [18]. Most studies have been conducted by representatives of medical sciences and public health specialists, but not by economists, for whom relations between socio-demographic categories and perceived quality of life are of great significance.

There have been very few studies on the quality of life of people living in poverty [19], and it remains unclear whether the quality of life assessment in this particular group is homogeneous, or whether it is perhaps modified by social and demographic factors other than income. The research on the ties between quality of life and socio-demographic status has not taken into account such factors as the number of people in the household, having regular income from sources other than work (e.g., alimony, benefits, family assistance), having savings or debt. Reducing these research gaps is one of the key tasks of the present study.

The aim of the study is to identify the relationships between the quality of life and socio-demographic factors in Wrocław residents at risk of poverty rate. This objective is specified in detail in the following research questions:

How do Wrocław residents with low incomes assess their overall quality of life and health-related quality of life?

Are there any links between the overall quality of life and perceived health condition and socio-demographic factors among Wrocław residents living at the poverty threshold?

2 Theoretical bases for the study

Anything we do in life always determines its quality in some way, either directly or indirectly. Quality of life is and should be the overriding goal of all our individual actions, and on a collective scale, of all activities by every local, regional, national, or international (global) community. In this respect, the fundamental significance of quality of life most often manifests itself in the construction of different development strategies focused on multiple aspects (dimensions) of the quality of life of inhabitants of a given area. Therefore, quality of life is manifested everywhere, and everything a person does should serve this quality.

Despite this fundamental importance of quality of life, it is surprising that it still remains in the range of notions which have not yet been properly defined in literature. There is no entry for “quality of life” in any of the world’s largest encyclopedias, e.g., The International Encyclopedia of Social Sciences, Encyclopedia Britannica, , or Meyers Enzyklopädisches Lexikon [20].

Two trends can be clearly distinguished in discussions on the terminology of quality of life and related concepts. The first, which has been dominating for many years, is the often expressed belief that quality of life cannot be defined universally as there are too many interpretations and dimensions that need to be taken into account in order to arrive at a uniform definition. “Let’s hang up ‘quality of life’ as a hopeless term” is one of the typical examples of this trend expressed in a study by a research team of six Italian-Spanish authors [21]. The lack of terminological unification is confirmed by the common practice of using many terms expressing, in fact, different classifications of quality of life, without explicitly highlighting their precise criteria.

The other trend is manifested in attempts, based on the analysis of multiple approaches and interpretations, to approach the definition of quality of life as a natural and integrative effect of the universalization of the essence of quality of life as well as the universalization of the essence of life [22]. It is noteworthy that publications that have endeavored to define quality of life in this way represent a negligible part of all the works in this field. The few definitions of quality of life that aspire to a universal approach certainly include the World Health Organization’s definition of quality of life as “An individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns. It is a broad ranging concept affected in a complex way by the person’s physical health, psychological state, personal beliefs, social relationships, and their relationship to salient features of their environment”. Interestingly, this definition has a clearly exposed axiological focus and quality of life determinants originating from the human surroundings. To a large extent a convergent, albeit more synthetic, definition of quality of life is provided by The SAGE Encyclopedia of Quality and the Service Economy [23] published in 2015, according to which quality of life is the image of our lives based on a specific system of values (axiological system) and, what is worth emphasizing, the resulting external determinants of this system (social, economic and environmental conditions). This image as a collective property of a person or a group of people, depending on the tools used to describe it, can be expressed subjectively or objectively, unidimensionally or multi-dimensionally, etc., and the tools describing quality of life form its various typologies [24].

Therefore, any further specification of the concept of quality of life must include the already clearly defined typological criteria, generating different quality of life types (perceptions of our lives) based on the same, universal essence of this concept. The typology of quality of life has obvious implications for research methodology, especially measurement and classification of quality of life indicators. In this article, two fundamental criteria will be taken into account from among four criteria of quality of life typology, which will openly highlight the axiological aspects of quality of life:

The first criterion takes into account the degree of objectivity of quality of life measurement. It involves a division into objective quality of life, which is also defined as the standard of living, and subjective quality of life [25].

The second criterion takes into account the degree of quality of life integration. This criterion, in turn, entails a division into an overall (holistic, global) quality of life – covering a whole range of observations, and a partial (constituent) quality of life – covering fragmentary areas of observation according to particular domains of overall quality of life.

The first criterion introduces one of the most important quality of life classifications, which is used in almost all statistical standards of research. The objective quality of life is a collection (vector) of qualitative facts (objective forms of satisfying human needs) characterizing various aspects of human life, i.e., it is a confirmation of these qualitative states, which takes place without their comparative or psychological assessment. In this paper, the research methodology is based mainly on the subjective category of quality of life, which is a vector of qualitative facts assessments (assessments of the degree of satisfaction with various objective forms of fulfilling human needs), characterizing various aspects of human life on a psychological scale. Taken together, subjective quality of life is therefore a multidimensional assessment of an individual’s life in the specific cultural context that surrounds him or her, and of the values that he or she professes. It is primarily an expression of well-being in its physical, mental, and spiritual aspects [26]. Thus, subjective quality of life is the value (assessment) of the function of preferences defined on the basis of objective qualitative states (Fig. 1), i.e., it expresses, according to the universal definition, a subjective perception of one’s own life within a specific system of values (internal determinants) and the resulting social, economic and environmental conditions (external determinants).

Fig. 1

The flowchart of transformation of objective quality of life into its subjective images.

The importance of simultaneous indicator-based measurement of objective and subjective quality of life results from the complexity of the relations between these categories. Campbell’s assertion of limited substitutability between the measures of both types of quality of life [27] is fundamental to the analysis of these relationships. The conclusions of this limited substitution will be used to discuss the results of the present study.

The second criterion introduces a quality of life classification based on the degree of human self-fulfillment. It sets the scope of perception of quality of life by defining a set of domains determining overall quality of life and partial (constituent) qualities of life. In literature, the degree of recognition of these constituent qualities is varied. These qualities differ not only in quantity, but also in the approach to their identification. A review of them allows us to distinguish, in the simplest way possible, two approaches:

The first approach involves three basic domains of overall quality of life: physical, psychological (emotional-mental), and emotional (spiritual) 1 [23, 26]. To a certain extent, this approach to the quality of life definition coincides with:

W. Ostasiewicz’s claim [28] that quality of life is a synthesis of welfare and well-being and concerns several dimensions of human existence, including economic and non-material existence,

the identification of four quality of life domains in the present study, derived from the World Health Organization Quality of Life (BREF) questionnaire [29], according to which, the full quality of life comprises of the physical, psychological, social, and environmental domains.

