个体与环境交互作用下中国成人超重肥胖情况变化趋势及影响因素研究

doi:10.18306/dlkxjz.2020.01.010

Abstract

Abstract:

In recent years, with the rapid development of socio-economy and acceleration of urbanization, China has entered the stage of a health transition, which means a shift to low fiber, high sugar and cholesterol diet, as well as a sedentary lifestyle. During the health transition, Chinese residents are facing severe obesity and the problems caused by metabolic system-related diseases. So it is significantly important to find the factors which influencing the physical health of Chinese residents during the special period. This study is based on longitudinal tracking survey data of 29586 adult residents from 635 communities in 25 provinces across the country from 2010 to 2016, using non-linear development models and multi-level logistic regression models to explain the trends of overweight or obesity in Chinese residents, and explore the mechanism under the interaction of individuals and the environment. The results show that the risk of overweight and obesity in Chinese adults measured by body mass index increased year by year, in which women, age, spouses, and average daily exercise time negatively affect the growth rate of Chinese body mass index. Moreover, the differences in overweight and obesity among Chinese adults are multilayered. Socioeconomic attributes, dietary habits, and behavioral patterns at the individual level, the built environment and natural environment at the community level, and the level of urbanization at the provincial level can all affect the occurrence of overweight and obesity in China. Finally, the influence factors of overweight and obesity between different levels have an interactive relationship, and the environment can indirectly affect the residents' overweight and obesity results by affecting the individual's psychological state and behavior choices. The purpose of this research is to help residents achieve better health and to provide theoretical basis for government agencies to formulate policies to promote population health.

Key words: adult, urbanization, overweight or obesity, multilevel model, Chinese family, panel studies

WANG Yiru, WANG Chen, ZENG Jindi. Study on the trend and influencing factors of overweight and obesity in Chinese adults under interactions of individual and environment[J].PROGRESS IN GEOGRAPHY, 2020, 39(1): 100-110.

Figures/Tables 7

Tab.1

Descriptive statistics of variables"

影响因素	描述	最小值	最大值	平均值
个体层面
性别	男=1;女=0	0	1	0.48
年龄	2010年个体年龄(岁)	16	110	45.51
教育年限	2010年个体接受教育年限(a)	0	22	7
城乡属性	城镇=1;乡村=0	0	1	0.46
工作性质	没有工作=0;农业工作=1;非农工作=2	0	2	0.76
有无配偶	有配偶=1;无配偶=0	0	1	0.8
是否吸烟	吸烟=1;不吸烟=0	0	1	0.3
是否酗酒	一周饮酒3次以上=1;一周饮酒未超过3次=0	0	1	0.16
出行方式	步行或自行车=1;其他=0	0	1	0.71
有无确诊慢性病	近半年有确诊慢性病=1;无确诊慢性病=0	0	1	0.15
抑郁得分	家庭追踪调查综合指标,用以衡量成人抑郁程度	6	30	26.93
工作日睡眠时间	工作日均睡眠时间(h)	0	20	8.1
工作日锻炼时间	工作日均锻炼健身时间(h)	0	8	0.27
工作日吃饭时间	工作日均用餐及其他饮食活动时间(h)	0	10	1.46
工作日看电视时间	工作日均观看电视包括其他音频设备时间(h)	0	16	1.66
休息日睡眠时间	节假日均睡眠时间(h)	0	20	8.49
休息日锻炼时间	节假日均锻炼健身时间(h)	0	15	0.3
休息日吃饭时间	节假日均用餐及其他饮食活动时间(h)	0	10	1.49
休息日看电视时间	节假日均观看电视包括其他音频设备时间(h)	0	16	2.03
肉类频次	最近一个月每周食用肉类次数(次)	0	43	3.94
奶制频次	最近一个月每周食用奶制品次数(次)	0	45	1.31
豆制频次	最近一个月每周食用豆制品次数(次)	0	34	2.02
蛋类频次	最近一个月每周食用蛋类次数(次)	0	43	3.05
油炸食物频次	最近一个月每周食用膨化/油炸食品次数(次)	0	21	0.53
腌制食物频次	最近一个月每周食用腌制食品的次数(次)	0	50	2.35
社区层面
社区属性	居委会=1;村委会=0	0	1	0.35
环境污染	方圆5 km内是否有化工厂、造纸厂等高污染企业	0	1	0.21
道路条件	社区内土路占比(%)	0	100	41.22
省域层面
人口城市化率	城镇人口占常住人口的百分比(%)	34	89	53

