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UNDERSTANDING SOCIO-ECONOMIC INEQUALITIES AFFECTING OLDER PEOPLE

PAUL MCGILL

Understanding Socio-Economic Inequalities Affecting Older People2

AcknowledgementsThis research forms part of a programme of independent research commissioned by the Office of the First Minister and Deputy First Minister (OFMDFM) to inform the policy development process and consequently the views expressed and conclusions drawn are those of the author and not necessarily those of OFMDFM.

Paul McGillCentre for Ageing Research and Development in Ireland

June 2014

3Understanding Socio-Economic Inequalities Affecting Older People

CONTENTSAcknowledgements 2

Executive summary 5

Introduction 7

Research questions 7

What are socio-economic inequalities? 7

1. Analysis of CARDI research reports 8

CARDI ageing research 9

Part 1: References to inequality 10

Part 2: Poverty and disadvantage 12

Part 3: Research projects with statistics on inequalities 15

Summary 22

2. Distribution and deprivation of older people in NI 23

Part 1: Spatial distribution of older people in NI 26

Part 2: Income Deprivation affecting Older People 28

Part 3: A local profile of deprivation among older people 31

Summary 35

3. Income inequalities in Ireland, North and South 36

Part 1: Earnings 37

Part 2: Pay inequalities within the older age group 41

Part 3: Income inequalities 45

Part 4: Accounting for greater income inequality 49

Summary 52

4. Policy background 53

Part 1: Broad policy context 54

Part 2: Public policy in Ireland 56

Summary 58


5. Implications for policy 59

Social inclusion 61

Care 61

Poverty 62

Health and well-being 62

Income inequalities 63

Social transfers/benefits 64

Occupational and private pensions 65

Spatial deprivation and income inequalities 65

Implications for data collection 65

Conclusion 66

6. References 67

Appendix 1: Data on inequalities within the older population, NI and ROI 72

Appendix 2: Income deprivation among older people (NI) 74


EXECUTIVE SUMMARYThere is long-standing evidence of the impact of inequalities in areas such as life expectancy, health, employment, education, housing and social inclusion. This debate has been particularly intense in the recent years of economic austerity. However, less attention in this field has been given to the dimension of age.This report explores socio-economic inequalities, with a particular focus on older people, and seeks to answer four main questions:

1 Are there inequalities that affect older people as a group compared with younger people, or inequalities that exist within the older population?

2 If so, how are these inequalities changing over time?

3 Do these socio-economic inequalities have a detrimental impact on older people or on a substantial number of them?

4 How can any harmful socio-economic inequalities be reduced or eliminated and what are the implications for policy-making?

It uses data from both Northern Ireland and the Republic of Ireland to examine the total income of older people and particularly earnings from employment, social transfers/benefits and occupational pensions. It also presents findings on socio-economic inequalities from CARDI-funded research. Finally it analyses spatial data in Northern Ireland to examine the geographical distribution of disadvantaged older people.

KEy FINDINGS*

In RoI the poorest older people had a rise of €32 per week between 2004 and 2011 in total incomes while those with the highest incomes had a rise of €255 (CSO 2013).

Total incomes of the poorest pensioner couples in NI did not change between 2003-06 and 2008-11 but the best off had a rise of £37 per week (DSD 2013).

Employees aged 60+ earn €10,000 less per year than earners in their peak years in RoI and £2,400 less in NI (CSO Database and NISRA 2012)

The richest older people in RoI earn 14 times more from employment than the poorest. In NI it is 36 times more for single pensioners and 44 times more for pensioner couples (CSO 2013; NISRA 2013).

The gap in weekly earnings between top and bottom earners aged 60+ in NI rose from £294 to £430 between 2005 and 2012 (NISRA 2012).

In the two years 2009-2011 the incomes of the poorest older people in ROI declined by €24 per week (11.4%) (CSO, 2013).

* the ‘richest older people’ refers to the highest fifth by income while the ‘poorest older people’ refers to the lowest fifth by income


A considerable body of evidence points to a knock on relationship between income or social inequalities with wider inequalities in areas such as health and social inclusion and the evidence in this report suggests that inequalities are increasing in some aspects among our ageing population.

Policy implicationsTo improve the lives of older people, policy, practice and resource allocation should be made on the best information available. The research summarised in this report points to important policy conclusions in a number of areas, including:

• the need to improve the incomes and living conditions of the poorest people in order to reduce inequalities;

• the benefits of improved transport in promoting social inclusion;• pay and taxation policies that provide incentives for improved pensions;• Initiatives to tackle structural inequality and promote healthy ageing;• Improved data collection, especially on a cross-border basis, to enhance mutual learning.


INtRoDuCtIoNResearch questions

This report explores socio-economic inequalities and seeks to answer four main questions.

1 Are there inequalities that affect older people as a group compared with younger people, or inequalities that exist within the older population?


3 Do these socio-economic inequalities have a detrimental impact on older people or on a substantial number of them?

4 How can any harmful socio-economic inequalities be reduced or eliminated and what are the implications for policy-making?

The Equality and Human Rights Commission and age sector groups in the UK (EHRC 2009) state that:

What are socio-economic inequalities? The EHRC (2009) states that, to date, policies have not focused on inequalities that result from class differences and other socio-economic factors. This is despite evidence that people of all ages from lower socio-economic groups tend to have poorer outcomes: for example, to be in poor health, drop out of school, be unemployed, live in poor housing and/or go to prison.

The growing body of literature on health inequalities referred to later in this report shows that social class can affect everything from birth weight through health and disability to mortality rates. Poor people are more likely to have bad health in childhood and this is likely to persist right through the life cycle and to cause earlier death than for people who are well-off.

Socio-economic inequalities will be examined in this report in three contexts. Chapter 1 examines evidence in Ireland, North and South, contained in research reports funded by the Centre for Ageing Research and Development in Ireland (CARDI). Chapter 2 carries out an analysis of spatial deprivation, specifically the proportion of older people in small areas of Northern Ireland with low incomes. Chapter 3 examines the earnings and incomes of older people in Ireland, North and South, including the impact of the first few years of the recession.

Chapter 4 then sets out some of the general policy background to inequalities and outlines policy developments in Ireland, North and South. Finally, Chapter 5 discusses the policy implications with reference to the preceding chapters.

Socio-economic inequalities are defined as inequalities that relate to differences in income, social class, occupational background, educational achievement and neighbourhood deprivation. These are distinguished from socio-demographic differences, which relate to factors such as age, gender, ethnicity, marital status, number of children, household composition and living arrangements. (EHRC 2009: 44)


ANALYSIS OF CARDI RESEARCh REPORTS

1.


CARDI AGEING RESEARChThis chapter summarises research projects funded by CARDI with a particular focus on inequalities related to socio-economic status, deprivation or income. CARDI funded 25 cross-border and inter-disciplinary studies, which reported in the years 2009–12, on themes such as social inclusion, health and illness, poverty, care systems, dementia, physical activity, rural older people and pharmacy. These studies had a research focus that has a bearing on policy and practice, with the aim of improving the lives of older people, especially those who are disadvantaged. Thirteen of these reports with findings related to inequality are summarised in Chapter 1 as follows:

Part 1 five have brief references to inequalities;

Part 2 four dealing broadly with aspects of poverty, disadvantage or inequality;

Part 3 four present statistics on a range of topics, including variables related to social class or areas of disadvantage.

Panel 1.1 summarises the theme, topic, lead applicant or author and date of the 13 research reports which contained findings related to socio-economic inequalities.

Panel 1.1: CARDI-funded research projects relevant to socio-economic, income and deprivation inequalities among older people

Theme Topic Reference

Social inclusion Public transport Ahern and Hine 2010

Rural social exclusion Walsh, O’Shea and Scharf 2012

Care Telecare Delaney et al 2011

Future demand for long-term care Wren et al 2012

Poverty Impact of the recession Hillyard et al 2010

Living standards Hillyard and Patsios 2011

Fuel poverty Goodman et al 2011

Older women workers and pensions Duvvury et al 2012

Health and well-being Prostate cancer Donnelly et al 2012

Depression and physical activity Morgan et al 2011

Multimorbidity Savva et al 2011

Food and nutrition Bantry White et al 2011

Memory clinics Barrett and Savage 2011


PARt 1: REFERENCES to INEquAlItyThis part of Chapter 1 sets out the brief references to inequalities in five studies funded by CARDI.

Public transportPublic transport emerged as a critically important service in several research reports funded by CARDI (Ahern and Hine 2010; HARC 2010; O’Sullivan 2011). Good transport provides links to essential services such as post offices, shopping and health services and offers opportunities for social inclusion through visits to friends, relations, social and recreational activities or opportunities to work or volunteer.

The high cost of running a car, especially for older people who may be faced with increased insurance costs, introduces an element of inequality since many older people may be unable to afford a car. Community Technical Aid (2003) identified poverty and low income in NI as one of the four factors causing access problems for disadvantaged and socially excluded older people. This is supported by figures which show that in ROI retired people spend an average of €70.19 per week on transport (CSO 2007). In NI the average spend of people aged 65–74 is £41.20 (ONS 2009). There are other factors operating as well: for example, many older women have never learned to drive and older old people may suffer disabilities that prevent them from driving. In this context it is notable that in NI the average amount spent on transport by people aged 75+ falls to £16.00 (ONS 2009). Ahern and Hine (2010) suggested that it would be cheaper for the state to give taxi vouchers to older people than to introduce new bus and rail services.

Access to telecareTelecare can be defined as the remote or enhanced delivery of health and social services to people in their own home by means of telecommunications and computerised systems. It uses information and communication technology to trigger human responses, or shut down equipment to prevent hazards (Delaney et al 2011).

In ROI access to telecare was initially based on ability to pay, with the result that people with greater resources were better able to afford the services on offer, except where voluntary and community organisations were able to step in. However, there are examples where policy interventions can make access more equal. In ROI, for example, the Department of Community, Rural and Gaeltacht Affairs offered grants for the installation of social alarms to people who could not otherwise afford them. This initiative was replaced by the Seniors Alert Scheme in May 2010. It supports a monitored personal alarm, monitored smoke detectors, monitored carbon monoxide detectors, additional pendant, external security lights and internal emergency lighting. Grants are administered by community and voluntary groups (Delaney et al 2011).

Recruitment by memory clinicsDementia refers to a group of diseases characterised by a progressive and generally irreversible decline in mental functioning, predominantly affecting people over the age of 65. It is a major social and economic challenge for countries with ageing populations as growing numbers of people are living to an age when dementia is likely to occur (Barrett and Savage 2010).

In a study of people presenting with symptoms of dementia to memory clinics in Belfast and Dublin, social class was not one of the variables recorded although education level was logged. Barrett and Savage (2012) found, using education level as a proxy of social class, that Mercer’s clinic in Dublin may have recruited more advantaged patients and, conversely, that the Belfast clinic may have been serving less advantaged people. They found that the Dublin clinic may have had greater success at detecting cases of mild cognitive impairment and Alzheimer’s disease among higher socio-economic groups and conclude that, in Dublin:


Social exclusionWalsh et al (2012), researching ageing in rural communities, found that the term ‘social exclusion’ is useful for encompassing aspects of disadvantage other than shortage of income or wealth. However, the term presumes a dividing line between an ‘included majority’ and an ‘excluded minority’. This can have several negative effects, including obscuring inequalities and differences among the included; framing inequality and poverty as an aberration rather than an integral feature of capitalist societies; and preserving existing structural inequalities between those who are marginalised and those who are not (Walsh et al 2012).

Long-term careThe issue of how to provide and pay for care in the home and in residential settings is becoming a major issue. Understanding what the demand for care will be is a major part of this consideration. Wren et al (2012) did not include socio-economic variables as part of the study on the demand for long-term care, North and South. However, a literature review by Wren et al (2012) stresses the importance of factors such as socio-economic status, resources and house ownership in determining the need for and access to care. Furthermore, people in low socio-economic classes are more likely to suffer poor health, whereas wealthier people are more likely to be in good health and better able to afford the supports needed to live independently and thus postpone or avoid admission to residential care (Wren et al 2012, citing Grundy and Jitlal 2007).

Wren et al, citing Breeze et al (1999), found lower risk of admission to long-term care among owner-occupiers as compared to renters. Furthermore, they found that men in rented accommodation had a 90% excess risk of institutionalisation and women a 40–45% excess risk. Partly, this may be because people who own their own homes are wealthier and more likely to be in good health than renters. It may also be partly explained by the deterrent effect of means testing, namely that housing assets are taken into account when deciding on payment for care. McCann et al (2011) agree that home ownership may act as a disincentive to enter residential care. They showed that the main difference in admission rates is between those who rent and those who own their homes but that the value of the house makes little difference. Families may choose to increase the amount of informal care-giving (and perhaps paid care) to prevent the sale of the home.

Referrals to the service of better-educated people are being made with greater regularity and, taken together with changes in other demographics, it could be tentatively suggested that secondary health service provision for dementia in the ROI increasingly favours higher socio-economic groups and, possibly, males. (Barrett and Savage 2012: 26)


PARt 2: PovERty AND DISADvANtAGEThis section deals with the four reports funded by CARDI which had a strong focus on disadvantage and poverty, though not necessarily on socio-economic inequalities: Hillyard et al 2010; Hillyard and Patsios 2011; Goodman et al 2011 and Duvvury et al 2012.

Poverty and the impact of the recession on older peopleHillyard et al (2010), following detailed analysis of social datasets in Ireland, North and South, uncovered several factors causing differentials within the older population and found substantial differences between NI and ROI. First, NI has much higher rates of pensioner poverty than ROI. Second, the two jurisdictions are going in different directions, with a rapid decline in the proportion of pensioners in poverty in ROI and an increase in NI. Third, the actual numbers of both single pensioners and pensioner couples living in poverty have increased. Fourth, older people who live alone are at much greater risk than those who live with someone else. Fifth, a far higher number of women pensioners are likely to be in poverty than men and the older women get, the more likely this is to be the case.

Figure 1.1: risk of poverty (60% median) among older people in NI and ROI (%)

Source: EU-SILC (CSO 2013) and Poverty in Northern Ireland 2010/11 (NISRA 2012b) Note: ‘older people’ means 65+ except for women in NI, where it means 60+.

2003 2004 2005 2006 2007 2008 2009 2010 2011

30 30

27

25

20 2021 21 21

20

14

1717

18 18

15

1110 10

9

27 27

2424

22

28 28

NI BHC

NI AHC

ROI


Since Hillyard et al (2010) collected their data (the latest year covered was 2009), the official poverty risk among older people has declined, as shown in Figure 1.1. With one exception, the risk of poverty among older people in ROI declined each year from 2003 to 2010, followed by a rise in 2011. In NI, the rate of poverty after housing costs declined from 2008 onwards and before housing costs a year later. In part the decline in poverty rates may be because average incomes in the population declined, especially in ROI, with the result that the benchmark figure of 60% of median income also declined; since the state pension was not reduced in ROI and was increased in NI, the result was that more older people ended up above the 60% figure.

