Socio‐economic inequalities in bodily pain over the life cycle: longitudinal evidence from Australia, Britain and Germany

type="main" xml:id="rssa12058-abs-0001"> We document the extent of socio-economic status (SES) inequalities in bodily pain in Australia, Britain and Germany, with a particular focus on whether such inequalities widen over the life course. Random-effects logistic and kernel regressions are used to estimate odds ratios of experiencing severe pain by income, educational qualification and occupational status, and to graph age–pain profiles, while accounting for individual heterogeneity. Cohort level regression analysis is used to control for cohort effects. Low SES is consistently related to higher levels of bodily pain in each country and inequalities widen with increasing age. The odds of experiencing severe bodily pain for individuals in the lowest, relative to the highest, household income quartile is up to two times higher, whereas the odds for those with minimum relative to university education are up to three times higher. For each country, the odds of experiencing severe pain by machine operators are around three times higher than for professionals. Maximum levels, and maximum SES differences in pain, are both reached at around age 60 years, with the differentials ranging between 0.2 and 0.7 of sample standard deviations. No convergence of pain profiles is observed by age 70 years. Controlling for cohort effects in the Australian data confirms the results from the age group analysis. Taken together these results suggest that low SES and manual work have cumulative health effects over the life cycle.

[1]  P. Langley,et al.  The impact of pain on labor force participation, absenteeism and presenteeism in the European Union , 2010, Journal of medical economics.

[2]  Nicole Watson,et al.  The Household, Income and Labour Dynamics in Australia (Hilda) Survey: Wave 1 , 2002 .

[3]  P. Langley,et al.  The prevalence, correlates and treatment of pain in the European Union , 2011, Current medical research and opinion.

[4]  G. Ejlertsson,et al.  Chronic pain in a geographically defined general population: studies of differences in age, gender, social class, and pain localization. , 1993, The Clinical journal of pain.

[5]  P. McGrath,et al.  The epidemiology of chronic pain in children and adolescents revisited: A systematic review , 2011, PAIN.

[6]  C. Phillips,et al.  The economics associated with persistent pain , 2011, Current opinion in supportive and palliative care.

[7]  U. Gerdtham,et al.  Does income-related health inequality change as the population ages? Evidence from Swedish panel data. , 2010, Health economics.

[8]  E. van Doorslaer,et al.  Differential health reporting by education level and its impact on the measurement of health inequalities among older Europeans. , 2008, International journal of epidemiology.

[9]  G. Pflug.  Kernel Smoothing. Monographs on Statistics and Applied Probability - M. P. Wand; M. C. Jones. , 1996 .

[10]  M J Shipley,et al.  Do socioeconomic differences in mortality persist after retirement? 25 Year follow up of civil servants from the first Whitehall study , 1996, BMJ.

[11]  J. Mackenbach,et al.  The size of mortality differences associated with educational level in nine industrialized countries. , 1994, American journal of public health.

[12]  Gert G. Wagner,et al.  The German Socio-Economic Panel Study (SOEP) - Evolution, Scope and Enhancements , 2007 .

[13]  Lorie A. Kloda,et al.  A systematic literature review of 10years of research on sex/gender and experimental pain perception – Part 1: Are there really differences between women and men? , 2012, PAIN.

[14]  A. Stone,et al.  Assessment of pain: a community-based diary survey in the USA , 2008, The Lancet.

[15]  V. Shavers.  Measurement of socioeconomic status in health disparities research. , 2007, Journal of the National Medical Association.

[16]  Mark Wooden,et al.  The Cross-National Equivalent File (CNEF) and its Member Country Household Panel Studies , 2007, Journal of Contextual Economics – Schmollers Jahrbuch.

[17]  S. Preston,et al.  Educational differentials in mortality: United States, 1979-85. , 1996, Social science & medicine.

[18]  Richard Percival,et al.  The impact of back problems on retirement wealth , 2012, PAIN.

[19]  B. Thorn,et al.  The relationship of demographic and psychosocial variables to pain-related outcomes in a rural chronic pain population , 2010, PAIN®.

[20]  Aldi J. M. Hagenaars,et al.  Poverty Statistics in the Late 1980s: Research Based on Micro-data , 1994 .

[21]  I. Kåreholt,et al.  Prevalence of musculoskeletal pain in the general Swedish population from 1968 to 2002: Age, period, and cohort patterns , 2010, PAIN.

[22]  E. Bruera,et al.  Critical issues on opioids in chronic non-cancer pain: An epidemiological study , 2006, Pain.

[23]  David R. Williams,et al.  Measuring social class in US public health research: concepts, methodologies, and guidelines. , 1997, Annual review of public health.

[24]  R. Lipton,et al.  Lost productive time and cost due to common pain conditions in the US workforce. , 2003, JAMA.

[25]  Kim M. Shuey,et al.  Cumulative Advantage Processes as Mechanisms of Inequality in Life Course Health1 , 2007, American Journal of Sociology.

[26]  T. Lallukka,et al.  Pain and disability retirement: A prospective cohort study , 2012, PAIN.

[27]  A. Deaton,et al.  Aging and Inequality in Income and Health , 1998 .

