These data contain lifetables derived from the ONS Longitudinal study dataset, and according to age, sex and individual socio-economic status measured with education, occupation or wage in England and Wales in 2011. Life table according to age, sex and individual’s education, or occupation or wage for the England & Wales population in 2011 The data contained in these files are aggregated data from the ONS Longitudinal Study (ONS LS). The ONS LS is a long-term census-based multi-cohort study. It uses four annual birthdates as random selection criteria, giving a 1% sample of the England and Wales population (10.1093/ije/dyy243). The initial sample was drawn from the 1971 Census, and study members’ census records have been linked every 10 years up to the 2011 Census. New members enter the study through birth or immigration, and existing members leave through death or emigration. Vital life events information (births, deaths and cancer registrations) are also linked to sample members’ records. File lifetab_2011_educ.csv Life table according to age, sex and education level for the England & Wales population in 2011 age x: attained age (years) from 20 to 100 sex: 2 categories: male (m) and female (f) educ: 6 categories of highest educational attainment: A: no qualifications; B: 1-4 GCSEs/O levels; C: 5+ GCSEs/O levels, D: Apprenticeships/Vocational qualifications, E: A/AS levels, F: Degree/Higher Degree mx: mortality rate for 1 person-year qx: annual probability of death ( = 1 - exp(-mx) ) ex: life-expectancy (years) File lifetab_2011_inc.csv Life table from age 20 onwards and according to age, sex and income level for the England & Wales population in 2011 age x: attained age (years) from 20 to 100 sex: 2 categories: male (m); female (f) inc: 5 categories of income: Least deprived; 4; 3; 2; Most deprived mx: mortality rate for 1 person-year qx: annual probability of death ( = 1 - exp(-mx) ) ex: life-expectancy (years) File lifetab_2011_occ.csv Life table from age 20 onwards and according to age, sex and occupation for the England & Wales population in 2011 age x: attained age (years) from 20 to 100 sex: 2 categories: male (m); female (f) occ: 3 categories of occupation: C: Technical/Routine; B: Intermediate; A: Managerial/Administrative/Professional mx: mortality rate for 1 person-year qx: annual probability of death ( = 1 - exp(-mx) ) ex: life-expectancy (years) File lifetab_2011_overall.csv Life table from age 20 onwards and according to age and sex for the England & Wales population in 2011 age x: attained age (years) from 20 to 100 sex: 2 categories: male (m); female (f) mx: mortality rate for 1 person-year qx: annual probability of death ( = 1 - exp(-mx) ) ex: life-expectancy (years) More details can be found in the following paper: Ingleby F, Woods L, Atherton I, Baker M, Elliss-Brookes L, Belot A. (2021). Describing socio-economic variation in life expectancy according to an individual's education, occupation and wage in England and Wales: An analysis of the ONS Longitudinal Study. SSM - Population Health, doi: 10.1016/j.ssmph.2021.100815In the UK, people who reside within more income-deprived areas live a shorter period of time after a diagnosis of cancer compared to people living in less income-deprived areas. At least part of these inequalities in cancer survival are due to inequalities in cancer care, even considering differential patient and tumour factors such as stage at diagnosis. The specific mechanisms by which area-based deprivation levels lead to poorer individual health outcomes within the context of a universal healthcare system, free at the point of use, are not well understood. These analyses will enable, for the first time, the examination of how an individual patient's socio-economic status is associated with poorer cancer survival in England, and will demonstrate how these associations might be modified by the level of deprivation in the small area within which the patient resides. Our aim is to perform an in-depth study of the association between the individual patient's deprivation and cancer survival, considering in particular how this is influenced by their socio-economic context, whether it varies over time since diagnosis and whether it has changed over calendar time. We will focus on three indicators of deprivation: income, education and occupation. We will first examine the correlation between individual and area deprivation, by each of these indicators, and then secondly describe the association between individual deprivation and survival. Third, we will assess whether the association between individual deprivation and patients' survival is modified by area deprivation; that is, whether equally deprived individuals in different areas fare better, or worse, according to the socio-economic context of the area within which they live. Finally we will gain the insights of patients, carers, and healthcare professionals on these data, and communicate these to cancer policy makers. We will use data from the ONS Longitudinal Study, which contains individual deprivation information on 1% of individuals in England present at each national census since 1971. The ONS-LS is linked to Cancer Registry data so that information on all diagnoses of invasive cancer amongst cohort members can be examined. These data will be further linked to the Indices of Multiple Deprivation (IMD) defined at the Lower Super Output Area (LSOA, mean population 1,500) to obtain area-based measures of deprivation. We will fit regression models for the excess mortality hazard (EMH) in order to examine how cancer survival varies with individual deprivation status. The EMH represents the mortality hazard that is observed among cancer patients, taking into account each patient's expected mortality. We will construct life tables stratified by individual deprivation, using the ONS-LS mortality and population data, in order to account as accurately as possible for this background mortality. We will assess whether these associations are modified according to the ecological level of deprivation through the use of interaction terms. We will examine time-dependent associations between individual deprivation and the EMH using flexible functions, and will account for the correlation between observations coming from the same small area through a shared random-effect (defined at LSOA level). The results will allow us to determine the degree of correspondence between individual and area deprivation for cancer patients; to assess how individual deprivation (income, education or occupation) is associated with cancer-specific mortality; and to quantify if and how these associations are modified according to area deprivation, as well as how these associations vary by the time since diagnosis. During the final phases of the project we will seek the insights of patients, carers and healthcare professionals upon our findings. These will then be directly shared with policy makers in a half-day workshop, so that future policies aimed at reducing socio-economic inequalities are more targeted.

We examined the Office of National Statistics Longitudinal Study (LS) (Shelton et al., 2019; Hattersley & Creeser, 1995), a long-term cohort study comprised of people living in England and Wales under selection criteria of one of four annual birthdates (representing a random sample of approximately 1% of the population clustered by date of birth). All census variables from the 1971 census through to the most recent 2011 census are directly linked to cohort members via unique identifiers, and additional variables are also derived via individual linkage, including administrative data such as births and deaths. We included LS members enumerated at the 2011 census (the most recent census to have taken place) and linked to mortality data to include deaths in the 12-month period subsequent to the census (i.e.01-Apr-2011 to 31-Mar-2012). Age, sex, and data relating to occupation and educational qualifications for 2001 and 2011 censuses were extracted and used to categorise LS members according to three dimensions of individual-level socio-economic circumstances: occupation, education, and wage.