Hillyard et al (2010) argued that tax policies do not promote equality but appear to benefit those who are well-off. One example is the differential tax relief given for pension contributions, which is heavily skewed towards the better off. UK Treasury figures show that of the £37 billion of tax relief, some 60% goes to higher-rate taxpayers, with 25% – nearly £10bn a year – going to the top 1% of earners. In ROI Callan et al (2009) found that changes to tax relief on pensions would save public money and be fairer, and that tax relief at a standard rate could promote a more efficient and equitable public pension policy. Currently, over €8 out of every €10 of tax relief goes to taxpayers in the top fifth of the income distribution. Moloney and Whelan (2009) have noted that the pension subsidy is no more than 22% for persons in the first seven income deciles (incomes under €34,000 per annum) but is 34% for people on high incomes. Therefore the tax subsidy is highest for the top earners, in both percentage terms and overall amounts.

Hillyard et al (2010) stated that taxation policies have boosted pension provision among the well-paid to a greater degree than among those on smaller salaries:

Living standards of older peopleHillyard and Patsios (2011), in a study of living standards, noted that, on average, older people were better off than younger people in Ireland, both North and South, on most measurements of deprivation. However, in contrast to the reduction in at risk of poverty rates among older people, they found the recession is having a very real impact on all households, including both single pensioners and pensioner couples. There has been an increase in the proportion of single pensioners in NI unable to keep their house warm from 4.0% in 2007 to 5.5% in 2009. In ROI the proportion has nearly doubled from 2.4% in 2007 to 4.7% in 2009. In NI, the proportion of pensioner couples struggling to heat their home has more than trebled from 2.2% to 6.9%, while in ROI the increase has been more modest.

The proportion of single pensioners in NI who cannot afford an annual holiday has gone down slightly, but there has been a large increase in ROI, from 13.3% in 2007 to 40.5% in 2009. The proportion of pensioner couples who were unable to afford an annual holiday rose from 14.8% to 19.3% in NI and from 14.9% to 26.3% in ROI.

Hillyard and Patsios (2010) state that while many of the inequalities in older age are structured in terms of class, gender and ethnicity, there are other cross-cutting inequalities between those with occupational pensions and those without, between employees and the self-employed, and between those with public sector pensions and those on state pensions only.

The inequality arises not only because of inequality in salaries but also because high income earners are more likely to participate in pension schemes, more likely to make higher contributions, and the value of tax relief at the top rate of income tax is about double that for the standard rate taxpayer. There is a strong incentive for high earners to contribute to pension schemes, but a weaker incentive for those with low and middle incomes. (Hillyard et al 2010: 63)


Fuel povertyGoodman et al (2011) argued that fuel poverty is caused by the interaction of high fuel prices, low income and poor energy efficiency in the home. Following a multi-methods research project, their main findings were that older people experience a ‘dual burden’. They are more likely to suffer fuel poverty and, because older people are more likely to have chronic diseases, they are also particularly vulnerable to poor health and social harm as a result. Low temperatures do not just have an immediate acute effect; a study in Dublin showed that a one-degree Celsius drop in temperature is associated with a 2.6% increase in deaths among older people over the following 40 days (Goodman et al 2004). The numbers of older people vulnerable to ill-effects from cold homes, North and South, will increase due to increases in the number of people aged 80 and over and those living with chronic illness or disability.

Goodman et al (2011) note that in ROI between one-fifth and one-quarter of older people are in fuel poverty (that is, spending more than 10% of their disposable household income after tax on fuel and electricity) and this was true of over 35% of older people living alone. In NI 44% of households were in fuel poverty in 2009: 53% where the household reference person is aged 60–74 and 76% where he/she is aged 75+.1 Older households account for a disproportionately large share of all households in fuel poverty; households where the head is an older person accounted for nearly half of all fuel-poor households in Northern Ireland in 2009. Moreover, older people tend to underestimate the problems facing them, so that their self-reported ‘subjective’ measures of fuel poverty and levels of debt/arrears should be interpreted with caution (Goodman et al 2011).

Several factors help to determine the extent of fuel poverty, including living in a private household; tenure; whether the home is a detached or semi-detached house, a terraced house or a flat; age and condition of the building; and the type of fuel used. One important factor is whether or not the resident lives alone; about a quarter of older people living alone in ROI and a third in NI face particular challenges in heating a home on a single income due to diseconomies of scale. The situation where a single older person may still occupy a family home with many vacant rooms is especially noteworthy (Goodman et al 2011).

Older women and pensionsDuvvury et al (2012) studied why older women workers have lower pension provision than men. The research illustrates the interaction of different forms of disadvantage over the life course. It found that women are at a disadvantage as a result of ‘a male breadwinner model’, especially because of absence from the paid workforce to raise children and take on other caring duties. Women in low-paid, temporary work lose out most because they often cannot afford to make pension contributions.

Most older women depend heavily on the state pension: in NI nearly 56% of female interviewees in employment and 82% of those who were not relied solely on the state pension (Duvvury et al 2012, citing Evason and Spence 2002). This suggests the need to ensure that the basic state pension is adequate. Duvvury et al (2012) found that the current emphasis on occupational and personal pensions tends to reinforce the link between the pension system and earnings, length of service and employment status. Reinforcing this link is likely to exacerbate gender inequality in pension provision, given that women typically have lower earnings and interrupted employment records (Duvvury et al 2012: 9).

Opportunities to earn income across the life course largely determine the amount of pension a worker can accumulate (Duvvury et al 2012, citing Giele and Elder 1998). Many factors influence pension-building behaviour and therefore wealth in older age, such as women’s socio-economic class, parental influence at the outset of working life, level of education, internalised gendered caring norms, legislation and economic conditions (Duvvury et al 2012: 63).

1 By 2011, fuel poverty in households aged 75+ had declined to 66%; among those aged 60–74 it was largely unchanged (NIHE 2012).


PARt 3: RESEARCh PRojECtS wIth StAtIStICS oN INEquAlItIESThis part deals with four reports which present statistics on a range of topics, including variables related to social class or areas of disadvantage.

Prostate cancerDonnelly et al (2012)2 investigated prostate cancer, the most common cancer in men in Ireland. They used data from 1996, 2001 and 2006 on rates of prostate cancer among men aged 70+ compared with younger men, with extent of deprivation of the area in which the patients lived as one of the variables. The areas were divided into five equal parts (quintiles) according to their degree of disadvantage based on the 2005 multiple deprivation measure in NI (NISRA 2005) and using five domains derived from the National Deprivation Index in ROI (Kelly & Teljeur 2004). An unusual pattern emerged in which NI and ROI were almost mirror images of one another (Figure 1.2). In NI the lowest rates of prostate cancer are found among people living in the least and most deprived areas and higher rates apply in the three middle quintiles. In ROI people in the least and most deprived areas have higher rates of the disease whereas lower rates exist in the three middle quintiles.

Figure 1.2: men diagnosed with prostate cancer in 2006 by area deprivation (%) Donnelly et al 2012: 25

2. Donnelly was the main author but the project was led by Dr Anna Gavin at the Northern Ireland Cancer Registry.

NIROI

1 Least deprived 2 3 4 5 Most deprived

19

25

23

16 16

18

21 21

27

14


Figure 1.3: NI and ROI men with prostate cancer who saw urologist in 1996 and 2006 by area deprivation (%)

Donnelly et al 2012

However, the researchers indicate that there may not be a genuine socio-economic deprivation difference since the results could be an artefact of how deprived areas are defined in the distinct measures of deprivation in NI and ROI or could reflect differences in the two systems or the profile of men taking Prostate-Specific Antigen tests (Donnelly et al 2012: 33).

Figure 1.3 shows that men in Ireland as a whole with prostate cancer were more likely to see a urologist in 2006 than was the case a decade previously. Moreover, in 2006, but not in 1996, there was an unbroken deprivation gradient: men from the least deprived areas were most likely to visit the specialist (91%) and the proportion declined for each level of deprivation, to 79% for men from the most deprived areas.

19962006

1 Least deprived 2 3 4 5 Most deprived

68.7

90.6

58.4

88.5

62.7

83.5

53.6

59.3

78.5

85.9


Important differences exist North and South. Between 1996 and 2006, the estimated proportion3 of men seen by a urologist increased markedly in NI from 59% to 94%, but remained stable in ROI at approximately 81% (Donnelly et al 2012). Moreover a multivariate analysis revealed marked variations, as highlighted in Figure 1.4.

Figure 1.4: estimated probability of seeing urologist by area deprivation (1996, 2001 and 2006 data combined)

There is no difference in NI in the likelihood of men from the most and least disadvantaged areas seeing a urologist; men from the middle group are least likely to do so. In ROI, by contrast, there is a clear gradient, with men from the least deprived areas more likely to visit the specialist (86%) than men from the most deprived areas (76%) (Donnelly et al 2012).

In 2006 men in ROI with prostate cancer were twice as likely (16.8% compared with 7.3%) to undergo radical prostatectomy as men in NI. Combining data for 1996, 2001 and 2006, men from the least deprived areas were 77% (or 1.77 times) more likely to have radical prostatectomy than men in the most deprived areas.

There has been a big rise in the proportion of men receiving radical radiotherapy in the decade 1996–2006. NI men living in the most deprived areas had a lower probability of receiving the treatment – about 7% compared with more than 11% of men in the best off areas. Donnelly et al (2012) comment on these differences:

3. Missing values were imputed, as explained in Donnelly et al 2012: 27.

NIROI

1 Least deprived 2 3 4

80.8

86.4

80.9

84.5

80.8

77.977.7

80.5

76.1

79.7

5 Most deprived

Donnelly et al 2012

Men in more socio-economically deprived areas in NI were less likely to receive radiotherapy. However, it should be noted that, after adjusting for other variables, men in NI’s worst socio-economically-deprived group were receiving the same level of radiotherapy as men in ROI. It is not clear why there would be a deprivation gradient in NI as the NHS is a free system, equally accessible to all, but perhaps cultural attitudes determine uptake of treatment.(Donnelly et al 2012: 52).


Depression and anhedoniaMorgan et al (2011) undertook a data-mining study of depression and anhedonia (the inability to derive pleasure from activities). They analysed data about older people from SLÁN, the Survey of Lifestyle, Attitudes and Nutrition 2007 (DoH 2008) in ROI, which had 4,255 adults aged 50+, and the Northern Ireland Health and Social Wellbeing Survey (NIHSWS) 2005-6, which had 1,904 adults aged 50+ (NISRA 2007).

The variables included socio-economic status (SES), which can be combined into three groups as follows:

I. SES 1 & 2 (professional, managerial and semi-professional): ‘high’

II. SES 3 & 4 (lower non-manual and skilled manual): ‘mid’

III. SES 5 & 6 (semi-skilled and unskilled manual): ‘low’.

Depression in older adults is not just a serious illness but is also associated with increased risk of morbidity, suicide and self-neglect and it decreases physical, cognitive and social functioning. Low SES has been found to be correlated with a higher prevalence and incidence of depression (Morgan et al 2011, citing Everson et al. 2002).

ROI respondents in high SES reported less psychological distress than those in low classes. This was also true in NI but the differences were not statistically significant. The results are shown in Figure 1.5, which also makes clear that rates of depression among people aged 50+ are higher in NI in each SES (Morgan et al 2011).

Figure 1.5: people aged 50+ with depressed mood and/or anhedonia by social class (%)

Morgan et al 2011

NIROI

12.1

24.4

14

27.5

15.5

31.5

SES 1&2SES 3&4SES 5&6


A logistic regression undertaken by the researchers showed no SES association in NI, unlike ROI where the probability of people aged 50+ in low SES having depression and/or anhedonia was 43% higher than for high SES.

Morgan et al (2011) concluded that depressive symptoms in ROI were negatively associated with male gender, older age groups, being a former smoker and moderate to high levels of physical activity, while depressive symptoms were positively associated with low social class and being a current smoker. In NI, depression was negatively associated with older age categories, being a former or current smoker and higher levels of physical activity. Being widowed was positively associated with elevated depressive symptoms.

MultimorbiditySavva et al (2011) used SLÁN 2007 (DoH 2008) and NIHSWS 2005/6 (NISRA 2007) to study the causes and consequences of multimorbidity (having more than one chronic condition) in older people in Ireland. The literature review explains why SES is relevant to multimorbidity:

Savva et al (2011) estimated the relative risks of having one of eight chronic conditions4 and also the risk of having two or more of these conditions. The risk of people in mid and low SES was compared with the risk of people in high SES, as shown in Figures 1.6a (one chronic disease) and 1.6b (multimorbidity).

Figure 1.6a: Risk of mid and low SES having one chronic disease compared with high SES

Figure 1.6B: Risk of mid and low SES having 2+ chronic diseases compared with high SES

Note: in ROI risk of mid SES group having multimorbidity was the same as for the high SES.

4 These are heart attack, angina, stroke, diabetes, asthma, chronic obstructive pulmonary disease, musculo-skeletal pain (including rheumatism, arthritis and back pain) and cancer.

Low Low

Mid Mid

1.135 1.645

1.043 1

1.697 2.171

1.371 1.66

ROINI

ROINI

Given the long-standing association between income inequality and incidence of chronic illness and the social determinants of health, it is important to advance the understanding of the impact of socio-economic status on health outcomes for older people with multiple chronic illnesses. The increasing gap in the health outcomes of older people across the socio-economic gradient will become an important public health issue, especially as the population ages. (Savva et al, 2011: 7)

Savva et al (2011)Savva et al (2011)


People in ROI in the low SES category are 13.5% more likely to have a chronic condition than people in high SES but in NI older people in low SES are nearly 70% more likely to have a chronic condition compared with those in high SES. Among older people with multimorbidity, the difference between the high and low SES increases; in ROI the gap grows to 64.5% and in NI to 117% (Savva et al 2011). There is therefore a socio-economic gradient in both parts of Ireland but it is considerably stronger in NI, where those in the low SES group are 2.2 times as likely to report multimorbidity as those in the high group. In ROI, the low SES group is only 1.6 times as likely to report multimorbidity as the high group.

The data showed an unbroken social class gradient in both NI and ROI in the likelihood of reporting health as only poor or fair; in limitations of daily activity; and in having poor or fair quality of life: i.e. people in low SES were more likely to report worse outcomes on these three variables than people in higher SES. In all cases, the social class difference among NI respondents was greater than in ROI.

