The few UK studies examining variations in screening uptake and coverage have had significant methodological limitations either because they used ecological measures of socio-economic status [5,6] or have been based on surveys [7,8]. For example, in the largest UK study published to date, Moser et al [9] examined reported use of breast and cervical screening in 3,185 women interviewed as part of the National Statistics Omnibus Surveys (2005-07). They found that car availability and housing tenure were associated with uptake of breast screening but not with cervical screening (though the effect sizes were suggestive). However, with response rates of 64-69%, there are concerns surrounding representativeness. In addition, the reliance on self-reported information introduces the possibility of recall bias and reporting error, and even after combining nine surveys the relatively small study size limited the extent of the analyses so that the recognized lower screening uptake in larger conurbations such as London [10,11] could not be confirmed. Similar difficulties are apparent with research relating to screening for colorectal cancer; in some studies just over half of those eligible for screening responded [12], and others have had to use ecological proxies for either deprivation [13] or ethnicity [14].

The deficiencies in the current methods for assessing and monitoring screening programmes and the need for further high quality information to inform the screening programmes has been highlighted by the UK National Screening Programmes Information Strategy [15] which concluded … “Assessing equity is a particular concern as analyses by variables currently available fall short of the ideal”, or as Weller and Campbell [16] have stated “…effective and efficient cancer screening programmes based on sound evidence are needed.”

The Northern Ireland Longitudinal Study (NILS) is a representative sample of approximately 28% of the population (nearly 500,000 people) formed from the linkage of the Health Card registration system and the 2001 Census returns [18]. NILS is maintained by the Northern Ireland Statistics and Research Agency (NISRA). It is modeled on the Office for National Statistics Longitudinal Study (ONS-LS) [19] and is similar to the Scottish Longitudinal Study [20]. The core NILS database includes cohort members’ Census records and contextual information relating to household composition and the characteristics of the area of residence. It also contains the Health and Care Number that enables unique linkage to other health service databases including the National Breast Screening System. The screening data and NILS were linked using the encrypted Health and Care number as the matching field, a process carried out jointly by the respective data custodians within the secure setting in NISRA, after which the matching field, and other identifiers, were removed. The dataset was then anonymised before being supplied to the researchers, and was held in a secure setting by the Registrar General. At no time were patient identifiable data available. The approval for the record linkage by the data custodians in the respective organisations was facilitated by the obvious policy relevance of the study and underpinned by detailed data transfer agreements. The study was approved by the Office for Research Ethics Committee (ORECNI), the local ethics committee in Northern Ireland (ref: 07/NIR01/90).

All characteristics of women in the cohort were as recorded on the Census form and selected as factors shown from other studies to be associated with screening uptake. Age was included as 5-year bands (≤49, 50-54, 55-59, 60-64); marital status was categorised as married/co-habiting, never married, and a final group combining the widowed, separated or divorced (as analyses showed similar levels of uptake in these women). Household composition (dichotomised as single person household or not) was also included. Four census-based indicators of socio-economic status were included: the National Statistics Socio-Economic Classification (six bands see Table ​Table1)1) [21]; highest educational attainment (ranked as: university level, ‘A-level’, ‘O-level’ or their equivalents, and no qualifications); household car availability (two or more cars, one car, no car access) and housing tenure (owner occupier, private renter and social renter). Two census-based measures of self reported morbidity were also included; one on the presence of limiting long term illness (with a yes/no response) and another on general health in the year preceding the Census which offered three responses – good, fairly good and not good. An indicator of the urban/rural character of the area in which the respondent lived was included, divided into three bands; urban (population size greater than 75,000), intermediate (population size between 2250 and 75,000) and rural (population size less than 2250) [22].

Multivariate logistic regression using STATA version 10 was used to explore the relationship between uptake of breast screening and the socio-demographic and socio-economic variables (Table2). The odds ratios (and 95% confidence intervals) for each of the regression models are presented in this paper.

The factors associated with lower uptake for all women invited for screening also applied to first-time invitees. Consequently, only the former are described in detail. Table ​Table11 shows that uptake rates were highest in the 50-59 year olds and about 8% lower for women aged either less than 50 or aged 60 and over. Married women constituted approximately 70% of this age group and these women had higher uptake rates than either those who were never married (OR=0.74; 95% CI=0.67, 0.81) or those who were widowed, separated or divorced (OR=0.84; 95% CI=0.79, 0.90).

Uptake of screening was strongly linked to both car availability and housing tenure in the fully adjusted model, but not to educational attainment or occupational social class (NSSEC). Compared to owner occupiers, social renters (who comprised 15.3% of the cohort) were about one third less likely to have attended for screening (OR=0.67; 95% CI=0.63, 0.73) with little difference between social and private renters. Compared to women with household access to more than two cars: those with access to one car only (41.7% of the cohort) were less likely to attend screening (OR=0.89; 95% CI=0.84, 0.95); while those with no car access (14.8% of the cohort) were least likely to attend (OR=0.63; 95% CI=0.58, 0.69). There was no significant interaction between car access and urban/rural residence (chi-square=2.67, p=0.615) indicating that the association between screening attendance and car access was similar in urban and rural areas. There was no association between educational attainment and invitation for screening - in the fully adjusted model women with no formal qualifications (62% of the cohort) were as likely as those with a degree (12% of cohort) to have attended. No gradients in uptake were apparent across social class, though those classified as ‘Other’ (comprising 6% of the cohort -including those classified as having ‘never worked’ and the long-term unemployed) were less likely than those in the professional & managerial occupations to have attended for screening (OR=0.74; 95% CI=0.66, 0.82).

The record linkage methodology enabled the records of almost 40,000 of those invited for screening to be analysed at an individual level, exceeding the largest published survey by a factor of ten. The findings both confirm and add to what was previously known about the social and socio-economic factors influencing screening attendance. The lower uptake at older ages persists after adjustment for other factors such as health status and is worrying given the increased incidence of cancer amongst older people. Uptake in the 65-69 year range was not measured as the extension of breast screening to older ages had not yet been introduced in Northern Ireland. The higher breast screening uptake amongst women who are currently married has been found in other countries [25], but to our knowledge this is the first study to report it in the UK.

While the study reaffirms the relationship between attendance for breast screening and socio-economic status, it also suggests that this is not due to potential confounders such as health status. Not all indicators of disadvantage were important: uptake was related to car availability and housing tenure but not to educational attainment or occupational social class (with the exception of those who never worked and the long-term unemployed). Interpretation of indicators of disadvantage is difficult and explanations other than those related to deprivation are possible [26]: while the association with car availability might suggest difficulties with accessing screening facilities, the availability of both individual and area factors enabled us to show that as there is a similar relationship between screening uptake and car ownership in both rural and urban areas (the latter with good public transport networks), that socio-economic factors, rather than the simpler issue of transport, may be more important. Similarly, housing tenure represents more than wealth and encompasses aspects of the physical and social environment of residence that can shape lifestyle choices and health behaviours [27]. The absence of any relationship between screening uptake and educational attainment confirms findings of other UK-based studies [9,23]. This might imply either that prior attainment (maybe thirty years previously) is not closely related to current socio-economic status, or that the socio-economic gradients are related to health beliefs and attitudes rather than a lack of knowledge.

The health of the women at baseline was also important in determining attendance at screening though, surprisingly, the relationship was with general health rather than limiting long-term illness (LLTI). Why this is so is unknown, though it is possible that the more general self-rated health measure can more easily capture a contribution to future ill-health if the perception of poorer health leads to less engagement with preventative practices (such as attendance at screening) [28].