The association between non-occupational TV and computer screen-time viewing and cancer risk: Findings from the UK Biobank, a large prospective cohort study


 Background Evidence is suggestive of sedentary behaviour being associated with an increased risk of endometrial cancer, but the evidence base is too limited to draw any conclusions for other cancers. The aim of the study was to investigate the association between sedentary behaviour and total cancer incidence and site-specific cancer incidence.Methods This prospective population-based cohort study involved data from the UK Biobank (470 578 adults; 53.8% females; mean age 56.3 years). Sedentary behaviours including television viewing time, computer use time and daily total screen time were the exposure variables. Primary and secondary outcome measures included incident total cancer, and site-specific cancers identified from the International Classification of Diseases, 9th and 10th revisions (ICD-9 and ICD-10). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) showing the relationship between sedentary behaviour and cancer using continuous (hours/day) and categorical exposure variables. Partition models and isotemporal substitution models were used to investigate the impact of substituting sedentary behaviour with physical activity.Results During a mean follow-up time of 7.6 years, 28 992 incident cancers were identified. A 1-hour increase in daily TV screen time was associated with higher risk of oropharyngeal cancer (HR 1.06, 95% CI: 1.02, 1.11), stomach cancer (HR 1.06, 95% CI: 1.001, 1.13), oesophagus and stomach cancer (HR 1.04, 95% CI: 1.005, 1.09), and colon cancer (HR 1.04, 95% CI: 1.01, 1.06) in fully adjusted models. Participants who reported ≤1 hour/day of TV screen time had a lower risk of lung cancer (HR 0.85, 95% CI: 0.73, 0.997), breast (female only) cancer (HR 0.92, 95% CI: 0.85, 0.996), stomach cancer (HR 0.66, 95% CI: 0.45, 0.97), and oesophagus and stomach cancer (HR 0.78, 95% CI: 0.62, 0.98) compared to participants who reported 1-≤3 hours/day of TV screen time. Isotemporal substitution models showed reduced risk of total cancer (HR 0.97, 95% CI: 0.95, 0.99) and some site-specific cancers when replacing 1-hour/day of TV viewing with moderate-intensity physical activity or walking.Conclusions Our findings show that sedentary behaviours were associated with some site-specific cancers (including oropharyngeal, oesophagus and stomach, colon and lung cancer), particularly for TV viewing time. Our findings were less consistent for time spent on computer and daily total screen time. Substitution models showed that replacing 1-hour per day of TV viewing with 1-hour of moderate-intensity physical activity or walking was associated with lower risk of total cancer and lower risk of several site-specific cancers. Health promotion strategies should endorse the message to minimise sedentary behaviour, replacing it with health-enhancing physical activity, and to particularly target TV viewing.


