Diversity & Equality in Health and Care Open Access

Keywords

Health behaviors; Health inequalities; Quality of life; SF 36; Social inequalities

What is Known About this Topic?

• The "Black Report" is the first report which shows that social inequalities are important for identifying health

• The level of inequalities among different social groups and between people living in different parts of the world remains high.

• Health-related quality of life is a multi-dimensional concept that includes domains related to physical, mental, emotional, and social functioning.

• The causes, as well as the importance of different influencing factors are not clear.

What the Paper Adds?

• Various factors that appear to be associated with low quality of life related to health are: female gender, older age, low education, lower occupational classes, reduced income and some health behaviors such as smoking, alcohol consumption, lack of physical activity and obesity.

• Although the health of the population in most countries in the world is improving, the rate of improvement is not the same for all social groups.

• Women seem to have lower scores in quality of life.

• Social gradient was associated with poorer self-rated health and poorer quality of life in both men and women. Regardless of their health status, people with lower social status are more likely to report poor health status (self-rated) and poorer quality of life.

Introduction

Quality of life appeared in the literature in early 1960’s [1]. Health-related quality of life (HRQoL) can be defined as an individual’s ability to carry out some activities refers to functioning, while an individual’s subjective feelings refers to prosperity [1,2]. Thus, health-related quality of life represents a broad concept of physical, psychological factors with social functioning and well-being [2].

According to World Health Organization [3] health inequalities show that social inequalities in health are a scientific, academic, research, political and social issue. While significant progress has been made in the health sector, the level of inequalities among different social groups and between people living in different parts of the world remains high [4,5].

Social inequalities in health have been at the heart of discussions and reflections at European Union, international organizations and the scientific community in recent years. The "Black Report" is the first report which shows that social inequalities are important for identifying health and was published in 1980, from the British Ministry of Labour. According to that report, the 1971 mortality rate for the ages of 15-64 was twice as high for lower social classes as for those in the upper social class. The conditions under which people live and work are important for identifying health and illness, with reference to the impact of the socio-occupational category on the determination of the level of health and the existence of inequalities in morbidity and mortality rates among the categories [6,7].

Comparative and national studies suggest that the existence of inequalities in health is not only universal, (among the European and non-European populations), but it has also remained stable or even increased with time [8-11].

Defining social inequalities in health

Social inequalities in health is the general term that is used to define differences in the health of individuals and groups, both in relation to individual features and feature-subgroups of a group level population [12].

Social inequalities in health refer to the systematic

differences in health between different socio- economic groups. Three characteristics, when presented in combination, are the notional difference between what is considered as a simple variation in health and social inequality in health [13]. The first characteristic refers to the systematic pattern of differences in health. These differences are not distributed randomly; instead, they seem to have a stable pattern. An example is the systematic differences in health between the different socio-economic strata of the population. The second characteristic refers to the differences in health that have roots in social processes, and they are not biologically defined. The third characteristic of social inequalities in health is that they are widely viewed as unfair because they are created and maintained by what Evans & Peters [14], have called "Unjust Social Arrangements," and which they inflict fundamental concepts of justice [3].

Importance of social inequalities in health for community and public health nursing

The extent of health inequalities varies between countries, within countries and between people. This suggests that these inequalities are influenced by the social policy of the state and the individual’s characteristics - and therefore are likely to be modifiable. In Scotland, for example, a child born in the most disadvantaged neighborhood of Glasgow is expected to live up to 10 years less than a child growing up in the most affluent neighborhood [3].

Although the health of the population in most countries in the world is improving, the rate of improvement is not the same for all social groups. This social pattern of disease is global, although its degree and extent vary from country to country [4]. Reversing these trends is one of the greatest challenges in recent time. WHO has set as immediate priority on achieving justice and equity in health [15-17].

The existence of social inequalities in health is a challenge to public health and, at the same time, public health is a core of work for all nurses. Nurses are daily confronted with the consequences of social inequalities in health and wellbeing of communities. The community development approach takes a broad-based positive view of health, instead of focusing on illness and includes evaluation of the social aspects that determine the health and well-being (e.g. housing, poverty, education level). Empowering individuals and communities to take control of their lives will help significantly in improving their health [18].