Savva et al (2011) analysed the proportion of older people reporting fair or poor health by number of chronic diseases (Figures 1.7a and 1.7b). Again NI displays a clear social class gradient and respondents reported worse health than in ROI. People with two or more chronic conditions are much more likely to report that their health is only fair or poor compared to people with one or no chronic conditions. In ROI, among older people with multimorbidity in the highest SES, 53% reported fair or poor health but this was true of 74% of people in the lowest SES groups who had multimorbidity. Among older people with multimorbidity in NI, 75% of those with high SES said their health was poor or fair compared with 89% of those with low SES.

Figure 1.7a: ROI older people reporting poor or fair health by morbidity and SES (%)

Figure 1.7b: NI older people reporting poor or fair health by morbidity and SES (%)

Savva et al 2011 Savva et al 2011

HighMediumLow

HighMediumLow

No chronic disease No chronic disease1 chronic disease 1 chronic disease2+ chronic diseases 2+ chronic diseases

8 8

2629

53

75

1116

26

49

63

81

1620

40

54

74

89


If this is the case it would appear that the socio-economic effect on health- related quality of life has two distinct components, first in the occurrence of chronic disease, possibly influenced by life-life course factors associated with low SES, and second by affecting the support available to people with disability and multimorbidity. (Savva et al 2011: 28)

Savva et al (2011) found that many of the diseases investigated were more common in those from lower SES classes, both in NI and ROI. However, the social class gradient with respect to multiple chronic conditions is significantly stronger in NI. They indicate that the effect of SES on quality of life is largely explained by health status; after adjusting for disease and disability there is only a small independent effect of SES in reporting ‘poor’ quality of life – and it appears that this effect is restricted to those with multimorbidity, though this is difficult to test due to the small numbers.

Food and nutritionGood nutrition is an important element of health and is essential to adequate functioning and quality of life for older adults. Malnutrition in older age is a significant public health problem which often goes undiagnosed. It is associated with outcomes such as prolonged hospitalisation and rehabilitation, infection, pressure ulcers, poor wound healing, reduced cognitive function, impaired muscle function and mortality (Bantry White et al 2011).

In NI, an estimated four out of ten older people who are admitted to hospital are suffering from malnutrition on arrival. Patients over the age of 80 admitted to hospital have a five times higher prevalence of malnutrition than those under the age of 50. Six out of ten people are at risk of becoming malnourished (DHSSPS 2007). In ROI, it is estimated that 70,000 Irish people over 65 years of age may be either malnourished or at significant risk of malnutrition (UCD 2010).

Bantry White et al (2011) analysed data from the Household Budget Survey 2004–5 (CSO), which covered 6,884 households, including 1,444 over 65, and the Expenditure and Food Survey 2004–5 (NISRA) with 533 households in NI, 144 over 65. This study included an income variable with respondents grouped into three categories: below 60% median income (at risk of poverty); between 60% and the median; and above the median.

Bantry White et al (2011) found that both NI and ROI older households, especially aged 75 and older, spend less on food than any other age group.5 The biggest spenders are aged 45–54 in ROI and 35–44 in NI. Much of this difference is related to household size since middle-aged groups are more likely to have children and, by comparison, the 75+ cohort includes many people living alone, mostly women. Another feature is that the weekly food spend in ROI is a lot higher than for NI in every age group; in both the 65–74 and 75+ age groups, people in ROI spend 40% more than in NI.

5. Amounts were converted using the 2005 exchange rate of £1 equals €1.37.


Spending covers all categories included in the survey, not all of them related to good nutrition: for example, spending on alcohol and tobacco may harm health and welfare. Households in ROI spend a lot more on this than in NI and young people far more than older people. Households in ROI aged 15–24 spend an average of €82 per week on alcohol and tobacco and those aged 25–34 spend €54, compared with €28 in the 65–74 age range and €17 among people aged 75+. Similarly in NI, households in the two youngest age groups spend €29 and €27 respectively on alcohol and tobacco compared with €20 for those aged 65–74 and €13 for those aged 75+. Gender differences exist as well. In single older households, men in ROI spend three times more on alcohol and tobacco than women and in NI they spend twice as much (Bantry White et al 2011).

In NI there is little difference in expenditure on vegetables, butter, fat and oils as a proportion of all food spending. Low income households allocate 11.7% of their budgets to snacks and confectionery, compared with 7.7% for high earners; by contrast high income families spend a greater share of their food budgets on fruit than mid or low income households. Bantry White et al (2011) suggest that high-earning families in NI spend more on healthy food items and less on unhealthy ones than lower-income families.

SummARyIn the context of the questions posed in the introduction, research funded by CARDI either cited or uncovered many examples of inequalities affecting older people. These include socio-economic differences in access to transport, memory clinics and long-term care; marked differences in income from pensions and other sources; greater fuel poverty and worse nutrition among poorer older people. Older people in higher social groups or least deprived areas were more likely to receive treatment for prostate cancer, less likely to have multimorbidity or a low quality of life and had the highest spending on food. Limited evidence exists on change over time, but poverty rates of older people have declined in recent years. The examples of inequalities cited relate to issues that can have a seriously detrimental impact on many older people’s health, life expectancy, social inclusion and quality of life.

The subsequent questions of how the inequalities can be reduced or eliminated and the implications for policy-making are considered in Chapter 5.

Bantry white et al (2011) found that:

• Total food spending of the high income group is double that of the low group in ROI but only one-third higher in NI.

• In ROI the greatest gap is in ‘meals out’, where the high income group spends four times more than the low group; in NI it is 85% more.

• In ROI there is a clear income gradient in spending on alcohol and tobacco; in NI the middle group, not high earners, spends most.

• In NI and ROI there is an income gradient in spending on both fruit and vegetables (Bantry White et al 2011).


DISTRIBUTION AND DEPRIVATION OF OLDER PEOPLE IN NI

2.


This chapter considers two important and related issues for policy-makers. The first is whether deprivation among older people can be tackled effectively through spatial strategies, as distinct from policies aimed at the individual. Secondly, if spatial strategies are appropriate, how best can they target the largest possible number of disadvantaged older people? This chapter focuses on NI due to the lack of official data in ROI.

Part 1 of this chapter shows how the population of older people (women aged 60+ and men 65+) is distributed across NI. Part 2 gives a preliminary analysis of the relationship between Income Deprivation affecting Older People (IDAOP) and the more commonly used Multiple Deprivation Measure (MDM); and the health domain. It then looks at the distribution of older people according to IDAOP rankings and compares these with where older people live, as shown in Part 1. Part 3 profiles some of the most and least deprived Super Output Areas (SOAs) according to IDAOP to see what particular characteristics the different areas exhibit, which might give an indication of the best means to go about reducing inequalities.

This analysis is based on MDM (NISRA 2010b), annual estimates of mid-year populations (NISRA 2011) and data on the Northern Ireland Neighbourhood Information Service (NINIS various dates). First MDM is described in Panel 2.1.

The Multiple Deprivation Measure (MDM), published by NISRA, has been used for many years to measure spatial disadvantage in NI. It is made up of seven domains, which contribute to the overall MDM as follows:

• income deprivation 25%• employment deprivation 25% • health deprivation and disability 15%• education, skills and training deprivation 15%• proximity to services 10%• living environment 5% • crime and disorder 5%

NISRA also published, along with the MDM, an index of Income Deprivation affecting Older People (IDAOP). The scores for income can be interpreted as the percentage of the relevant population that is deprived. The various indicators do not have uniform scales. Excluding Aldergrove 1 because it has no older people, scores for IDAOP range from 0.03 to 0.95. MDM scores run from 1.65 for the least deprived area to 82.16 for the most deprived; health scores range from 3.13 in the most deprived area to –3.10 in the healthiest area (NISRA 2010b). The most deprived SOA is ranked 1st and the least deprived is ranked 890th.

See http://www.nisra.gov.uk/deprivation/nimdm_2010.htm for full information

Panel 2.1: NI Multiple Deprivation Measure 2010


Several indicators are relevant to older people but only IDAOP refers specifically to them. This indicator merits further investigation as a means of identifying the spatial distribution of potentially vulnerable older people. A benefit of IDAOP is that it is reported for each of the 890 SOAs, which have an average total population of 2,000 (NISRA 2010b), of whom an average of 346 were women aged 60+ or men aged 65+ in 2010 (NISRA 2011). See panel 2.2 for a definition of IDAOP.

IDAOP is a stand-alone measure published with the MDM combining the percentage of a Super Output Area’s population aged 60+ and their partners (if 60+), living in households in receipt of Income Support, State Pension Credit, income-based Jobseeker’s Allowance, income-based Employment and Support Allowance, Housing Benefit, Working Tax Credit or Child Tax Credit. Tax credit claimants are included only where the equivalised income is below 60% of the NI median before housing costs. Scores represent the proportion of older people judged to be deprived e.g. a score of 0.92 means that 92% of over-60s in that area are income-deprived (NISRA 2010b).

Panel 2.2: Income Deprivation affecting Older People

A limitation is that IDAOP is not reported at Output Area level (of which there are 5,022 with an average population of 360), which means it is not possible to identify small pockets of deprivation among older people. This is likely to affect rural areas in particular. A study of the composite MDM showed that no rural areas were in the top 10% most deprived SOAs in 2010 but that 15 rural areas featured in the most deprived 10% of Output Areas, indicating that smaller geographical units aided the identification of deprivation in rural areas (NISRA 2010c).

6 Men aged 65+ 112,435; women aged 60+ 195,885; total 308,320.


PARt 1: SPAtIAl DIStRIButIoN oF olDER PEoPlE IN NIIn this part, spatial distribution of older people in NI at District Council and SOA level is studied more closely. In 2010 in NI as a whole, 17.1% of the population was made up of women aged 60+ and men aged 65+ (NISRA 2011). Older people were not evenly distributed across the 26 districts in NI, however, as is clear from Table 2.1. The proportion7 of older people ranges from 14% in Derry to 21.7% in North Down. In Coleraine, Ards and Castlereagh older people constitute one-fifth or more of the inhabitants. By contrast, less than 15% of the population in Limavady, Dungannon, Newry & Mourne and Magherafelt are older people. North Down also has the highest proportion of people aged 85+, who make up 2.6% of its total population, followed by Castlereagh (2.2%). At the other end of the spectrum, only 1.1% of the population of Derry and Newry and Mourne are aged 85+.

District total all ages All 60/65+ Aged 85+ % 60/65+ % 85+

North Down 79,900 17,300 2,000 21.7 2.6

Coleraine 56,800 11,500 1,200 20.2 2.1

Ards 78,200 15,800 1,500 20.1 1.9

Castlereagh 67,000 13,500 1,500 20.1 2.2

Larne 31,700 6,300 500 19.9 1.7

Moyle 17,000 3,400 400 19.6 2.1

Ballymena 63,500 12,400 1,200 19.6 2.0

Newtownabbey 83,600 15,700 1,400 18.7 1.7

Carrickfergus 40,200 7,300 700 18.3 1.8

Belfast 268,700 47,200 5,100 17.6 1.9

Fermanagh 63,100 11,000 1,100 17.5 1.8

Ballymoney 30,600 5,300 500 17.3 1.6

Down 70,800 12,000 1,300 17.0 1.9

Armagh 59,400 10,000 900 16.6 1.4

Strabane 40,100 6,600 500 16.3 1.2

Lisburn 117,800 19,100 1,600 16.2 1.4

Banbridge 48,000 7,800 800 16.2 1.6

Craigavon 93,600 15,000 1,400 15.9 1.5

Antrim 54,100 8,300 700 15.3 1.3

Cookstown 36,700 5,500 500 15.2 1.5

Omagh 52,900 8,000 800 15.0 1.4

Limavady 33,600 4,900 400 14.9 1.3

Dungannon 57,700 8,400 800 14.6 1.4

Newry & Mourne 99,900 14,500 1,100 14.5 1.1

Magherafelt 44,700 6,400 600 14.4 1.3

Derry 109,800 15,400 1,200 14.0 1.1

Northern Ireland 1,799,400 308,400 29,700 17.1 1.6

Table 2.1: NI Local Government Districts by number and percentage of older and very old people

7. The proportion of older people is used because districts vary by size e.g. Belfast has almost 16 times more inhabitants than Moyle. Table 2.1 also gives the number of older people in each District.

Note: figures have been rounded to the nearest 100.

NISRA 2011


Small area levelIf smaller areas such as SOAs are used to examine populations, the extremes are far greater. In three of the North Down SOAs, more than one-third of the population are older people and the same is true of Donaghadee South 2 in Ards. At the other extreme (and excluding the Antrim SOA which consists of an army base), there are four areas with less than 4% older people.

If we rank all the SOAs according to their proportion of older people, we find that 15 of them fall into North Down and 13 into Belfast (which is by far the largest of the 26 districts). Close behind are Newtownabbey with 12, Coleraine with 11 and Ards with 10. The pattern is for concentrations of older people in districts in and around Belfast and, to a lesser extent, on the north coast. By contrast, there is a wedge of eight districts, running north-west from the triangle of Armagh-Craigavon-Banbridge through Dungannon, Cookstown and Magherafelt and west to Omagh and Strabane, which have no SOAs in which there are high proportions of older people.

Some of the wide variation in the distribution of older people can be seen in Table 2.2, which lists the 25 SOAs with the highest and lowest proportions of older people.

25 highest 25 lowest

SoA District % oP SoA District % oP

Churchill 1 North Down 37.8 Culmore 5 Derry 7.3

Groomsport North Down 35.3 Collin Glen 1 Lisburn 7.2

Donaghadee South 2 Ards 34.4 Kilwaughter 1 Larne 7.1

Princetown North Down 33.4 Culmore 3 Derry 7.1

Upper Malone 1 Belfast 32.7 Glencolin 1 Belfast 6.9

Carnmoney 2 Newtownabbey 32.5 Collin Glen 3 Lisburn 6.8

Gardenmore Larne 32.4 Shantallow West 1 Derry 6.8

Broadway 2 North Down 32.2 West 1 Strabane 6.3

Bryansburn 2 North Down 32.0 Cairnshill 1 Castlereagh 6.2

Springhill 2 North Down 31.8 Crevagh 2 Derry 6.2Crawfordsburn North Down 31.6 Stranmillis 2 Belfast 5.9

Fortwilliam 1 Belfast 31.6 Shantallow West 4 Derry 5.8

Boneybefore Carrickfergus 31.0 Botanic 2 Belfast 5.3

Abbey 1 Newtownabbey 30.9 Crevagh 3 Derry 5.1

Bryansburn 1 North Down 30.9 Shantallow West 3 Derry 5.1

Mount Sandel Coleraine 30.8 Ballycrochan 2 North Down 5.0

Bradshaw's Brae 2 Ards 30.7 Botanic 4 Belfast 4.9

Crumlin 1 Belfast 30.4 Mallusk 2 Newtownabbey 4.9Bangor Castle North Down 30.4 Loughview 2 North Down 4.8

Cherryvalley 1 Belfast 30.2 Derryaghy 1 Lisburn 4.6

Knockbracken 2 Castlereagh 29.9 Botanic 1 Belfast 4.4Stormont 1 Belfast 29.6 Collin Glen 2 Lisburn 3.8

Cultra North Down 29.5 Botanic 3 Belfast 3.7

Burnthill 2 Newtownabbey 29.2 Derryaghy 2 Lisburn 3.2

Lagan Valley 2 Lisburn 29.0 Gresteel 2 Limavady 3.0

Table 2.2: SOAs by highest and lowest percentage of older people

Note: older people (OP) means women aged 60+ and men aged 65+.