The other approach to quality of life has generated some controversy. In this approach, quality of life subsets are created in different, extensive ways, with a high degree of convergence of the basic scope of observation. The authors of this article have identified at least a dozen or so such proposals [30], which are in fact attempts to answer the key question: Which areas (determinants, predictors) of our lives are the most important? The axiological background to this question is obvious. It determines the different distributions of importance of these areas generated by the diversity of systems of values and levels of human awareness [30]. The basic conclusion to be drawn from the analysis of these propositions of the “domain range” of quality of life is as follows: All these proposals emphasize the significance of the health domain in human life, e.g., 4-domain proposal (purposefulness, time, health, relationships); 5-domain proposal (health, love, happiness, friendship, sense of security); and WHO 7-domain proposal (food, housing, health, education, recreation, social security, material comfort); or 13-domain proposal [27] (marriage and family life, health, neighborhood, friends and acquaintances, life in the USA, place of residence, housing, professional work and house chores, free time, education and its usefulness and financial security).

The above justifies the choice of the research subject of the present study. The article considers the measurement of the quality of life in the objective and global aspects, as well as the subjective and selected aspects – health-related quality of life, in particular – a key predictor of overall quality of human life [31, 32]. The research framework is presented in Fig. 2.

Fig. 2

The flowchart of empirical research.

3 Methods

The research was conducted in Wrocław (Poland). The study involved 1215 respondents (751 women, 464 men) whose monthly gross income per capita in their households did not exceed the income poverty threshold of 1043 PLN adopted in Poland [8].

A questionnaire-based diagnostic survey, i.e., the WHOQOL-BREF questionnaire [29] was used to assess respondents’ health-related quality of life. The questionnaire consists of 26 closed questions with answers on a five-level Likert scale. Suggestions for evaluation of subjective qualities of life are formulated as: verbal evaluation – numerical evaluation and are expressed in terms of intensity:

Emotional states: from negative emotions (very dissatisfied, dissatisfied, or very bad, bad) through neutral emotions (neither dissatisfied nor satisfied, or neither good nor bad) to positive emotions (satisfied, very satisfied, or good, very good). Half of the assessments (13 items) are constructed in this way, and they are all quality of life stimulants.

Perception states and the scale of success (including financial) in life: from negative feelings (not at all, slightly) through neutral (medium or moderate) to positive feelings (to a large extent, quite well, mostly and to a very large extent, very well, fully). Most of the other assessments (12 items) are constructed in this way, 9 being quality of life stimulants and 2 are destimulants.

The frequency of emotional sensations such as dejection, despair, anxiety, and depression on a verbal scale from “never” to “always”.

Answers to questionnaire items were used in accordance with the accepted data processing key to determine the following indicators: overall quality of life (1–5 pts.); perceived health condition (1–5 pts.); and health-related quality of life in four domains: physical (7–35 pts.); psychological (6–30 pts.); social (3–15 pts.); and environmental (8–40 pts.). For quality of life indicators in the physical, psychological, social, and environmental domains, a transformation of raw scores into a 4–20 scale [29] was carried out. The overall quality of life, health-related quality of life in four domains, and the perceived health condition variables were also expressed on a nominal scale [33]. The median values of these indices, where a result lower or equal to the median meant average or lower than average quality of life and, analogous average or lower than average level of satisfaction with one’s own health, and higher than the median above average level of these variables, were used as conventional division points in the classification.

Information on empirical distributions of selected socio-demographic factors was also obtained, i.e., gender (female, male), age (up to 34, 35–44, 45 and more years), education (primary and basic vocational, secondary, and higher), marital status (single, married), number of people in the household (up to 2, 3–4, 5 and more), profession (physical worker, white-collar worker, student, unemployed), having a stable source of income (no, yes), having savings (no, yes), and being in debt (no, yes).

The data of the study were collected using the survey method. Informed consent was obtained from all subjects involved in the study. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of the University School of Physical Education in Wrocław (protocol code 11/2016). The manuscript adheres to the reporting guidelines relevant to the research design.

The obtained data were subjected to statistical analysis, which resulted in determining the number (n) and percent (%) in empirical distributions of respondents within the categories of dependent (quality of life) and independent (socio-demographic factors) variables. The compliance of observed distributions of the analyzed variables with the theoretical distribution was assessed using the Chi-square goodness of fit test (χ²). The null hypothesis (H₀) that the distribution of variants is uniform in comparison to the alternative hypothesis (H₁) that it is not uniform was verified. The median (Me), first (Q₁), and third (Q₃) quartiles for quality of life indicators were also calculated. The range of differences in the levels of dependent variables in groups of respondents according to socio-demographic factors was assessed with the Mann-Whitney U test (Z) and the Kruskal-Wallis H test (H). In both Z and H tests, the null hypothesis (H₀) that the mean ranks of quality of life indicators were equal in groups of respondents with a different socio-demographic status compared to the alternative hypothesis (H₁) that they were different was verified. To evaluate the relationships between the dependent variables: overall quality of life, perceived health condition expressed on a nominal scale, and independent variables: socio-demographic factors, logistic regression was used in the variant of backward stepwise elimination of independent variables [33]. Statistical inference in the verification of the adopted statistical hypotheses was carried out at the level of significance α=.05. The calculations were performed using IBM SPSS Statistics 26 (IBM Corporation, Armonk, NY, USA).

4 Results

4.1 Socio-demographic factors assessment

The breakdowns of respondents according to selected socio-demographic characteristics are presented in Table 1. In the surveyed group, women accounted

Table 1
Socio-demographic characteristics of Wrocław residents with gross income≤1043 PLN (N = 1215)

Variable	n	%
Gender
Female	751	61.8
Male	464	38.2
Age
≤34 years	559	46.0
35–44 years	188	15.5
≥45 years	468	38.5
Education
Primary	567	46.7
Secondary	508	41.8
University	140	11.5
Marital status
Single	545	44.9
Married	670	55.1
Persons per household
≤2	324	26.7
3–4	737	60.7
≥5	154	12.7
Occupation
Physical worker	332	27.3
White collar worker	287	23.6
Student	255	21.0
Unemployed	341	28.1
Stable income
No	423	34.8
Yes	792	65.2
Savings
No	1023	84.2
Yes	192	15.8
Indebtedness
No	528	43.5
Yes	687	56.5

Notes: n: number of participants, %: percentage of participants.

for 62%, while men for 38% of all respondents. Among the respondents 46% were aged up to 34 years, 15% –25–44 years, and 39% –45 years or more. Basic vocational or primary education was declared by 47%, secondary education by 42%, and higher education by 11% of Wrocław residents with low incomes. There were about 45% of respondents living alone, and about 55% living in marriages. Approximately 27% of the respondents lived in one- or two-person households, 61% in three- or four-person households, and 13% in five- or more-person households. In the analyzed group, physical workers constituted 27%, white-collar workers 24%, school students or college students 21%, and the unemployed 28% of the surveyed residents. In the group of respondents, 65% had a stable source of income, 15% had money savings, and 56% were in debt (Table 1).

