Inequality in Beijing: A Spatial Multilevel Analysis of Perceived Environmental Hazard and Self-Rated Health

Figures & data

Figure 1. Population (%) in self-rated health (1 = very good, 5 = very poor) and perceived exposure to environmental hazard (1 = very low, 5 = very high) categories.

Figure 2. Population (%) reporting good or very good health by environmental hazard (1 = very low, 5 = very high) category with 95 percent confidence intervals.

Figure 3. Spatial distribution of self-rated good health and perceived environmental hazard indexes at subdistrict level in urban Beijing.

Table 1. Key sociodemographic attributes in the residential satisfaction and health survey

Variable names	Description	Proportion (%)
Age	<20	2.6
	20–29	40.3
	30–39	29.6
	40–49	16.0
	50–59	8.5
	60+	3.0
Monthly income (RMB)	<3,000	8.2
	3,000–4,999	20.5
	5,000–9,999	34.3
	10,000–15,000	20.8
	15,000+	16.2
Gender	Male as base category	50.6
Marital status	Married	60.6
Residence status	Migrants	35.6
Housing tenure	Owners	50.8
Housing type	Commodity housing	45.1
	Affordable housing	22.9
	Daiwei housing	11.9
	Self-built housing	19.9
Housing area (square meters)	80+	44.4
	40–80	33.0
	<40	22.6
Child presence	Household with child under 6	13.6
Employment	Employed	84.7
Education	Primary	10.2
	Secondary	26.6
	Tertiary	63.2

Note: RMB = renminbi, official Chinese currency.

Table 2. Model fit comparisons

	DIC	PD	Log-likelihood	BF
Logistic model	5,689.34	29.86	−2,990.95	545,795
Multilevel logistic model	5,637.84	79.64	−2,983.45	301
Spatial LCAR multilevel logistic model	5,627.13	71.23	−2,977.74

Note: DIC = deviance information criterion; P_D = number of effective model parameters; log-likelihood = marginal log-likelihood from each model; BF = Bayes factor with the preferred model being the spatial LCAR multilevel logistic model; LCAR = a conditional autoregressive model developed by Leroux, Lei, and Breslow (1999). For example, the BF of spatial LCAR multilevel logistic model against multilevel logistic model is calculated as exp((−2,977.74) – (−2,983.45)), which equals about 301.

Table 3. Estimation results from the spatial LCAR multilevel logistic model

	Posterior median odds ratios	2.5%	97.5%
Age
20–29	0.358^*	0.192	0.617
30–39	0.244^*	0.129	0.430
40–49	0.235^*	0.122	0.420
50–59	0.186^*	0.096	0.336
60+	0.096^*	0.047	0.187
Female	0.962	0.843	1.097
Marital status	1.142	0.94	1.389
Education
Secondary	1.05	0.832	1.322
Tertiary	1.294^*	1.019	1.638
Employment	1.018	0.827	1.25
Income (RMB)
3,000–4,999	1.091	0.84	1.413
5,000–9,999	1.187	0.92	1.528
10,000–15,000	1.536^*	1.158	2.034
15,000+	2.005^*	1.475	2.724
Residence status	0.972	0.82	1.15
Child presence	1.023	0.833	1.261
Housing tenure	1.066	0.892	1.273
Housing area (m^2)
40–80	0.886	0.754	1.041
<40	0.972	0.802	1.18
Housing type
Daiwei housing	0.954	0.749	1.218
Commodity housing	1.279^*	1.06	1.542
Affordable housing	1.01	0.828	1.231
Log of distance to the nearest hospital	1.12^*	1.019	1.23
Log of distance to the nearest green park	0.949	0.837	1.074
Log of distance to the city center	1.31^*	1.104	1.556
Log of population density	0.96	0.855	1.076
Perceived traffic air pollution	0.848^*	0.781	0.921
Perceived noise pollution	0.826^*	0.762	0.894
Perceived landfill pollution	0.906^*	0.835	0.984
λ	0.903^*	0.523	0.953
σ^2	0.287	0.134	0.567

Note: RMB = renminbi, official Chinese currency; LCAR = a conditional autoregressive model developed by Leroux, Lei, and Breslow (1999).

* Statistically significant at the 95% percent credible level.

Figure 4. The impacts of significant covariates on self-rated health based on the results in Table 3 (a value > 1 indicates positive effect and a value <1 indicates negative effect).

Table 4. Estimation results from the spatial LCAR multilevel logistic model with perceived environmental hazards as binary variables

	Posterior median odds ratios	2.5%	97.5%
Age
20–29	0.36^*	0.193	0.62
30–39	0.245^*	0.129	0.432
40–49	0.235^*	0.122	0.421
50–59	0.186^*	0.096	0.336
60+	0.096^*	0.047	0.186
Female	0.962	0.843	1.097
Marital status	1.144	0.941	1.391
Education
Secondary	1.049	0.831	1.322
Tertiary	1.291^*	1.017	1.635
Employment	1.015	0.824	1.246
Income (RMB)
3,000–4,999	1.091	0.840	1.413
5,000–9,999	1.189	0.921	1.53
10,000–15,000	1.54^*	1.161	2.04
15,000+	2.011^*	1.480	2.733
Residence status	0.973	0.822	1.152
Child presence	1.027	0.836	1.267
Housing tenure	1.067	0.892	1.274
House area (m^2)
40–80	0.885	0.754	1.04
<40	0.972	0.801	1.179
Housing type
Daiwei housing	0.952	0.746	1.215
Commodity housing	1.277^*	1.058	1.54
Affordable housing	1.009	0.828	1.231
Log of distance to the nearest hospital	1.117^*	1.016	1.228
Log of distance to the nearest green park	0.948	0.834	1.076
Log of distance to the city center	1.317^*	1.107	1.567
Log of population density	0.973	0.860	1.101
District-average of environment hazard	1.259	0.662	2.382
Proportion of the elderly (65+)	0.994	0.967	1.022
Perceived traffic air pollution	0.846^*	0.778	0.918
Perceived noise pollution	0.823^*	0.759	0.892
Perceived landfill pollution	0.905^*	0.833	0.983
λ	0.895^*	0.496	0.995
σ^2	0.297	0.139	0.584

Note: RMB = renminbi, official Chinese currency; LCAR = a conditional autoregressive model developed by Leroux, Lei, and Breslow (1999).

* Statistically significant at the 95% percent credible level.

Figure 5. District-level random effects on self-rated health. The breaking points correspond to the lower, median, and upper quartiles of the district effects.

Figure 6. Population (%) in self-rated good health across income categories and age cohorts.

Figure 7. Population (%) in perceived high (and very high) exposure to environmental hazards across different sociodemographic strata.