Tab.1

Tab.2

Tab.3

Tab.4

Tab.5

Tab.6

Fig.1

References 33

[1]	Pendola R, Gen S . BMI, auto use, and the urban environment in San Francisco[J]. Health & Place, 2007,13(2):551-556.
[2]	Gong P, Liang S, Carlton E J , et al. Urbanisation and health in China[J]. Lancet, 2012,379:843-852.
[3]	Xu H . Multilevel socioeconomic differentials in allostatic load among Chinese adults[J]. Health & Place, 2018,53:182-192.
[4]	Popkin B M . Part II. What is unique about the experience in lower-and middle-income less-industrialised countries compared with the very-high income industrialised countries? : The shift in stages of the nutrition transition in the developing world differes from past experiences![J]. Public Health Nutrition, 2002,5:205-214.
[5]	于晓薇, 胡宏伟, 吴振华 , 等. 我国城市居民健康状况及影响因素研究[J]. 中国人口·资源与环境, 2010,20(2):151-156.
	[ Yu Xiaowei, Hu Hongwei, Wu Zhenhua , et al. The health status of citizens in China and its influencing factors. China Population, Resources and Environment, 2010,20(2):151-156. ]
[6]	孙斌栋, 阎宏, 张婷麟 . 社区建成环境对健康的影响: 基于居民个体超重的实证研究[J]. 地理学报, 2016,71(10):1721-1730.
	[ Sun Bindong, Yan Hong, Zhang Tinglin . Impact of community built environment on residents' health: A case study on individual overweight. Acta Geographica Sinica, 2016,71(10):1721-1730. ]
[7]	张延吉, 秦波, 唐杰 . 基于倾向值匹配法的城市建成环境对居民生理健康的影响[J]. 地理学报, 2018,73(2):333-345.
	[ Zhang Yanji, Qin Bo, Tang Jie . The impact of urban built environment on residential physical health: Based on propensity score matching. Acta Geographica Sinica, 2018,73(2):333-345. ]
[8]	Galea S, Vlahov D . Urban health: Evidence, challenges, and directions[J]. Annual Review of Public Health, 2005,26(1):341-365.
[9]	Kearns R, Moon G . From medical to health geography: Novelty, place and theory after a decade of change[J]. Progress in Human Geography, 2002,26(5):605-625.
[10]	Zhang J, Mauzerall D L, Zhu T , et al. Environmental health in China: Progress towards clean air and safe water[J]. Lancet, 2010,375:1110-1119.
[11]	Handy S L, Boarnet M G, Ewing R , et al. How the built environment affects physical activity: Views from urban planning[J]. American Journal of Preventive Medicine, 2002,23:64-73.
[12]	Kerri N, Robert W, David M , et al. Using signs, artwork, and music to promote stair use in a public building[J]. American Journal of Public Health, 2001,91(12):2004-2006.
[13]	Belon A P, Nieuwendyk L M, Vallianatos H , et al. Perceived community environmental influences on eating behaviors: A photovoice analysis[J]. Social Science & Medicine, 2016,171:18-29.
[14]	杨振, 丁启燕, 王念 , 等. 中国人口健康脆弱性地区差异与影响因素分析[J]. 地理科学, 2018,38(1):135-142.
	[ Yang Zhen, Ding Qiyan, Wang Nian , et al. 2018. Distribution characteristics of health vulnerability and its influence factors in China. Scientia Geographica Sinica, 2018,38(1):135-142. ]
[15]	王晓蕾, 王惠君, 苏畅 . 中国九省城市化水平对儿童青少年超重肥胖影响的多水平研究[J]. 卫生研究, 2016,45(6):888-896.
	[ Wang Xiaolei, Wang Huijun, Su Chang . Study on multilevel and longitudinal impacts of urbanization levels on overweight/obesity among Chinese children and adolescents on nine provinces. Journal of Hygiene Research, 2016,45(6):888-896. ]
[16]	Miao J, Wu X . Urbanization, socioeconomic status and health disparity in China[J]. Health & Place, 2016,42:87-95.
[17]	顾丽娟, Mark R, 曾菊新 . 社会经济及环境因子对不同收入群体自评健康的影响[J]. 地理研究, 2017,36(7):1257-1270.
	[ Gu Lijuan, Mark R, Zeng Juxin . The impacts of socioeconomic and environmental factors on self-rated status among different income groups in China. Geographical Research, 2017,36(7):1257-1270. ]
