Air Pollutants and Daily Hospital Admissions for Psychiatric Care: A Review
Abstract
Objective:
Methods:
Results:
Conclusions:
HIGHLIGHTS
Methods
Results
Pollutantc | ||||||||||||
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Study | Study period | Country | Sample size | Type of admissiona | Admission reasonb | PM2.5 | PM10 | CO | NO2 | O3 | SO2 | NO |
Bai et al., 2019 (12) | 2014–2016 | China | 11,373 | HA | SCZ | * | ||||||
Bernardini et al., 2020 (10) | 2015–2016 | Italy | 1,860 | ED | MD | X | X | X | * | |||
Chen et al., 2018 (14) | 2013–2015 | China | 39,143 | HA | MD | X | * | * | X | X | * | |
Cho et al., 2015 (21) | 2005–2009 | Korea | 2,320 | ED | PA | X | X | X | * | X | ||
Duan et al., 2018 (4) | 2014–2016 | China | 3,469 | HA | SCZ | * | * | * | ||||
Gao et al., 2017 (8) | 2013–2015 | China | 13,291 | HA | MD | * | * | X | X | X | X | |
Kim et al., 2019 (11) | 2015–2016 | Korea | 67,561 | ED | MD | * | X | X | X | X | ||
Lee et al., 2019 (2) | 2003–2013 | Korea | 80,634 | ED | MD | * | X | X | X | X | X | |
Oudin et al., 2018 (7) | 2012–2016 | Sweden | 1,644 | ED | MD | * | X | X | ||||
Qiu et al., 2019 (20) | 2015–2016 | China | 10,947 | HA | MD | * | * | X | X | X | X | |
Song et al., 2018 (13) | 2014–2016 | China | 9,156 | HA | MBD | * | * | |||||
Strahilevitz et al., 1979 (9) | 1972 | United States | 149 | ED | * | * | X | * | ||||
Szyszkowicz, 2007 (19) | 1992–2002 | Canada | 15,556 | ED | D | * | * | * | * | * | * | |
Szyszkowicz et al., 2009 (18) | 1992–2002 | Canada | 27,047 | ED | D | X | * | * | * | X | * | |
Szyszkowicz et al., 2010 (17) | 1999–2003 | Canada | 1,605 | ED | SA | X | * | * | * | X | * | |
Szyszkowicz, 2011 (16) | 1999–2002 | Canada | 404 | ED | D | * | ||||||
Szyszkowicz et al., 2016 (15) | 2004–2011 | Canada | 118,602 | ED | D | X | X | * | X | |||
Szyszkowicz et al., 2018 (5) | 1992–2002 | Canada | 27,534 | ED | SAD | * | * | * | * | X | X | |
Wang et al., 2018 (6) | 2014–2015 | China | 19,646 | HA | D | * | * | X | X | X | ||
All studies | 12 | 16 | 13 | 17 | 13 | 15 | 1 | |||||
N of studies finding significant association | 8 | 13 | 6 | 7 | 4 | 6 | 1 |
Study | Type of admissiona | Admission reasonb | Significance and magnitudec | Additional remarks |
---|---|---|---|---|
Bai et al., 2019 (12) | HA | SCZ | NO2 was significant. The estimated RR per interquartile range (IQR) increase in NO2 at lag day 1 was 1.10 (95% CI=1.01–1.18). Greater association was observed among young patients (RR, 1.11; 95% CI=1.02–1.19). | The modeled concentration-response curves of the NO2-schizophrenia relationship suggested possible threshold effects of NO2 for all ages combined, young patients, men, and both seasons. |
Duan et al., 2018 (4) | HA | SCZ | NO2, PM10, and SO2 were significant. NO2 and PM10 had short-term effects of 4 days and 3 days (NO2, lag 0–4, RR=1.84 [95% CI=1.49–2.27]; PM10, lag 0–3, RR=1.97 [95% CI=1.57–2.36]). SO2 had longer effects for 10 days (SO2, lag 0–10 RR, 2.93 [95% CI=2.10–4.10]). | Different age groups were more sensitive to the onset of schizophrenia under the high NO2 exposure, such as patients ages 20–39 and 40–59 and male patients. |
Szyszkowicz, 2007 (19) | ED | D | CO, NO2, SO2, O3, PM2.5, and PM10 were significant. Increments in daily ED visits for D were 6.9% (95% CI=1.3%–12.9%) for CO for all patients in the warm season; 6.6% (95% CI=1.2%–12.4%) for NO2 in warm season; and 2.7% (95% CI=.4%–5.0%) for PM10 in all seasons. | Effects were generally stronger for female patients. Increments in daily visits were also associated with other pollutants and seasons: 4.5% (95% CI=.1%–9.1%) for SO2 for female patients in warm season; 6.9% (95% CI=.6%–13.6%) for ground-level O3 1-day lagged for female patients in warm season; and 7.2% (95% CI=2.0%–12.8%) for PM2.5 for females in the cold season. |