INTRODUCTION
Research in sedentary behaviours has grown rapidly over recent years (1). Such behaviours are seen as distinct from physical inactivity or sleep, and have been defined as "any waking behaviour characterised by an energy expenditure ≤ 1. Evidence demonstrates that prolonged sedentary time is associated with increased risk of non-communicable diseases (NCDs). Mechanistically, sedentary behaviour is thought to impact particularly on cardio-metabolic diseases through adverse effects on lipid and glucose metabolism (7,8). Recent evidence from a meta-analysis has demonstrated a significant direct association between 6-8 hours daily sedentary time and increased all-cause mortality, cardiovascular disease mortality and Type 2 Diabetes Mellitus risk (9). Prolonged sedentary behaviour is therefore a significant burden on our healthcare systems. In 2016-2017, for example, it was estimated to cost the UK National Health Service £0.8 billion (10). 5 However, much less is known about sedentary behaviour and cancer, and known biological mechanisms are less well understood (11). The World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) global report in 2018 stated that evidence on sedentary behaviours is limited but is suggestive as being associated with an increased risk of endometrial cancer (pooled risk estimate from three studies comparing the highest versus lowest levels of sitting time was 1.46, 95% CI: 1.21, 1.76, cases = 1579) (11)(12)(13)(14). The evidence base was deemed too limited to draw any conclusions for other cancers (11) More recent evidence from analyses of the large, prospective UK Biobank cohort shows mixed evidence for an association between sedentary behaviour and cancer outcomes (15). Celis-Morales et al (2018) found significant associations of discretionary screen-time (time spent in TV viewing or computer screen use during leisure time) exposure and all-cause mortality (hazard ratio [HR] 1.06, 95% CI: 1.05, 1.07), and cancer incidence (HR 1.04, 95% CI: 1.03, 1.04). This study also found that these results were substantially attenuated by physical activity, cardiorespiratory fitness and grip strength (15). Our research group have previously found no association between non-occupational screen-based sedentary behaviour levels and oesophago-gastric cancer risk within the UK Biobank cohort (16). In contrast, higher levels of TV viewing time were associated with a greater risk of colon cancer in the same study population (HR for ≥ 5 hours per day vs ≤ 1 hour per day = 1.32, 95% CI: 1.04, 1.68) (17), although time spent using computers (excluding using a computer at work) was not associated with colorectal cancer risk 6 in the UK Biobank cohort (17). The findings of a 2017 meta-analysis including six studies also demonstrated significant associations between the highest compared with the lowest levels of occupational sedentary behaviour, and risk of colon cancer (pooled RRs 1.44, 95% CI: 1.28, 1.62) (18). On the other hand, there was little evidence of an association between sedentary behaviour and rectal cancer risk (18).
Many of the previous studies investigating the association between sedentary behaviour and health outcomes have attempted to adjust for physical activity levels in their analysis. A recent US Government report has highlighted limited evidence on the role of physical activity in displacing the mortality risks associated with sedentary behaviour (6). An improved understanding of these interactive effects would enable more specific recommendations to be made regarding quantifying prolonged sedentary time. Analytical techniques such as partition models and isotemporal substitution models (19) could help to model such predictions, but have yet to be extensively applied in large cohort analyses.
Therefore, this study aimed to investigate sedentary behaviour (including TV viewing, computer use and total screen-use) in relation to total cancer risk and risk of site-specific cancers (including endometrial, colorectal, pre-and post-menopausal breast, prostate, lung, and other cancers) in the large UK Biobank cohort study. The study investigated whether associations varied by gender, age, socio-economic status, smoking and excess body weight. Finally, partition and isotemporal substitution models were used to investigate the impact of substituting sedentary behaviour with physical activity.

Study design 7
Between 2006 and 2010, UK Biobank recruited a cohort of 502 619 adults (5.5% response rate) aged 40-69 years from the general population (20,21). Approximately 9.2 million invitations were mailed to potential participants who were registered with the National Health Service (NHS) and living within a 25-mile radius of one of the 22 assessment centres across England, Scotland and Wales. Screen time assessment Relevant screen-time exposure variables were assessed by self-reported time spent watching TV, time spent using the computer outside of work, which were used to derive total screen time. Self-reported TV screen time was assessed for all participants by asking the following question: "In a typical DAY, how many hours do you spend watching TV? (Put 0 if you do not spend any time doing it)?". Selfreported computer screen time was assessed for all participants by asking the following question: "In a typical DAY, how many hours do you spend using the computer? (Do not include using a computer at work; put 0 if you do not spend any time doing it)." Durations of < 0 hours were set to missing, as were responses of "Do not know" or "Prefer not to answer". If the respondent replied "Less than an 8 hour a day", this was recoded to 0.5 hours. Total screen time was then computed as the sum of hours spent watching TV and hours spent using the computer. If the summation of total hours spent watching TV and hours spent using the computer was greater than 24, this was set to missing (n = 35).
Physical activity assessment Self-report physical activity was assessed for all participants using the validated short-form International Physical Activity Questionnaire (IPAQ) (22) on which participants reported the frequency (i.e. days/week) and duration (i.e. minutes/day) of walking, moderate-and vigorous-intensity physical activity in the past seven days. For each domain (walking, moderate, vigorous), durations of < 10 minutes/day were recoded to 0 and durations of > 180 minutes were truncated at 180 minutes/day in line with IPAQ processing rules. This was used to derive hours/day spent in walking, moderate-and vigorous-intensity physical activity. All data processing was carried out according to official IPAQ rules (23).