4.2 Quality of life assessment

The overall quality of life index of the respondents living in income poverty was 3.00 (3.00–4.00), while their perceived health condition index was 3.00 (2.00–4.00). Respondents rated their health-related quality of life in the social 14.67 (13.33–16.00) and psychological 13.33 (12.00±14.67) domains higher than in the physical 12.57 (10.86–13.71) and environmental 12.50 (10.50–13.50) domains (Table 2).

Table 2
Characteristics of overall quality of life and health-related quality of life of Wrocław residents with gross income≤1043 PLN (N = 1215)

Variable Me Q₁ Q₃

Overall quality of life (1–5) 3.00 3.00 4.00

Perceived health condition (1–5) 3.00 2.00 4.00

Quality of life: physical domain (4–20) 12.57 10.86 13.71

Quality of life: psychological domain (4–20) 13.33 12.00 14.67

Quality of life: social domain (4–20) 14.67 13.33 16.00

Quality of life: environmental domain (4–20) 12.50 10.50 13.50

Variable	Me	Q₁	Q₃
Overall quality of life (1–5)	3.00	3.00	4.00
Perceived health condition (1–5)	3.00	2.00	4.00
Quality of life: physical domain (4–20)	12.57	10.86	13.71
Quality of life: psychological domain (4–20)	13.33	12.00	14.67
Quality of life: social domain (4–20)	14.67	13.33	16.00
Quality of life: environmental domain (4–20)	12.50	10.50	13.50

Notes: Me: median, Q1: first quartile, Q3: third quartile.

Almost 57% of low-income Wrocław residents rated their overall quality of life as average or below average, while about 43% rated it above average (statistically significant difference p < .001). In the physical and social domains, slightly more than 60% of the respondents, while in the mental and environmental domains slightly more than 50%, assessed their health-related quality of life as average or below average. The average or lower than average perceived health condition was assessed by 53% of respondents, and above average by 47% of respondents (statistically significant difference p < .05) (Table 3).

Table 3

Characteristics of the overall quality of life and health-related quality of life of Wrocław residents with gross income≤1043 PLN. Cut-off point in the median ranking (N = 1215)

Variable	n	%	χ ²	p
Overall quality of life
Average and below (≤3.00)	691	56.9	22.9	<.001
Above average (>3.00)	524	43.1
Perceived health condition
Average and below (≤3.00)	644	53.0	4.4	.036
Above average (>3.00)	571	47.0
Physical domain
Average and below (≤12.57)	746	61.4	63.2	<.001
Above average (>12.57)	469	38.6
Psychological domain
Average and below (≤13.33)	641	52,8	3.7	.055
Above average (>13.33)	574	47.2
Social domain
Average and below (≤14.67)	731	60,2	50.2	<.001
Above average (>14.67)	484	39.8
Environmental domain
Average and below (≤12.50)	661	54.4	9.4	.002
Above average (>12.50)	554	45.6

Notes: n: number of participants, %: percentage of participants, χ²: chi-square goodness of fit test, p: chi-square goodness of fit test probability value.

4.3 Overall quality of life in terms of socio-demographic status

The results of intergroup differences showed that the general health-related quality of life is significantly (p < .001) determined in the group of low-income Wrocław inhabitants by their age, level of education, marital status, household size, professional status, stable source of income, savings and debt. Their perceived assessment of overall quality of life deteriorated with age and was the highest (Me = 4.00) in the youngest, and the lowest (Me = 3.00) in the oldest respondents. The assessment of overall quality of life also increased with the level of education. Among the Wrocław low-income residents with a primary and basic vocational education, the median of this indicator was 3.00, and among those with a secondary or higher education, it was 4.00. Single respondents rated their health-related quality of life higher (Me = 4.00) than married respondents (Me = 3.00). The respondents’ self-assessment of the quality of life also rose with the increase in the number of people in the household. It was the lowest for respondents from one- or two-person households (Me = 3.00), and the highest for respondents from households with five or more persons (Me = 4.00). Among the respondents, the highest average overall quality of life was noted among students and white-collar workers (Me = 4.00), and the lowest among the unemployed and physical workers (Me = 3.00). People with a stable source of income were characterized on average by a higher overall quality of life than those without it. Wrocław residents with savings on average (Me = 4.00) rated their quality of life higher than those without savings (Me = 3.00), while the indebted respondents (Me = 3.00) assessed their quality of life lower than those without debt (Me = 4.00) (Table 4).

Table 4
Overall quality of life of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable n Me Q₁ Q₃ MR Z/H p

Gender

Female 751 3.00 3.00 4.00 618.75 –1.5 .146

Male 464 3.00 3.00 4.00 590.60

Age

≤34 years 559 4.00 3.00 4.00 715.85 144.9 <.001

35-44 years 188 3.00 3.00 4.00 631.65

≥45 years 468 3.00 3.00 3.00 469.68

Education

Primary 567 3.00 3.00 4.00 521.37 80.8 <.001

Secondary 508 4.00 3.00 4.00 666.58

University 140 4.00 3.00 4.75 746.28

Marital status

Single 545 4.00 3.00 4.00 650.17 –4.0 <.001

Married 670 3.00 3.00 4.00 573.70

Persons per household

≤2 persons 324 3.00 2.00 3.00 457.75 105.5 <.001

3–4 persons 737 3.00 3.00 4.00 644.76

≥5 persons 154 4.00 3.00 4.00 748.18

Occupation

Laborer 332 3.00 3.00 4.00 575.81 180.7 <.001

White collar worker 287 4.00 3.00 4.00 707.80

Student 255 4.00 3.00 4.00 765.38

Unemployed 341 3.00 2.00 3.50 437.65

Stable income

No 423 3.00 2.00 4.00 504.18 –8.1 <.001

Yes 792 3.00 3.00 4.00 663.45

Savings

No 1023 3.00 3.00 4.00 585.08 –5.6 <.001

Yes 192 4.00 3.00 4.00 730.10

Indebtedness

No 528 4.00 3.00 4.00 738.61 –12.2 <.001

Yes 687 3.00 3.00 4.00 507.62

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	3.00	3.00	4.00	618.75	–1.5	.146
Male	464	3.00	3.00	4.00	590.60
Age
≤34 years	559	4.00	3.00	4.00	715.85	144.9	<.001
35-44 years	188	3.00	3.00	4.00	631.65
≥45 years	468	3.00	3.00	3.00	469.68
Education
Primary	567	3.00	3.00	4.00	521.37	80.8	<.001
Secondary	508	4.00	3.00	4.00	666.58
University	140	4.00	3.00	4.75	746.28
Marital status
Single	545	4.00	3.00	4.00	650.17	–4.0	<.001
Married	670	3.00	3.00	4.00	573.70
Persons per household
≤2 persons	324	3.00	2.00	3.00	457.75	105.5	<.001
3–4 persons	737	3.00	3.00	4.00	644.76
≥5 persons	154	4.00	3.00	4.00	748.18
Occupation
Laborer	332	3.00	3.00	4.00	575.81	180.7	<.001
White collar worker	287	4.00	3.00	4.00	707.80
Student	255	4.00	3.00	4.00	765.38
Unemployed	341	3.00	2.00	3.50	437.65
Stable income
No	423	3.00	2.00	4.00	504.18	–8.1	<.001
Yes	792	3.00	3.00	4.00	663.45
Savings
No	1023	3.00	3.00	4.00	585.08	–5.6	<.001
Yes	192	4.00	3.00	4.00	730.10
Indebtedness
No	528	4.00	3.00	4.00	738.61	–12.2	<.001
Yes	687	3.00	3.00	4.00	507.62

Notes: n: number of participants, Me: median, Q1: first quartile, Q3: third quartile, MR: mean rank, Z: Mann-Whitney U test (standardized test statistic), H: Kruskal-Wallis test, p: probability value.

