Material deprivation and health-related dysfunction in older Dutch people: findings from the SMILE study

Abstract

Background: Even in generally wealthy Western countries material deprivation and poverty are not uncommon. There is, however, little data on the prevalence of material deprivation and its associations with health-related dysfunction in older people. Methods: Cross-sectional data from the SMILE study were used to examine the prevalence of material deprivation and the associations between material deprivation and health-related dysfunction in persons aged 55 years and older (n > 4000). Material deprivation was measured with a comprehensive questionnaire assessing seven subdomains referring to current and anticipated financial problems and poverty in childhood. Health-related dysfunction was measured using the SF36-based physical and mental components. In addition, self-reported heart disease was examined as an indicator of health-related dysfunction as well. Results: Almost 29% of subjects experienced at least one financial problem. Those reporting material deprivation had more than twice the risk of physical (OR = 2.22; 95% CI: 1.72–2.86) and mental (OR = 2.34; 95% CI: 1.84–2.97) dysfunction compared with non-deprived persons. A slightly weaker association was found when self-reported heart disease was used as an outcome variable (OR = 1.74; 95% CI: 1.40–2.15). Although odds ratios were generally higher for diseased older persons, no significant interaction effect between chronic disease and material deprivation subscales was found. Conclusions: Material deprivation in the Netherlands is not uncommon and is strongly related to both mental and physical dysfunction, and therefore needs further attention in public health policy. Longitudinal research is necessary to clarify the causal nature of our results and to develop appropriate interventions.

Introduction

Although the definition of poverty in a rich country differs qualitatively from that in a poor country, many developed countries have experienced a sharp rise in income inequality.¹ In addition, there is evidence that income inequality is still increasing.² This is also manifested in the fact that material deprivation is not uncommon even in generally wealthy Western countries. Moreover, the rise in the number of ‘foodbanks’ or food rescue organizations in these countries³ indicates that many people have trouble making ends meet.

In the Netherlands, it has recently been documented that persons between the ages of 55 and 64 live below the poverty line relatively often (10.4% of this group can be defined as ‘poor’, compared with 9.1% in the general Dutch population). Moreover, income inequality in this group of ‘young’ older people is highest.^4,,5

Although inconsistent results have been found, most research evidence suggest that differences in health (morbidity and mortality) across groups of different socioeconomic status are also present in early old age.^6–9 However, evidence on the prevalence of material deprivation and its effects on health-related dysfunction, in particular in these older persons, is rather sparse^7,,10–13 and only a small number of deprivation indicators have been examined (mostly as proxies for socioeconomic status).^14,,15

Apart from the dearth of information, material deprivation and material factors have been conceptualized in different ways, from restricted standards of living (the lack of two or more of 10 items or activities that are considered necessary by the majority of society),^16,,17 having financial problems (difficulties with paying bills for food, rent or electricity),¹⁸ limited or lack of health insurance, no car ownership and no household tenure¹⁹ to restricted household item ownership (from basic needs to luxury goods).²⁰ An in-depth examination of the prevalence of material deprivation—measured using a comprehensive questionnaire—and its effects on health is lacking, particularly in older people.

To obtain an in-depth insight into the potential relevance of material deprivation for public health (policy), this article describes the prevalence of material deprivation in a large community-based older population and explores the link between material deprivation and mental and physical dysfunction and heart disease.

Methods

Design

Data were obtained from the longitudinal SMILE study (i.e. Study on Medical Information and Lifestyles Eindhoven). This dynamic cohort study started in November 2002 in collaboration between Maastricht University and nine primary health care centres in Eindhoven, a city in the south-eastern part of the Netherlands. By means of postal questionnaires, data on health, lifestyle and health care use have been collected. From May 2003, all people aged 55 and older who were registered with the participating primary health care centres (including persons living in homes for older people) received a questionnaire.

Study population

The present study uses data that were collected in May 2004, from 5109 (response rate = 45.7%) men (N = 2313; 45.3%) and women (N = 2796; 54.7%) between the ages of 55 and 98 (mean age = 68.2; SD = 9.0). The respondents’ age and gender distribution was similar to that of the target population of May 2004 (N = 11 172). Data on educational level was extracted from the May 2003 questionnaire. However, due to missing data (N = 533 for material deprivation, N = 67 for educational level and N = 738 for mental and physical dysfunction—partly overlapping persons), analyses were conducted with a minimum number of 4019 persons.

