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Physical activity exposure and impact
Using trip sets and the synthetic population, total_mmet
computes total MMETs per person as the sum of walking MMETs per day and cycling MMETs per day, which are scaled up to a week via the PA scalar, and work/leisure MMETs per week.
We calculate the proportion of people who do no work/leisure PA according to the confidence in the PA survey. First, we calculate the raw probability that a person in demographic group completes no non-travel PA. Then, we set the probability to use as the raw value if our confidence is 1. If it's less than, we map the confidence to parametrise a Beta distribution.
Finally, for each person in the population, we sample non-travel MMETs as zero with the calculated probability and from the raw non-zero density of their demographic group.
gen_pa_rr
uses each person's MMETs per week to compute their relative risk of six diseases, using curves found from meta analysis. Each disease (except type 2 diabetes) has a threshold beyond which there is no further change in relative risk. (Total cancer, breast cancer, colon & rectum cancer, endometrial cancer, & coronary heart disease: 35; lung cancer: 10; stroke: 32; all cause: 16.08.) For all other diseases, we use mortality.
The relative risk for each person for each disease is calculated in PA_dose_response
using the curve selected, which is an interpolated mean or a sample of functions. See https://www.overleaf.com/read/mrjtkhffzfzr for an example.
combined_rr_ap_pa
combines the relative risks of gen_ap_rr
and gen_pa_rr
through multiplication. Not all diseases have a dose--response relationship for both AP and PA. Just stroke, lung cancer, and IHD have both. For the other diseases, only one of the RRs is different from one.
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Overarching modules
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Overarching project domains
- Coding guidelines
- Documentation
- Scientific publications
- Dissemination
- Case studies/applications