I
S
THE
AIR
WE
BREATHE
WHILE
SLEEPING
CONDITIONING
OUR
SLEEP
QUALITY
?
N. Canha
1,2,*, J. Lage
1, J. Belo
3, C. Viegas
4,5, T. Faria
1, S. Cabo Verde
1,
M. Meira Cruz
6,7, C. Alves
2, S.M. Almeida
11 C2TN, Instituto Superior Técnico, Universidade de Lisboa, Portugal |2 CESAM, University of Aveiro, Portugal 3 ESTeSL - Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Portugal 4GIAS, ESTeSL - Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Portugal 5Centro de Investigação em Saúde Pública, Escola Nacional de Saúde Pública, Universidade NOVA de Lisboa, Portugal
6Portuguese Association of Chronobiology and Sleep Medicine, Portugal 7Autonomic Function Group, Cardiovascular Center of Lisbon University, Portugal
O
UTLINE
1. Background
2. Goals
3. Methodology
4. Preliminary Results
5. Conclusions and future work
1. B
ACKGROUND
ICUH
Human exposure to air pollution
PM10 PM2.5 O3 NO2 SO2 B(a)P 16% 8% 8% 7% 0.5% 24% PM10 PM2.5 O3 NO2 SO2 B(a)P 50% 88% 96% 7% 42% 88% Valor limite União
Europeia
Valor guia Organização Mundial de Saúde
EU Limit Value WHO
Guideline Value
Air Quality in Europe – 2016 Report EEA Report | No 28/2016
40 µg.m-3
25 µg.m-3
20 µg.m-3
1. B
ACKGROUND
Human exposure to air pollution
Air quality monitoring station
Is this strategy representative of the human exposure?
1. B
ACKGROUND
Human exposure to air pollution
Is this strategy representative of the human exposure?
N
O
1
High variability of air pollutants concentration
within a city
N
O
2
People spend more than 90% of their time at
indoor environments
N
O
3
High variability of patterns of spaces’
occupation within the population
1. B
ACKGROUND
Human exposure to air pollution
1. B
ACKGROUND
0 10 20 30 40 50 60 70 80 90Outdoor Schools Homes Integrated
exposure
[PM
10]
(μ
g.m
-3)
EU LV WHO LVICUH
1. B
ACKGROUND
Homes
Around 1/3 of our life is
spent sleeping
W
HAT
DO
WE
KNOW
NOW
?
Sleep has a vital role in human welfare
1. B
ACKGROUND
Homes
Around 1/3 of our life is
spent sleeping
1
Low ventilation rates
2
Breathing area closer to potential sources of pollutants
3
Lack of studies about exposure during sleep
4
1. B
ACKGROUND
Why sleep matters – the economic costs of
insufficient sleep [2016]
ICUH
Sleep has an overall impact on the countries’ richness
1
Lower productivity levels and higher mortality
risks related to insufficient sleep can result in substantial economic losses to modern economies
2
Insufficient sleep among its populations cost the 5 OECD countries under consideration (USA, UK, Japan, Germany and Canada) up to $680 billion of economic output lost every year.
1. B
ACKGROUND
Preliminary study
CDCW CDOW ODCW ODOW
0 20 25 30 35 Te mp er atu re (ºC)
CDCW CDOP ODCW ODOW
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 [CH 2 O] m g m -3
CDCW CDOW ODCW ODOW
0 2 4 6 8 10 [CO] m g m -3
CDCW CDOW ODCW ODOW
0 30 40 50 60 Relative Humidity (% )
CDCW CDOW ODCW ODOW
0.0 0.5 1.0 1.5 2.0 2.5 [V OC] m g m -3
CDCW CDOW ODCW ODOW
0 10 20 30 40 50 60 70 [P M2 .5 ] g m -3
CDCW CDOW ODCW ODOW
0 10 20 30 40 50 60 70 80 [P M1 0 ] g m -3
CDCW CDOW ODCW ODOW
0 10 20 30 40 50 60 70 [P M1 ] g m -3
CDCW CDOW ODCW ODOW
500 1,000 1,500 2,000 2,500 3,000 [CO 2 ] m g m -3 • Multi-pollutant approach • Values above guidelines
were found for VOC,
formaldehyde and PM2.5
N. Canha, J. Lage, S. Candeias, C. Alves, S.M. Almeida (2017) Indoor air quality during sleep under different ventilation patterns.
