Looking beyond the ‘meaty motorists’ Using travel and dietary behaviours to identify and describe healthy, low-carbon lifestyles in the UK Michaela A. Smith, Jan R. Böhnke, Hilary Graham, Piran C. L. White, Stephanie L. Prady 20 June 2017 Hi everyone Today I’m going to be presenting a piece of research related to my PhD, where we looked at associations between active travel and dietary behaviours in the National Diet and Nutrition survey.

Background Climate change + chronic disease -> growing attention on promotion of lifestyles that are healthy and low-carbon (HLC) e.g. reducing car travel, red and processed meat (RPM) consumption But current understanding of HLC lifestyles is very limited, most research has focused on single behaviours in isolation e.g. active travel OR low-carbon diets To truly understand people’s lifestyles + their impacts, need to understand how different behaviours may interact or intersect People may engage in HLC behaviour in one domain but not in others Hypotheses Largest class will be meaty motorists Healthy, low carbon class will include cyclists Class typologies will differ by gender More typologies in NDNS because it includes more age groups

For example… Some people may engage in healthy, low carbon behaviours in one domain but not in others cycling itself is obviously low in carbon, estimating the full impact of a ‘cycling lifestyle’ needs to consider what is ultimately fuelling the cyclist: to use an extreme example, a cyclist fuelled by calories from cheeseburgers has the same emissions per mile as two people driving a fuel efficient car (Berners-Lee, 2010). A cyclist fuelled by cheeseburgers has the same carbon emissions per mile as 2 people driving a fuel efficient car (Berners-Lee, 2010)

Research Aim Understand how travel and dietary behaviours are patterned together across the UK population Describe the prevalence and patterning of HLC lifestyles by identifying clusters of travel and dietary behaviours with health and carbon relevance RQ: how travel and dietary behaviours are patterned together across the UK population ?

Methods: Data Source National Diet and Nutrition Survey (NDNS) Nationally representative sample Dietary data collected via 4-day food diary Travel behaviour data collected via Recent Physical Activity Questionnaire (RPAQ), age 16+ Years 2, 3, 4 of rolling programme (2009-2012), n=1609

Measures Diet Travel Mode use FV: average portions/day < 3 3 – <5 5+ (meets guideline) RPM: average grams/day None >0 – 70 g >70 g (exceeds guideline) Never consumes RPM Never consumes any meat, poultry, fish (vegetarian) Mode use Car/private transport Public transport Walking Cycling Non-work travel Main mode only (1 variable) Commuting travel Frequency of each mode: always, usually, occasionally, never/rarely (4 variables)

Analysis Latent Class Analysis (LCA) Type of cluster analysis Individuals classified into subgroups (typologies / patterns of behaviour) based on responses to observed variables Group membership assigned by statistical probabilities Best-fitting models selected using information criteria (AIC, BIC), bivariate residuals, interpretability Models calculated separately by gender

Healthy, low-carbon rating After identification in LCA model, each subgroup was characterised as higher-carbon, lower-carbon, mixed Based on distribution of travel and dietary behaviour compared to gender-specific average Dietary behaviour Travel behaviour Rating Colour > avg RPM > avg car use Higher-carbon ≤ avg RPM, < avg FV predominant car use, but < avg Mixed < avg RPM, > avg FV predominant non-car use Healthy, low-carbon After identifying each subgroup, each cluster / typology characterised as higher-carbon or lower-carbon based on distribution of travel and dietary indicators compared to gender-specific average

Results: LCA models Females (n=904), 9 classes Key points: Females: 9 classes, males: 8 classes, rating scale for each group at the bottom Right off the bat: largest classes are red (high carbon), patterns are different by gender Don’t have time to go through each group in detail but I will try to go over some of the highlights Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour Class # 1 2 3 4 5 6 7 8 Travel behaviour Dietary behaviour

Females (n=904) Lower-carbon groups (2) Cyclists (1%) Low RPM, high FV Public transport users (7%) Low RPM, low FV Lower-carbon groups were cyclists, and PT commuters, both of which had lower RPM consumption than average Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

Females (n=904) Mixed groups (5) Usual car commuters (7%) Low RPM, high FV Mostly walkers (7%) Highest RPM, low FV No RPM car commuters (4%) No RPM non-commuters (2%) Mixed travel non-commuters (25%) High RPM, lowest FV Mixed groups – travel and dietary behaviour went in the opposite direction. These were: usual car commuters, mostly walkers, two groups that didn’t consume RPM but travelled predominantly by car, and the largest group, Mixed travel non-commuters Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