[18]	Maass R, Kloeckner C A, Lindstrøm B , et al. The impact of neighborhood social capital on life satisfaction and self-rated health: A possible pathway for health promotion?[J]. Health & Place, 2016,42:120-128.
[19]	马静, 柴彦威, 符婷婷 . 居民时空行为与环境污染暴露对健康影响的研究进展[J]. 地理科学进展, 2017,36(10):1260-1269.
	[ Ma Jing, Chai Yanwei, Fu Tingting . Progress of research on the health impact of people's space- time behavior and environmental pollution exposure. Progress in Geography, 2017,36(10):1260-1269. ]
[20]	Jones-Smith J C, Popkin B M . Understanding community context and adult health changes in China: Development of an urbanicity scale[J]. Social Science & Medicine, 2010,71(8):1436-1446.
[21]	Sun Y, Shang J . Factors affecting the health of residents in China: A perspective based on the living environment[J]. Ecological Indicators, 2015,51:228-236.
[22]	李红娟, 杨柳, 张楠 . 身体质量指数作为肥胖筛查标准的判别准确性评价[J]. 中国预防医学杂志, 2014,15(6):571-575.
	[ Li Hongjuan, Yang Liu, Zhang Nan . Accuracy of body mass index as a screening standard for obesity. Chinese Journal of Epidemiology, 2014,15(6):571-575. ]
[23]	中国肥胖问题工作组数据汇总分析协作组. 我国成人体重指数和腰围对相关疾病危险因素异常的预测价值:适宜体重指数和腰围切点的研究[J]. 中华流行病学杂志, 2002,23(1):5-10.
	[ Coorperative Meta-analysis Group of China Obesity Task Force. Predictive values of body mass index and waist circumference to risk factors of related diseases in Chinese adult population. Chinese Journal of Epidemiology, 2002,23(1):5-10. ]
[24]	盖笑松, 张向葵 . 多层线性模型在纵向研究中的运用[J]. 心理科学, 2005(2):429-431.
	[ Gai Xiaosong, Zhang Xiangkui . The application of multilevel model in longitudinal research. Psychological Science, 2005(2):429-431. ]
[25]	Zhang B, Zhai F Y, Du S F , et al. The China health and nutrition survey, 1989-2011[J]. Obesity Reviews, 2014,15:2-7.
[26]	James W P T . The foundamental drivers of the obesity epidemic[J]. Obesity Review, 2008,9:6-13.
[27]	周洁, 柴彦威 . 中国老年人空间行为研究进展[J]. 地理科学进展, 2013,32(5):722-732.
	[ Zhou Jie, Chai Yanwei . Research progress on spatial behaviors of the elderly in China. Progress in Geography, 2013,32(5):722-732. ]
[28]	敖荣军, 李浩慈, 杨振 , 等. 老年人口健康的空间分异及影响因素研究: 以湖北省为例[J]. 地理科学进展, 2017,36(10):1218-1228.
	[ Ao Rongjun, Li Haoci, Yang Zhen , et al. Spatial differentiation and influencing factors of health level of the elderly population: A case study of Hubei Province. Progress in Geography, 2017,36(10):1218-1228. ]
[29]	Pearce J, Cherrie M, Shortt N , et al. Life course of place: A longitudinal study of mental health and place[J]. Transactions of the Institute of British Geographers, 2018,43(4):555-572.
[30]	鲁斐栋, 谭少华 . 建成环境对体力活动的影响研究: 进展与思考[J]. 国际城市规划, 2015,30(2):62-70.
	[ Lu Feidong, Tan Shaohua . Built environment's influence on physical activity: Review and thought. Urban Planning International, 2015,30(2):62-70. ]
[31]	Stappers N E H, Van Kann D H H, Ettema D , et al. The effect of infrastructural changes in the built environment on physical activity, active transportation and sedentary behavior: A systematic review[J]. Health & Place, 2018,53:135-149.
[32]	Lekkas P, Paquet C, Howard N J , et al. Illuminating the lifecourse of place in the longitudinal study of neighbourhoods and health[J]. Social Science & Medicine, 2017,177:239-247.
[33]	Theodore K, Emily J, David B . Regarding obesity as a disease: Evolving policies and their implications[J]. Endocrinology and Metabolism Clinics of North America, 2016,45(3):511-520.