Atmospheric Pollution Research (in press).
http://dx.doi.org/10.1016/j.apr.2017.05.004 0 5 10 15 20 25 30 35 40 45 50 0 30 60 90 120 150 180 210 240 270 300 P M con ce n tr at ion s (µ g m -3) Time (minutes) PM2.5-PM10 PM1-PM2.5 PM1 0 5 10 15 20 25 30 35 40 45 50 0 30 60 90 120 150 180 210 240 270 300 330 360 P M con ce n tr at ion s (µ g m -3) Time (minutes) PM2.5-PM10 PM1-PM2.5 PM1 0 5 10 15 20 25 30 35 40 45 50 0 30 60 90 120 150 180 210 240 270 300 330 P M con ce n tr at ion s (µ g m -3) Time (minutes) PM2.5-PM10 PM1-PM2.5 PM1 CDCW – Day 2 ODOW – Day 2 Movement tests A B C
ICUH
2. G
OALS
D
OES
I
NDOOR
A
IR
Q
UALITY
INFLUENCES
S
LEEP
Q
UALITY
?
3. M
ETHODOLOGY
D
OES
I
NDOOR
A
IR
Q
UALITY
INFLUENCES
S
LEEP
Q
UALITY
?
IAQ monitoring
(multi-pollutant approach)
Sleep quality assessment
Multi-disciplinary team
3. M
ETHODOLOGY
Strategy
Assessment of IAQ at bedrooms and sleep parameters
Study population
Monitoring Period
(per bedroom) Lisbon district, Portugal
Healthy, non-smokers, aged between 25 – 45 years old
Total of 10 days (starting Monday and ending on Wednesday)
10 homes (10 couples) GrayWolf - Wolfsense Continuous monitoring IAQ Monitoring Actigraphy10 days PSG2 days IAQ 3days T, RH, CO2, CO, VOCs Formaldemeter Htv-M Formaldehyde DustTrak PM1, PM2.5, PM10
Physical and Chemical parameters
Fungi
Sampling of air samples of the bedroom (250L), in triplicates, before and after sleep
Bacteria
Microbiological Parameters
Actigraphy
Sleep and Activity Monitoring
Activity
Polysomnography Sleep structure and parameters
D
OES
I
NDOOR
A
IR
Q
UALITY
INFLUENCES
S
LEEP
Q
UALITY
?
3. M
ETHODOLOGY
In situ apparatus (black box)
ICUH
IAQ monitoring
3. M
ETHODOLOGY
ICUH
Polysomnography – 2 nights
Assessment of Sleep Quality
Actigraphy – 10 days
Individual questionnaires
• SomnoWacht® actigraph
• Sleep/wake rhythm monitoring
• Pittsburgh Sleep Quality Index (PSQI) • Berlim Questionnaire (BQ)
• Sleep diary
• Polysomnography- level II was used in volunteers
• Sleep parameters:
• Total sleep time • Sleep latency
• REM sleep latency • Sleep efficiency
• Heart rate variability
• Respiratory disturbance index • Oxygen desaturation index • and others
3. M
ETHODOLOGY
ICUH
Polysomnography – 2 nights
Assessment of Sleep Quality
Actigraphy – 10 days
Individual questionnaires
• SomnoWacht® actigraph
• Sleep/wake rhythm monitoring
• Pittsburgh Sleep Quality Index (PSQI) • Berlim Questionnaire (BQ)
4. R
ESULTS
CO
2Concentrations
• Sleeping period lasted for 7 hours (eg. Couple 5)
• Sleeping period always had mean CO2 values higher than LV of 2250mg.m-3 (Portuguese legislation)
ICUH
0 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000 22:48 0:00 1:12 2:24 3:36 4:48 6:00 7:12 8:24 [C O 2 ] (m g /m 3 )Time (sleeping period)
Carbon Dioxide
Day 1 Day 3 LV, mg/m3
4. P
RELIMINARY
R
ESULTS
Particulate Matter during sleep
ICUH
