Figure 3 shows the proportion of food from each category for each London borough.
- On the low end, the Borough of Harrow’s groceries by weight were 19.4% animal products, and just 10.6% from meat.
- Other low-animal-product boroughs included the lowest meat-eating Borough of Newham (19.5% animal products, 10.2% meat) and Sutton (19.5% animal products, 10.9% meat).
- On the high end, animal products made up 24.7% of groceries by weight in the Borough of Kensington and Chelsea, and meat made up 13.3%.
- Other high-animal-product-consumption boroughs were Hammersmith and Fulham (24.0% animal products, 13.7% meat) and the highest meat-eating Borough of Lambeth (24.0% animal products, 14.5% meat).
The results of the linear regression on the association between various demographic factors and meat consumption are shown in Table 3. Green rows indicate a significant association with less meat consumption; red rows indicate a significant association with more meat consumption.
Several significant predictors of higher meat consumption in an area were identified, some of which confirmed our hypotheses, but some which were directly counter to our hypotheses. The hypothesized and observed results are summarised in Table 4.
As shown, six out of nine hypotheses related to demographic predictors of meat consumption were rejected. Contrary to our expectations, there was an inverse statistical effect for the influence of age, education level and conservative political views on meat consumption.
Areas with older populations, lower education populations, and more conservative political records had a lower proportion of meat consumed. In addition, no statistical significance could be found for the influence of the proportion of males and income on meat consumption.
On the other hand, there was a statistically significant effect for population density and health on meat consumption. In alignment with our expectations, a lower proportion of meat consumed could be observed in areas with higher population density and better health. With regard to the religion variables, we did observe a lower proportion of meat sold in areas with more Hindus, but observed that the opposite was true for areas with more Buddhists.