[28]  M. Johannesson,et al.  Increasing socio-economic inequalities in life expectancy and QALYs in Sweden 1980-1997. , 2005, Health economics.

[29]  M. Beckett.  Converging health inequalities in later life--an artifact of mortality selection. , 2000, Journal of health and social behavior.

[30]  A. Gray,et al.  The economic burden of back pain in the UK , 1999, Pain.

[31]  D. Collett,et al.  Modelling Binary Data. , 1994 .

[32]  Katherine Newman,et al.  Socioeconomic disparities in health: pathways and policies. , 2002, Health affairs.

[33]  A. Kapteyn,et al.  Dynamics of Work Disability and Pain , 2006, Journal of health economics.

[34]  Jinyoun Kim,et al.  Socioeconomic status and age trajectories of health. , 2007, Social science & medicine.

[35]  E. van Doorslaer,et al.  Health and income across the life cycle and generations in Europe. , 2009, Journal of health economics.

[36]  James P. Smith.  The Impact of SES on Health over the Life-Course , 2005 .

[37]  P. Leino-Arjas,et al.  Socio-economic differences in the prevalence of acute, chronic and disabling chronic pain among ageing employees , 2005, Pain.

[38]  David A. Williams,et al.  Assessor status influences pain recall. , 2007, The journal of pain : official journal of the American Pain Society.

[39]  B. Collett,et al.  Survey of chronic pain in Europe: Prevalence, impact on daily life, and treatment , 2006, European journal of pain.

[40]  Joseph E. Schwartz,et al.  Variability of Momentary Pain Predicts Recall of Weekly Pain: A Consequence of the Peak (or Salience) Memory Heuristic , 2005, Personality & social psychology bulletin.

[41]  P. Herd.  Do Functional Health Inequalities Decrease in Old Age? , 2006 .

[42]  R. Kington,et al.  Demographic and economic correlates of health in old age , 1997, Demography.

[43]  F. Blyth,et al.  Unpacking the burden: Understanding the relationships between chronic pain and comorbidity in the general population , 2012, PAIN.

[44]  Antony Fielding,et al.  An introduction to anchoring vignettes , 2011 .

[45]  C. Ross,et al.  Education, age, and the cumulative advantage in health. , 1996, Journal of health and social behavior.

[46]  Russell V. Lenth,et al.  Regression Models for Categorical Dependent Variables Using Stata (rev.) , 2005 .

[47]  A. Unruh.  Gender variations in clinical pain experience , 1996, Pain.

[48]  J. Ware.  SF-36 health survey: Manual and interpretation guide , 2003 .

[49]  A. Agresti.  Categorical data analysis , 1993 .

[50]  Matthew P. Wand,et al.  Kernel Smoothing , 1995 .

[51]  John E. Ware,et al.  SF-36 Health Survey. , 1990 .

[52]  P. Martikainen,et al.  Occupational class inequalities across key domains of health: results from the Helsinki Health Study. , 2005, European journal of public health.

[53]  O. Ekholm,et al.  Epidemiology of chronic non-malignant pain in Denmark , 2003, Pain.

[54]  T. V. Ourti,et al.  Socio-economic inequality in ill-health amongst the elderly: Should one use current or permanent income? , 2003 .

[55]  James P. Smith.  Unraveling the SES health connection , 2004 .

[56]  J. S. Long,et al.  Regression models for categorical dependent variables using Stata, 2nd Edition , 2005 .

[57]  Income-related inequality in life-years and quality-adjusted life-years. , 2000, Journal of health economics.

[58]  P. Langley,et al.  The societal impact of pain in the European Union: health-related quality of life and healthcare resource utilization , 2010, Journal of medical economics.

[59]  Amanda Sacker,et al.  Social inequalities in self reported health in early old age: follow-up of prospective cohort study , 2007, BMJ : British Medical Journal.

[60]  K. Jordan,et al.  Trajectories of pain in adolescents: A prospective cohort study , 2011, PAIN®.

[61]  R. Fillingim,et al.  Sex differences in the perception of noxious experimental stimuli: a meta-analysis , 1998, Pain.

[62]  O. Ekholm,et al.  Epidemiology of chronic pain in Denmark: An update , 2009, European journal of pain.

[63]  James P. Smith.  The Impact of Socioeconomic Status on Health over the Life-Course , 2007, The Journal of Human Resources.

[64]  Scott M. Lynch,et al.  Cohort and life-course patterns in the relationship between education and health: A hierarchical approach , 2003, Demography.

[65]  A. Case,et al.  Broken Down by Work and Sex: How Our Health Declines , 2003 .

[66]  P. Croft,et al.  Patterns of pain and mobility limitation in older people: cross-sectional findings from a population survey of 18,497 adults aged 50 years and over , 2008, Quality of Life Research.

[67]  K. Wilson,et al.  Self-perceived burden in chronic pain: Relevance, prevalence, and predictors , 2012, PAIN®.

[68]  S. Chatterji,et al.  Does Reporting Heterogeneity Bias the Measurement of Health Disparities? , 2006, Health economics.

[69]  Andrew M. Jones,et al.  Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models , 2006 .