0 20 40 60 80 100 120 140 60 11 40 22 20 33 00 43 80 54 60 65 40 76 20 87 00 97 80 1 0 8 6 0 1 1 9 4 0 1 3 0 2 0 1 4 1 0 0 1 5 1 8 0 1 6 2 6 0 1 7 3 4 0 1 8 4 2 0 1 9 5 0 0 2 0 5 8 0 2 1 6 6 0 2 2 7 4 0 2 3 8 2 0 2 4 9 0 0 2 5 9 8 0 2 7 0 6 0 2 8 1 4 0 2 9 2 2 0 3 0 3 0 0 3 1 3 8 0 3 2 4 6 0 3 3 5 4 0 3 4 6 2 0 3 5 7 0 0 3 6 7 8 0 3 7 8 6 0 3 8 9 4 0 4 0 0 2 0 PM co n cen tr atio n s (µg m -3 ) Time (s) PM2.5-PM10 PM1-PM2.5 PM1Day 1
Example: Couple 5
4. P
RELIMINARY
R
ESULTS
PM2.5 (µg.m-3) PM10 (µg.m-3) Indoor 31.0 ± 9.5 [17.0 – 62.0] 39.0 ± 13.2 [20.0 – 90.0] LV 25 50 0 10 20 30 40 50 60 70 0 50 100 150 200 250 300 350 400 450 PM 2 .5 , µg. m -3Time (sleeping period, minutes)
Day 1 Day 2 Day 3 LV PM2.5
Particulate Matter during sleep
Example: Couple 5
4. P
RELIMINARY
R
ESULTS
Fungi
ICUH
0 100 200 300 400 500 600 700 C1 C2 C3 C4 C5 C6 C7 C8 C9 CF U /m 3 Sample Night Morning * * * * * * * ** Exceedance of Recommended Limit Value [Indoor > Outdoor]
Fungi (CFU/m3) Night 158 ± 91 Morning 199 ± 178 Indoor > Outdoor Night 3 Morning 5
4. P
RELIMINARY
R
ESULTS
Fungi
ICUH
• 45 different Fungi species found • More prevalence of 3 Fungi species: • Penicillium sp. (27%) • Cladosporium sp. (22%) • Chrysosporium sp. (22%) Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%
Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Rhizopus sp. 4% Alternaria sp. 5% Chrysonilia sp. 7% Mucor sp. 3% Penicillium sp. 27% Cladosporium sp. 27% Chrysosporium sp. 22% Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%
Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%
Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Penicillium sp. Alternaria sp. Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%
Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Cladosporium sp. Rhizopus sp. Penicillium 27% Cladosporium 22% Chrysosporium 22% Chrysonilia 7% Alternaria 5% Rhyzopus 4% Mucor 3% Others 10%
Prevalence of Fungi species at bedroom
Penicillium Cladosporium Chrysosporium Chrysonilia
Alternaria Rhyzopus Mucor Others
Chrysosporium sp. Mucor sp.
4. P
RELIMINARY
R
ESULTS
Bacteria
Bacteria (CFU/m3) Night 571 ± 181 Morning 1458 ± 1732ICUH
0 1000 2000 3000 4000 5000 6000 7000 8000 C1 C2 C3 C4 C5 C6 C7 C8 C9 CF U /m 3 Sample Night Morning * * * * * * * * * * * **Exceedance of Recommended Limit Value [Outdoor + 350 CFU/m3]
Indoor > LV
Night 5
4. P
RELIMINARY
R
ESULTS
ICUH
Actigraphy
4. P
RELIMINARY
R
ESULTS
Polysomnography
Example: Couple 5 - Man
5. C
ONCLUSIONS
AND
F
UTURE
WORK
• Several pollutants (PM2.5, CO
2, VOCs, CH
2OH, bacteria and fungi)
have been found to be above limit values established by
Portuguese legislation
• Sleep quality will be assessed in each case by actigraphy and
polysomnography with the aim of using actigraphy as a sleep
quality surrogate
• Future work will evaluate different settings (type of area –
urban/rural, seasons, type of household, others)
ICUH
• Associations between sleep quality and indoor air quality during
sleep will be assessed in order to understand which are the main
environmental factors that influence sleep quality
6. A
CKNOWLEDGMENTS
• Postdoc grant SFRH/BPD/102944/2014 • Project UID/Multi/04349/2013 - C2TN/IST • Project UID/AMB/50017/2013 - CESAM