个体层面变量	因子1	因子2	因子3	因子4	因子5	因子6
工作日吃饭时间	0.957
节假日吃饭时间	0.955
工作日锻炼时间		0.942
节假日锻炼时间		0.939
工作日看电视时间			0.934
节假日看电视时间			0.931
工作日睡眠时间				0.930
节假日睡眠时间				0.930
食用肉类频次					0.670
食用奶制品频次					0.650
食用豆制品频次					0.650
食用蛋类频次					0.650
食用油炸食品频次					0.480
食用腌制食品频次						0.931

年份	超重BMI≥24	肥胖BMI≥28
2010	27.8	5.4
2012	29.6	6.1
2014	32.4	6.8
2016	33.5	7.0

参数	空模型		线性发展模型		非线性发展模型
参数	估计值	标准误	估计值	标准误	估计值	标准误
第一层
身体质量指数	22.719^***	0.018	22.454^***	0.019	22.430^***	0.019
时间编码			0.177^***	0.004	0.247^***	0.013
时间编码的平方					-0.023^***	0.004
随机部分ε	2.124	1.458	2.072	1.440	2.071	1.439
第二层
随机部分γ	9.185	3.031	9.198	3.033	9.198	3.033
偏差度	508029		505839		505815

第一层
	估计值		标准误
身体质量指数	19.259^***		0.158
时间编码	0.679^***		0.037
时间编码的平方	-0.023^***		0.004
第二层
	第一层截距		第一层增长斜率
	估计值	标准误	估计值	标准误
城乡属性	0.499^***	0.042	-0.007	0.009
性别	0.518^***	0.049	0.033^**	0.011
年龄	0.020^***	0.002	-0.008^***	0.000
是否有配偶	1.203^***	0.054	-0.051^***	0.012
教育年限	0.012^**	0.005	0.001	0.001
是否有确诊慢性病	0.310^***	0.054	-0.013	0.012
是否抽烟	-0.368^***	0.050	-0.018	0.011
是否酗酒	0.120^**	0.053	-0.024	0.012
抑郁得分	0.040^***	0.005	-0.002	0.001
出行方式	-0.507^***	0.041	0.005	0.009
没有工作
农业工作	-0.064	0.047	0.027^**	0.011
非农工作	0.342^***	0.048	-0.006	0.011
日均吃饭时间	-0.022	0.018	0.008^*	0.004
日均锻炼时间	0.244^***	0.021	-0.018^***	0.005
食用易胖食品频次	-0.024	0.020	-0.007	0.005
日均看电视时间	0.203^***	0.019	-0.004	0.004
日均睡眠时间	-0.081^***	0.019	0.002	0.004
食用不健康食品频次	0.159^***	0.018	0.003	0.004
偏差度	502025

