The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) is a general population cohort study of men and women aged 40–79 years living in Norfolk recruited from general practices between 1993–1997. The response rate for recruitment was approximately 40%. The cohort has similar characteristics to national population surveys except for a lower prevalence of current smokers [25]. The study has ethics committee approval and all participants gave informed signed consent for study participation including access to medical records. The cohort is flagged for mortality and hospital admissions from linkage to national databases held by NHS Digital and hence there is virtually no loss to follow-up.
At recruitment, participants completed a lifestyle questionnaire where they were asked about their occupational and leisure physical activity. Occupational activity was assessed using a four category question (“sedentary”, “standing”, “moderate physical work” and “heavy manual work”) with examples such as office worker, shop assistant, plumber and construction worker respectively. Leisure activity in both summer and winter was assessed from the number of hours per week spent cycling, attending keep fit classes or aerobics and swimming or jogging. Estimated average hours of leisure activity was calculated as the mean of summer and winter activities and categorised using 0, (0,3.5], (3.5,7] and >7. A combined score, divided into four ordered categories with individuals labelled as “inactive”, “moderately inactive”, “moderately active” and “active” was created combining leisure and occupational elements. Those who did not complete the activity question were placed in the inactive category. The score was validated against energy expenditure measured by free-living heart rate monitoring with individual calibration [26]. It has been reported to predict all-cause mortality and cardiovascular disease incidence [27].
Participants attending the baseline health examination had their height to the nearest 0.1 kg measured using a stadiometer (Chasemores, UK) and their weight to the nearest 100g measured in light clothing without shoes (Salter, West Bromwich, UK). Body mass index (BMI) was calculated using measured weight in kilograms divided by the square of measured height in square metres. Two yes/no questions were used to derive smoking status: “Have you ever smoked as much as one cigarette a day for as long as a year?” and, where a positive response was given, “Do you smoke cigarettes now?” Participants also completed questions about their employment and that of their partner with details of both current and past employment recorded. Occupational social class was defined according to the Registrar General’s classification [28, 29]. A list of common UK qualifications was used to establish educational attainment and participants were asked to mark all relevant qualifications. These were then categorised using the highest qualification attained. Participants were asked at baseline “Has the doctor ever told you that you have any of the following?” followed by a list of common conditions including “Heart attack (myocardial infarction)”, “Stroke” and “Cancer”.
Surviving participants were invited to complete a lifestyle questionnaire and attend a health examination (second time-point, “TP2”) between 2006 and 2011 [30] . Questions on physical activity and cigarette smoking, similar to those at baseline, were included in a postal questionnaire, completed by a subset of 9827 of the original cohort. Weight and height were measured on 8094 by clinic staff and body mass index calculated in the same way as at baseline described previously.
Ascertainment of hospital usage through record linkage
The National Health Service (NHS) in Britain treats residents without charge at the point of service so covers virtually all major health service usage. The EPIC-Norfolk cohort was regularly linked to hospital records from 1999 onwards as previously reported [20]. Briefly, NHS numbers were used to perform linkage to hospital databases between 1999 and 2019. Initially, up to 2009, linkage was made via the East Norfolk Primary Health Care Trust while later, national databases held by NHS Digital were used [31]. All hospital activity for EPIC-Norfolk participants was captured wherever they were treated in England and Wales. Hospital episode statistics (HES) records which included admission and discharge dates were used to calculate time in hospital and numbers of admissions. Contiguous admissions were merged and counted as a single admission.
Statistical analysis
For the main analysis, 625 men and women who died before 1999 were excluded. Dichotomous variables were created for the socioeconomic status variables. Professional, managerial and technical and non-manual skilled occupations (codes I, II and IIIa respectively) were classed as non-manual while manual skilled, partly skilled and unskilled (codes IIIb, IV and V respectively) were classed as manual. Educational attainment was categorised into “Higher education level” (which includes those with qualifications at secondary level or above) and “Lower education level” (those with no qualification). The numbers of individuals with missing values for covariables were: 53 BMI, 218 smoking status, 545 social class, 18 education level. Validation of the physical activity measures [26] suggested that participants with missing data be classified inactive.