Source: NISRA (2011)


In the most extreme case, the proportion of older people in Churchill 1 in North Down is 12 times greater than in Derriaghy 2 and Gresteel 2. Overall, there are seven times more people aged 65+ in the 25 SOAs with the highest proportions of older people (31.6%) than in the 25 SOAs with the lowest older populations (4.2%).

GenderIn 2010 in NI as a whole 36.5% of older people were men and 63.5% were women, though the female group includes everyone aged 60+ whereas the male group is 65+ (NISRA 2011). There are marked variations in the gender balance at SOA level with the proportion of older women compared with older men ranging from 56.1% in Gransha, Banbridge, to 75.2% in Shantallow West 2 in Derry.

The number of women aged 60+ as a proportion of all women averages 21.4% in NI as a whole but ranges greatly from 4.3% in Gresteel in Limavady to 47.4% in Churchill 1 in North Down. In the case of men aged 65+ as a proportion of all men, the NI average is 12.7%, ranging from 1.7% in Gresteel to 27.3% in Groomsport in North Down (NISRA 2011).

PARt 2: INComE DEPRIvAtIoN AFFECtING olDER PEoPlEThis section studies the relationship between IDAOP, MDM and the health domain and the spatial distribution of older people according to IDAOP rankings.

Multiple deprivation measureThe MDM is the best known of the indicators of spatial disadvantage in NI and is used by government departments to identify deprivation. It is closely correlated by rank with the IDAOP (.9003 for all 890 SOAs) but the correlation for the 100 most deprived areas according to IDAOP is lower at .4365 (source: the author). There are several SOAs which have very different rankings on the two measures. For example, Culmore 4 in Derry has very high income deprivation among older people, with a rank of 23, but a much lower MDM rank of 149 (NISRA 2010b). Gresteel in Limavady has an IDAOP rank of 94 but it is 564 places further down in the MDM rankings at 658. Conversely, some areas which are high on the IDAOP measure are much lower on the MDM score. An example is Woodvale 1 SOA in Belfast, which is placed as 267th in IDAOP but on a much higher ranking of 57 on MDM. Likewise Ballymaglave in Down is nearly 300 places lower on IDAOP than on MDM (NISRA 2010b). Table 2.3 gives details of these and other examples of disparity between the indices.

SoA District IDAoP score

IDAoP rank

mDm score mDm rank

Coalisland South Dungannon 0.90 10 46.54 82

Culmore 4 Derry 0.84 23 36.27 149

Forkhill 2 Newry & Mourne 0.72 56 22.54 336

Gresteel 2 Limavady 0.64 94 9.95 658

Woodvale 1 Belfast 0.48 267 52.60 57

Antiville Larne 0.38 451 38.32 128

Scrabo 1 Ards 0.29 606 30.36 207

Ballymaglave 2 Down 0.23 704 18.18 413

Source: NISRA 2010bTable 2.3: selected comparisons of IDAOP and MDM scores and ranks


In summary the significance of such disparities is that if government departments and official bodies use the MDM scores and ranks to identify and target deprivation on a geographical basis, they may be missing several areas in which there is a high degree of income deprivation among older people. Examples of these are anti-poverty and neighbourhood renewal policies (see Chapter 5). Spatial strategies to combat inequalities in the general population or among older people in particular need to take account of the specific forms of deprivation they experience in order to be effective.

health deprivationHealth deprivation and disability forms one of the seven domains of the MDM and accounts for 15% of the total weight. The health ranks correlate very strongly with IDAOP ranks across the 890 SOAs (.8830) but the correlation is weaker for the 100 most deprived SOAs on the IDAOP index (0.4248) (source: the author). Table 2.4 sets out some examples of where SOAs with high levels of IDAOP deprivation had much lower levels of deprivation (lower ranks) in the health domain. Feeny, for example, has a health ranking 375 places lower than its IDAOP rank. Two-thirds of older people in Gresteel 2 have low incomes but they are living in an area which scores quite well in health deprivation (–0.64) and overall deprivation (9.95).

SoA District IDAoP score

IDAoP rank

mDm score

Crossmaglen Newry & Mourne 0.82 26 127

Ardboe Cookstown 0.79 31 156

Culmore 3 Derry 0.72 55 181

Forkhill 2 Newry & Mourne 0.72 56 323

Feeny Limavady 0.64 93 468

Gresteel 2 Limavady 0.64 94 670

Source: NISRA 2010bTable 2.4: selected comparisons of IDAOP and health Deprivation & Disability

Older populations and IDAOPIn summary, the evidence suggests that policies and initiatives that use the MDM or health scores to identify the most deprived areas are likely to overlook several SOAs with high levels of IDAOP. A further difficulty arises in targeting large numbers of income-deprived older people, namely that the areas with the highest levels of IDAOP tend to have the smallest numbers of older people living in them. Conversely, the areas with the largest concentrations of older people tend to have few low-income older people.

If we divide the 890 SOAs into ten groups according to the size of their older populations (women 60+ and men 65+) (NISRA 2011), the first decile (with the highest populations) includes only two of the most deprived SOAs according to IDAOP and the next decile includes only four.8 By contrast the ninth-lowest population decile contains 24 of the most low-income SOAs and the lowest-population decile contains 19 of them. If we plot all 10 deciles according to the number of older people, from largest to smallest older population, the average IDAOP score increases as population declines (see the trend line in Figure 2.1). In other words, having a lower older population in an area tends to be associated with a higher degree of income deprivation among older people. This means that spatial strategies directed towards the most deprived IDAOP SOAs will reach relatively few deprived people. The difference is substantial. The highest decile has an average of nearly 53,000 older people whereas the lowest one has only 13,300.

8 See Appendix 2 for fuller figures and a more detailed explanation of this methodology.


Figure 2.1: average IDAOP score by size of older population by SOA in deciles

Figure 2.2: NI Districts by SOAs in 100 most deprived by IDAOP scores

Source: author, based on NISRA 2010b and 2011

NISRA 2010b

Note: 1st decile represents the SOAs with highest populations and 10th decile represents the SOAs with the lowest populations.

Figure 2.2 illustrates the districts which have the highest numbers of SOAs with high income deprivation among older people. Whereas North Down includes 15 of the most populous SOAs by older population, it contains none of the SOAs with the highest rates of IDAOP. Forty-four of the most income-deprived SOAs are in Belfast and 18 in Derry. The next-largest numbers are in Craigavon, Lisburn and Newry and Mourne. This contrast between population and IDAOP strengthens the point that spatial policies and initiatives aimed at deprived older people may reach relatively small numbers of them – initiatives aimed at areas with high proportions of older people, such as North Down, would reach few who are income-deprived whereas initiatives aimed at the most deprived according to IDAOP would target relatively small numbers of older people.

Av IDAOP score Linear (Av IDAOP score)

1 2 3 4 5 6 7 8 9 10

y = 0.013x + 0.325R2 = 0.654

0.30

0.380.38

0.430.440.48

0.400.41

0.390.36

Belfast

Coleraine

Craigavon

Derry

Dungannon

Limavady

Lisburn

Newry & Mourne

Strabane

Others (1 each)

44

2

8

8

7

18

3

3

4

3

SOA’s in worst 100


PARt 3: A loCAl PRoFIlE oF DEPRIvAtIoN AmoNG olDER PEoPlEPart 3 profiles some of the most and least deprived SOAs according to IDAOP to show what particular characteristics these areas exhibit.

Extreme case studiesThe NI Neighbourhood Information Service (NINIS)9 provides data at various geographical levels, including SOAs. It includes census data but is regularly updated using administrative data. This makes it possible to compare and contrast different small areas, in this case (Panel 2.3) the most and least deprived area as measured by the IDAOP index.

9. See http://www.ninis2.nisra.gov.uk/public/home.aspx for more information.

most deprived SoA least deprived SoA

Drumnamoe 1 in Craigavon is the most deprived SOA in NI as measured by IDAOP, with 95% of its older people experiencing income deprivation. It is also in the most deprived tenth of SOAs in the income, employment, health, education and child deprivation measures and in the overall MDM. It is in the least deprived fifth of the rankings in the ‘proximity to services’ and ‘crime and disorder’ domains.

Only 3% of older people are income-deprived in Jordanstown 2 in Newtownabbey, making it the least deprived SOA on this index (excluding Aldergrove 1, which has no older people). It is also in the least deprived tenth of SOAs on employment, income, health, education, living environment, crime and child deprivation indices and in the MDM. It is close to average in ranking on proximity to services.

In the 2011 Census Drumnamoe 1 had 1,270 inhabitants, of whom 14.3% were aged 65 or older, close to the NI average of 14.6%. Population declined by 16% between 2001 (1,518) and 2011.

In 2011 Jordanstown 2 had a population of 2,047, of whom only 6.1% were aged 65 or older, well below the NI average of 14.6%. The population increased by 27% between 2001 (1,611) and 2011.

The area is characterised by low educational attainment, with only 8% of the inhabitants aged 16+ holding degrees compared with a NI average of 24%; 64% had no or low-level qualifications, well above the NI average of 41%. The proportion of people with limiting long-term illness in 2011 was 34%, as opposed to 21% in NI and the number reporting at least good health (64.3%) was 15 percentage points below the NI average (79.5%).

The area has high educational attainment, with 43% of people aged 16+ holding degrees, substantially higher than the NI average of 24%; 20% had no or low educational attainments, well below the NI average of 41%. The proportion of people with limiting long-term illness in 2011 was 9.0%, far below the NI average of 21%, and the proportion reporting good health or better was 91.6%, well above the NI average of 79.5%.

50% of households lived in rented homes, compared with 30% in NI as a whole. Access to a car or van averaged 0.7 per household in 2011 and 47.4% of households had no car or van.

Only 4% of households rented their homes, far below the NI norm of 30%. Access to a car or van averaged 1.9 per household in 2011 and 2.3% of households had no car or van.

In Drumnamoe 1 in 2011, 50% of people aged 16+ were economically active, lower than the NI average of 66%; unemployment at 9% was higher than the NI average of 5%. Administrative data for 2011 indicate that there were 155 income support claimants, 83 for incapacity benefit and 24 for employment and support allowance. If we express these as a % of men aged under 65 and women under 60 in 2010 (NISRA 2011), they work out at 13.6%, 7.3% and 2.1% respectively.

In 2011 78% of residents in Jordanstown 2 aged 16–74 were economically active, 12 percentage points above the NI average; unemployment stood at 2.6%, about half the rate in NI. Data for 2011 show that there were less than five income support claimants, 25 for incapacity benefit and 11 for employment and support allowance. Expressed as a proportion of men under the age of 65 and women under 60 in 2010 (NISRA 2011), these equal 0.2%, 1.3% and 0.6% respectively.

Census 2011Panel 2.3: comparison of the most and least deprived SOAs in NI

Note: see Table 2.5 for further details.


Ranks in 2010 Drum Ard Creg Cross Bally up mal jordan

IDAOP 1 2 3 26 887 888 889

MDM 31 9 10 112 857 859 888

Income 34 3 2 67 862 865 887

Employment 23 21 6 110 857 860 869

Health & disability 16 6 13 127 870 867 878

Education, skills & training 57 45 75 254 778 866 854

Proximity to services 715 862 622 244 285 390 458

Living environment 335 70 122 424 859 770 890

Crime & disorder 726 67 562 548 793 373 861

Income deprivation among children 62 5 2 113 716 838 868

NISRA (2010b)

These case studies reveal that income deprivation among older people is not an isolated indicator. It is associated with many other forms of disadvantage. Drumnamoe 1 in Craigavon has higher rates of income deprivation among children and working-age people than Jordanstown 2, poorer health and much lower educational attainment. Closely related to these indicators is that Jordanstown 2 residents are far more likely to be in work and that, conversely, a much higher proportion of Drumnamoe 1 residents are in receipt of benefits. Jordanstown 2 inhabitants are far more likely to have a car and to own their own homes than are those in the Craigavon SOA.

Data on most and least deprived areasThe two case studies above highlight important differences between the most and least deprived areas as measured by IDAOP. However, IDAOP is only one measure of deprivation and big differences in rank can result from small changes in the number of income-deprived older people. This section examines whether the characteristics that distinguish the top and bottom SOAs are also evident in other areas. For this purpose Table 2.5 presents data on the three most and least deprived SOAs on the IDAOP measure. Since these are all urban areas, Crossmaglen is also included because it is the rural SOA with the lowest IDAOP scores (highest rank), to see if it shares the characteristics of the deprived urban areas.

Table 2.5: rank of selected SOAs on deprivation measures

Note: the names of the seven areas in full are Drumnamoe 1 in Belfast, Ardoyne 3 in Belfast, Creggan Central 1 in Derry, Crossmaglen in Newry and Mourne, Ballymaconnell 2 in North Down, Upper Malone 1 in Belfast and Jordanstown 2 in Newtownabbey.


A low rank on IDAOP is closely associated with low rank on child and overall income, employment, health, education and skills, living environment and MDM. Rural Crossmaglen scores somewhat better on these indicators than the deprived urban SOAs (Drumnamoe 1, Ardoyne 3 and Creggan Central 3), i.e. older people are somewhat more deprived than the general population (this may possibly indicate that there are low levels of occupational and private pensions in that area). Conversely the three areas with low income deprivation among older people (Ballymaconnell 2, Upper Malone 1 and Jordanstown 2) also do well on these specific indicators, typically falling into the top 10% or better.

In the three least deprived areas, as measured by IDAOP, the proportion of people who reported good health in the 2011 Census ranged from 85% to 92%, which is better than Creggan Central 1 (76%) and Crossmaglen (77%) and much better than Drumnamoe 1 (64%) and Ardoyne 3 (67%) (Figure 2.3). The proportion of people with limiting long-term illness is markedly less in the three SOAs with low levels of poverty among older people, ranging from 9% to 18%, than in the four deprived areas, where the rate varies from 23% to 34%.