4.4 Perceived health condition in terms of socio-demographic status

Age, level of education, marital status, household size, professional status, and having a stable source of income and debt, significantly (p < .001) differentiated the health status of Wrocław residents with low incomes. The highest perceived health condition index was characteristic for respondents aged up to 34 years (Me = 4.00), and the lowest for respondents aged 45 or more (Me = 2.00). The Kruskal-Wallis test results showed that the average rank of perceived health condition assessment in groups separated by educational level, differed significantly from each other (H = 87.0, p < .001). The analysis of the median values indicates that the perceived health condition of respondents rose with the level of education. Marital status (Z=–6.7, p < .001) was also a factor differentiating the perceived health condition of low-income Wrocław residents. Individuals living alone rated it higher (Me = 4.00) than married respondents (Me = 4.00). The best perceived health condition was declared by respondents from five- and more-person households (Me = 4.00), and the worst from one- and two-person (Me = 3.00) households. Students and white-collar workers (Me = 4.00) rated their perceived health condition higher, while the unemployed and manual workers (Me = 3.00) lower. The assessment of perceived health condition also differed significantly in the groups of respondents separated by having a stable source of income (Z=–3.4, p = .001) and was higher in those who had it, compared to those who did not. Statistically significantly higher (Z=–6.4, p < .001) perceived health condition was also observed in those without debt (Me = 4.00) than in those with debt (Me = 3.00) (Table 5).

Table 5
Perceived health condition of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable n Me Q₁ Q₃ MR Z/H p

Gender

Female 751 3.00 3.00 4.00 603.01 –0.7 .506

Male 464 3.50 2.00 4.00 616.07

Age

≤34 years 559 4.00 3.00 4.00 735.10 233.2 <.001

35–44 years 188 3.00 3.00 4.00 685.51

≥45 years 468 2.00 2.00 4.00 425.05

Education

Primary 567 3.00 2.00 4.00 514.24 87.0 <.001

Secondary 508 4.00 3.00 4.00 679.01

University 140 4.00 3.00 4.00 730.07

Marital status

Single 545 4.00 3.00 4.00 679.31 –6.7 <.001

Married 670 3.00 2.00 4.00 549.99

Persons per household

≤2 persons 324 3.00 2.00 4.00 509.47 42.1 <.001

3–4 persons 737 3.00 3.00 4.00 634.46

≥5 persons 154 4.00 3.00 4.00 688.66

Occupation

Laborer 332 3.00 2.25 4.00 596.13 112.6 <.001

White collar worker 287 4.00 3.00 4.00 661.58

Student 255 4.00 3.00 4.00 748.58

Unemployed 341 3.00 2.00 4.00 469.34

Stable income

No 423 3.00 2.00 4.00 564.02 –3.4 .001

Yes 792 3.00 3.00 4.00 631.49

Savings

No 1023 3.00 2.00 4.00 609.13 –0.3 .784

Yes 192 3.00 2.00 4.00 601.96

Indebtedness

No 528 4.00 3.00 4.00 678.10 –6.4 <.001

Yes 687 3.00 2.00 4.00 554.12

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	3.00	3.00	4.00	603.01	–0.7	.506
Male	464	3.50	2.00	4.00	616.07
Age
≤34 years	559	4.00	3.00	4.00	735.10	233.2	<.001
35–44 years	188	3.00	3.00	4.00	685.51
≥45 years	468	2.00	2.00	4.00	425.05
Education
Primary	567	3.00	2.00	4.00	514.24	87.0	<.001
Secondary	508	4.00	3.00	4.00	679.01
University	140	4.00	3.00	4.00	730.07
Marital status
Single	545	4.00	3.00	4.00	679.31	–6.7	<.001
Married	670	3.00	2.00	4.00	549.99
Persons per household
≤2 persons	324	3.00	2.00	4.00	509.47	42.1	<.001
3–4 persons	737	3.00	3.00	4.00	634.46
≥5 persons	154	4.00	3.00	4.00	688.66
Occupation
Laborer	332	3.00	2.25	4.00	596.13	112.6	<.001
White collar worker	287	4.00	3.00	4.00	661.58
Student	255	4.00	3.00	4.00	748.58
Unemployed	341	3.00	2.00	4.00	469.34
Stable income
No	423	3.00	2.00	4.00	564.02	–3.4	.001
Yes	792	3.00	3.00	4.00	631.49
Savings
No	1023	3.00	2.00	4.00	609.13	–0.3	.784
Yes	192	3.00	2.00	4.00	601.96
Indebtedness
No	528	4.00	3.00	4.00	678.10	–6.4	<.001
Yes	687	3.00	2.00	4.00	554.12

4.5 Health-related quality of life in the physical, psychological, social, and environmental domains in terms of socio-demographic status

Among the Wrocław residents living in income poverty, the differences in health-related quality of life in four of its domains (physical, psychological, social, and environmental) were also considered, depending on socio-demographic variables (Tables 6–9). In the physical and psychological domains, the men rated their health-related quality of life higher than the women (p < .001). The age of respondents was significantly (p < .001) associated with the assessment of health-related quality of life in the psychological, social, and environmental domains, with the lowest quality of life in these domains being assessed by the oldest respondents. The health-related quality of life in the psychological, social, and environmental domains also increased with the level of education of the respondents and was higher in individuals living alone than in married respondents. Health-related quality of life in the physical, psychological, social, and environmental domains was rated the highest by respondents living in five- and more- person households and the lowest by respondents from one- and two-person households. The respondents’ professional status turned out to be a factor significantly differentiating (p < .001) their health-related quality of life in the psychological, social, and environmental domains. It was rated the highest by students and white-collar workers, and the lowest by the unemployed and manual workers. Respondents with savings rated their health-related quality of life in all domains significantly higher (p < .01) than those without them. The assessment of health-related quality of life in the psychological, social, and environmental domains was also statistically significant (p < .001) in relation to indebtedness, as those without debt rated it higher than those with debt (Tables 6–9).