Social inequalities in health, seriously threaten social cohesion and, therefore, their investigation is essential for public and community health. Poverty reduction, effective health care for citizens and improved quality of life are long-term objectives for ensuring social and economic cohesion [19-21].

Aim of the paper

Despite the extensive literature on inequalities in health, the causes, as well as the importance of different influencing factors (e.g. smoking, alcohol, obesity, physical activity), are not clear [4]. Some of the factors [4,22], also include: the natural environment (high levels of pollution, noise, geographical distribution), the working environment (e.g. work stress), the health system (quality of health services, access to health services) and the social environment (social support environment, access to social resources). Why this is here move it up- here only aim the aim of the paper is to present the review of the literature of population and community studies, that have used the SF36 tool to investigate the quality of life in the general population.

Materials and Methods

This is a systematic review contacted in SCOPUS database. Articles were also searched, using the web search engines. The inclusion criteria were:

• Year of the study 2011-2017.

• Study area: European country, whether the study has a national scope or concerns a specific area, city, etc

• Studies that used the SF36 quality of life-related health assessment tool, regardless of whether other assessment tools and related concepts were used in parallel.

• Studies used the 8 subscales of SF36 only or the two component scores (physical and mental component scores).

• Studies in English or Greek language.

• Studies whose main research question was to investigate the quality of life in a general "healthy" population regardless of whether the sampling was conducted in the community or in a clinical environment, and regardless of whether they limited the investigation to an age group or gender. Studies were included which concerned a specific sample of the population but had "general population".

• Aim of the studies: (a) to estimate population norms for the population under study) and / or (b) to investigate social status in QoL and presenting data in QoL in relation to social status indicators (either individuals such as education, income, occupational class, eco- indicators of socio-economic disadvantage of the residence area, or other indicators of material deprivation and social exclusion) and / or (c) studies to investigate gender differences and / or (d) to investigate the correlation of health behaviors and lifestyle factors (e.g. smoking, physical activity) and relevant factors (e.g. obesity) with quality of life.

• Research studies with primary data regardless methodological design (descriptive correlation studies or comparison whether sectional or longitudinal and / or studies on experimental design if they provided data for QoL at the reference point).

Search methods

A systematic review of the literature was performed at SCOPUS database from January 2017 to August 2017. An advanced search was built in one level of searching, using as key words: SF – 36 OR SF 36 OR SF36 OR Short Form 36. Only research studies were selected, either Article or Article in Press.

Results

The searching led to the selection of 5815 articles. Of these, 5758 were discarded after reading the title, 25 after reading the abstract and 14 after the full text reading. A total of 18 research studies were identified, which complied with the eligibility criteria (Figure 1).

Description of the studies

Year, place, type of data and conducted level of the included studies

All studies that met the criteria conducted between 2012 and 2017.

The search has led to a variety of studies as far as the country is concerned. Specifically, the choice of 18 studies includes countries such as Norway [23], Portugal [24], Finland [25-27], Spain [28,29], Great Britain [30,31], France [32-34], Poland [35,36], Greece [37], Russia [35], Lithuania [35], Holland [38], Ireland [38] and Czech Republic (Table 1) [35].

Table 1: Multistage probability sampling studies.

The purpose of the studies was to investigate the quality of life in relation to different health situations or even in relation to various health behaviors, using the SF36 as the main tool.

Methodology of studies

Most of studies, were cross-sectional [23,25,27,31,33,35-37,39]. In cross-sectional studies, although there is a time dimension, data is collected at a given point time, so there is the opportunity to explore both population groups that differ in evolution or experience stage [40]. In addition, two studies had as a design the descriptive correlation study [34,41], one the descriptive study [28], one was Trend survey [32], one was panel study [26], one was prospective study [24], and four were cohort studies [29-31,38].

In seven studies out of 18 (7/18), the data were obtained through an interview [24,27,28,30,33,39,41]. Some researchers chose postal questionnaire technique and the subjects completed self-administrated questionnaires [28,35,36,38], some others chose combination of an interview and self-administrated questionnaire [23,32,34] or an interview and physical examination [24,25,29] or self-administrated questionnaire and physical examination [31], or even self-administrated questionnaire, interview and physical examination [37].