Census 2011 Table KS301NIFigure 2.3: health status of people in selected SOAs in 2011

Note: see Table 2.5 for the full names of the SOAs.

At the time of the 2011 Census there was a large difference in the proportion of people with degrees or higher qualifications according to low income among older people. Figure 2.4 shows that in the urban deprived areas the rate was only 7–8%, while that for the rural deprived area was twice as high (16%).

Limiting long-term illnessStated health good/very good

34

64.3

32

66.5

15.117.8

9

76.6

23.4 23.7

85.3 86.2

91.6

75.6

Drum Ardoy Creg Cross Bally Up Mal Jordan


Source: Census 2011 Table KS501NIFigure 2.4: education status of people aged 16+ in selected SOAs in 2011 (%)


Figure 2.5 (p34) shows that there are huge differences in the proportion of people who rent their homes between the urban deprived (50–72%) and urban non-deprived SOAs (4–12%) on the IDAOP index, with Crossmaglen coming in between (29%). Households in the least deprived IDAOP SOAs also have almost universal access to a car or van (92–98%), unlike the urban deprived areas (29–53%). Here too the rural area is different, with quite a high car access rate (77%). The 2011 Census also shows that the number of cars or vans per household was: Drumnamoe 1, 0.7; Ardoyne 3, 0.4; Creggan Central 1, 0.5; Crossmaglen, 1.3; Ballymaconnell 2, 1.8; Upper Malone 1, 1.6; and Jordanstown 2, 1.9.

Age 16+ with degrees or higherAge 16+ with low/no qualifications

7.6

64.2

7.2

65.3

35.4

56.5

42.948.6

8.1

16

24.419.4 20.1

60.3




SummARyThe number of older people is unevenly distributed across NI. At District Council level, the number of women aged 60+ and men aged 65+ ranges from 14% in Derry to 21.7% in North Down (NISRA 2011). At SOA level, the extremes run from 3% to 37.8%, excluding Aldergrove 1 because no older people live there. SOAs with high proportions of older people tend to have relatively few of them on low incomes and vice versa. There are also cases where SOAs have high ranks on IDAOP but much lower ranks on overall multiple deprivation and health and disability and cases where SOAs have low ranks on IDAOP but much higher ranks on the other two measures.

There are very stark contrasts on many indicators between the least and most deprived areas as judged by IDAOP. An analysis over time, e.g. between the 2001 and 2011 Censuses, has not been provided but could be developed. The inequalities identified at SOA level affect very many older people on issues such as income, home ownership, access to a car, health status, employment and benefit dependency.

Source: Census 2011 Tables KS402NI and KS405NI

House rented Access to car or van

50.1 52.6

71.7

28.7

7.312.3 4.2

76.870.5

28.8

9591.9

97.7

41.8


Figure 2.5: home and car ownership by household in selected SOAs in 2011 (%)


INCOME INEQUALITIES IN IRELAND, NORTh AND SOUTh

3.


10 The CSO’s Earnings Hours and Employment Costs Survey in ROI does not give earnings data by age.

This chapter presents data on income inequalities in Ireland, North and South, as income is a useful indicator for social inclusion and a good metric of inequality. Part 1 deals with earnings from employment by 10-year age bands, while Part 2 is concerned with inequalities in pay within the older age group (60+). Part 3 reviews statistics on incomes generally and Part 4 identifies some of the factors behind inequalities by examining the sources of income of older people (aged 65+ in ROI and in NI women 60+ and men 65+).

PARt 1: EARNINGSOnly a minority of older people are in paid employment but earnings from employment account for a great deal of the difference in overall incomes of the richest and poorest older people. In ROI, for example, the fifth of people aged 65+ with the lowest incomes earned €16 per week on average in 2011 whereas the fifth with the highest incomes earned €223 (CSO 2013). In NI earnings from employment averaged £10 per week for the lowest fifth of older couples in terms of income in 2008–11, compared with £442 for the highest fifth; single pensioners on the lowest incomes earned an average of £1 in 2008–11 while those on the highest incomes averaged £36 (NISRA 2013). Hence, Part 1 of Chapter 3 examines differences in earnings.

It might be assumed that older workers are better paid than younger ones because they have been in post longer and are therefore likely to be at the top of their pay scales. This is not the case in Ireland, North and South, where employees begin with low wages in their 20s and reach their peak earning years in their 40s; it remains high in their 50s (and in NI people aged 50–59 are the highest earners in some of the years) but falls off quite sharply after that (NISRA 2012).

Republic of IrelandThe CSO database provides data on total annual earnings by age on its main database (Figure 3.1).10 The difference in average annual earnings between workers in their 40s (€46,049) and those aged 60+ (€36,078) totalled almost €10,000 in 2009. Another feature is that average earnings of older workers declined in 2008 and then picked up again; overall, however, they were €623 per year lower in 2009 than two years previously. The 40–49 group enjoyed higher earnings in 2009 than in 2007, an increase of more than €3,000 per year; the drop of about €300 between 2008 and 2009 indicates the early impact of the recession on earnings.


11 In some cases the coefficient of variation of ASHE figures is between 10% and 20%, which affects the quality of the estimates (ONS 2012); this is the case with many of the figures given for people aged 60+.

Figure 3.1: ROI total average annual earnings by age group 2007–9 (€)

* figures are shown only for the peak years (40–49) and 60+

Northern IrelandMore detailed and more recent statistics are provided in NI by the Annual Survey of Hours and Earnings (ASHE), including a helpful analysis by age group (ONS 2012). 11

Figure 3.2: NI median weekly gross pay of full-time workers by selected age group 2004–12 (£)

Note: 2012 data are provisional.

40 - 4960+

42,87046,376 46,049

36,70134,706 36,078

2007 2008 2009

50-5960+

444

363 388

469 470

389

506

386

509

423

520

444

524

477446

386

423

326

2004 2005 2006 2007 2008 2009 2010 2011 2012

CSO Database*

ASHE 2012, ONS


Unlike ROI, the oldest full-time workers (defined as 60+) have enjoyed the largest increases in median gross weekly pay in recent years, increasing by 46% between 2004 and 2012, from £326 to £477. People in their 50s had an uplift of 24% over the eight-year period. Notwithstanding this, older workers still had lower pay in 2012 than those aged 50–59, as shown in Figure 3.2. In 2012 employees aged 60+ were 9% behind those in their 50s, a difference of £47 per week or approximately £2,440 per year.

Figure 3.3a shows that women workers are lower paid than men across the age range, with the largest differential of £82 per week occurring in the 50–59 age range in 2012. Median weekly gross pay of full-time women workers is 95% that of men in the 30–39 age range, 93% among workers in their 40s, 85% in their 50s and 88% among workers aged 65+. This supports the finding in several CARDI-funded research projects that older women are at a severe disadvantage compared with men, leading to lower female pension income in older age (Hillyard et al 2010; Hillyard and Patsios 2011; Duvvury et al 2012). Figure 3.3a also shows that both men and women aged 60+ are paid considerably less than men and women in their 40s and 50s respectively: e.g. men aged 60+ in work receive an average of £80 less than men in their 40s and women aged 60+ receive £99 less than women in their 40s (figures in the graph have been rounded).

ASHE 2012, ONSFigure 3.3a: NI median weekly gross pay of full-time workers by selected age group and sex 2012 (£)

An analysis of hourly gross pay for all employees in 2012 (Figure 3.3b) shows the same broad pattern as weekly pay. Male employees aged 60+ earn 17% less per hour than those in their 40s and 13% less than those in their 50s; women aged 60+ earn 24% less per hour than women in their 40s and 19% less than women in their 50s. In addition, the increase in the gender gap with age is more pronounced in hourly than in weekly earnings. Women in their 30s earn 30 pence per hour less than men; in their 40s and 50s the difference is much higher at £2.23 and £2.10 respectively. Finally, women in their 60s are paid £2.59 less than men of the same age, £8.50 compared with £11.09. Looking at female hourly earnings as a proportion of male hourly earnings, the figures fall from 97% aged 30–39 to 83% aged 40–49, 83% aged 50–59 and 77% aged 60+.

MaleFemale

480 459

569

529560

478 490

431

30-39 40-49 50-59 60+


ASHE 2012, ONSFigure 3.3b: NI median hourly gross earnings of all employees by selected age group and sex 2012 (£)

In sum, this shows that older workers, North and South, are paid considerably less than workers in their 40s and 50s. In NI, but not in ROI, the gap is narrowing because older workers have gained larger increases in recent years than their younger colleagues. Women are paid less than men at all ages and the gender gap is wider at ages 50+ than at ages 30–39.

MaleFemale

11.19 10.89

13.37

11.14

12.70

10.5111.09

8.50

30-39 40-49 50-59 60+


PARt 2: PAy INEquAlItIES wIthIN thE olDER AGE GRouPThis part of Chapter 3 examines inequalities in earnings within the older worker group. Differences in earnings explain much of the variation in overall incomes, which in turn greatly influences access to goods and services and overall quality of life.

It is simplistic to think of older workers as a homogenous group. The term covers a wide range of employees, from low-paid manual workers such as security staff or cleaners to highly paid professionals. In the case of earnings, the analysis is confined to NI because data are not available for ROI on the distribution of wages within the older population.

hourly earningsIn analysing earnings, two measures are given in this chapter: the median hourly earnings of all employees and the median weekly earnings of full-time employees. These are analysed by comparing people on different ranks on the income spectrum. The literature on pay (see, for example, Brewer et al 2008) uses ratios such as the 90/10 comparison: i.e. the pay of somebody at the 90th percentile compared with an employee at the 10th percentile. ONS (2012) does not give a figure for the 90th percentile for employees aged 60+ as it is unreliable, so the analysis below uses alternative ratios: 75/25 and 80/20. 13.

ASHE 2012, ONSFigure 3.4a: NI gross hourly earnings of workers aged 60+ on the 25th and 75th percentile 2004–12 (£)

13. The coefficient of variation of the 75th and 80th percentiles is 10–20%.

2004 2005 2006 2007 2008 2009 2010 2011 2012

12.0512.76 12.52

6.10 6.216.74

7.46 7.37

12.48 12.95

6.455.86

7.47 7.32

13.8414.49

15.1714.90

75th

25th


Taking the 75/25 ratio for hourly pay first (Figure 3.4a), the income of the quarter of people aged 60+ with the lowest earnings rose by £1.46 between 2004 and 2012 (and £1.11 between 2006 and 2012), from £5.86 to £7.32. The top quarter’s hourly pay rose by £3.12 over the same period (and £2.65 from 2006 to 2012), from £12.05 to £15.17. In 2012 the highest group was earning just over twice as much per hour as the lowest group. In the three years 2009–12, marked by economic austerity, the average older employee on the 75th percentile had a rise of £1.33 per hour, while one on the 25th percentile had a decrease of 14 pence.

An alternative measure is the earnings of people on the 80th and 20th percentiles, though Figure 3.4b also shows how low pay has essentially tracked, and may have been influenced by, changes in the national minimum wage (NMW). Here we see that inequality is growing more rapidly. The bottom fifth of employees aged 60+ had an hourly pay rise of £1.18 over the seven-year period compared with an increase for the top group of £3.65, so that the gap between them has risen from £8.44 to £10.91. Older people on low pay had an average rise in the three years of the recession of 10 pence per hour, compared with a 35 pence increase in the NMW. People in the top fifth may have been less affected by the recession in 2009–12, with an increase in hourly earnings of £2.19. The impact of these changes on people aged 60+ was that the ratio of earnings of people on the 80th percentile to those on the 20th percentile increased from 2.28 in 2009 to 2.57 in 2012 (author’s calculations).

ASHE 2012, ONSFigure 3.4b: NI gross hourly earnings of workers aged 60+ on the 20th and 80th percentiles 2005–12 (£)

Note: no figure is given for the 80th percentile in 2004.

2005 2006 2007 2008 2009 2010 2011 2012

5.79

17.18

6.00

5.055.93 6.08

5.35 5.73 5.80

6.19 6.386.87

5.524.85

15.45

14.23 14.49

16.27

17.88

15.41 15.69

80th

20th

NMW

6.95 7.01 6.97


Weekly earningsThis section compares weekly earnings of full-time older workers in NI on the 75th and 25th percentiles (Figure 3.5). There is a widening gap, from £244 in 2004 (and £267 in 2006) to £296 in 2008 and then to £369 in 2012. The higher-paid group did not just gain three times more than the lower group in cash terms (£197 compared with £71) over the eight years, but it also had a bigger percentage increase (38.8% as opposed to 26.9%). In 2004, full-time employees aged 60+ on the 75th percentile earned 1.9 times more than those on the 25th percentile (also 1.9 in 2006). In 2012 they earned 2.1 times more. In the three years of the recession 2009–12, the top quarter enjoyed a weekly rise of £92, compared with £30 for the bottom quarter.

ASHE 2012, ONSFigure 3.5: NI gross weekly earnings of full-time employees aged 60+ on the 25th and 75th percentiles 2004–12 (£)

Low payThe final paragraphs of Part 2 consider the position of older people at the bottom end of the spectrum, i.e. those with the lowest earnings, compared with average and higher-paid employees (Figure 3.6).

Older workers on the 75th percentile had an overall pay rise of £197 (38.8%) between 2004 and 2012 (£155 in 2006–12). People on average earnings received a larger percentage increase of 46.3%, which amounted to an additional £151. The lowest-paid 10th percentile had the smallest increase of any group in both cash and percentage terms, rising by £60 per week or 28.5%. The ratio of weekly pay received by older people on the 75th percentile compared with those on the 10th percentile has risen from 2.4 to 2.6 between 2004 and 2012 and the 50/10 ratio has gone up from 1.5 to 1.7 (there was no change in these ratios between 2006 and 2012). In other words, low-paid workers have fallen further behind those on both average and high earnings between 2004 and 2012.

14. The 80/20 ratio is not examined here because ONS rates the 80th percentile figure of weekly earnings for people aged 60+ as unreliable for five of the years covered.

2004 2005 2005 2007 2008 2009 2010 2011 2012

264.10 274.50 283.00 294.90 298.60 304.70 305.80335.10

320.80

528.90550.00

594.80 612.70651.50

579.30

507.60

658.10704.5

75th

25th


ASHE 2012, ONSFigure 3.6: NI gross weekly earnings of full-time employees aged 60+ on median, 10th and 75th percentiles 2004–12 (£)

A feature of Figure 3.6 is the pay increases the top groups have enjoyed in the last three years, despite economic austerity. The top quarter had pay rises of 15%, adding £92 to their weekly pay; median pay increased between 2009 and 2012 by 24%, or £91 per week. The lowest 10% of older workers had a pay rise over the three years of 10%, amounting to £25 per week.