Assessment of covariates
Height (m), weight (kg), and waist and hip circumference (cm) were measured by staff at the UK Biobank study centre. Body mass index (BMI) was then calculated from the weight and height measurements (kg/m 2 ). Waist circumference measurements were taken from the level of the umbilicus and regarded as a measure of central obesity, using official cut-off values established by the International Diabetes Federation (> 94 cm in men and > 80 cm in women) (24).
Age, sex and postcodes were acquired from a central registry for all participants and updated by the participant. Participants also self-reported their ethnicity, educational attainment, lifestyle behaviours (smoking status, alcohol consumption, dietary intake and sunscreen/ultraviolet (UV) protection use) and medical history using electronic questionnaires. Townsend deprivation scores were derived from postcodes (25). Core confounders for all models included socio-demographic factors (i.e. age, sex, ethnicity, educational attainment and deprivation index), smoking status, alcohol consumption, fruit and vegetable consumption, BMI, height and waist-hip ratio. Cancer site-specific confounders included use of sun/UV protection (melanoma), self-reported oesophageal reflux (oesophagus cancer), diabetes at baseline (pancreatic and colorectal cancers), aspirin use (colorectal cancers), red and processed meat intake (colorectal cancers), hormone replacement therapy (HRT) use (breast, uterus and colorectal cancers), oral contraceptive use (breast and uterus cancers), number of live births (breast and uterus cancers), age at menarche (breast and uterus cancers), age at menopause (breast and uterus cancers), hysterectomy status (breast and uterus cancers) and self-reported family history of cancer (total cancer, lung, prostate, and breast cancers), based on known aetiological risk factors for these tumours.