Table 6
Health-related quality of life in the physical domain of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable n Me Q₁ Q₃ MR Z/H p

Gender

Female 751 12.00 10.86 13.14 574.62 –4.2 <.001

Male 464 12.57 11.43 13.71 662.02

Age

≤34 years 559 12.00 10.86 13.71 610.45 5.6 .061

35–44 years 188 12.57 11.43 13.71 656.59

≥45 years 468 12.57 10.86 13.14 585.55

Education

Primary 567 12.57 10.86 13.14 584.11 5.9 .052

Secondary 508 12.57 10.86 13.71 621.99

University 140 12.57 11.43 13.71 654.02

Marital status

Single 545 12.00 10.86 13.71 627.74 –1.8 .075

Married 670 12.57 10.86 13.14 591.94

Persons per household

≤2 persons 324 12.00 10.86 13.14 564.38 7.7 .021

3–4 persons 737 12.57 11.43 13.71 619.05

≥5 persons 154 12.57 11.43 13.71 646.88

Occupation

Laborer 332 12.00 10.86 13.71 586.08 7.5 .059

White collar worker 287 12.57 11.43 13.71 655.75

Student 255 12.57 10.86 13.71 604.78

Unemployed 341 12.57 11.43 13.14 591.55

Stable income

No 423 12.57 11.43 13.14 614.33 –0.5 .644

Yes 792 12.57 10.86 13.71 604.62

Savings

No 1023 12.57 10.86 13.14 595.72 –2.8 .005

Yes 192 12.57 11.57 13.71 673.41

Indebtedness

No 528 12.57 11.43 13.71 630.58 –2.0 .048

Yes 687 12.57 10.86 13.14 590.65

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	12.00	10.86	13.14	574.62	–4.2	<.001
Male	464	12.57	11.43	13.71	662.02
Age
≤34 years	559	12.00	10.86	13.71	610.45	5.6	.061
35–44 years	188	12.57	11.43	13.71	656.59
≥45 years	468	12.57	10.86	13.14	585.55
Education
Primary	567	12.57	10.86	13.14	584.11	5.9	.052
Secondary	508	12.57	10.86	13.71	621.99
University	140	12.57	11.43	13.71	654.02
Marital status
Single	545	12.00	10.86	13.71	627.74	–1.8	.075
Married	670	12.57	10.86	13.14	591.94
Persons per household
≤2 persons	324	12.00	10.86	13.14	564.38	7.7	.021
3–4 persons	737	12.57	11.43	13.71	619.05
≥5 persons	154	12.57	11.43	13.71	646.88
Occupation
Laborer	332	12.00	10.86	13.71	586.08	7.5	.059
White collar worker	287	12.57	11.43	13.71	655.75
Student	255	12.57	10.86	13.71	604.78
Unemployed	341	12.57	11.43	13.14	591.55
Stable income
No	423	12.57	11.43	13.14	614.33	–0.5	.644
Yes	792	12.57	10.86	13.71	604.62
Savings
No	1023	12.57	10.86	13.14	595.72	–2.8	.005
Yes	192	12.57	11.57	13.71	673.41
Indebtedness
No	528	12.57	11.43	13.71	630.58	–2.0	.048
Yes	687	12.57	10.86	13.14	590.65

Table 7

Health-related quality of life in the physiological domain of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	13.33	12.00	14.67	581.85	–3.3	.001
Male	464	14.00	12.00	15.33	650.33
Age
≤34 years	559	14.00	12.00	15.33	639.27	17.0	<.001
35–44 years	188	14.00	12.00	14.67	644.60
≥45 years	468	13.33	12.00	14.00	555.94
Education
Primary	567	13.33	12.00	14.67	575.29	48.4	<.001
Secondary	508	13.33	12.00	14.67	591.65
University	140	14.00	13.33	16.67	799.82
Marital status
Single	545	14.00	12.00	15.33	649.14	–3.7	<.001
Married	670	13.33	12.00	14.00	574.53
Persons per household
≤2 persons	324	12.67	11.33	14.67	539.78	17.0	<.001
3–4 persons	737	14.00	12.00	14.67	630.75
≥5 persons	154	13.67	12.00	14.67	642.64
Occupation
Laborer	332	13.33	12.00	14.50	568.74	16.3	.001
White collar worker	287	14.00	12.00	15.33	671.73
Student	255	13.33	12.00	14.67	623.43
Unemployed	341	13.33	11.67	14.67	581.05
Stable income
No	423	13.33	12.00	14.67	596.41	–0.8	.398
Yes	792	13.33	12.00	14.67	614.19
Savings
No	1023	13.33	12.00	14.67	592.92	–3.5	.001
Yes	192	14.00	12.67	15.33	688.36
Indebtedness
No	528	14.00	12.00	15.33	653.53	–4.0	<.001
Yes	687	13.33	12.00	14.67	573.01

Table 8

Health-related quality of life in the social domain of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	14.67	13.33	16.00	598.01	–1.3	.201
Male	464	14.67	13.33	16.00	624.16
Age
≤34 years	559	16.00	13.33	17.33	694.34	86.6	<.001
35–44 years	188	14.67	13.33	16.00	634.91
≥45 years	468	13.33	13.33	16.00	494.06
Education
Primary	567	14.67	13.33	16.00	579.78	10.0	.007
Secondary	508	14.67	13.33	16.00	620.53
University	140	14.67	13.33	17.33	676.85
Marital status
Single	545	14.67	13.33	17.33	661.13	–4.8	<.001
Married	670	14.67	13.33	16.00	564.79
Persons per household
≤2 persons	324	13.33	12.00	16.00	549.72	12.8	.002
3–4 persons	737	14.67	13.33	16.00	626.55
≥5 persons	154	14.67	13.33	16.00	641.84
Occupation
Laborer	332	14.67	13.33	16.00	576.30	26.2	<.001
White collar worker	287	14.67	13.33	16.00	621.84
Student	255	16.00	13.33	17.33	696.51
Unemployed	341	14.67	12.00	16.00	561.03
Stable income
No	423	14.67	13.33	17.33	621.52	–1.0	.320
Yes	792	14.67	13.33	16.00	600.78
Savings
No	1023	14.67	13.33	16.00	587.86	–4.7	<.001
Yes	192	16.00	14.67	16.00	715.32
Indebtedness
No	528	14.67	13.33	16.00	670.62	–5.5	<.001
Yes	687	14.67	13.33	16.00	559.88

Notes: n: number of participants, Me: median, Q₁: first quartile, Q₃: third quartile, MR: mean rank, Z: Mann-Whitney U test (standardized test statistic), H: Kruskal-Wallis test, p: probability value.