Hourly rates for the lowest-paid 10% of older workers rose by £1.37 between 2004 and 2012, which works out at 27.5% (in 2006–12 the increase was £1.14 or 21.9%). This is lower than the increase in the NMW, which went up by £1.58 per hour (35.1%) between 2004 and 2012. In the three most recent years, the low-paid older workers had an increase in hourly pay of only 35 pence.

In summary, NI data show that earnings inequalities are increasing over time, including the period of the recession (2009–12), whether measured in hourly or weekly pay. The earnings gap between the lowest-paid fifth of workers aged 60+ is increasing compared with both average earners and the highest-paid workers of the same age.

2004 2005 2006 2007 2008 2009 2010 2011 2012

326363 386 388 389 386

423

477444

529550

595 613652

579

508

658705

75th

50th

10th

250246214214 204

250275

232 240


PARt 3: INComE INEquAlItIESEarnings from employment form a large part of the income of many older people but most are not in paid employment at all. Consequently, earnings account for only a small part of the total incomes of all older people: 16% of gross equivalised income of people aged 65+ in ROI in 2011 (CSO 2013), 23% of NI pensioner couples mean gross income after housing costs and 4% in the case of single pensioners in 2008–11 (DSD 2013). This part of Chapter 3 therefore focuses on the total incomes of older people.

Northern Ireland incomesMedian net incomes of the poorest pensioners in NI have barely changed in recent years whereas the richest have enjoyed larger incomes (DSD 2013). In the case of incomes before housing costs (BHC), the median net incomes of the poorest fifth of pensioner couples increased by £2 per week between 2003–6 and 2008–11 and the income of the next-poorest fifth increased by £6. The incomes of the richest fifth of older couples increased by £20 per week. The pattern was broadly similar for single pensioners BHC, with the income of the poorest fifth declining by £1 per week between 2003–6 and 2008–11 and the richest fifth receiving an increase of £7.

These BHC statistics are not shown but Figures 3.7a and 3.7b show that the picture is similar for incomes after housing costs (AHC).

DSD, Pensioners’ Income Series, 2013

Figure 3.7a: NI pensioner couples’ net weekly income after housing costs by quintile (£)

Among pensioner couples, median net incomes AHC of the poorest quintile remained unchanged. The richest fifth increased by 5.7%, boosting their incomes by £37 per week. The second-poorest quintile of pensioner couples had an increase of £16 per week, the middle group £23 and the second-richest quintile an increase of £20.

2003 - 062008 - 11

Q1 Q2 Q3 Q4 Q5

177 177

249 265

652

461

324

441

689

347




Figure 3.7b: NI single pensioners’ net weekly income after housing costs by quintile (£)

Figure 3.7c: NI pensioner units’ net weekly income in lowest and highest quintiles AhC (£)

The incomes of single pensioners AHC are only just over half those of pensioner couples, emphasising the particular vulnerability of older people who live alone, most of whom are women. In the case of inequality within the single pensioner population (Figure 3.7b), the poorest single pensioners had an increase in income of £2 per week, from £99 to £101. The next three quintiles rose by £9–£10 whereas the weekly income of the richest fifth of single pensioners AHC expanded by £20 per week.

These data indicate that inequalities among pensioners in NI have increased, regardless of which measure is used. Using the AHC figures, the net income ratio of the highest to lowest quintiles of pensioner couples increased from 3.7 to 3.9 and for single pensioners it rose from 3.0 to 3.2 (author’s calculations using data in DSD 2013). The ratio for pensioner couples is similar to that for the UK as a whole (3.8), as is the ratio for the single pensioner group (3.1 in the UK) (Thane 2012: 25). The statistics for NI are presented in Figure 3.7c for the top and bottom quintiles.

2003 - 062008 - 11

Q1

COUPLES2003-2006

SINGLES2003-2006

COUPLES2008-2011

SINGLES2008-2011

Q2 Q3 Q4 Q5

99 101

135 144

300

234

176

224

320

186

177 177

99 101

652689

300 320

lowest fifth highest fifth



Low-income pensioners are distributed quite unevenly across the 26 local government districts in NI (Figure 3.8). Five districts, headed by Armagh and Down, are better off than or equal to the UK average of 16% of pensioners below 60% median income and another four are at or below the NI average of 19%. In Banbridge the rate of pensioner poverty at 38% is twice as high as the NI average (19%). The three next-highest rates are in Dungannon, Carrickfergus and Larne and Moyle (which are combined due to sample size requirements), all with poverty rates of 30–32%.

Figure 3.8: NI pensioners below 60% median income by local government district 2009/10 AhC (%)

Source: DSD, Households Below Average Income Report 2009–2010, (2011b) Note: six LGDs have been combined into three pairs due to sample size requirements: Cookstown and Magherafelt; Omagh and Strabane; and Larne and Moyle.

ARMAGH

DOWN

DERRY

7

9

13

ARDS

NORTH DOWN

ALL UK

15

16

16

ANTRIM

CASTLEREAGH

COLERAINE

17

18

19

COOKSTOWN & MAGHERAFELT

ALL NI

NEWTOWNABBEY

19

19

20

NEWRY & MOURNE

CRAIGAVON

LISBURN

21

22

22

BALLYMONEY

BELFAST

FERMANAGH

24

24

25

OMAGH & STRABANE

BALLYMENA

LIMAVADY

25

27

29

CARRICKFERGUS

LARNE & MOYLE

DUNGANNON

BANBRIDGE

30

30

32

38


Republic of Ireland incomesThe bottom fifth of people aged 65+ in ROI in terms of weekly equivalised income had incomes equal to 53.2% of the average income in 2004 but this fell to 47.0% in 2010 and to 45.0% in 2011. Compared with the best-off older people (top quintile), the poorest fifth fell from 26.2% in 2004 to 22.0% in 2011 (CSO 2013). The quintile data for 2004 and 2011 are set out in Figure 3.9,15 which shows that the lowest group had a modest overall increase in weekly income of €32, compared with €85 for the next group, €97 for the middle group, €123 for the second richest fifth and €255 for the richest older people. The ratio of incomes in the top and bottom quintiles has widened from 3.8 to 4.5.

CSO 2013Figure 3.9: ROI equivalised weekly incomes of people aged 65+ by quintile 2004–11 (€)

Changes between 2004 and 2011 disguise an increase and a subsequent decline. For example, average incomes of people aged 65+ increased by 48.4% between 2004 and 2009 but then declined by 5% between 2009 and 2011. This indicates that older people have not been protected from the effects of the recession in ROI, where gross domestic product declined in each of the years 2008–10 (IMF 2013). More importantly, the incomes of the poorest fifth of older people increased by less than average between 2004 and 2009 (36.2%) and then declined more sharply between 2009 and 2011 (–11.4%); in cash terms the decline in the latest two years amounts to €24, from €209 to €185 per week. The incomes of the richest fifth of older people rose faster than for any other quintile between 2004 and 2009 (55.2%), followed by a two-year decline of 7.6%.

15. More detailed figures are given in Appendix 1.

2004

2011

154185 189

215

301

587

274

312

424

842

Q1 Q2 Q3 Q4 Q5


PARt 4: ACCouNtING FoR GREAtER INComE INEquAlItyThis part of Chapter 3 cites evidence of the sources of income for rich and poor pensioners and how these have changed in recent years. This will help us to understand the main factors underlying income inequality. Figure 3.10 shows that between 2004 and 2011 the main factors explaining the growing differential between the bottom and top quintiles in terms of income were social transfers (see below) and occupational pensions, which increased by an average of €104 (85%) per week for the highest quintile and by €2 (55%) for the lowest quintile. On the other hand, the lowest quintile had an extra €8 from earnings over the seven years whereas earnings for the top quintile declined by €21.

ROI sources of incomeCSO 2013Figure 3.10: ROI sources of weekly income of people aged 65+ in top

and bottom quintiles, 2004 and 2011 (€)

The broad pattern was an increase in income between 2004 and 2009 for all quintiles and sources of income, followed by a more mixed pattern between 2009 and 2011. The lowest quintile had big relative declines in income from occupational pensions, investment and property, but these were from a small base and were offset by higher earnings. Older people in the highest quintile experienced a decline of €54 per week in earnings and €23 in property income from 2009 to 2011 as well as a drop in other income.

In ROI most of the decline in the incomes of the poorest older people between 2009 and 2011 came from a €25 per week reduction in social transfers.16 Figure 3.11 illustrates that the richest fifth of older people receive much more in social transfers than the poorest fifth. In 2011, for example, the top income quintile received an average of €314 per week in benefits whereas the poorest fifth received only €159, a difference of €156. Moreover the gap between them has grown enormously from €23 in 2004.

16. CSO includes under social transfers unemployment-related payments, old-age related payments, family/children-related allowances and other transfers such as sickness or disability benefits.

All Other IncomeOccup Pension

243.99

Q1 2011 Q5 2004 Q5 2001

34,70615.82

5.83

122.66

222.76

226.66

Q1 2004

7.83

3.75

Social TransfersEarnings


CSO 2013Figure 3.11: ROI average weekly income by quintile from social transfers 2004 and 2011

NI sources of incomeThe most recent available data on components (or sources) of gross incomes in NI, which are presented separately for pensioner couples and single pensioners, relate to the three-year average figures for 2003–6 and 2008–11 (DSD 2013). This means that it is now possible to estimate an initial recession effect in the NI data.

As in ROI, the richest fifth of pensioners (both couples and singles) in NI receive more in benefits than the poorest fifth (see Figure 3.12) but an important difference is that the gap is getting smaller rather than bigger. In 2003–6 the quintile of pensioner couples with the highest incomes received £202 per week in benefits and the bottom quintile £160, a margin of £42. In 2008–11 the amount received by the top fifth declined to £197 and the sum received by the lowest quintile increased by £9. This reduced the gap in benefit receipts for the top and bottom fifths of pensioner couples to £28 per week.

17. In NI ‘pensioner’ means women aged 60+ and men aged 65+ though the retirement age for women is increasing to 65 by 2020.18. See Appendix 1 for fuller details of components of gross income.19. This section is based on gross incomes whereas the earlier part of this chapter used net income data.

2004

2011

137.43

158.69

179.47 178164.97 160.45

260.55275.45

266.85

314.40

Q1 Q2 Q3 Q4 Q5


NISRA Pensioners’ Income Series 2013

Figure 3.12: NI pensioner couples’ main sources of gross weekly income by quintile 2008–11 (£)

Figure 3.12 also shows that the main factor distinguishing between rich and poor pensioner couples is earnings from employment. The poorest fifth received only £13 per week on average from this source in 2003–6, declining to £10 in 2008–11. All of the higher quintiles had larger and increasing earnings, especially the richest quintile, whose average earnings rose from £368 to £442 per week. Apart from benefits and earnings, the main sources of difference between the richest and poorest pensioner couples in 2008–11 were occupational and personal pensions (£17 for the bottom quintile and £414 for the top) and investments (£1 per week for the poorest and £122 for the richest).

In the case of gross incomes, the ratio between the highest and lowest pensioner couples was 5.6 in 2003–6, rising to 6.0 in 2008–11. In cash terms the gap has risen from £889 to £986 per week between the richest and poorest pensioner couples.

Incomes of single pensioners are just half those for couples. The gap between the richest and poorest single pensioners in benefit income reduced slightly because the top group had a drop of £2, from £206 to £204 while the bottom quintile had an increase from £111 to £115. Money received from occupational pensions, rather than earnings, is the main factor explaining the difference between rich and poor single pensioners, as shown in Figure 3.13.

All Other IncomeEarnings

Occupation & Personal PensionBenefits

Q2

36,701

241

16

Q1

169

10 255

Q3

53

Q4

34,706

256

87

Q5

34,706197

442


NISRA, Households Below Average Income (2013)

Figure 3.13: NI single pensioners’ main sources of weekly income 2003–6 and 2008–11 (£)

Occupational and personal pensions made a negligible contribution to the weekly budgets of the poorest single pensioners, £5 per week in both 2003–6 and 2008–11. By contrast, the richest pensioners received £141 from this source in 2003–6 and £160 in 2008–11. The smaller range of incomes among single pensioners compared with pensioner couples meant that the ratio between top and bottom incomes was less extreme. Moreover, unlike the pattern with net incomes, the gap between the highest and lowest single pensioner groups has become smaller in recent years due to a decline in gross income of the highest quintile from £461 to £419 per week (–£42). This means the gross income ratio declined from 3.8 to 3.4 between 2003–6 and 2008–11.

The examination of sources of income shows that in ROI the growing gap between the richest and poorest quintiles in the years 2004–10 is largely explained by big increases in social transfers and private and occupational pensions by the highest group. In NI the gap in receipts from benefits has reduced in the latest time period (2003–6 to 2006–9) but the richest quintile of pensioner couples has gained much more from earnings.

SummARyThis chapter, which focused on income inequalities in Ireland, North and South, outlined the big pay differences between older and younger workers, amounting to €10,000 per year in ROI and £4,000 in NI. Within the older worker group there are big differences in earnings and the gap between the highest and lowest earners is getting greater. Even during the austerity years, 2009–11, top earners received larger rises while the low-paid were virtually at a standstill. In the case of total incomes, the poorest pensioner units in NI have had a drop in net incomes (but not in gross incomes) in recent years while the richest have had an increase. In ROI both the richest and the poorest older people had lower incomes in 2011 than in 2009 but in the seven years covered by SILC data (2004–11) the lowest fifth of older people had a growth in equivalised income of €32 per week while the richest fifth had an increase of €255. Most of the difference is accounted for by greater receipts by the richest older people from social transfers, occupational pensions and earnings from employment.

All Other IncomeEarnings

Occupation & Personal PensionBenefits

206

Q1 03-06 Q1 08-11 Q5 03-06 Q5 08-11

34,706

111

36,701

115

55

141

204

160


POLICY BACkGROUND

4.


One of CARDI’s objectives is to help ageing research influence policy and lead to improvements in the lives of older people. Part 1 of this chapter therefore presents a short review of the broad policy context in the field of inequalities, while Part 2 outlines the policy background in Ireland, North and South. The policy context includes strategies that are specific to older people in ROI and NI in order to tackle existing inequalities within the older population. However, it is important to look at the life course and to target policies at the population as a whole in order to avoid or mitigate future inequalities among older people.

PARt 1: BRoAD PolICy CoNtExt There is strong evidence that income and social class are closely associated with health status and that sizeable inequalities exist in morbidity and mortality between those who are well off and those who are not. The World Health Organization’s Commission on Social Determinants of Health (2008) thoroughly documented global inequalities and made three over-arching recommendations:

1 improve daily living conditions

2 tackle the inequitable distribution of power, money and resources

3 measure and assess the problem and assess the impact of action.