Cancer ascertainment
For the present analysis, the main outcomes were incident total cancer (excluding non-melanoma skin cancer) and site-specific cancers. Incident cancers for participants in the UK Biobank cohort were identified through records maintained at national cancer registries (Health and Social Care Information Centre and the NHS Central Register) and identified from the International Classification of Diseases, 9th and 10th revisions (ICD-9 and ICD-10 (26)). Cancer outcomes were coded according to ICD-9 and ICD-10 as follows: all cancers excluding non-melanoma skin cancer (ICD-10: C00-C97 excluding C44; ICD9: 140-209 excluding 173), melanoma   Tables 2-6). These included use of sun/UV protection, HRT use, oral contraceptive use, number of live births, age at menarche, age at menopause, hysterectomy status, diabetes at baseline, aspirin use, red meat intake, processed meat intake.
For analyses including gender-specific covariates (e.g. incident total cancers, colorectal cancer, colon cancer and rectum cancer), separate models were run for males and females and HRs were combined using inverse variance meta-analysis and a fixed-effects model (27)(28)(29). Participants were excluded from the analysis if they did not have the complete exposure and covariate data required for each model. We did not adjust for total dietary energy intake as the large amount of missing data (for 57.6% of participants) made this unfeasible. Further analyses were conducted to investigate the role of anthropometric factors by running all models with and without adjustment for waist-hip ratio, as a proxy for central adiposity.
Models including incident total cancers, breast cancer, prostate cancer and lung cancer were run with and without adjustment for self-report family history (mother, father, siblings). The oesophageal cancer model was also run with and without adjustment for self-reported gastro-oesophageal reflux Disease (GORD).
These analyses were repeated separately to investigate the relationship between a 1-hour increase/day in (1) time spent using the computer; (2) total screen time; and cancer risk. Since the association between time spent in sedentary behaviour and cancer risk may not be linear (9,30), we repeated these analyses with categorised independent variables as follows: daily TV screen time (  (17). The analysis including total screen time was not considered to be the primary analysis since summing the time spent watching TV and the time spent using computers may overestimate total screen time through double counting (if participants watched TV and used computers at the same time). Therefore, the daily TV screen time analysis was considered to be the primary analysis.
A series of partition models and isotemporal substitution models (19) were used for each type of cancer to examine the associations of daily TV screen time, time spent walking/day, time spent in moderate-intensity physical activity/day, time spent in vigorous-intensity physical activity/day and cancer incidence (19,(31)(32)(33)(34). Partition models examined all behaviours simultaneously, without adjusting for total physical activity time. Therefore, the HR for one type of physical activity represented the effect of increasing this type of physical activity (by 1-hour/day) while holding the other physical activities constant. Since total physical activity time is not included in the model (and thus is not held constant), these results represent the effect of 13 adding a physical activity type whilst holding the others constant. The effects of substituting one physical activity type by another for the same amount of time (i.e. replacing 1-hour/day of TV screen time for 1-hour/day of walking, moderateintensity physical activity or vigorous-intensity physical activity) was investigated using isotemporal substitution models which adjusted for time spent walking/day, time spent in moderate-intensity physical activity/day, time spent in vigorousintensity physical activity/day and total activity time/day (i.e. the summation of walking, moderate activity, vigorous activity and TV screen time). In this case, since total physical activity is included the model (and thus is held constant), these results represent the effect of replacing TV screen time with the same amount of another physical activity type (i.e. walking, moderate-or vigorous-activity) while holding the others constant. Sensitivity analyses were conducted by confining the analysis to cancers diagnosed at least two years following baseline to examine the impact of removing prevalent disease. Subgroup analyses were conducted by selected baseline characteristics.
These included sex, age, deprivation index, smoking status and BMI with reference to obese/non-obese thresholds defined for various ethnic groups by gender in a previous UK Biobank study (35), assuming that participants with mixed backgrounds or 'other' ethnicities had the same obesity thresholds as white participants since cut-off points were not available for this group. Further analyses were conducted by creating four categories based on body fat percentage and physical activity levels defined according to the IPAQ. Body fat percentage cut-points were derived from previously established thresholds defined by age, gender, ethnicity and BMI (36).
We assumed participants with mixed backgrounds or 'other' ethnicities had the same body fat percentage thresholds as white participants. Subgroup analyses were 14 also conducted by menopausal status for female-specific cancers (i.e. breast, uterus, ovary cancers). Interactions were tested using the Wald test for homogeneity and declared significant if p < 0.01 in line with previous studies (37).
The proportional hazards assumption was tested for each model formally using Schoenfeld residuals (p < 0.05 indicated potential violation of the proportional hazards assumption), and by visual inspection of scaled Schoenfeld residual plots (38) and log-log plots (parallel curves indicated that there was no evidence for violation of the proportional hazards assumption). Analyses were carried out using Stata 13 (39).

RESULTS
Participant characteristics according to total daily screen time are shown in Table 1.
Among the 470 578 participants included in this analysis, 53.8% were women and the mean age was 56.3 years. Most participants reported that they spent between 2 and 8 hours/day watching TV or using the computer. During a mean follow-up time of 7.6 (SD 1.4) years (median 7.8 years, interquartile range 7.0-8.5), 28 992 incident cancers were identified.   eAdditional site-specific covariates in the final model include diabetes at baseline (yes/no), aspirin use (regular use/non-regular use or no use), HRT use (ever used/never used), red meat intake (portion/week), processed meat intake (portion/week). fFinal model also adjusted for waist-hip ratio (> 94 cm in men, > 80 cm in women).
gResults for males and females combined using meta-analysis as covariates are different.
hFinal model also adjusted for family history of cancer (mother/father/sibling had cancer, no family history). **Schoenfeld test indicated potential violation of the proportional hazards assumption (p < 0.05).
Subgroup analyses and tests of effect modification (supplement 1, tables 1. Association of cancer risk and daily time spent on the computer  Association of cancer risk and daily total screen time Table 6 shows the association between a 1-hour increase in total daily screen time and total cancer risk and site-specific cancer risk. A 1-hour increase in daily total screen time was associated with a higher risk of lung cancer (HR 1.03, 95% CI:  After excluding cancers diagnosed within the first 2 years following baseline, all associations were attenuated except those for oesophagus and stomach cancers, and colon cancers (Table 3). Whilst the results of the Schoenfeld residual tests indicated that some of our models may not have been in line with the proportional hazards assumption, our visual inspection of log-log plots and Schoenfeld residual plots showed no serious violations. Therefore, we proceeded with the analyses as planned. Table 3 Results of Cox proportional hazards analyses investigating the association between self-report TV screen time and cancer incidence (excluding cancers diagnosed within the first 2 years following baseline). (Never/rarely/sometimes; most of the time/always; do not go out in sunshine).
bAdditional site-specific covariates in the final model include HRT use (ever used/never used), oral contraceptive use (ever used/never used), number of live births (0, 1, 2, 3 + live births), age at menarche (early menarche

