大城市郊区居民通勤模式对健康的影响研究——以北京天通苑为例

doi:10.18306/dlkxjz.2018.04.010

Abstract

Abstract:

Suburbanization of Chinese cities has exacerbated home-work separation and led to the increase of long-distance commuting of suburbanites, which may affect their health status. In this article, taking Tiantongyuan in the inner suburb of Beijing as a case study, we focused on the impacts of suburban residents' commuting pattern on the health outcomes. In general, the overall commuting space of the full-time workers living in Tiantongyuan showed an uneven radial pattern centered at the community's location. According to commuting distance, commuting time, and commuting modes, the commuting patterns of the full-time employees living in Tiantongyuan can be clustered into three main types, including short distance-active commuting-public transit commuting, medium to long distance-public transit-car driving commuting, and long distance-public transit-car driving commuting. Controlling for other socioeconomic variables, this study used binary logistic regression models to verify the effect of commuting patterns on both physical and mental health outcomes. It was found that the effect of commuting patterns on poor sleep quality, frequent sick leaves, fatigue, stress, and other health risks showed an inverted U-shaped trend. Moderate commuting may be good for health, while extremely long commuting might be harmful to health. Especially, long distance-public transit-car driving commuting significantly increased the health risks of poor sleep quality, frequent sick leaves, and stress. Improving the home-work connection of the suburb is not only helpful for improving the efficiency of urban operation, but more importantly, is also meaningful for the improvement of the life quality of suburban residents.

Key words: commuting pattern, health behavior, physical health, mental health, suburbanization, Beijing, Tiantongyuan

Tingting FU, Yan ZHANG, Yanwei CHAI. Implications of commuting pattern for suburban residents’ health in large Chinese cities: Evidences from Tiantongyuan in Beijing[J].PROGRESS IN GEOGRAPHY, 2018, 37(4): 547-555.

Figures/Tables 7

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References 22

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社会经济属性		生理健康			心理健康			合计
社会经济属性		BMI不正常	睡眠差		经常请病假		疲惫	压力大	情绪低落
性别	男	39.3	16.1	2.5	20.7	53.4	13.9	56.5
性别	女	33.0	12.9	3.2	19.5	43.5	11.6	43.4
户口	本地户口	40.1	10.3	4.8	17.8	48.3	9.3	41.4
户口	外地户口	34.3	17.8	2.8	20.2	49.8	13.1	58.6
教育	本科以下	37.6	20.1	2.7	22.7	47.7	15.8	31.4
	本科及以上	35.7	12.1	2.9	20.2	49.3	9.4	68.6
职业	机关事业单位	34.5	9.9	5.2	18.0	42.6	7.0	16.4
	私营企业主	42.9	12.8	4.3	17.4	54.1	11.5	11.2
	一般劳动者	37.3	21.5	2.3	29.8	50.4	15.2	32.5
	企业管理者	38.9	9.3	0.9	14.3	49.1	9.3	12.4
	专业技术人员	31.4	13.6	3.7	18.8	50.0	10.1	13.7
	其他	38.8	14.7	0.8	12.0	50.9	13.4	13.8
住房产权	自有产权	40.9	11.2	3.1	16.5	48.6	8.6	44.2
住房产权	非自有产权	33.2	14.6	2.7	20.3	48.9	13.3	55.8
是否有13岁以下孩子	没有	36.5	14.2	2.8	22.3	49.3	12.7	62.2
是否有13岁以下孩子	有	39.3	15.5	2.4	20.4	47.1	10.1	37.8
合计		36.6	14.6	2.8	20.2	48.8	12.1	100.0

通勤模式		短距离-积极-公交通勤	中长距离-公交-小汽车通勤	超长距离-公交-小汽车通勤	合计
职住距离/km	均值	2.37	12.34	17.05	7.77
	中位数	1.11	12.58	17.06	5.24
	标准差	3.82	5.94	7.67	7.66
通勤时间/min	均值	17.0	52.6	95.9	38.9
	中位数	15.0	50.0	90.0	35.0
	标准差	9.2	9.1	17.9	27.4
通勤方式/%	积极通勤	44.2	3.3	2.6	23.9
	公交通勤	21.1	72.4	76.6	46.9
	小汽车通勤	17.0	23.0	20.8	19.7
	其他	17.7	1.3	0.0	9.5
样本数		389	304	77	770