Logistic regression was used to model hospitalisation outcomes on physical activity category, adjusting for covariables. Several dichotomous outcome categories were calculated based on total admissions and length of stay spanning two periods: 1999–2009 (10-year follow-up) and 1999–2019 (20-year follow-up). Total admissions from 10-year follow-up were used to define “any hospital admissions” and “7 or more admissions” while length of stay from 10-year follow-up was used to create “greater than 20 hospital days”. These thresholds were chosen to represent those with higher levels of hospital usage and were consistent with previous work [20]. Dichotomous outcome categories based on 20-year follow-up and having approximately the same proportion of the population as their 10-year follow-up counterparts include “12 or more admissions” and “greater than 50 hospital days” while “7 or more admissions” and “greater than 20 hospital days” were also calculated for this period to serve as a comparison. Hospital days are defined as the sum of total bed days (overnight stays) and day-cases. Linear regression was used to calculate the absolute difference in adjusted mean bed days between inactive participants and participants reporting any activity.
To address change in physical activity, we also used physical activity measured at TP2 approximately 12 years later as a second baseline. We excluded 105 participants who died prior to 2009, leaving 9722. Multiple imputation was used to address missing values, in particular for body mass index at TP2 where data for 1733 were not available for participants who completed a TP2 questionnaire but did not attend a health examination. Predictive mean matching with 5 multiple imputations and 50 iterations was used with baseline variables BMI, occupational social class and education attainment and TP2 current smoking. Changed-activity categories use combinations of physical activity categories at the baseline and TP2. The category shown as “Inactive/Inactive” is the set of participants who reported being inactive at baseline and remained inactive when asked again at TP2. The group who initially reported any activity but became inactive later is shown as “Any-activity/Inactive” while the other two categories “Inactive/Any-activity” and “Any-activity/Any-activity” were similarly defined.
The cost to the NHS of one bed-day is £496, calculated using the Reference Costs for English Hospitals 2017/18 for elective (5.4 £bn) and non-elective (18 £bn) admissions [32] and the total available beds (approximately 129200) [33]. The cost per hospital day (overnight stays and day-cases) is £587 when the cost of day-case activity is included (4.4 £bn per year). The reported OECD UK per capita expenditure on health in 2017, was £3375 (exchange rate at the time of writing) [34]. Per-person costs were calculated by multiplying the cost per hospital day and hospital days per person. Percentage of NHS per-capita health expenditure was calculated as the ratio of per-person cost and OECD UK per-capita expenditure.
Adjusted mean hospital days by physical activity category were determined first by calculating hospital days for each one year period restricted to participants surviving to the given year. Linear regression of hospital days on physical activity adjusted for age, sex, occupational social class, educational attainment, current smoking and body mass index was then used. Adjusted means by category were obtained using estimated marginal means. The overall mean difference of days was calculated by taking the mean of the annual differences over for each of two periods (1999–2009 and 2009–2019).
Sensitivity analyses were conducted in which the physical activity exposure was dichotomised into inactive and any-activity groups, using the outcome more than 20 hospital days over the period 1999–2019. Multivariable adjusted odds ratios were examined stratified by sex, age <65 and ≥65 years, manual and non-manual social class, lower (no qualifications) and higher level of education, former or never smoking and current smoking, BMI ≤30, >30 kg/m², chromic disease (heart attack, stroke or cancer) and no reported chronic disease, survival to the end of follow-up (March 2019) and died during follow-up period. A further multivariable model was performed using the narrower follow-up period of 2004–2019, a minimum of five years after participants reported their level of physical activity excluding participants who died prior to 2004.
All analyses were performed using the R statistical language (R Foundation for Statistical Computing, Vienna, Austria version 3.6.0 with packages ggeffects, knitr, Gmisc, tidyverse, intubate, mice)