Measures

Material factors

Material deprivation was defined as a financial strain and/or the enforced lack of material resources.^21,,22 It was measured in May 2004 using a new, 20-item instrument developed by the Social and Cultural Planning Office of the Netherlands (SCP).²² The instrument comprises six subscales on problems with living expenses (one item), problems with managing the household income (one item), negative outlook on the upcoming year's financial situation (one item), problems with settling debts (one item), reports of economic strain (nine items), and lack of durables for financial reasons (seven items). Results of principal component analyses indicate that these six indicators all point to one factor: material deprivation (explained variance: 45%).²²

The scales on living expenses, managing with household income, outlook on the upcoming year's financial situation, and settling debts were dichotomized, defining persons that report moderately heavy, heavy to very heavy problems as materially deprived (indicated in table 1).²² Economic strain and the lack of durables were also dichotomized as defined in table 1.

In addition, one item concerning poverty in childhood was appropriated from the Dutch GLOBE study.¹⁹ Originally, this item consisted of four potential answers ranging from ‘in the past we constantly lacked money to buy food or new clothes/shoes when necessary’ to ‘we never lacked money in the past’. This item was also dichotomized (table 1).

After all subscales were dichotomized, a compound deprivation score (0–1) was also computed. Subjects were then considered deprived when reporting three or more material problems according to the seven subscales. With a Cronbach's α of 0.67, the internal consistency of the total seven-item material deprivation scale was found acceptable. When deleting the item relating to poverty in the past, Cronbach's α increased to 0.76. Both the compound score and the individual subscale scores were used in the analyses.

Health

Three indicators of health-related function were used: self-reported mental and physical dysfunction and self-reported heart disease. Information about mental and physical dysfunction was derived from the Dutch version of the MOS SF36, measured in May 2004.^23,,24 The SF36 is a short-form health survey of 36 questions, clustered in eight subscales relating to functional health and well-being. The eight scales can be recoded in two distinct higher ordered components: physical and mental function. Several factor analytic studies have confirmed that the physical and mental function components account for 80–85% of the reliable variance in the eight scales in general populations.^24,,25 For the purpose of this study, physical and mental dysfunction was defined as having a score below the 10th percentile (scores of 29 and 35 out of a range from 0 to 100, respectively). The prevalence of self-reported heart disease in May 2004 (13.8%) was also used as an indicator of health-related function. Heart disease is often used as an outcome variable in relation to socioeconomic measures such as income, education and occupation.²⁶ However, the relationship between heart disease and measures of material deprivation in older people has been studied much less frequently.²⁷

Confounders

Education was measured in May 2003, using a seven-point scale. Three categories were then created in such a way that each group contained a third of the sample: primary school only (low); lower vocational education and intermediate general education (middle); intermediate vocational education; higher general education; higher vocational education and university (high).

Age and gender were also considered as confounding variables. Furthermore, because physical and mental dysfunction may be more common among persons with somatic disease,²⁸ severe chronic diseases were also included as confounding variables in the analyses in which physical and mental dysfunction were the outcome variable. In addition, these analyses were performed separately for persons with (46%) and without (54%) at least one of the following selected chronic (self-reported) diseases: COPD/asthma (15.6%), heart diseases (13.8%), bowel diseases (9.6%), liver diseases (1.9%), kidney diseases (3.0%), diabetes (10.4%), cancer (10.7%), epilepsy (1.8%) or stroke (4.6%).

Statistical analyses

Chi-square tests were performed to evaluate whether there were gender, age and educational differences in material deprivation. Moreover, multiple logistic regression models were fitted to examine how material deprivation scores were related to physical and mental dysfunction and self-reported heart disease. The ‘not deprived’ condition was always used as the reference category in these analyses (OR = 1). In analyses in which physical and mental dysfunction were the outcome variables, the first model was adjusted for age and gender. The second model also included educational level and the third the indicator for prevalent severe diseases. Furthermore, analyses were performed separately for persons with and without severe diseases, and interactions between disease, gender and age and material deprivation subscales were tested as well.

In analyses in which self-reported heart disease was the outcome variable, the first model was adjusted for gender and age. The second model additionally included educational level.

All statistical analyses were performed using SPSS 12.0.1.