Results of partition models and isotemporal substitution models
Partition models showed there was an association between a 1-hour increase in daily TV screen time and a higher risk of total cancer (HR 1.01, 95% CI: 1.002,
f Final model also adjusted for waist-hip ratio (>94cm in men, >80cm in women).
g Results for males and females combined using meta-analysis as covariates are different.
h Final model also adjusted for family history of cancer (mother/father/sibling had cancer, no family history).
Association of cancer risk and daily time spent on the computer Table 5 shows the association between a 1-hour increase in daily time spent using computers and total cancer risk and site-specific cancer risk. A 1-hour increase in daily computer screen time was associated with lower risk of oropharyngeal cancer (HR 0.93, 95% CI: 0.87, 0.998). The categorical analysis showed that participants who reported that they spent no hours using computers had a higher risk of oropharyngeal cancer (HR 1.27, 95% CI: 1.03, 1.56), and ovary cancer (HR 1.23, 95% CI: 1.01, 1.50) compared to participants who reported ≤ 1 hour of daily time spent using the computer.
Participants who reported > 3 hours using computers had a higher risk of lung cancer (HR 1.36, 95% CI: 1.12, 1.65) compared to participants who reported ≤ 1 hour of daily time spent using the computer. Association of cancer risk and daily total screen time Table 6 shows the association between a 1-hour increase in total daily screen time and total cancer risk and site-specific cancer risk. A 1-hour increase in daily total screen time was associated with a higher risk of lung cancer (HR 1.03, 95% CI:

Overview of key findings
This large, prospective cohort study indicates that sedentary behaviours were associated with some site-specific cancers (notably oropharyngeal, oesophagus and stomach, colon and lung cancer), particularly for TV viewing time. Results for oesophagus and stomach cancers, and colon cancers were robust to the omission of cancers occurring within the first two years of follow-up. Our study provides no evidence for an association between sedentary behaviour and total cancer risk.
However, the results of our isotemporal substitution models revealed a benefit in terms of reduced total cancer risk and reduced risk of several site-specific cancers when replacing 1-hour of TV viewing per day with 1-hour of moderate-intensity physical activity or walking. Results were less consistent for time spent on computer and daily total screen time. This may suggest that the mechanism of action is more nuanced and complex than the act of being sedentary, but the specific activity that is being undertaken during sedentary time (i.e. watching TV or using the computer) is an important mechanistic driver. Indeed, Patterson F et al (2018) suggested that sedentary behaviour was not a homogenous behaviour and found that different sedentary behaviours had different determinants (40). This will be explored further below.