The size of the sample varied among the studies. Specifically, in the studies of Wanderley et al. [41] and González-Rubio et al. [28], the sample was 85 and 231 respectively. In contrast, the studies of Dorynska et al. [35] and Delpierre et al. [34], had a very big sample, 34431 and 21785 respectively. Five out of eighteen studies had a sample less than 1,000 people, while eight out eighteen studies had a sample of over 5,000 people. The sampling design was different between the studies. Some studies used stratified and random sampling design [33,34], some used convenience sampling [23,24,28,29,31,36,37,41], some other used random sampling [32,35], while some studies used the sample from previous studies [25-27,30,38] and one study used the multistage probability sampling (Table 1) [39].

Quality of life and correlation with other variables

Factors that appear to be associated with low quality of life related to health are: female gender, older age, low education, lower occupational classes, reduced income and some health behaviors such as smoking, alcohol consumption, lack of physical activity and obesity (Table 2: Correlations of quality of life with other variables).

Table 2: Correlations of quality of life with other variables.

Gender

As shown in Table 2, 13 out of 18 studies investigate differences in quality of life and gender. The studies that investigated the correlation of quality of life with gender, show that women seem to have lower scores in quality of life [24,25,31-33,41]. Specifically, the study of Garratt et al. [23], shows women to have lower scores than men, in all dimensions of the SF36 quality assessment tool. The study of Wanderley et al. [41], presents men to have higher scores in 4 dimensions: physical functioning (p=0.02), general health (p=0.03), vitality (p=0.03) and mental health (p<0.01). However, in women, the factors that appear to be protective factors are low BMI, low risk of diabetes and low risk of other chronic diseases [24].

Age

Age was studied in 7 out of 18 studies [23,24,31,32,36,38,39]. Żołnierczuk-Kieliszek et al. [36], conducted a study that shows younger women to have a significantly better quality of life than older women (p <0.05). Garratt et al. [23], found that the two youngest age groups (<30 years) have better scores in the physical component summary scale, while the age groups 40- 49 years and 60-69 years showed the highest scores in mental component summary scale - emotional role and mental health.

Educational level

A significant predictor of higher quality of life scores is the level of education [35-37]. In particular, higher quality of life scores were shown between women having a bachelor and master degree, while the lowest scores were showed between women with no primary education, women who completed only primary education and women who graduated from high school [36].

Occupational status and income

According to Pietiläinen et al. [26], lower occupational classes showed lower score in physical component summary scale, both between men and women.

Women in full-time employment enjoyed a significantly better quality of life than the other participants. The type of occupation is also important, as manual workers seem to have lower quality of life scores than those working as teachers or in a profession with high levels of responsibility. Better income corresponds to a better quality of life [36].

Social gradient

Delpierre et al. [34], showed that social gradient was associated with poorer self-rated health and poorer quality of life in both men and women. Regardless of their health status, people with lower social status are more likely to report poor health status (self-rated) and poorer quality of life.

Health behaviors

In relation to alcohol consumption, men seem to consume higher amounts of alcohol (15.8 gr) per day than women (10.8 gr) per day [28]. Women showed statistically significant reduced alcohol consumption, lower BMI and less physical activity than men (p <0.001).

In relation to smoking, male smokers showed lower scores in physical fitness and general health, while younger male smokers showed higher scores in health-related quality of life [33].

A significantly lower quality of life was showed in single women (unmarried women, women in separation, divorced or widowed). Significant difference in quality of life is shown in women living alone, singled, divorced, widows or even in a dimension. Lower quality of life was also indicated in women participants living in rural areas [36].

Lente et al. [40], showed clear correlations between increased levels of self-rated of health, active physical activity, reduced visits to general practitioner (GP), and good mental health (p<0.001).

Discussion

This study reviewed 18 research papers, which have used the SF36 tool to investigate the quality of life in the general population. Most of the studies were observational studies, that involves a cross-sectional design and all the measurements for a sample member are obtained at a single point in time.