Results

Table 1 presents the prevalence of material deprivation according to age, gender and level of education. The results show that 18.4% of our study population reported at least three of the selected material problems. Moreover, almost 29% experienced at least one of the financial problems. In particular, replacing old furniture (20.9%), inviting family and friends for dinner (16.4%), and going on a one-week holiday (15.3%) were financially problematic items. However, it is also striking that 4% was not able to eat a meal with meat, chicken or fish every two days and that more than 6% was not able to heat their house adequately because of economic strain. Three percent of the study population had difficulties in the settling of debts.

The results further show that persons between 55 and 64 years of age were significantly more likely to be materially deprived: 20.3% of the youngest age category reported at least three problems, compared with 18.3% and 14.8% in the higher age categories. There were no substantial gender differences concerning material deprivation. However, women had a slightly better expectation of their financial situation for the upcoming 12 months compared with men (18.2% versus 21.9% expected her/his financial situation to deteriorate), though women experienced more current financial strain (30.6% versus 26.6% reported at least one immediate financial problem at present). With the exception of the upcoming year's financial outlook and the settling of debts, lower educational level was consistently and significantly related to the prevalence of material deprivation (28.1% of the lowest educated group reported at least three material problems, compared with 11.6% of the highest educated group).

Table 2 shows a strong association between material deprivation and mental and physical dysfunction. Deprived persons had over twice the risk of physical (OR = 2.63; 95% CI: 2.05–3.36) and mental dysfunction (OR = 2.57; 95% CI: 2.04–3.25) compared with non-deprived persons (model 1). These associations remained when adjusted for age, sex and educational level (model 2). When further adjusted for chronic severe diseases (model 3), the settling of debts (with its low prevalence; see also table 1) was no longer significantly related to physical dysfunction. All other odds ratios for material deprivation remained significantly associated with physical and mental dysfunction (OR = 2.22; 95% CI: 1.72–2.86 and OR = 2.34; 95% CI: 1.84–2.97, respectively).

Although it was hypothesized that persons with severe chronic disease may be more strongly affected by material deprivation, no significant interaction between disease and material deprivation subscales was found. However, results for both physical and mental function differed between persons that were and were not diseased. Odds ratios were, overall, slightly higher for the diseased older persons (table 3).

Heart disease

The odds ratios of heart disease for the deprivation indicators were slightly weaker, but still substantial and consistent across the deprivation measures even when controlled for educational level (table 4) (OR = 1.74; 95% CI: 1.40–2.15). A negative outlook on the financial situation and poverty in the past were not related to reports of heart disease. Adjusted odds ratios for other subscales ranged from 1.55 (95% CI: 1.27–1.88) for experiencing living expenses as (very) heavy to 2.85 (95% CI: 1.90–4.28) for the settling of debts.

Effects were similar in men and women and for both the younger and older age groups. Interaction terms were not significant in our analyses. Furthermore, when using linear regression analyses with mental and physical function as continuous variables, similar associations were found. In additional analyses, in which we corrected for individualized income instead of education (not tabulated), the odds ratios decreased but remained significant (OR = 1.68; 95% CI: 1.14–2.48 for physical dysfunction and OR = 1.62; 95% CI: 1.10–2.38 for mental dysfunction, respectively). In the analyses presented here, we controlled for education, as correcting for income could have resulted in over-adjustment given that material deprivation and income are conceptually highly correlated.

Discussion

This study showed that material deprivation is highly prevalent among older adults in the Netherlands. One-fifth of our subjects reported problems with managing the household income, one-fifth expected future financial problems and one-fifth could not afford to buy new furniture. Material deprivation was more common in those younger than 65 and those with a lower educational level. Persons reporting material deprivation had more than twice the risk of physical and mental dysfunction compared with non-deprived persons. Although odds ratios were slightly higher for the diseased older persons, interaction tests revealed that deprivation had similar effects on physical and mental function in persons with and without a severe disease. Associations between material deprivation and heart disease were only slightly weaker compared with that of physical and mental dysfunction.