TV viewing and cancer risk
Television viewing was the most common sedentary behaviour in this population.
Our results showed that a 1-hour increase in TV viewing time was associated with higher risk of oropharyngeal, stomach, oesophagus and stomach, and colon cancers.
Compared with our reference group of 1-3 hours of TV viewing per day, reporting 57 less than 1-hour TV viewing per day was associated with decreased risk of lung, breast, stomach, and oesophagus and stomach cancers. Thus our analytical approach has allowed us to contribute a novel finding to the literature, highlighting the benefits of zero TV screen-time hours for these cancers. There is some evidence in the literature that higher levels of physical activity may reduce lung cancer.
Mechanistically, this is likely to be due to increased respiratory ventilation, reducing the concentration of carcinogenic agents in the lungs (41). Previous research also provides evidence for a relationship between higher levels of physical activity and lower risk of incident breast cancer due to decreased sex and metabolic hormone levels, decreased adiposity, reductions in insulin resistance and reduced inflammation (37,(42)(43)(44)(45). It is plausible that similar mechanisms could be applied to the relationship between these cancers and sedentary behaviour.
Previous research has suggested that individuals who have increased TV viewing time tend to have poor lifestyle behaviours, such as being more likely to smoke, eating a poor diet, doing little, if any, physical activity, and being overweight or obese (7). Further, Ogden et al (2013) discussed the concept of 'mindless eating', where the distraction of watching the TV led to individuals consuming more calories (46). A review of the literature on sedentary behaviour and biological pathways by Lynch (2010) supported the hypothesised role of adiposity and metabolic dysfunction as mechanisms operant in the association between sedentary behaviour and cancer (7). Our findings and other evidence would suggest that sedentary behaviour is much more than an act of not being 'active' or being in a stationary position for a prolonged period, but rather a range of sedentary behaviours where the 'activity' being undertaken while sedentary is very important. Subsequently, mechanisms of action are likely to act via a number of complex pathways, such as indirectly. For example, TV viewing has been associated with increased risk of being obese or overweight (47), and there is also a strong evidence base associating being overweight or obese to increased cancer risk (7,48). However we adjusted for BMI in our models to try to account for this. Known mechanisms associated with body fatness, such as sex hormones, insulin, and inflammation, may explain part of the association between sedentary behaviours and cancer risk. The association between prolonged TV viewing time and lower levels of vitamin D have also been hypothesised as a possible mechanistic pathway (7,11).

Computer use and cancer risk
The mean computer use time was 1.1 hours/day, which is almost three times less prevalent as a sedentary behaviour than daily TV viewing time within this UK population. Paradoxically, our findings showed that a 1-hour/day increase in computer use was associated with lower risk of oropharyngeal cancer and the results of the categorical analysis showed that 0 hours/day of computer use was associated with higher risk of oropharyngeal and ovary cancers compared with ≤ 1 hour/day. Reporting > 3 hours/day of computer use was also associated with increased risk of lung cancer. It is difficult to compare the findings for computer use with other literature given the explicit exclusion of 'using a computer at work' from our measure. Most of the previous literature is focused on occupational sedentary time which largely encompasses computer use [17].

Daily total screen-time and cancer risk
The mean daily total screen-time was almost 4 hours/day, reflecting combined TV and computer screen time. The most notable associations were observed for an increased risk of lung cancer in both continuous and categorical analysis. Previous 59 literature has demonstrated that household air pollution exposure from solid fuel is associated with high rates of lung cancer, especially in low-and middle-income countries, such as China (49). However, this seems an unlikely mechanistic pathway in the UK. It is plausible that indoor sedentary behaviour may be linked to increased residential radon exposure which is known to be associated with an increased risk of lung cancer, particularly in European populations (50). Results were somewhat mixed for other cancers which may be due to the combined nature of essentially two different behaviours (i.e. TV viewing and computer use).

Findings in relation with other literature
Our observations are somewhat mixed to those previously reported for total cancer incidence (15), oesophago-gastric cancer risk (16) and colon cancer risk (17) in relation to sedentary behaviour. However, it is difficult to draw direct comparisons between these studies and our current analysis, since each of those used the lowest category of screen-time exposure as their reference category. Due to our a priori hypothesis that individuals with less than 1-hour of screen time may have different characteristics, we chose 1-3 hours of screen-time as our reference category. This revealed some novel associations not previously identified, such as protective associations for lung, breast, oesophageal, stomach, and oropharyngeal cancers in individuals with the lowest screen-time exposure, and increased risks of lung cancer in individuals with higher levels of exposure to screen time.