The common feature of most studies seems to be that they are investigating many factors such as income, presence of chronic diseases, health behaviors (smoking, alcohol consumption, and physical activity), obesity and more. Although they present data on both genders, no study shows the social gradient and how it differs in gender.

The studies seem to consider the area of living as a variable to correlate with quality of life. None of these studies are using the area evaluation as a composite indicator and how the quality of life of the individual is affected by the characteristics of the area in which he or she lives. They use the variable area of living just to present data from the urban or rural area.

Almost no study determines the individual's social status in multiple ways. All studies use one's own individual characteristics such as income, education, and occupation. Τhe only study referring to socioeconomic position over the life is that of Otero-Rodriguez et al. [29], who consider socioeconomic position as an index of three variables, father’s occupation, educational level and occupation of the household head.

A special reference should be made to two studies. The first one is the study of Bosma et al. [38] that refer to the concept of ‘perceived unfairness’. Perceived unfairness was most often reported by persons with lower socioeconomic position, women and elderly. Both perceived unfairness and socioeconomic position were related to lower score of quality of life. The second study is the study of Otero-Rodríguez et al. [29], who studied the concept of social status both in childhood and in adulthood. The lowest socio-economic position in childhood is associated with a higher risk, both for physical and mental health. In contrast, social status in adulthood does not seem to be related to changes in quality of life levels.

Systematic review seems to present the phenomenon of multiple-role woman. As women continue to balance with working outside the home, as well as with their responsibilities within the home, the idea of simultaneously participating in multiple roles has become a social 'rule' [42]. In addition, maintaining the multiple roles can lead to a stressful conflict between the roles resulting in a person's dissatisfaction with the ability to perform those roles. This may have negative psychological and physical effects [43].

Inequalities affect everyone. Conditions that lead to marked health disparities are detrimental to all members of society. Some types of health inequalities have obvious spillover effects on the rest of society, for example, the spread of infectious diseases, the consequences of alcohol and drug misuse, or the occurrence of violence and crime,Public and community health nursing advocates for a healthy society established on a foundation of social justice. Community and public health nurses are daily confronted with the consequences of social inequalities in health. Nurses reach deep into families and communities and provide care to wider population in a complex work environment [16,21,44].

Public health and community nurses incorporate the identified needs of the population in policy development and program or service planning, evaluates effectiveness of advocacy and strives to resolve conflicting expectations from populations, providers and other stakeholders [18].

Our study has a number of limitations. Initially, a limitation is the fact that only the studies that used have SF36 been selected, however is one of our inclusion criteria and one of the most trusted tools to investigate the quality of life. Another limitation is the fact that the investigation was limited to Europe, although the population is as homogeneous as possible.

Conclusions

Over the past two decades, social inequalities in health became a scientific, academic, research, political and social issue. The economic crisis of recent years has highlighted the social inequalities in the most basic question in relation to the overall health of a country.

The global life expectancy curve, which appears to have a tremendous increase in the proportion of the population that manages to live up to an older age, urges societies to an increased understanding of how to ensure health and quality of life at older ages.

Differences in the professional class, which relate to physical functioning, appear to be widening. There is a reduction in physical function in lower professional classes. Various health behaviors, the employment status and material conditions may explain to some extent the widening of differences in physical function of the professional classes.

The majority of studies show that gender, as a factor, affects the risk factor patterns and this has a different impact on the quality of life. For this reason, gender specificities should be considered in health prevention strategies.

All health and care professionals should have a better understanding of the causes and consequences of health inequalities so that services that reduce health inequalities become an intrinsic part of care services.

Public and community health nurses advocate for government policy to address these issues could result in important changes to reduce income inequality and improve the health of the population. Nurses, together with other health professionals, must create a climate where socioeconomic differentials are unacceptable, and thus remain true to one’s heritage of advocating for a healthy society.

Competing Interests

None declared.

Authors' Contributions

PE, CK and NM planned the study. PE performed the database search and analyzed the data. PE searched the literature and drafted the manuscript. All authors participated in the selection of inclusion criteria. All authors assisted with the manuscript and read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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