Temperature and humidity effects on hospital admissions in Darwin, AustraliaJames Goldie

With Steven Sherwood, Lisa Alexander & Donna Green

17 July 2015

This talk

!Background

Heat stress andepidemiology

?Our studyDarwin hospital

admissions

#Results &

DiscussionOvernight humidity

How we overheat

https://www.flickr.com/photos/hddod/203141621

☼When it’s hot,

we sweatWhen it’s

humid, our sweat drips

(and doesn’t cool us)

☼ ○When it’s hot and humid,

we’re in trouble!

Epidemiology: statistical analysis of public health

Epi models can make inferences about health relationships and predict future health responses

&Health

response

☼Climate

predictor(s)

TemperatureHumidityPollution

Hospital admissionsMortalities

Ambulance callouts

~

Where’s the humidity?

Google Earth: Data SIO, NOAA, US Navy, NGA, GEBCO, Image Landsat

Melbourne: ~ 15–20 hPa

Sydney: ~ 25 hPaAdelaide: ~ 15–20 hPa

Perth: ~ 20 hPa

Brisbane: ~ 25–30 hPa

Cairns: ~ 30–35 hPa

Darwin: ~ 30–35 hPa

There aren’t enough epi studies looking at humidity in the tropics!

#*

#* Darwin Airport HadISD Station

Included Darwin Airport SLAs

Other 2006 SLAs

0 30 60 90 12015Kilometers

Darwin Airport CohortDarwin residents (~ 18k admissions)

ResponseDaily hospital admission count

PredictorsDaily temperature and relative humidity

Tmax, Tmin, Tmean, RHmax, RHmin, Rhmean

Our study in Darwin

Darwin Airport weather station

Cohort areas

Non-cohort areas

&

☼

'

Linear effects studies with GLMs

admission count ~logged population offset +predictor

Non-linear effects studied with subset

Daily series split into five equal binsAdmission rates of bins compared w/

Two analyses

Each analysis performed for one predictor, then two

https://upload.wikimedia.org/wikipedia/commons/c/cc/Darwin_Australia_aerial_photo_1984.JPEG

Linear analysis of one predictor

Predictor Tmax Tmin Tmean RHmax RHmin RHmean

Effect Size 1.74% -0.19% 0.13% 3.73% 0.02% 1.21%P-value 0.049 0.800 0.863 < 0.001 0.968 0.049

Max. relative humidity is extremely significantMax. temp, mean relative humidity are also significant

% change per 2 °C change % change per 10 p.p. change

Non-linear analysis of one predictor

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Non-linear analysis of two predictors: RHmean within TmaxEstimates (points) and 95% confidence intervals (lines) for each bin

What do the results mean?

Overnight humidity is important!Other studies found no humidity effects—but they weren’t in the tropics!

Humidity and temperature act at different times of dayHeat policies assume equal contributions throughout the day

Humid heat affects sleepMore wakefulness, less deep sleep on humid/hot days

(

https://www.flickr.com/photos/mindfulness/21264368/

)

Summary

Epidemiology: stats meets healthNot enough epi studies looking at humidity in the tropics

Hospital admissions of Darwin residentsDaily count of selected hospital admissions

Daytime temp, overnight humidity affect admissionsHeat policies assume equal contributions throughout the day#

&

○

Thanks!Questions?

J. Goldie, S. C. Sherwood, D. Green & L. Alexander (Accepted). Temperature and humidity effects on hospital morbidity in Darwin, Australia. Annals of Global Health.+

References

Tong, S., Wang, X. Y., Yu, W., Chen, D., & Wang, X. (2014). The impact of heatwaves on mortality in Australia: a multicity study. BMJ Open, 4(2), e003579. doi:10.1136/bmjopen-2013-003579

Vaneckova, P., Neville, G., Tippett, V., Aitken, P., FitzGerald, G., & Tong, S. (2011). Do Biometeorological Indices Improve Modeling Outcomes of Heat-Related Mortality? Journal of Applied Meteorology and Climatology, 50(6), 1165–1176. doi:10.1175/2011JAMC2632.