The commission was chaired by Sir Michael Marmot (2010), who went on to make a similar analysis in the English context. For example, he showed that people living in the poorest neighbourhoods die, on average, seven years earlier than people living in the richest neighbourhoods. ‘Even more disturbing, the average difference in disability-free life expectancy is 17 years. So, people in poorer areas not only die sooner, but they will also spend more of their shorter lives with a disability’ (Marmot 2010:16).

Wilkinson and Pickett (2009) have also documented how life expectancy, social mobility and educational attainment are lower and physical and mental illness higher in societies with highly unequal income distributions than in those with a greater degree of equality – inequality was a more potent factor than overall low income.

This conclusion is supported by a study (Ronzio et al 2004) showing that income inequality is the most significant social variable associated with preventable or immediate death rates; it claimed that a unit increase in the Gini coefficient (which measures income distribution) is associated with 37% higher death rates in US cities. In light of this, the debate on what are known as the social determinants of health has been labelled ‘the politics of preventable deaths’ (Ronzio et al 2004).


The Organisation for Economic Co-operation and Development (OECD) (2011) argues that reforming tax and benefit policies is the most direct and powerful instrument for redistribution, but this weapon has been blunted by the recession. It maintains that:

Furthermore, good services promote social inclusion and well-being among older people and almost certainly reduce demands on health and care services. On average, OECD governments spend as much on public social services as they do on cash benefits and this spending reduces inequality by about one-fifth on average (OECD 2011).

The need to tackle underlying social determinants has been recognised at EU level. Needle (2011) argues that the overarching EU 2020 strategy for smart, inclusive and sustainable growth in a decade has few health specific components but a myriad of potential impacts on health equity e.g. climate and energy targets, industry, and employment and education flagships.

The most promising way of tackling inequality is more than ever by the employment route. More and better jobs, enabling people to escape poverty and offering real career prospects, is the most important challenge. The report clearly identifies upskilling of the workforce as one of the most powerful instruments at the disposal of governments to counter rising inequality (OECD 2011:18–19).


PARt 2: PuBlIC PolICy IN IRElANDPart two of Chapter 4 sets out the policy context to inequality in Ireland, North and South.

In various all-Ireland studies, the Institute of Public Health in Ireland (IPH) has highlighted the importance of deprivation from birth (McAvoy et al 2006) through perceptions of health (Balanda and Wilde 2003) to death (Balanda and Wilde 2001). It has also collaborated with the Combat Poverty Agency (CPA) in a report illustrating the extent to which health outcomes are influenced by social factors, such as poor housing, nutrition and education (Farrell et al 2008). The report summarises three broad approaches to reducing health inequalities in Ireland, based on work by Whitehead and Dahlgren (2006):

1 focus on the most disadvantaged groups to improve their health through specific measures;

2 narrow health gaps: e.g. set targets and introduce initiatives for those who are poorest and most disadvantaged;

3 reduce differences and equalise health all along the income ladder.

The foreword by O’Kelly and Wilde (2008) to Farrell et al (2008) argues that policy-makers in housing, education, transport, health and social policy need to understand how they can influence people’s chances of health, in particular to ensure:

Health and longevity cannot be seen in isolation. As this report’s analysis of spatial deprivation confirms in NI (Chapter 2), poor health is linked with low income, poor educational achievement, rented housing and other factors. This relationship was recognised in the seminal Investing for Health strategy (DHSSPS 2002), which prompted public health initiatives at local level and involved other government departments. However, a commentary by Wilson and Oliver argued that the strategy lacked political leadership in a system with ten largely autonomous departments and noted that ‘progress can only be made in levelling the social gradient in health if all ministers – not just the health minister – see it as a political priority and are prepared to work as a team to achieve it’ (Wilson and Oliver 2007:19).

that people have an adequate income, education and decent housing as, without these, people will continue to suffer poor health and quality of life and appalling inequalities in health… in Ireland and Northern Ireland we face particular issues in respect of income inequality, child poverty and fuel-poor housing (O’Kelly and Wilde 2008:7).


Northern Ireland policyThe strategy Ageing in an Inclusive Society was published in NI in 2005 by OFMDFM with a focus on promoting the social inclusion of older people. It included action for ‘improvement in general health and well-being and reductions in health inequalities amongst older people’.20

OFMDFM’s over-arching anti-poverty strategy Lifetime Opportunities, published in 2007, refers to inequalities but inequalities are not considered in the section titled ‘Older Citizens – Beyond Working Age’ apart from the goal of reducing the gap in life expectancy between the fifth most deprived and least deprived areas. However, measures of income inequality are included in the monitoring framework for the anti-poverty strategy (OFMDFM 2010).

Most of the explicit discussion of inequalities is in health policies. For example, the NI draft health strategy for the next decade fully accepts the argument that inequality plays a powerful role in determining health outcomes:

A consultation document on a public health strategy for 2012–22 (DHSSPS 2012a) notes that men living in the 10% least deprived areas in NI can expect to live almost 12 years longer than those in the 10% most deprived areas; and for women the gap is more than eight years. The report also refers to very steep social class gradients in deaths from circulatory and respiratory diseases and from cancer, especially lung cancer. Another recent DHSSPS report (2012b) gives full details of health inequalities, including evidence that, on many indicators, the gap between people from the most deprived and least deprived areas has increased in the last decade, despite the Investing for Health priority (DHSSPS 2002) to reduce inequalities.

The 2012 consultation document was launched jointly by the First and Deputy First Ministers and the Minister for Health, in recognition of the imperative for co-ordinated action since many policies can impact on equality and health:

The DHSSPS also notes that health promotion initiatives are unlikely to reduce health inequalities and may even exacerbate them. It cites the Healthcare Commission on this point:

20. An updated ageing strategy was launched for consultation in NI in February 2014.

Higher income and social status are linked to better health. There is strong international evidence that the key social determinant is poverty or deprivation. World Health Organization (WHO) asserts that poverty is the single largest determinant of health, and ill health is an obstacle to social and economic development. Poorer people live shorter lives and have poorer health than affluent people – this is a pattern repeated in many countries, including in Northern Ireland (DHSSPS 2012a:14).

Therefore to be effective this strategy will require buy-in from not just Executive departments but, crucially, broad cross-sectoral buy-in at regional and local levels including from key organisations and from individuals and local communities. (DHSSPS 2012a:10)

Tackling the determinants of health does not automatically tackle the determinants of health inequalities. Heath promotion initiatives and improvements in technology and service delivery can increase inequalities because higher social classes are more likely to avail of them. (Raleigh and Polato 2004)


Republic of Ireland policyThe ROI’s first National Positive Ageing Strategy, published in April 2013 following extensive consultation, refers to older people who may be ‘financially vulnerable’ and to ‘marginalised, vulnerable, hard-to-reach and minority groups of older people’ who may need particular attention, but it does not refer to inequalities in its vision, goals or objectives (Department of Health 2013a: 13). However, the document does promise collaboration to ensure coherence in the implementation of both the positive ageing strategy and the government’s health strategy for 2013–25 (Department of Health: 2013b), which has an explicit aim to reduce health inequalities. In June 2011 the Department of Health (2011) noted that the terms of reference of the group developing a new long-term health strategy included the ‘wider determinants of health and health inequalities’ and ‘inter-sectoral and cross-sectoral approaches at policy and practice level’.

In 2012 the ROI Government issued a health strategy for the years 2011–14 (Department of Health 2012). It focused on improved access to health services through ‘a universal, single-tier health service, supported by Universal Health Insurance (UHI), where access is based on need, not income’. It also pledged universal primary care ‘which will provide access to GP care, free at the point of delivery, to the entire population on a phased basis within the Government’s term of office’ (Department of Health 2012:15).

SummARyInequality has received considerable attention from academics and international bodies, which have pointed to a relationship between income or social inequalities and health inequalities. A general theme of the literature is the need to improve the incomes and living conditions of the poorest people and reduce inequalities between them and better-off members of society

Policies in Ireland, North and South, point to the need to create broad alliances of government agencies and other organisations to reduce poverty and health inequalities, but evidence suggests that health inequalities persist and are increasing on some indicators.


IMPLICATIONS FOR POLICY

5.


This chapter returns to the research questions posed in the introduction and attempts to bring together some of the strands contained in Chapters 1–3. Of the four questions posed on page 6, the first three were:

1 Are there inequalities affecting older people as a group compared with younger people, or inequalities when comparing within the older population?


3 Do these socio-economic inequalities have a detrimental impact on older people or a substantial number of them?

The first three chapters of this report contain evidence of substantial inequalities affecting older people. There are differences between older and younger people, such as treatment rates of men with prostate cancer, the incidence of fuel poverty and large differences in earnings from employment. There are also marked differences within the older population in earnings, pensions and social transfers; access to some services; and in health status, especially multimorbidity and resulting quality of life. In all these cases people in the lowest social classes or lowest income brackets fare much worse than better-off people in the same older age group.

In some cases, such as earnings and incomes, the evidence points to a widening of inequalities in recent years in both NI and ROI. Further analysis of the 2011 Censuses and other recent data sources in Ireland, North and South, will enable us to establish whether other inequalities are increasing or reducing, such as the spatial differences identified in Chapter 2.

These inequalities can have a seriously detrimental impact on many older people’s health, life expectancy, social inclusion and quality of life. They therefore represent an important issue to be tackled by government and social partners, leading to the fourth question posed on page 6.

Reducing socio-economic inequalities and policy implications How can any harmful socio-economic inequalities be reduced or eliminated and what are the implications for policy-making?

In seeking to answer this question, this report focuses on the areas covered by CARDI-funded research projects, where possible linked to the other evidence on spatial deprivation and income gaps. It groups the research into themes, as follows.


SoCIAl INCluSIoNResearch under the theme of social inclusion consists of two reports on health and inclusion in rural areas (HARC 2010; Walsh 2012) and one on transport for older people. In addition to the specific report on transport (Ahern 2010), several other research reports noted the importance of physical access if older people are to conduct their normal business, such as going to work, shopping, or visiting the post office or health facilities. These essential activities in themselves promote social inclusion but older people, especially in rural areas, also need transport in order to visit friends, attend clubs and social, cultural and sporting activities. In this way they can enjoy full social inclusion and the connectedness that promotes well-being and especially good mental health. There is more emphasis in the literature on older people’s health and longevity than on having fun and enjoying life, but transport is an essential facilitator of many of the pursuits that people value for a fulfilling older age.

The analysis of spatial deprivation in NI in Chapter 2 highlighted that people in well-off areas have much better access to private cars than people in disadvantaged areas. One implication for governments is that expenditure on public transport, especially services for both rural and urban deprived areas, has the potential to improve access for people who cannot afford to buy or run a car.

Often the debate about transport is too narrowly focused. Many argue that a rural bus or train route is uneconomic in the sense that it does not generate enough revenue from passengers to pay for the cost of running the service. Since population density is much lower in rural than in urban areas, transport services in the former are more at risk from narrowly based economic assessments. Other factors to be added to the debate include the need for people in rural areas to get to work and to services and the benefits that result. In the case of older people, who are less likely to drive than younger citizens, transport is even more important to ensure social inclusion. As the recent NI draft health strategy noted, connectedness is very important:

CARE Chapter 1 highlighted that people in low socio-economic groups and/or living in deprived areas are more likely to be disabled than better-off people and are less likely to be able to afford the supports needed to continue living at home (Wren et al 2012). The specific evidence that men in rented accommodation are 90% more likely and women 40–45% more likely to enter institutions than owner-occupiers (Wren et al 2012, citing Breeze et al 1999) is very pertinent to the analysis of measures of deprivation in Chapter 2. That showed that levels of home ownership, as distinct from renting, are an emphatic distinguishing feature of deprived and privileged areas. Another is access to a car or van, which is very pertinent to McCann et al (2011b), who found that older people in NI with access to a car were 42% less likely to enter residential care than those without a car.

Reducing the need for care by social class/area of deprivation partly relates to the health inequalities discussed earlier – if rates of ill-health and disability among the most deprived are reduced to match those of the average and above-average, then their need for residential care will be lessened. This can come about only through the sort of social reforms indicated by the NI health strategy, involving a wide range of public, private and voluntary bodies and local communities.

Greater support from families, friends and communities is linked to better health. The links that connect people within communities (described as social or community capital) can provide a source of resilience through social support. People’s participation in communities, and the added control over their lives that this brings, has the potential to contribute to well-being and other health outcomes. (DHSSPS 2012a: 13)


However, there remains the narrower issue of resources for care, such as public spending on support for older people in their own homes or money which people devote to their own care. Since there are inequalities in income and wealth, as detailed in Chapter 3, governments have a duty to ensure that access is equitable. One example is the scheme operated in the Republic of Ireland through voluntary groups, which gave older people access to telecare technology even if they had low incomes (Delaney et al 2011). It can benefit both older people and their carers and can bring financial savings to finance department by reducing the need for more expensive residential care.

PovERtyPoverty is the greatest risk factor for health and well-being (DHSSPS 2012a) and it is also closely related to poor educational achievement, inferior housing, poor mental health, greater risk of teenage pregnancies, obesity, suicide and greatly increased mortality. Research funded by CARDI suggests that higher incomes are the best way to cut through the social problems that most affect disadvantaged older people. Hillyard et al (2010) point out that most older people in NI and ROI depend on the state pension to survive and that in NI the level of the state pension is very low. Hillyard and Patsios (2011) show how the recession has affected the living standards of older people. Goodman et al (2011) highlight the impact of fuel poverty on older people on low incomes; part of the solution is to raise these incomes, though action is also needed on energy efficiency and fuel prices. Duvvury et al (2012) document the particular problems facing older women, who are less likely to have occupational and private pensions and, if they do have them, to receive lower payments than men because of broken careers for caring duties.

Duvvury et al (2012) and Hillyard and Patsios (2011) advocate action to ensure that future pensioners are better provided for, though they differ to an extent in their policy prescriptions. They are agreed, however, that the cost of more generous pensions need not be prohibitive if the money devoted to generous tax reliefs for the pensions of well-off directors and high-paid employees were re-directed to the basic pension, North and South.

In the alternative scenario of reduced social transfers, Goodman et al (2011) warn that older people’s incomes are heavily reliant on such transfers. Erosion of these transfers and benefits will almost certainly lessen the income of older people with the indirect effect of worsening the fuel poverty situation for older people, who already have a higher risk of experiencing fuel poverty. ‘Furthermore, older people are particularly vulnerable to health and social harm associated with this experience of fuel poverty’ (Goodman et al 2011:4).