Implications of findings
Our findings would support the continued promotion of public health messages and interventions to minimise and reduce sedentary behaviours. However, rather than broad messaging and strategies to simply 'sit less', our findings suggest that there is a need to tackle specific sedentary behaviours, in particular TV viewing. Such messages should not only promote the need to reduce sitting time but to also be mindful of the unhealthy behaviours, such as mindless eating, associated with watching TV.
Public health practitioners should also think about what activities they should promote while displacing sedentary behaviour. Results from our partition and substitution models show the benefits of replacing 1-hour of TV viewing time with 1hour of moderate-vigorous intensity physical activity or 1-hour of walking, particularly for total cancer, breast, colorectal, colon, oropharyngeal, and lung cancers. So rather than messages and interventions to 'sit less', such strategies should also promote healthy, displacement physical activity.

Strengths and limitations
This study provides a comprehensive overview of sedentary behaviours for total cancer risk and site-specific cancers. The findings from the partition and isotemporal substitution models are the first, to our knowledge, to model the impact of displacing 1-hour of sedentary behaviour with more physically active behaviours.
The UK Biobank has previously been criticised for not being a representative sample for physical activity levels, obesity prevalence and other co-morbidities, indicating a healthy volunteer bias. However, the cohort is representative of the UK population in terms of age, sex, ethnicity and deprivation for the targeted age group (15,51) and a recently published generalisability study suggest that the results of UK Biobank studies can be generalised to England and Scotland (52). All models were adjusted for important socio-demographic, health and behavioural variables, including BMI which is hypothesised to be on the causal pathway between sedentary behaviour and cancer incidence. Some have argued that this may lead to over-adjustment and therefore underestimation of the strength of the tested associations (15). Due to the large amount of missing data, the analyses were not adjusted for total calorie consumption or dietary habits other than total fruit and vegetable intake, red and processed meat consumption. Further, we have interpreted our results of effect modification with caution owing to the number of cancer sites and number of subgroups which have been investigated.
The analysis uses self-report sedentary behaviour data, which may be subject to social desirability and recall bias, and the measure has not been investigated for criterion validity (15). However, the estimates are in line with previous population estimates (53,54). Although the UK Biobank cohort does measure sedentary behaviour using accelerometers, we were unable to use this data to examine the association with cancer incidence as the follow-up time was too short (mean followup time 1.9 years). The nature of the observational study means that we cannot attribute causal interpretations to our results owing to the potential for residual confounding. Finally, some associations were attenuated when excluding cancers diagnosed within the first two years of follow-up, suggesting that our results could have been affected by a possible reverse causation bias. Accelerometer data has been assessed in UK Biobank during secondary waves of data collection, and so this will be possible given longer follow-up in due course. In addition, the current analysis focussed on cancer risk, but much remains unknown about the interactive effects of physical activity and sedentary behaviour on cancer mortality. These areas of research have been highlighted as important evidence gaps in the US 2018 physical activity guidelines (6).

CONCLUSIONS
In summary, the current study adds to the much-needed evidence base on sedentary behaviours and cancer risk, including total cancer risk and site specific cancers (particularly lung cancer). Our findings show that sedentary behaviours were associated with some site-specific cancers (including oropharyngeal, oesophagus and stomach, colon and lung cancer), particularly for TV viewing time.
Our findings were less consistent for time spent on computer and daily total screen time. Substitution models showed that replacing 1-hour per day of TV viewing with 1-hour of moderate-intensity physical activity or walking was associated with lower risk of total cancer and lower risk of several site-specific cancers. Health promotion strategies should endorse the message to minimise sedentary behaviour, replacing it with healthy physical activities, and to particularly target TV viewing.

Abbreviations
AICR American Institute for Cancer Research BMI Development Agency. It has also had funding from the Welsh Assembly government and British Heart Foundation. The research was designed, conducted, analysed, and interpreted by the authors entirely independently of the funding sources. All authors had full access to all of the data (including statistical reports and tables) in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.  The association between daily TV screen time and total cancer risk and site-specific cancer r