Elsevier

Health & Place

Volume 26, March 2014, Pages 88-93
Health & Place

Are health inequalities between differently deprived areas evident at different ages? A longitudinal study of census records in England and Wales, 1991–2001

https://doi.org/10.1016/j.healthplace.2013.12.010Get rights and content

Abstract

The notion that mortality inequalities between differently deprived areas vary by age is logical since not all causes of death increase in risk with age and not all causes of death are related to the gradient of deprivation. In addition to the cause-age and cause-deprivation relationships, population migration may redistribute the population such that the health-deprivation relationship varies by age.

We calculate cross-sectional all cause mortality and self-reported limiting long-term illness (LLTI) rate ratios of most to least deprived areas to demonstrate inequalities at different ages. We use longitudinal data to investigate whether there are changes in the distribution of cohorts between differently deprived areas over time and whether gradients of LLTI with deprivation also change.

We find similar deprivation inequalities by age for all cause mortality and self-reported health with less inequality for young adults and the elderly but the greatest inequalities during mid life. Over time there are systematic movements of cohorts between differently deprived areas and associated increases and decreases in the gradient of LLTI across deprivation. It seems likely that population migration does influence inequalities by age. Further work should investigate whether the situation exists for other morbidities and, to better inform public health policy, whether restricting summary measures of area health to ages between 30 and 60 when inequalities are greatest will highlight between area differences.

Introduction

The notion that mortality inequalities between differently deprived areas vary by age is logical since not all causes of death increase in risk with age and not all causes of death are related to the gradient of deprivation. Dibben and Popham (2013) investigate these phenomena and provide a compelling argument that in late adolescence, heightened exposure to the risk of land transport accidents increases levels of mortality in the least deprived areas such that inequalities disappear at this age. Using a similar framework, Green (2013) also found an equalisation of mortality differentials in early adulthood but that mortality rates for transport accidents declined during the 2000 s in less deprived areas. He concludes (p. 98) that “social inequality is not consistent across the life course and during adolescence there is a clear decline in the level of inequality” and that “equalisation is only truly evident amongst the very elderly.”

In addition to the interaction between the cause–age and cause–deprivation relationships, it may be that population migration redistributes the population over time such that health-deprivation inequalities vary by age. This proposition is based on: the distinctive profile of age-specific migration rates (Raymer and Rogers, 2008, Rogers et al., 2010); that place characteristics are important determinants of migration (Walters, 2000, Dennett and Stillwell, 2011), and that the factors which potentially ‘push’ or ‘pull’ migrants between different places vary with age and stage in the life course (Boyle et al., 1998, Champion et al., 1998, Champion, 2005). Moreover, since the migration process is health selective (Norman et al., 2005), this can lead to changes in overall health rates (both morbidity and mortality) at the geographic origin from which people have come and at their destination. Over time, healthy people tend to move to less deprived locations and less healthy people to move into, or be non-migrants in more deprived locations (Boyle and Norman, 2009). As a result, Norman et al. (2005) find that rates of mortality and of self-reported limiting long-term illness (LLTI) are lower in less deprived areas and higher in more deprived areas than they would have been if people had stayed in the same locations.

These patterns are noted in other work but there are variations of findings in relation to geographic scale (Brown and Leyland, 2010) and the time frame of studies (Boyle et al., 2002, Curtis et al., 2009, Connolly et al., 2011). Whilst population movements away from more deprived locations tend to exaggerate overall inequalities between areas (Norman et al., 2011), not all studies find this to be the case (Popham et al., 2011). In terms of health differences between areas by age, the evidence is also mixed with Kibele and Janssen (2013) determining that mortality variations between areas are exaggerated by migration whilst other studies (Martikainen et al., 2008, Jongeneel-Grimen et al., 2011a, Jongeneel-Grimen et al., 2011b) find that health selective migration does not enlarge inequalities.

The previous cross-sectional (Dibben and Popham, 2013) and time-series (Green, 2013) analyses are important because they help our understanding of which causes of death have distinctive relationships with age and deprivation. What we add here is the use of morbidity, since self-reported health can have greater area deprivation inequalities than mortality (Norman and Bambra, 2007), and through the use of a longitudinal approach, an understanding of the demographic drivers which lead to differences in population structures (Rees et al., 2013).