Increasing the incomes of older people, particularly the poorest among them, is a necessary but not sufficient step to reduce inequality. Hillyard et al (2010) and Hillyard and Patsios (2011) point to fears among older people, especially in ROI, that cuts in public services will have a severe impact on them. The analysis of multiple deprivation in NI suggests that spatial strategies to combat poverty among older people are likely to be hampered by the fact that deprived areas tend to have small numbers of older people living in them, as shown in Chapter 2, Part 1. This means that improved services and initiatives such as anti-poverty and neighbourhood regeneration should be targeted at those most in need.

hEAlth AND wEll-BEINGAn unequivocal conclusion from the health-related research funded by CARDI (HARC 2010; Morgan et al 2011; Bantry White et al 2011; Savva et al 2011) is that social class matters a great deal, whether defined by socio-economic group, income or living in deprived areas. People who are poor or in lower social classes are more likely than well-off people to have chronic diseases, disability and mental health difficulties and more likely to die at a younger age. This reinforces the case made earlier for wide-ranging action to tackle health inequalities.


HARC (2010) argues that promoting healthy ageing in rural areas should be at the core of rural policy-making and that services for older people should be improved rather than being determined solely by arguments about economic efficiency. It also points to the active contribution of older people themselves to their rural communities and believes the role of community organisations should be enhanced. This dual approach of improved public services and community engagement suggests action is needed on structural inequality in society (employment, incomes, education, housing and so on). However, initiatives also need to target the most disadvantaged people and communities through, for example, active ageing and healthy living initiatives that tackle lifestyle factors responsible for physical and mental ill-health. In this context Morgan et al (2011) found that moderate to high levels of exercise could reduce the risk of depression among over 50s by 50%; initiatives could be targeted to ensure that lower social classes, who are more likely to suffer depression, benefit the most.

Similarly, Bantry White et al (2011) support policies to address structural inequalities in the context of food and low income, but they also propose practical steps such as community-based food projects targeting vulnerable groups such as those living alone and single men; and allotments, which may have social, health and nutritional benefits including increased access to vegetables, especially green leafy varieties. They also advocate an integrated health and nutrition policy for older adults in Ireland, North and South, building greater awareness of dietary guidelines and a nutrition promotion programme meeting their specific needs.

There are no specific strategies in NI or ROI dealing with multimorbidity at any age but the strong evidence from Savva et al (2011) on the health gap between high and low social classes indicates that they are much needed. The care that people receive is often fragmented, incomplete, inefficient and ineffective and the risk of potentially avoidable hospital admissions or preventable complications increases dramatically as the number of chronic conditions increases among older people (CARDI 2011, citing Boyd and Fortin 2010). There are important implications for health services. For example, treatment needs to be centred on the person rather than the condition; people with multimorbidity and their caregivers need to be involved in public health policy initiatives; and practical help is needed for older people who may have to manage complicated medication and treatments (Savva et al 2011).

INComE INEquAlItIESEarnings from employment account for a large part of the difference in incomes between the richest and poorest older people in ROI and NI. Access to well-paid work is therefore a major factor in income inequalities. This adds force to the assertion of the OECD (2011) that the labour market should be ‘the first place to act’ when seeking to reduce inequalities. It argues that technological progress has been a motor for economic growth, but better-educated workers have reaped higher gains while those with lower skills have been left behind.

Improved education and training for low-skilled workers is one answer and extending the working lives of people on low incomes is also important. That is a difficult task since the evidence on health inequalities shows that people with low levels of education, skills and incomes are also most likely to be in poor health. Carefully designed programmes are needed to match the trainings and skills needs identified and they must be able to run for long enough to make a difference, ideally beginning with workers in their 40 and 50s.

Since the national minimum wage appears to determine the earnings of about the lowest-paid fifth of employees, the amount paid may need to be increased. As of February 2013, the statutory national minimum wage is £6.19 per hour but the Living Wage Foundation has set an unofficial ‘living wage’ outside London of £7.45, 20% higher than the statutory rate. It states that the living wage has so far led to over 45,000 working families in the UK being lifted out of poverty (Living Wage Foundation 2013). If employers in NI paid the living wage it would reduce absolute poverty rates by providing low-paid workers with an additional £1.26 per hour, equivalent to £37.80 more per week for someone working 30 hours. It would also reduce relative poverty rates because higher amounts at the bottom of the pay ladder would flatten levels of inequality between the highest- and lowest-paid workers.


So long as policies of austerity continue, such as severe spending restraints, reductions in salaries or pension provision and additional taxation, the main means to reduce pay inequalities is to cut pay rates at the top more than at the bottom. As and when Ireland moves towards economic growth, the NI and ROI governments, as both employers and persuaders, should consider allocating money for pay rises in a manner that will redistribute earnings gradually to low-paid workers. For example, flat-rate rather than percentage pay rises bring greater benefits to workers at the bottom of the pay scales.

More intensive research is needed on the issue of older employees. Among the topics to be explored are the reasons why older workers are paid less than younger workers; and the position of the 20% or more of people who are obliged to leave work before 65 through ill-health and disability. Research could illuminate the personal factors affecting these workers and the changes that might be needed in workplaces to ensure they can continue in employment.

SoCIAl tRANSFERS/BENEFItSThe operation of the benefit system in Ireland, North and South, merits very careful scrutiny. The highest fifth of single pensioners in NI in terms of gross income receive twice as much per week in benefit income as the lowest fifth. In ROI social transfers for the richest are almost twice as high as for the poorest older people. Since the pensioners with the highest incomes receive much more from earnings and occupational pensions than those with the lowest incomes, one might expect the balance of benefits to be reversed in order to redress the disparity. In fact, the gap in receipts from social transfers between the richest and poorest is growing wider in ROI for older people generally and for single pensioners in NI.

Further research is required on why these inequalities in benefits exist. One reason may be that the richest group has two or more people receiving state pensions and are more likely to be receiving the full pension than low-income pensioners on lower means-tested or non-contributory pensions. The argument is often made that people who contribute to a pension through National Insurance are entitled to receive more than a person who has not contributed. However, the ‘life course’ argument has been forcefully made that many of those receiving the lower non-contributory pension are women who have lost out by being absent from the labour force to bring up children or carry out other caring duties (Duvvury et al 2012).

If the difference in the income of the richest and poorest older people is very large and growing, it can be argued that the money available for benefits should be used to make up some of the gap. In stark terms, the latest figures (2008–11) show that the bottom fifth of single pensioners in NI has an average weekly income after housing costs of only £101 but they receive only about half as much from benefits as the top fifth.

In January 2013 the Secretary of State for Work and Pensions in the UK announced a new single-tier pension, currently set at £142.70, to be introduced in April 2017 or later. Recipients must have 35 years National Insurance contributions or exemptions. The proposals may particularly benefit women, low earners and the self-employed, who presently find it difficult to earn a full state pension. This could provide the basis for improving the incomes of the poorest pensioners and remove the means testing inherent in the pension credit system, if implemented in full.


oCCuPAtIoNAl AND PRIvAtE PENSIoNSOccupational and private pensions are another major source of inequalities in incomes within the older population but the solution is necessarily long-term. Chapter 3 shows that income inequalities exist at all age groups and people with low incomes are unlikely to accumulate good pensions, if any at all. This illustrates how poverty in old age must be seen in the context of the life course and also emphasises that many older people can do little to escape poverty apart from employment. Both Hillyard et al (2010) and Duvvury et al (2012) note that older women are particularly badly affected. Looking to the future, auto-enrolment systems being introduced in the UK and being considered in ROI, under which employees are enrolled in pension schemes unless they actively opt out, will make a contribution to older people’s incomes in future but the amounts are likely to be small. Greater incentives are needed to persuade low-paid workers to contribute to pension schemes or for their employers and/or the state to make higher payments on their behalf.

SPAtIAl DEPRIvAtIoN AND INComE INEquAlItIESThe analysis of spatial deprivation in Chapter 2 indicated that strategies to promote inclusion and reduce inequalities need to be carefully framed to the extent that they are aimed at older people. IDAOP is quite strongly correlated at local level with other measures of disadvantage, such as the MDM and the health domain, but several areas have ranks on poverty among older people that are very different (higher or lower) than their ranks on other indicators. This means that initiatives that are prioritised on one set of indicators will miss older people who do not appear to live in priority areas for the initiatives but are in fact highly deprived. For example, the anti-poverty strategy in NI (OFMDFM 2007) does not refer to IDAOP and the Neighbourhood Renewal initiative used the MDM to identify the 36 areas selected for attention.

Programmes targeted at older people need to span a range of public services. It is wrong to think, for example, that issues such as education, training and employment are not relevant to the older population. The low pay of many older workers and the fact that the majority of older people are not employed could be in part because they lack the skills or qualifications needed to achieve or hold on to well-paid jobs. As the pension age rises to 68 or older, issues of skills, certification and work will become increasingly important for older people.

We can conclude from this that services such as health, education, training, housing and others, as well as spatial policies to reduce inequalities, must be carefully targeted in order to recruit and involve older people as well as children and younger adults.

ImPlICAtIoNS FoR DAtA CollECtIoNHillyard and Patsios (2012) argue that measuring inequalities properly requires improved and co-ordinated data collection. In particular, a comprehensive and robust living standard index would allow comparisons to be made between people e.g. by class, gender and ethnicity and would permit the extent of the inequalities to be measured, North and South. They make the case for cross-border co-operation in data collection, especially at a time of economic stringency:

Over the coming years with both jurisdictions having to make deep cuts in public expenditure, the policy challenges are going to be considerable, in particular how to treat different groups in the population fairly. This requires robust and regular data. If they were comparable across the border then it would be possible to learn from the effects of different economies and different social policies in providing welfare to their respective populations. Until the data are standardised, a very real policy-sharing opportunity, which would be to the benefit of all the people on the island of Ireland, is being missed (Hillyard and Patsios 2011:29).


CoNCluSIoNIn order to improve the lives of older people, policy, practice and resource allocation should be made on the best information available. Important policy implications emerge from this piece of research.

Improving transport, tackling fuel poverty, addressing structural inequalities and promoting healthy ageing will help to tackle inequalities. Likewise, improved education and training can help improve the jobs and pay of low-skilled workers and lead to higher pay through the life course . In terms of inequalities in pension-saving, greater incentives may be needed for low-paid workers to contribute to occupational pensions. The evidence indicates that an increase in the national minimum wage could lift some low-paid workers out of poverty. This could particularly benefit workers over the age of 60.

More research is needed on issues affecting older people, such as why older workers are paid less and why better-off households benefit disproportionately from benefits/social transfers. Furthermore data collection to help inform policy should be improved on a cross-border basis so that both jurisdictions can learn from one another.

In conclusion, this report illustrates that socio-economic inequalities affecting older people influence not just the more obvious areas such as income and fuel poverty but a wide spectrum of later life issues including social inclusion, health, pensions, food and care. In order to tackle such inequalities now and for future generations of older people, policy must focus on inequalities through the life course.


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Pensioner couples

Bottom fifth Next fifth Middle fifth Next fifth Top fifth

03/06 08/11 03/06 08/11 03/06 08/11 03/06 08/11 03/06 08/11

Benefits 160 169 230 241 250 255 251 256 202 197

Occupational income 12 12 24 31 70 74 133 172 292 353

Personal pension income

5 5 8 9 16 13 13 16 67 61

Investment income 3 1 4 2 9 5 18 12 149 122

Earnings 13 10 24 16 24 53 98 87 368 442

Other income 1 1 1 1 2 1 1 1 5 8

Total 194 198 291 300 371 401 514 543 1083 1184

Single pensioners

Bottom fifth Next fifth Middle fifth Next fifth Top fifth

03/06 08/11 03/06 08/11 03/06 08/11 03/06 08/11 03/06 08/11

Benefits 111 115 150 161 179 191 214 221 206 204

Occupational income 4 5 7 12 19 22 35 39 133 155

Personal pension 1 0 1 2 1 0 6 3 8 5

Investment income 3 1 3 2 2 3 5 4 49 17

Earnings 0 1 2 1 4 2 2 11 57 36

Other 2 1 2 1 3 2 2 1 8 1

Total 121 124 164 180 208 220 265 280 461 419

Components of mean gross income of NI pensioners by quintile of net income (AhC) 2003–6 and 2008–11 (£ per week at 2010–11 prices)

APPENDIx 1: DAtA oN INEquAlItIES wIthIN thE olDER PoPulAtIoN, NI AND RoI

Source: DSD (2013) Table 4.3


Q1 Q2 Q3 Q4 Q5

2004 153.77 188.77 214.83 300.95 587.29

2009 209.41 277.34 320.77 430.44 911.44

2010 (revised) 197.15 276.63 322.13 426.94 841.38

2011 185.45 274.07 312.08 423.66 842.14

Change 2004–11 31.68 85.3 97.25 122.71 254.85

% change 20.6 45.2 45.3 40.8 43.4

Change 2009–11 -23.96 -3.27 -8.69 -6.78 -69.30

% change -11.4 -1.2 -2.7 -1.6 -7.6

Source: CSO 2013 Table 8

ROI weekly equivalised incomes for people aged 65+ by quintile (€)


APPENDIx 2: INComE DEPRIvAtIoN AmoNG olDER PEoPlE (NI)

Average IDAOP score by number of older people at SOA level

Decile No. of OP % of OP No of worst IDAOP Av IDAOP score

1 52690 24.0 2 0.30

2 41508 19.5 4 0.38

3 37592 18.2 7 0.40

4 34236 18.3 6 0.39

5 31186 18.2 5 0.36

6 28360 16.7 10 0.38

7 25938 16.3 12 0.43

8 23393 14.6 11 0.41

9 20118 13.0 24 0.48

10 13291 8.4 19 0.44

Source: NISRA 2010a

This appendix sets out in more detail the methodology underlying Figure 2.1 which shows the trend line relating to the number and proportion of older people in different areas and the extent to which they are deprived according to IDAOP.

Column 1 of Appendix 2 combines all 890 SOAs in NI into ten groups according to their size. The number of older people in each tenth is given in Column 2 and their share of the total population in Column 3. Column 4 shows how many of the worst 100 SOAs, as measured by IDAOP, are in each tenth, while Columns 5 shows the average IDAOP scores in each tenth.

For example, 52,690 older people live in the 89 SOAs with the highest older populations (the 1st decile) and older people make up 24% of the total populations of these SOAs. Only two of the 100 most income-deprived areas are in these 89 SOAs and their average IDAOP score is 0.30. By contrast the 10th decile, made up of the 89 SOAs with the lowest older populations (totalling 13,291 and making up 8.4% of their overall populations), contained 19 of the most deprived IDAOP areas and their average score on IDAOP was 44.


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