Interpretation

The meaning of poverty differs between rich and poor countries. In poor countries, material conditions influencing health include the mere absence of food, clean water and sanitation. In rich countries, they include not being able to afford a meal with meat, chicken or fish every second day or not being able to heat one's house properly. Both conditions might have direct biologically damaging effects on health and function.^20,,29 However, there may also be psychosocial pathways involved.³⁰ The psychosocial factor hypothesis implies that inequalities are due to the effects of chronic stress^16,,31–33 stemming from existing on the lowest rung of the socioeconomic hierarchy.^32,,34 This relative disadvantage, along with social comparisons with others higher in hierarchy—rather than absolute material circumstances and their potentially direct biological consequences—may also be relevant to explaining the poor health outcomes of socioeconomic adversity in Western countries.^31,,32 The additional importance of psychosocial mechanisms, even in cases of absolute poverty, was recently supported by the finding that Dutch food banks are increasingly being moved to the suburbs, where their customers report less shame and other psychosocial problems, given that their visits to these more secluded environments are less likely to be noticed.³

Our finding that the prevalence of material deprivation decreases with age (i.e. that persons between 55 and 64 years of age were more materially deprived compared with their older counterparts) is difficult to explain, especially when taking into account decreases in income due to retirement. However, this finding does correspond with previous research on poverty in the Netherlands.^4,,21,22 One explanation might be the ‘wealthy survivor’ effect: i.e. the most deprived persons have died prior to their 65th birthday. It may also be that older people differ in their perception of material well-being because its definition has changed over time.²¹ For example, buying new clothes and taking a week-long holiday was much less obvious in the past than it is nowadays. Moreover, ‘adaptive preferences’ (as explained below) might also account for this finding.

Limitations

Several methodological limitations may affect the interpretation of these results. First, our analyses were based upon cross-sectional data. Therefore, it is not possible to draw any conclusions about the causal direction of our results. The causation perspective assumes that material deprivation affects health-related function. The selection perspective assumes that poor health affects material deprivation.³⁵ In any case, we found substantial associations between material deprivation and health problems. The issue needs further examination in forthcoming longitudinal research: unravelling the causal mechanisms between material deprivation and health problems in older persons may help develop adequate interventions and programmes to promote healthy ageing.

Secondly, our study relied solely on self-reports, which might have led to bias in our dysfunction measures.³⁶ Individuals with a general tendency towards negative perceptions of material well-being may also over-report symptoms of (heart) disease,³⁷ which may have led to an overestimation of the presented association. Furthermore, individuals’ expectations and negative perceptions of their material well-being tend to decrease with long-term poverty, the so-called ‘adaptive preferences’.^38,,39 As a consequence, chronically poor people may have underreported their poverty. Out of shame, they may not want to admit not being able to afford certain items. Furthermore, the ‘poverty in the past’ item may have caused measurement errors due to the deteriorating memory in some of the older people. Whether and how these limitations have affected our findings, however, is unclear.

Thirdly, important indicators of material circumstances such as physical housing, neighbourhood and working conditions were not measured, and are therefore lacking in our study. The full impact of material factors on health-related dysfunction, then, is likely underestimated.

Finally, our research may be limited by possible selection biases. Older people living in convalescent homes were not included, which restricts the generalizability of our findings. The most disadvantaged older people may be underrepresented in our research, because of premature mortality (the ‘healthy survivor’ effect). Moreover, in the highest educated group (as reported in 2003), 24% were lost to follow up in 2004, versus 37% in the lowest educated group. Furthermore, 28% of persons reporting a good physical function in 2003 versus 34% of persons reporting physical dysfunction were lost to follow up in 2004. Finally, analyses revealed that persons with missing values on mental and/or physical function scales were generally more likely to be lower educated and more materially deprived. Similarly, persons with missing values on material deprivation items were more likely to report poor mental and physical function. This selective response and attrition may have led to an underestimation of the prevalence of material deprivation and the relationship between material deprivation and physical and mental dysfunction.

Conclusion

Material deprivation is not uncommon in older people in the Netherlands, between the ages of 55 and 65 in particular, and is strongly related to both mental and physical dysfunction. This issue, therefore, clearly requires further attention in public health policy. Taking into account the increasingly ageing population and associated health care costs, heightening public awareness of material deprivation and its adverse health effects is of great importance. Furthermore, more longitudinal research is necessary to develop efficient, targeted interventions.

Acknowledgements

The longitudinal SMILE study is carried out by the Department of General Practice of Maastricht University, in collaboration with the Eindhoven Corporation of Primary Care Centres. The researchers are indebted to the participants for their willingness to participate in the study.

Conflicts of interest: None declared.

References