Table 9

Health-related quality of life in the environmental domain of Wrocław residents with gross income≤1043 PLN depending on selected socio-demographic variables (N = 1215)

Variable	n	Me	Q₁	Q₃	MR	Z/H	p
Gender
Female	751	12.50	10.50	13.50	593.21	–1.9	.061
Male	464	12.50	11.00	13.50	631.94
Age
≤34 years	559	13.00	11.50	15.00	717.47	109.9	<.001
35–44 years	188	12.00	11.00	13.50	577.49
≥45 years	468	11.50	10.50	13.00	489.50
Education
Primary	567	11.50	10.50	13.50	529.95	63.5	<.001
Secondary	508	13.00	11.50	14.00	652.88
University	140	13.00	12.00	15.38	761.25
Marital status
Single	545	12.50	11.00	14.50	658.18	–4.5	<.001
Married	670	12.25	10.50	13.50	567.18
Persons per household
≤2 persons	324	11.50	10.50	13.50	507.48	36.5	<.001
3–4 persons	737	13.00	11.25	13.50	644.03
≥5 persons	154	12.50	11.00	14.50	647.06
Occupation
Laborer	332	12.00	10.50	13.00	528.48	79.6	<.001
White collar worker	287	12.50	11.00	13.50	629.42
Student	255	13.50	12.00	15.00	765.71
Unemployed	341	11.50	10.50	13.50	549.45
Stable income
No	423	12.00	10.50	13.50	591.03	–1.2	.216
Yes	792	12.50	10.50	13.50	617.07
Savings
No	1023	12.50	10.50	13.50	595.68	–2.8	.005
Yes	192	13.00	11.00	13.50	673.66
Indebtedness
No	528	13.00	11.50	14.50	697.37	–7.8	<.001
Yes	687	11.50	10.50	13.50	539.31

4.6 Impact of socio-demographic status on above-average assessment of overall quality of life

Table 10 presents a logistic regression model of relations between overall quality of life (dependent variable) and selected socio-demographic characteristics (independent variables) in low-income Wrocław inhabitants. The likelihood ratio LR = 356.0, p < .001 and the coefficient of determination (Nagelkerke’s R² = 0.34) for the model with six independent variables indicate that it differs significantly from the model containing only the intercept, and variables such as age, number of people in the household, professional status, having a stable source of income, savings and debt significantly determine the above-average assessment of overall quality of life. The likelihood of an above-average assessment of the overall quality of life was almost four and a half times higher in respondents aged up to 34 years (OR = 4.4, CI: 3.06–6.33), and about 70% higher in respondents aged 35–44 years (OR = 1.69, CI: 1.13–2.52) than in respondents aged 45 years or more. The odds for an above-average assessment of the overall quality of life of respondents from one- or two-person households were 81% lower, and of respondents from three- or four-person households were 52% lower than of respondents living in five- or more-person households. Physical workers had 39% lower odds of above-average overall quality of life assessments than the unemployed. The lower limit of confidence interval for OR was 0.30 for this variable, while the upper limit was 0.96. The likelihood of an above-average assessment of overall quality of life of Wrocław residents without a stable source of income was 52% lower than of those with it (OR = 0.48, CI: 0.33–0.70). The odds of an above-average assessment of overall quality of life in people with no savings were 65% lower than in those with savings (OR = 0.35, CI: 0.24–0.52). The overall quality of life was also related to respondents’ indebtedness, as those without debt were 2.5 times more likely to assess their overall quality of life above average than respondents with debt (OR = 2.5, CI: 1.89–3.31) (Table 10).

Table 10
Likelihood model of above-average assessment of overall quality of life by Wrocław residents with gross income≤1043 PLN (N = 1215)

Variable β SE Wald χ² p OR CI

–95% 95%

Intercept 0.52 0.34 2.28 0.131 – – –

Age

≤34 years vs≥45 years 1.48 0.19 63.81 <.001 4.40 3.06 6.33

35–44 years vs≥45 years 0.52 0.21 6.49 .011 1.69 1.13 2.52

Persons per household

≤2 persons vs≥5 persons –1.64 0.25 44.08 <.001 0.19 0.12 0.31

3–4 persons vs≥5 persons –0.74 0.21 12.72 <.001 0.48 0.32 0.72

Occupation

Laborer vs unemployed –0.49 0.23 4.55 .033 0.61 0.39 0.96

White collar worker vs unemployed 0.31 0.24 1.63 .202 1.36 0.85 2.17

Student vs unemployed 0.13 0.23 0.31 .579 1.14 0.72 1.79

Stable income

No vs Yes –0.74 0.19 14.68 <.001 0.48 0.33 0.70

Savings

No vs Yes –1.04 0.20 28.22 <.001 0.35 0.24 0.52

Indebtedness

No vs Yes 0.92 0.14 41.43 <.001 2.50 1.89 3.31

Variable	β	SE	Wald χ²	p	OR	CI
Intercept	0.52	0.34	2.28	0.131	–	–	–
Age
≤34 years vs≥45 years	1.48	0.19	63.81	<.001	4.40	3.06	6.33
35–44 years vs≥45 years	0.52	0.21	6.49	.011	1.69	1.13	2.52
Persons per household
≤2 persons vs≥5 persons	–1.64	0.25	44.08	<.001	0.19	0.12	0.31
3–4 persons vs≥5 persons	–0.74	0.21	12.72	<.001	0.48	0.32	0.72
Occupation
Laborer vs unemployed	–0.49	0.23	4.55	.033	0.61	0.39	0.96
White collar worker vs unemployed	0.31	0.24	1.63	.202	1.36	0.85	2.17
Student vs unemployed	0.13	0.23	0.31	.579	1.14	0.72	1.79
Stable income
No vs Yes	–0.74	0.19	14.68	<.001	0.48	0.33	0.70
Savings
No vs Yes	–1.04	0.20	28.22	<.001	0.35	0.24	0.52
Indebtedness
No vs Yes	0.92	0.14	41.43	<.001	2.50	1.89	3.31

Notes: β: assessment value of model parameters, SE: standard error β, χ²: chi-squared Wald test, p: chi-squared Wald test probability value, OR: odds ratio, CI: confidence interval for OR, LR = 356.0, df = 10, p < 0.001, Nagelkerke’s R² = 0.34.

4.7 Impact of socio-demographic status on the above-average assessment of perceived health condition

A model describing the likelihood of above-average assessment of perceived health conditions by Wrocław residents in income poverty is also well-fit (LR = 205.1, p < .001, Nagelkerke’s R² = 0.21) (Table 11). The likelihood of above-average assessment of perceived health condition was five times higher in respondents aged up to 34 years (OR = 5.01, CI: 3.60–6.98) and twice as high in respondents aged 35–44 years (OR = 2.27, CI: 1.56–3.29) than in respondents aged 45 years or more. Professional status also proved to be an important variable in perceived health condition assessment. White collar workers had twice (OR = 2.16, CI: 1.39–3.36), and students had one and a half times (OR = 1.58, CI: 1.03–2.42) higher odds of above-average assessment of perceive health condition than the unemployed. The probability of above-average perceived health condition assessment in respondents without a stable source of income was 30% lower (OR = 0.70, CI: 0.49–0.99) than in those with it, and in respondents without debt, the probability was 31% higher than in those with debt (OR = 1.31, CI: 1.01–1.70) (Table 11).