Szyszkowicz et al., 2009 (18) | ED | D | CO, NO2, CO2, and PM10 were significant but only for specific seasons. The percentage increase in daily ED visits was 15.5% (95% CI=8.0%–23.5%) for CO per .8 ppm and 20.0% (95% CI=13.3%–27.2%) for NO2 per 20.1 ppb for same-day exposure during warm weather (April–September). For PM10, the largest increase, 7.2% (95% CI=3.0%–11.6%) per 19.4 ug/m3, was observed during cold weather (October–March). | PM2.5 and O3 were not significant. |
Szyszkowicz, 2011 (16) | ED | D | SO2 significant for female patients ages ≥35. For female patients ages ≥35, OR=1.27 (95% CI=1.10–1.47) for same-day exposure. | Figure 1 of the study shows that for most of the age subgroups, the 95% CIs were large and that any conclusion should be taken carefully. Also, SO2 was the only pollutant considered in the study. |
Szyszkowicz et al., 2016 (15) | ED | D | O3 was significant for both females and males at multiple lag times. According to the lag, ORs ranged between 1.01 (95% CI=.98–1.04) and 1.04 (95% CI=1.01–1.07) for males, and the OR was 1.03 (95% CI=1.00–1.05) for females. | Increased SO2 was also associated with increased risk for females 7 days after exposure (OR=1.01, 95% CI=1.00–1.03). For males, exposure to PM2.5 was associated with increased risk 1 day after exposure (OR=1.01, 95% CI=1.00–1.03). NO2, PM2.5, and SO2 were not significant. |
Wang et al., 2018 (6) | HA | D | PM2.5 and PM10 were significant. The strongest effect was observed on the day of exposure (lag day 0) for PM10, with an IQR increase in PM10 associated with a 3.55% (95% CI=1.69%–5.45%) increase in admissions for depression. | Elderly patients were more sensitive to PM2.5, and patients with cardiovascular disease were more likely to be hospitalized after exposure to high levels of PM10, SO2, NO2, and CO pollutants, also included in the study but only as a control variable (typically not significant). |
Bernardini et al., 2020 (10) | ED | MD | O3 was significant. An increase of 1 µg/m3 of O3 concentration (relative to the average concentration of the past 20 days) resulted in .009 (95% CI=.005–.013) more hospital admissions. | O3 was significant also when the analysis controlled for other pollutants (PM10, NO2, and CO, which were not significant). |
Chen et al., 2018 (14) | HA | MD | PM10, CO, and SO2 were significant. A 10-μg/m3 increase in 2-day, moving-average concentration of inhalable CO, PM, and SO2 was significantly associated with increments of .16% (95% CI=.02%–.30%), 1.27% (95% CI=.28%–2.26%), and 6.88% (95% CI=2.75%–11.00%), respectively, in daily hospital admissions for MD. | The estimated association of SO2 was relatively robust to the adjustment of simultaneous exposure to other pollutants. The study found generally stronger associations of air pollutants with MD in warm seasons than in cool seasons. No significant differences in associations were noted between different sex and age groups. |
Gao et al., 2017 (8) | HA | MD | PM2.5 and PM10 were significant but only for female patients. A 10-μg/m3 increase in PM10 resulted in a .83% (95% CI=.15%–1.44%) increase in hospital admissions for mental disorders of female patients. | Stronger associations were observed for schizophrenia and for patients ages <45; results for male patients were not significant. All other pollutants considered had no significant effects. |