Therefore, in this paper we investigate whether inequalities between differently deprived areas vary by age and the role migration might play. First we use cross-sectional data to identify inequalities by age-group for all cause mortality and then see whether a similar situation exists for morbidity inequalities using self-reported limiting long-term illness (LLTI). After this we use longitudinal data to show how population by age is redistributed across differently deprived areas over time and how health inequalities then vary by age. Based on the life course migration literature and on texts more specifically investigating health selective migration, the following scenarios may play out to affect health inequalities by age between differently deprived areas

  • Moves of healthy young adults from less to more deprived areas.

  • Moves of healthy middle aged adults (and their children) from more to less deprived areas.

  • Moves of the elderly will be more of a mixed picture in terms of changes between differently deprived areas and in health status.

Section snippets

Cross-sectional analysis

For England and Wales, we use ward level vital statistics on mortality for persons by five year age groups for 2000–02 as numerators and 2001 mid-year estimates as denominators together with Carstairs scores and population weighted quintiles calculated using 2001 Census data (Norman, 2006). We aggregate the mortality and population data across the deprivation quintiles and calculate five year age-specific mortality rates. We then calculate mortality rate ratios of most to least deprived areas

Investigating cross-sectional inequalities by age

Fig. 1 shows inequalities for 2000–02 measured by five year mortality rate ratios (RRs) of most to least deprived quintiles. For children, the most deprived areas have considerably higher mortality rates than the least deprived areas (RRs 2.56 for age 0–4 and 2.52 for age 5–9). The inequality is lower for those aged 20–24 years (RR 1.14), before increasing during mid-life (largest RR 2.37 for age 55–59 years). From age 55–59 years inequalities are lower with increasing age to parity by age 85+

Discussion

Our cross-sectional analysis of differently deprived wards in England and Wales reveals inequalities by age for all cause mortality. Although our data: have less detailed age information (five year, not single year); are for persons (rather than males and females); have a different time reference (2000–02, not 1997–99); and a different deprivation measure (Carstairs, not Index of Multiple Deprivation), the age profile of inequalities shows close correspondence to Dibben and Popham (2013) (their

Acknowledgements

This research used Census data obtained via the MIMAS CASWEB facility a service supported by ESRC and JISC. The Census, official Mid-Year Estimates and Vital Statistics data for England and Wales have been provided by Office for National Statistics (ONS). These data are Crown copyright and are reproduced with permission of OPSI. The permission of the to use the ONS Longitudinal Study is gratefully acknowledged, as is the help provided by staff of the Centre for Longitudinal Study Information &

References (45)

  • S. Curtis et al.

    Area effects on health variation over the life-course: analysis of the Longitudinal Study sample in England using new data on area of residence in childhood

    Soc. Sci. Med.

    (2004)
  • M. Green

    The equalisation hypothesis and changes in geographical inequalities of age based mortality in England, 2002–2004 to 2008–2010

    Soc. Sci. Med.

    (2013)
  • B. Jongeneel-Grimen et al.

    Migration does not enlarge inequalities in health between rich and poor neighbourhoods in The Netherlands

    Health Place

    (2011)
  • A. Marshall et al.

    Geographies of the impact of retirement on health in the United Kingdom

    Health Place

    (2013)
  • P. Martikainen et al.

    The effects of migration on the relationship between area socioeconomic structure and mortality

    Health Place

    (2008)
  • P. Norman et al.

    Selective migration, health and deprivation: a longitudinal analysis

    Soc. Sci. Med.

    (2005)
  • P. Norman et al.

    Rising premature mortality in the UK's persistently deprived areas: Only a Scottish phenomenon?

    Soc. Sci. Med.

    (2011)
  • F. Popham et al.

    Selective internal migration. Does it explain Glasgow's worsening mortality record?

    Health Place

    (2011)
  • D. Smith

    Patterns and processes of studentification in Leeds

    Reg. Rev.

    (2002)
  • L. Berney et al.

    Lifecourse influences on health in early old age

  • M. Bland

    An introduction to medical statistics

    (2000)
  • D. Blane et al.

    Does social mobility affect the size of the socioeconomic mortality differential? Evidence from the Office for National Statistics Longitudinal Study

    J. R. Stat. Soc. A

    (1999)
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