Examining the joint effect of air pollution and green spaces on stress levels in South Korea: using machine learning techniques

Figures & data

Figure 1. South Korean study area showing the Sigungu municipal district boundaries.

Table 1. Survey population characteristics for all municipal districts in South Korea for the 2017–2022 period (unit: case (%)).

Year		2017	2018	2019	2020	2021	2022
Total		228,381	228,340	229,099	229,269	229,242	231,785
Sex	Male (%)	102,484 (44.9)	102,241 (44.8)	102,572 (44.8)	103,894 (45.3)	104,498 (45.6)	106,119 (45.8)
	Female (%)	125,897 (55.1)	126,099 (55.2)	126,527 (55.2)	125,375 (54.7)	124,744 (54.4)	125,666 (54.2)
Age groups	19–39 years (%)	54,215 (23.7)	51,675 (22.6)	50,095 (21.9)	51,490 (22.5)	50,428 (22.0)	47,584 (20.5)
	40–60 years (%)	80,439 (35.2)	81,427 (35.7)	80,082 (35.0)	80,505 (35.1)	78,610 (34.3)	77,717 (33.5)
	Over 60 years (%)	93,727 (41.1)	95,238 (41.7)	98,922 (43.1)	97,274 (42.4)	100,204 (43.7)	106,484 (45.9)

Table 2. Study variables and their descriptions.

Variable	Data source	Resolution	Years	Description
age	Korean Population and Housing Census (KPHC)	District	2017–2022	Mean age of individuals
pop_den	KPHC	District	2017–2022	Population density
male	CHS	District	2017–2022	Percentage of males
Avg_incom	KPHC	District	2017–2022	Average level of income
health	CHS	District	2017–2022	Self-reported health status of individuals
PM10	Air Korea	1500 × 1500 m	2017–2022	PM10 concentration
temp	Korea Meteorological Administration	1500 × 1500 m	2017–2022	Average temperature
water_body	Land Process Distributed Active Archive Center (LP DAAC)	500 × 500 m	2017–2020	Percentage of land cover water bodies classified as water body.
mix_forest	LP DAAC	500 × 500 m	2017–2020	Percentage of land cover classified as mixed forest.
urban	LP DAAC	500 × 500 m	2017–2020	Percentage of land cover classified as urban or built-up land.
dec_forest	LP DAAC	500 × 500 m	2017–2020	Percentage of land cover classified as deciduous forest.
grass	LP DAAC	500 × 500 m	2017–2020	Percentage of land cover classified as grasslands or open grasslands.
Shrubs	LP DAAC	500 × 500 m	2017–2020	Percentage of shrubs.
ever_forest	LP DAAC	500 × 500 m	2017–2020	Percentage of land cover classified as evergreen forest.
slope	Korea Meteorological Administration	90 × 90 m	2017–2022	Slope or gradient of the terrain, measured as a percentage.

Table 3. Comparison of performances of Random Forest using the hyper-parameter tuning.

		ntree = 1000	ntree = 1500	ntree = 2000
mtry = 5	R^2	0.594	0.595	0.594
	RMSE	0.066	0.066	0.066
	MAE	0.050	0.050	0.050
mtry = 7	R^2	0.589	0.589	0.589
	RMSE	0.067	0.067	0.067
	MAE	0.051	0.051	0.051
mtry = 10	R^2	0.580	0.580	0.580
	RMSE	0.067	0.067	0.067
	MAE	0.051	0.051	0.051
mtry = 15	R^2	0.569	0.569	0.570
	RMSE	0.068	0.068	0.068
	MAE	0.052	0.052	0.052

Figure 2. Perceived stress levels in the municipal districts for the period before (2018–2019) and during (2020–2021) the COVID-19 pandemic.

Table 4. Descriptive statistics for the municipal districts in South Korea.

Districts (n = 241)	Minimum	Maximum	Mean ± SD	Range
Stress level	1.5	2.3	2.0 ± 0.1	1–4
PM10 (µg/m3)	21.9	43.4	33.8 ± 3.5	0–∞
% evergreen forest	0.0	7.5	0.1 ± 0.5	0–100
% deciduous forest	0.0	65.2	10.2 ± 13.8	0–100
% mixed forest	0.0	26.2	2.7 ± 4.2	0–100
% grassland	0.0	10.2	0.3 ± 0.9	0–100
% urban and built-up	0.0	100.0	21.9 ± 28.8	0–100
Water bodies	0.0	55.9	27.9 ± 16.1	0–100
Slope	0.7	20.8	8.0 ± 4.0	0–360
Temperature (°C)	12.5	15.1	13.3 ± 0.2	−11°C–33°C
Reported health status	2.9	3.8	3.5 ± 0.1	1–5
Mean age	34.9	57.3	45.7 ± 5.0	>0
% male	46.2	54.6	49.7 ± 1.4	0–100
% average income	0.4	9.8	3.3 ± 1.6	0–100
Population density	0.00	0.02	0.00 ± 0.01	>0

Figure 3. Stress boxplots for the periods before (2017–2019) and during (2020–2022) the COVID-19 pandemic.

Figure 4. PM₁₀ boxplots for the periods before (2017–2019) and during (2020–2022) the COVID-19 pandemic.

Figure 5. Variables influencing stress levels in South Korea in the pre-COVID-19 pandemic period (2017–2019).

Figure 6. Variables influencing stress levels in South Korea during the COVID-19 pandemic period (2020–2022).

Figure 7. Nonlinear effects of PM₁₀ and forest type on stress for the periods before (2017–2019) and during (2020–2022) the COVID-19 pandemic.

Figure 8. Joint association of forest type and PM₁₀ levels with stress levels during the pre-COVID-19 pandemic period (2018–2019).

Note: the different colors represent different stress levels, with darker colors indicating lower stress values and lighter colors indicating higher values.

Figure 9. Joint association of forest type and PM₁₀ with stress levels during the COVID-19 pandemic period (2020–2021).

Note: the different colors represent different stress levels, with darker colors indicating lower stress values and lighter colors indicating higher values.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.