Table 11
Likelihood model of above-average assessment of perceived health condition by Wrocław residents with gross income≤1043 PLN (N = 1215)

Variable β SE Wald χ² p OR CI

–95% 95%

Intercept –1.20 0.22 29.48 <.001 – – –

Gender

Female vs male –0.26 0.14 3.72 .054 0.77 0.59 1.00

Age

≤34 years vs≥45 years 1.61 0.17 90.75 <.001 5.01 3.60 6.98

35–44 years vs≥45 years 0.82 0.19 18.45 <.001 2.27 1.56 3.29

Occupation

Physical worker vs unemployed 0.23 0.21 1.16 .282 1.26 0.83 1.91

White collar worker vs unemployed 0.77 0.23 11.75 .001 2.16 1.39 3.36

Student vs unemployed 0.46 0.22 4.48 .034 1.58 1.03 2.42

Stable income

No vs Yes –0.36 0.18 4.06 .044 0.70 0.49 0.99

Indebtedness

No vs Yes 0.27 0.13 3.99 .046 1.31 1.01 1.70

Variable	β	SE	Wald χ²	p	OR	CI
Intercept	–1.20	0.22	29.48	<.001	–	–	–
Gender
Female vs male	–0.26	0.14	3.72	.054	0.77	0.59	1.00
Age
≤34 years vs≥45 years	1.61	0.17	90.75	<.001	5.01	3.60	6.98
35–44 years vs≥45 years	0.82	0.19	18.45	<.001	2.27	1.56	3.29
Occupation
Physical worker vs unemployed	0.23	0.21	1.16	.282	1.26	0.83	1.91
White collar worker vs unemployed	0.77	0.23	11.75	.001	2.16	1.39	3.36
Student vs unemployed	0.46	0.22	4.48	.034	1.58	1.03	2.42
Stable income
No vs Yes	–0.36	0.18	4.06	.044	0.70	0.49	0.99
Indebtedness
No vs Yes	0.27	0.13	3.99	.046	1.31	1.01	1.70

Notes: β: assessment value of model parameters, SE: standard error β, χ2: chi-squared Wald test, p: chi-squared Wald test probability value, OR: odds ratio, CI: confidence interval for OR, LR = 205.1, df = 8, p < 0.001, Nagelkerke’s R² = 0.21.

5 Discussion

The study results show that many respondents with low incomes from Wrocław assessed their overall quality of life, perceived health condition, and health-related quality of life as average or below average. The results of the study correspond to the results by other authors. Although in their survey of adult Brazilians, Traebert et al. [34] found that as many as 75% of respondents assessed their overall quality of life and health status as good, the results were quite different in studies covering only respondents living in poverty. Sarti and Rodriguez [35], on the other hand, reported statistically significant differences in the self-assessment of overall quality of life of people from different social groups, with the worst results for those with low incomes. Low overall quality of life in the least affluent respondents was also observed by Hu [36]. The results of the present study and the corresponding findings by other authors, therefore, confirm that poor financial situation negatively affects the assessment of overall quality of life and health-related quality of life in people of working age. The reported associations are probably indirect, and factors directly influencing the assessment of quality of life in people with low income include psychosomatic diseases [2 –4], poor nutrition and low level of physical activity [56, 57], limited access to medical care [14] and a sense of social exclusion often faced by the poor [59, 61].

The respondents from Wrocław rated their health-related quality of life the highest in the social domain and the lowest in the physical and environmental domains. The results of previous studies regarding this issue are not unambiguous. While the highest average values of health-related quality of life in the social domain and the lowest in the environmental domain were recorded by Almeida-Brasil et al. [37], Cheung et al. [38], and Ping et al. [39], in none of these studies was the self-assessment of health in the physical domain low. On the other hand, patients [40] were characterized by low assessments of their health-related quality of life, which is explained by their ailments, being part of the assessment of this quality of life area. None of the cited studies, however, was conducted only among the poor, and negative correlations between the quality of life in the physical domain and the level of income are confirmed empirically [41]. The issue of differences in the assessment of health-related quality of life across domains among people living in poverty is therefore still open.

Among the residents of Wrocław with low incomes, their overall quality of life assessment was modified by age, household size, a stable source of income, savings and debt. The odds of above-average assessment of overall quality of life and perceived health condition decreased with respondents’ age. Gomez-Olive et al. [42] and Kim et al. [43] also noted a deterioration in the overall quality of life assessment with age. Age was also an important predictor of overall quality of life of low-income earners in a study conducted in China by Xiaoshi et al. [44]. Negative correlations of assessment of one’s own health condition with age were found by Gallegos-Carrillo et al. [45] and Traebert et al. [34]. The observed relationship is probably due to objective reasons, as numerous empirical studies indicate that health status, fitness, and psychophysical performance deteriorate with age [46, 47].

The odds of above-average assessment of respondents’ overall quality of life also increased with the number of persons per household. This variable had not been previously considered as a potential quality of life determinant. However, the data on income poverty in Poland [8] described in the paper indicate that in the worst material situation are not only large families with many children, but also less numerous single-parent families. This phenomenon does not have to be an artefact, which is also indirectly indicated by Morawski [48], who analyzed subjective thresholds reflecting the number of economic resources needed by households of all sizes to achieve the same level of well-being. He observed a decreasing marginal cost of living for subsequent children, which means that the average cost of living for one child is higher than for two and more children in a family. Moreover, the quoted studies show that the first child increases the cost of a two-person household more than the third adult. In the present study, information was collected only on the number of people in households, so the structure of households remains an open question. The methodological approach applied by Morawski [48] shows a worsening position of small households in well-being distribution in comparison to large households. This is rarely reflected in the implemented public policies, which may explain the study results obtained among the Wrocław residents. Moreover, Griep et al. [49] observed positive correlations of overall quality of life assessment with the number of children aged up to 18 in a family, which confirms that the quality of life is modified not only by economic but also psychological and social factors.

Unemployed respondents were significantly less likely to achieve above-average health assessments than students and white-collar workers. Low perceived health condition among the unemployed was also noted by Gallegos-Carrillo et al. [45], Janković et al. [50], and Traebert et al. [34]. Krug and Eberl [51] also showed that unemployment is often associated with emotional disorders, reduced levels of life satisfaction, and increased susceptibility to disease. Buffel et al. [52], on the other hand, reported helplessness, frustration, loss of self-esteem, increased stress, and depressive symptoms among the unemployed. Meneton et al. [53] noted a higher incidence of psychosomatic diseases, such as heart disease and cancer, in the unemployed than in the working population. Interesting observations were also made by Van Zon et al. [54], who surveyed people from three European countries: Poland, Spain and Finland and concluded that sometimes ill health – mainly disability, mental problems and visual and hearing impairments – create difficulties in maintaining or getting a job. In view of the above remarks, it seems obvious that the assessment of perceived health condition in the unemployed is worse than in students and employed individuals.