Females (n=904) Higher-carbon groups (2) Exclusive car commuters (26%) High RPM, low FV Mostly car non-commuters (21%) High RPM, highest FV Finally: 2 high carbon groups: exclusive car commuters and mostly car non-commuters, both of which had higher than average RPM consumption These are the meaty motorists… Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

Males (n=705) Similar groups: Exclusive car commuters (38%) Public transport users (9%) Mostly walkers (6%) Point out key highlights, distinctions, summaries Class # 1 2 3 4 5 6 7 8 Travel behaviour Dietary behaviour

Males (n=705) Similar groups: Differences Exclusive car commuters (38%) Public transport users (9%) Mostly walkers (6%) Differences Cyclists – highest RPM consumption – 79% exceeded guideline ‘No RPM’ groups less car dependent Mostly car non-commuters did not exist Point out key highlights, distinctions, summaries Class # 1 2 3 4 5 6 7 8 Travel behaviour Dietary behaviour

Summary Lower-carbon lifestyles are rare (8% females, 12% males) only 2% completely HLC (1% females, 1% males) Most groups have mixed lifestyles (45% females, 45% males) or higher-carbon lifestyles (47% females, 43% males) Clustering between travel and dietary behaviours differs by gender (only 3 groups patterned the same) Exclusive car commuters, PT commuters, Mostly walkers Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour Class # 1 2 3 4 5 6 7 8 Travel behaviour Dietary behaviour

Conclusions Examining travel and diet together can give greater insights into the full impacts of different lifestyles Most people who engage in HLC travel do not follow a HLC diet (and vice versa) Many people leading ‘mis-matched’ lifestyles (mix of high- and low-carbon behaviours) Future research: examine potential for behaviour change in intermediary ‘mixed’ groups in addition to the higher-carbon ‘meaty motorists’

Thanks! mas580@york.ac.uk

Distributions by gender Females (n=904) Males (n=705) % exceeding RPM guideline Point out key highlights, distinctions, summaries % using travelling by car for non-work journeys

Female classes – highlights Exclusive car commuters, high RPM, low FV 90% non-work car travel 100% car commuting 31% exceed RPM guideline 27% meet 5 a day Point out key highlights, distinctions, summaries Mixed travel non-commuters, high RPM, lowest FV 43% non-work car travel 33% exceed RPM guideline 5% meet 5 a day Mostly car non-commuters, high RPM, highest FV 75% non-work car travel 31% exceed RPM guideline 59% meet 5 a day Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

No RPM non-commuters No RPM car commuters Mostly walkers, 66% non-work car travel 65% always car commuting 92% no RPM, 54% vegetarian 46% meet 5 a day No RPM non-commuters 64% non-work car travel 80% no RPM, 33% vegetarian 36% meet 5 a day Mostly walkers, high RPM, low FV 78% walking travel 74% always commute on foot 36% exceed RPM guideline 24% meet 5 a day Usual car commuters, low RPM, high FV 72% non-work car travel 66% usual car commuting 26% exceed RPM guideline 33% meet 5 a day Point out key highlights, distinctions, summaries Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

Cyclists, low RPM, high FV PT travellers, low RPM, low FV 99% cycling travel 75% always commute by bike 11% exceed RPM guideline 57% meet 5 a day PT travellers, low RPM, low FV 60% PT travel 83% always commute by PT 24% exceed RPM guideline 27% meet 5 a day Point out key highlights, distinctions, summaries Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour

Females – Social Profile  - 40-54 age group + Non-White + No qualifications + Not employed + London   + Degree + Employed + Average deprivation + East Midlands + White + Degree + Yorkshire + South East  + 16-24 age group + Non-White + No partner + FT education + London - Wales   + 40-54 age group - Non-white + 3 person hholds + Children and partner + Degree + Higher ed <degree - Not employed + Higher man / prof occupations + Highest incomes - London + 16-24 age group + FT education + Employed - Least deprived - South East - 70+ age group + FT education + Employed Point out key highlights, distinctions, summaries - 40-54 age group + GCSEs + No qualifications + Not employed + Routine occupations, never worked + Lowest incomes + Highest deprivation + Scotland + 55-69 age group + 1 person hholds + No children + Foreign qualifications + Not employed + Lower man / prof occupations, small employers + Lowest deprivation   Class # 1 2 3 4 5 6 7 8 9 Travel behaviour Dietary behaviour