健康状况		短距离-积极通勤-公交通勤	中长距离-公交-小汽车通勤	超长距离-公交-小汽车通勤	卡方
生理健康	BMI不正常	33.4	38.9	36.0	2.253
	睡眠差	18.8	10.4	21.1	10.539^***
	经常请病假	2.3	2.8	4.2	0.903
心理健康	疲惫	23.8	15.8	25.7	7.626^**
	压力大	47.7	46.1	55.3	2.030
	情绪低落	14.1	8.5	6.6	7.056^**

影响因素	BIM不正常			睡眠质量差			请病假多
影响因素	Sig.		Exp(B)		Sig.	Exp(B)	Sig.	Exp(B)
通勤模式（参照：短距离-积极-公交通勤）	0.262			0			0.138
中长距离-公交-小汽车通勤	0.133	1.431		0.008	0.329		0.416	0.877
超长距离-公交-小汽车通勤	0.973	0.988		0.028	2.554		0.049	5.997
性别（参照：男性）	0.925	0.981		0.235	0.708		0.103	3.006
年龄	0.422	1.012		0.028	0.948		0.445	1.035
户口（参照：本地居民）	0.374	0.789		0.422	1.362		0.250	0.376
学历（参照：本科及以上学历）	0.421	1.206		0.779	1.091		0.954	1.047
个人月收入（元/月）	0.604	0.990		0.292	1.070		0.521	0.940
职业（参照：机关事业单位）	0.498			0.740			0.180
私营企业主	0.315	1.460		0.198	2.151		0.231	0.327
一般劳动者	0.195	1.528		0.524	1.385		0.007	0.042
企业管理者	0.410	1.363		0.846	0.875		0.997	0
专业技术人员	0.616	1.200		0.816	1.153		0.260	0.398
其他	0.598	0.800		0.896	1.086		0.997	0
居住年数	0.886	0.961		0.903	0.955		0.061	5.828
住房产权（参照：自有产权）	0.114	1.041		0.898	1.005		0.877	1.014
孩子（参照：没有13岁以下孩子）	0.779	1.061		0.964	1.015		0.945	1.045
常数	0.021	0.231		0.929	0.916		0.044	0.011
样本数	494			477			475
Log-likelihood	630.307			358.725			89.407
Cox & Snell R²	0.047			0.085			0.061
Nagelkerke R²	0.051			0.150			0.274

影响因素	疲惫不堪			压力大			情绪低落
影响因素	Sig.		Exp(B)		Sig.	Exp(B)	Sig.	Exp(B)
通勤模式（参照：短距离-积极-公交通勤）	0.162			0.084			0.349
中长距离-公交-小汽车通勤	0.513	0.819		0.669	0.905		0.180	0.576
超长距离-公交-小汽车通勤	0.149	1.791		0.062	1.915		0.365	0.537
性别（参照：男性）	0.334	0.785		0.025	0.642		0.002	0.304
年龄	0.641	1.008		0.298	1.015		0.675	1.010
户口（参照：本地居民）	0.597	0.837		0.862	1.046		0.811	0.897
学历（参照：本科及以上学历）	0.563	0.850		0.305	0.791		0.259	0.650
个人月收入/（元/月）	0.284	1.010		0.332	0.980		0.023	1.020
职业（参照：机关事业单位）	0.070			0.981			0.343
私营企业主	0.560	1.310		0.662	1.176		0.117	2.887
一般劳动者	0.390	1.400		0.965	0.986		0.429	1.642
企业管理者	0.044	0.285		0.901	0.955		0.067	3.734
专业技术人员	0.836	0.911		0.650	0.851		0.762	1.246
其他	0.293	0.557		0.942	1.029		0.630	1.435
居住年数	0.689	1.148		0.422	1.241		0.187	1.883
住房产权（参照：自有产权）	0.658	1.014		0.244	1.030		0.156	1.057
孩子（参照：没有13岁以下孩子）	0.116	0.652		0.468	0.859		0.649	0.846
常数	0.153	0.320		0.271	0.503		0.076	0.125
样本数	481			483			487
Log-likelihood	452.008			651.334			279.853
Cox & Snell R²	0.050			0.044			0.058
Nagelkerke R²	0.079			0.055			0.124

Implications of commuting pattern for suburban residents’ health in large Chinese cities: Evidences from Tiantongyuan in Beijing

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