The odds of above-average assessment of overall quality of life were the highest among people with a steady source of income and with no debt, and in the case of perceived health condition also among respondents with money savings. For people living in income poverty, these components of the general material situation turned out to be significant determinants of the quality of life. A stable source of income increases the chances of the household to maintain its financial liquidity, and having savings and not having debt may allow maintaining consumption at a satisfactory level. Thanks to this, it is also possible to undertake certain activities aimed at prevention, treatment, or possible rehabilitation, which is of great importance for the health condition both in an objective and subjective sense. This was confirmed by Gallegos-Carrillo et al. [45], who noted in their research a clear link between subjective assessment of one’s own health and the feeling of social and financial security. The results of previous studies also confirm the important role of material situation for lifestyle [55] and lifestyle for quality of life [56, 57]. The financial situation was also an important differentiating factor in the assessment of overall quality of life in studies conducted by Chinweuba et al. [58], Mebarki, Ahmed Fouatih and Mokdad [17], Lam et al. [59–60], Rėklaitienė et al. [16], and Zhang and Xiang [61], and of health status in studies by Traebert et al. [34]. McNamee and Mendolia [62] also showed that the negative impact of the material situation on the subjective assessment of overall quality of life is particularly evident among the poorest people, living on the verge of minimum subsistence.

The study has its strengths and weaknesses. One of the strengths is the study group, because people living in income poverty have rarely been the subject of previous studies on health-related quality of life. So far, researchers have not taken into account such quality of life determinants as the number of people in the household, income from sources other than work (e.g., alimony, benefits, or family assistance), savings or debt. This is important because among the respondents from Wrocław these variables significantly modified their quality of life. This obliges us to explore further the links between quality of life and not only with the level of income, but also with respondents’ comprehensive material situation. An interesting research approach could also be to analyze respondents’ affluence not only from the perspective of income, but also expenditure, as the latter is a real determinant of the level and structure of consumption, which may have some significance for quality of life assessment.

The main limitation of the study is its restricted spatial scope. Future research should cover the whole territory of Poland, as well as other heterogeneous national populations, so that its findings can be generalized. This is important in the context of the presence of different social policy systems in individual countries, which is manifested, for example, by wider safety social benefit nets in many European countries, including Poland, as compared to the United States. This is confirmed by Gomez-Olive et al. [42], who showed that relationships between quality of life, both overall and health-related, with age, gender and socio-economic status varied from country to country. In subsequent studies, poor people should not be treated uniformly but divided into study groups, e.g. based on such categories as minimum subsistence level and minimum of existence. This is justified in empirical studies, because, as shown by Zhang et al. [15], the assessment of overall quality of life among people with low incomes is significantly higher than in people with very low incomes.

6 Conclusions

6.1 Theoretical conclusions

The results of the study show that Wrocław residents aged 18–64 living in income poverty most often assessed the overall quality of their lives as average or below average. The highest average ratings for health-related quality of life were reported for the social domain and the lowest for the physical and environmental domains. Age, household size, stable income, having savings and debt were all associated with the assessment of the quality of life of the Wrocław residents. The respondents also identified statistically significant relationships between the assessment of perceived health condition, age, professional status, stable sources of income and indebtedness.

6.2 Program and policy implications

The results of the study of Wrocław residents should be used in prospective proposals to representatives of public authorities and health care professionals. Planned public health programs should be addressed to beneficiaries at risk of low self-assessment of their overall quality of life and health condition, i.e., people over 45 years of age, living in one- or two-person households, unemployed, without any other permanent sources of income and savings, as well as those in debt. This is particularly important as the coronavirus pandemic continues. The results of the study clearly indicate that the COVID-19 pandemic has a negative impact on the quality of life of adults. This applies not only to the sick but also to healthy individuals, mainly due to isolation, the need to perform professional work at home, limited physical activity, conflicts with family and fear of losing one’s job and deterioration of material status [63]. Particularly significant negative impacts of the pandemic have been reported for health-related quality of life in the psychological domain [64, 65]. This also creates the need to implement continuous research on adult quality of life, using research tools adapted to the conditions of the pandemic. The measures taken should be geared towards health status in a holistic way, covering physical, mental and social aspects. As Schuler [6] showed in his research, subjective perception of one’s current health condition is sometimes a better predictor of overall quality of life than the occurrence of a serious physical or mental illness (objective assessment of quality of life). This may constitute a justification for the concept of quality of life management postulated more and more often by scientists [67].

Footnotes

Acknowledgments

The authors have no acknowledgments.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

The authors report no funding.

The European Quality of Life Survey (EQLS), carried out by Eurofound every four years since 2003, is an example of a study that explores this approach to quality of life. The EQLS is based on the HBL triad (Having, Being, and Loving). It identifies 12 areas of quality of life and uses 161 indicators (First 2007).

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Variable	β	SE	Wald χ²	p	OR	CI
						–95%	95%
Intercept	0.52	0.34	2.28	0.131	–	–	–
Age
≤34 years vs≥45 years	1.48	0.19	63.81	<.001	4.40	3.06	6.33
35–44 years vs≥45 years	0.52	0.21	6.49	.011	1.69	1.13	2.52
Persons per household
≤2 persons vs≥5 persons	–1.64	0.25	44.08	<.001	0.19	0.12	0.31
3–4 persons vs≥5 persons	–0.74	0.21	12.72	<.001	0.48	0.32	0.72
Occupation
Laborer vs unemployed	–0.49	0.23	4.55	.033	0.61	0.39	0.96
White collar worker vs unemployed	0.31	0.24	1.63	.202	1.36	0.85	2.17
Student vs unemployed	0.13	0.23	0.31	.579	1.14	0.72	1.79
Stable income
No vs Yes	–0.74	0.19	14.68	<.001	0.48	0.33	0.70
Savings
No vs Yes	–1.04	0.20	28.22	<.001	0.35	0.24	0.52
Indebtedness
No vs Yes	0.92	0.14	41.43	<.001	2.50	1.89	3.31

Quality of life of low-income adults

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

2 Theoretical bases for the study

4 Results

4.1 Socio-demographic factors assessment

Table 1 Socio-demographic characteristics of Wrocław residents with gross income≤1043 PLN (N = 1215)

6 Conclusions

6.1 Theoretical conclusions

6.2 Program and policy implications

Footnotes

Acknowledgments

Conflict of interest

Funding

References

Table 1
Socio-demographic characteristics of Wrocław residents with gross income≤1043 PLN (N = 1215)