Kim et al., 2019 (11) | ED | MD | PM2.5 was significant. The adjusted risk ratio (ARR) in the model adjusted for SO2 was 1.01 (95% CI=1.00–1.02) for 10 μg/m3 of PM2.5 on lag day 1 for all psychiatric diseases (ICD-10-CM codes F00–F99). The ARR in the model adjusted for O3 was 1.02 (95% CI=1.00–1.03) for 10 μg/m3 of PM2.5 on lag day 1 for codes F40–F49 (neurotic, stress-related, and somatoform disorders). | Other pollutants considered (SO2, CO, O3, and NO2) had no significant effects. |
Lee et al., 2019 (2) | ED | MD | PM2.5 was significant. The RR of emergency admissions for mental illness was 1.01 (95% CI=1.00–1.02) for each 10-μg/m3 increase in 2-day average PM2.5 concentration. | The effect became stronger when the analysis controlled for other pollutants (which were not significant), but the association appeared to be limited to individuals ages <65 and only during the warm season. |
Oudin et al., 2018 (7) | ED | MD | PM10 was significant in the warmer season. A 10-μg/m3 increase in PM10 was associated with a 3.6% (95% CI=.4%–7.0%) increase in hospital visits in the warmer season. | The results were confirmed in a three-pollutant model. O3 and NO2 were not significant. |
Qiu et al., 2019 (20) | HA | MD | PM2.5 and PM10 were significant. Each 10-μg/m3 increase in PM2.5 and PM10 corresponded to an increase of 2.89% (95% CI=.75%–5.08%), 1.91% (95% CI=.57%–3.28%), and 3.95% (95% CI=.84%–7.15%) in daily HAs for MD. | The risk estimates of PM on MD hospitalizations were generally robust after adjustment for gaseous pollutants in two-pollutant models. Stronger associations were noted for male patients and in warm seasons. |
Strahilevitz et al., 1979 (9) | ED | MD | CO, NO2, and NO were significant. | The study estimated only simple correlations between pollutants and ED visits. |
Cho et al., 2015 (21) | ED | PA | O3 was significant. The RR of PA–related ED visits was 1.05 (95% CI=1.01–1.09) for same-day exposure to O3. In cumulative models, adjusted RRs were 1.07 (95% CI=1.03–1.11) for lag days 0–2 and 1.07 (95% CI=1.04–1.11) for lag days 0–3. | Other pollutants (SO2, PM10, NO2, and CO) were not significant. More significant results were found for younger patients (ages <40 years), for women, and during warm seasons. |
Song et al., 2018 (13) | HA | MBD | PM2.5, and PM10 were significant. A 10-μg/m3 increase in a 3-day average concentration (lag day 2) of PM2.5 and PM10 corresponded to an increase of .48% (95% CI=.18%–.79%) and .32% (95% CI=.03%–.62%), respectively, in daily HAs for MBD. | Stronger associations were found for male patients and for older individuals (ages >45 years). |
Szyszkowicz et al., 2010 (17) | ED | SA | PM10, CO, NO2, and SO2 were significant. The RR corresponding to an increase in one interquintile range of CO was 9.6% (95% CI=.9%–19.2%); of NO2, 11.2% (95% CI=.6%–22.8%); of SO2, 10.9% (95% CI=1.3%–21.5%); and of PM10, 13.2% (95% CI=1.9%–25.8%). | The largest increase was observed for males in the cold period for a 1-day lagged exposure to NO2, with an excess risk of 23.9% (95% CI=7.8%–42.4%) and OR of 1.21 (95% CI=1.03–1.41). In warm months, the associations were not statistically significant, and the highest positive value was obtained for O3 lagged by 1 day. |
Szyszkowicz et al., 2018 (5) | ED | SAD | PM10, CO, and NO2 were significant overall, and PM2.5 was significant only in the cold season. The OR for CO at lag day 1 was 1.02 (95% CI=1.01–1.04); for NO2 at lag day 6, 1.04 (95% CI=1.01–1.06); and for PM10 at lag day 2, 1.02 (95% CI=1.00–1.04). | The strongest associations were obtained in the cold period (October–March) for 1-day lagged CO (OR=1.03, 95% CI=1.01–1.05, IQR=.4 ppm) and NO2 (OR=1.04, 95% CI=1.01–1.07, IQR=12.8 ppb). ORs were also significant for CO and NO2, with lags of 2 to 6 days and 2 to 7 days, respectively. |
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