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Table 1 Key data Inputs

From: Estimating cardiovascular health gains from eradicating indoor cold in Australia

Parameter Data Source Comments/ notes/ model and data assumptions Value
Unhealthy indoor temperature prevalence at base year 2016 AHCD Prevalence of people experiencing indoor cold temperature was obtained from the Australian Housing Conditions Dataset (AHCD) [15]. The AHCD survey asked participants ‘Are you able to warm your house during winters’? Those responding ‘No’ were considered as experiencing indoor cold temperature. The original question was derived from the English Housing Survey [17]. We accounted for age variations in the prevalence as estimated from the AHCD
Uncertainty: Double of standard errors in age-specific prevalence obtained from AHCD with correlation of 1
5.74%
(Refer to Table 2 for age variations)
Average temperature in cold houses   Average outdoor temperatures: Victoria (15.04 °C), New South Wales (18.43 °C), South Australia (20.19 °C)
We assume average indoor cold temperature at 16 Celsius
 
All-cause mortality rates GBD Data on all-cause mortality rates by sex and age group for 2016 were obtained from the Global Burden of disease results tool and inputted directly [28] Refer to Table 2 for age and sex variations
All-cause morbidity rates GBD Data on years of life lived with disability (YLD) were obtained from the Global Burden of Disease study for each sex and age group in 2016. No time trend was allowed, as YLD rates by age in the GBD have not changed much over time. Morbidity rates were directly inputted in the main life table to estimate HALYs [28] Refer to Table 2 for age and sex variations
Disease specific incidence, prevalence and case fatality rates GBD We applied national disease-specific estimates from GBD [28] to the population of three states New South Wales, Victoria and South Australia. Comparison of disease specific morbidity across the three states and national estimates showed a maximum of 10% difference – therefore we applied Australian disease data to these three states. The disease-specific incidence rates, prevalence and mortality rates, and case fatality rates (mortality rate divided by prevalence) for ischemic heart disease and stroke were obtained from the GBD data [28]. Stroke includes ischemic stroke and haemorrhagic stroke (subarachnoid and intracerebral). Disease specific rates for subarachnoid and intracerebral haemorrhagic stroke were summed and the ratio to ischemic stroke was included in the model for uncertainty analysis. All disease-specific epidemiological inputs were processed through DISMOD II and used to ensure coherence and smoothing for age [29]
Annual Percentage Changes: the annual percentage changes were estimated using Poisson regression on incidence rates and case fatality rates from 1990 to 2016 GBD data and included as inputs to the PMSLT
Uncertainty: ± 5% SD (log normal distribution for incidence), correlations 1.0 between sexes for all disease
Refer to Table 2 for age and sex variations
Disease specific morbidity IHME/GBD The sex and age specific disability rates were calculated as disease’s YLD obtained from GBD [28]divided by the number of prevalent cases
Uncertainty: ± 10% SD
 
Relative risk from indoor cold to systolic blood pressure Review of relative risks as part of the project Using evidence and search terms from the WHO Housing and Health Guidelines, we reviewed the health effects of exposure to indoor cold. Our review found consistent evidence for the effect of indoor cold on hypertension. We performed risk of bias assessment using ROBINS-E and ROB tools on interventional and observational studies on the relationship between indoor cold and systolic blood pressure. Two studies (one cohort [6] and one randomised controlled trial[4]) were found to have low to moderate risk of bias. Relative risk from the randomised controlled trial was used
Uncertainty: As provided by Saeki, Obayashi [4]
5.8 mmHg (95% CI (-9.3, -2.4))
More detailed review results presented in Table 1 in Appendices
Systolic blood pressure distribution ABS Data on systolic blood pressure by age and sex was obtained from the National Health Survey 2017–18 from the Australian Bureau of Statistics (ABS) [30]. Mean and standard deviations of systolic blood pressure were included as input to the pMSLT simulation model
Uncertainty: As provided by the National Health Survey [30]
Refer to Table 4 in Appendices for age and sex variations
Relative risk from systolic blood pressure to ischemic heart disease and stroke Forouzanfar, Liu [20] Rate ratios for systolic blood pressure to ischemic heart disease, ischemic stroke and haemorrhagic stroke were taken from IHME GBD [28]
Uncertainty: As provided by Forouzanfar, Liu [20]
Refer to Table 5 in Appendices for age variations