	空模型		模型1		模型2		模型3		模型4		模型5
	估计值	标准误	估计值	标准误	估计值	标准误	估计值	标准误	估计值	标准误	估计值	标准误
个体层面
城乡属性			0.444^***	0.065	0.386^***	0.058	0.281^***	0.053	0.440^***	0.063	0.276^***	0.053
性别			0.276^***	0.041	0.236^***	0.047	0.275^***	0.042	0.275^***	0.041	0.245^***	0.047
年龄			0.013^***	0.002	0.013^***	0.002	0.013^***	0.002	0.013^***	0.002	0.013^***	0.002
是否有配偶			0.686^***	0.048	0.674^***	0.045	0.687^***	0.048	0.684^***	0.047	0.691^***	0.046
是否有确诊慢性病			0.205^***	0.044	0.223^***	0.046	0.204^***	0.044	0.204^***	0.045	0.229^***	0.047
是否吸烟			-0.224^***	0.034	-0.237^***	0.033	-0.221^***	0.034	-0.223^***	0.035	-0.243^***	0.033
是否酗酒			0.125^**	0.041	0.106^**	0.038	0.126^**	0.041	0.125^**	0.041	0.111^**	0.039
抑郁得分					0.015^***	0.004					0.016^***	0.004
出行方式					-0.222^***	0.036					-0.230^***	0.036
吃饭时间					-0.051^*	0.016					-0.048^**	0.015
锻炼时间					0.073^***	0.018					0.070^***	0.017
食用易胖食品频次					0.021	0.021					0.016	0.021
看电视时间					0.103^***	0.018					0.104^***	0.017
睡眠时间					-0.034^**	0.017					-0.032^**	0.016
食用不健康食品频次					0.050^**	0.019					0.053^**	0.020
社区层面
社区性质							0.138^**	0.053			0.114^**	0.055
环境污染							0.049^*	0.031			0.048^*	0.032
道路条件							-0.002^**	0.001			-0.002^*	0.001
省级层面
城市化水平									1.064^**	0.368	0.725^*	0.381
偏差度	85600		84415		83813		84390		84410		82597

Study on the trend and influencing factors of overweight and obesity in Chinese adults under interactions of individual and environment

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 33

Related Articles 15

Metrics

Comments

Recommended 0

[1]	LIANG Xinyuan, JIN Xiaobin, HAN Bo, SUN Rui, ZHANG Xiaolin, ZHOU Yinkang. Landscape multifunctionality change in rapidly urbanized areas of the Yangtze River Delta:A case study of Suzhou City [J]. PROGRESS IN GEOGRAPHY, 2021, 40(2): 207-219.
[2]	FAN Qingyu, YANG Shan. Spatial characteristics and formation mechanism of coordinated development of urbanization in the Yangtze River Delta [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 124-134.
[3]	YE Chao, YU Jie, ZHANG Qingyuan, ZHU Xiaodan. From governance to rural-urban co-governance: Research frontiers, trends, and the Chinese paths [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 15-27.
[4]	ZENG Guojun, XU Yuchen, WANG Longjie, ZHONG Shuru. From localization to de-localization and re-localization: Transformation of the human-land relationship in China’s urbanization process [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 28-39.
[5]	LI Bohua, LI Xue, CHEN Xinxin, DOU Yindi, LIU Peilin. Two-wheel driven construction of characteristic tourist towns under the background of new urbanization [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 40-49.
[6]	CHEN Mingxing, HUANG Xinrong, HUANG Gengzhi, YANG Yanshan. New urbanization and informal employment: Scale, pattern, and social integration [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 50-60.
[7]	AO Xue, ZHAI Qingfei, CUI Yan, ZHOU Xiaoyu, SHEN Lidu, ZHAO Chunyu, Ning Xilong. Detection of urbanization effect on the climate change in Liaoning Province based on empirical orthogonal function methods [J]. PROGRESS IN GEOGRAPHY, 2020, 39(9): 1532-1543.
[8]	XIAO Lei, PAN Jie. Re-examination of urbanization paths and mechanism in population outflow areas: A case study of counties in Sichuan Province [J]. PROGRESS IN GEOGRAPHY, 2020, 39(3): 402-409.
[9]	LIN Liyue, ZHU Yu, KE Wenqian. Changes in the form of population migration and mobility in China and corresponding policy responses at the late-intermediate stage of urbanization [J]. PROGRESS IN GEOGRAPHY, 2020, 39(12): 2054-2067.
[10]	XU Zening,GAO Xiaolu,WU Danxian,LIAO Liuwen. Change of rural human resources from 2000 to 2010 in China [J]. PROGRESS IN GEOGRAPHY, 2019, 38(8): 1259-1270.
[11]	Chunjiang LI, Jing MA, Yanwei CHAI, Mei-Po KWAN. Influence of neighborhood environment and noise pollution on residents’ mental health in Beijing [J]. PROGRESS IN GEOGRAPHY, 2019, 38(7): 1103-1110.
[12]	Li WANG, Jianjun ZHANG. The process of place identity iteration from a life-course perspective: An analysis of individual-family mobility [J]. PROGRESS IN GEOGRAPHY, 2019, 38(6): 896-903.
[13]	Kangmin WEN, Guoyu REN, Jiao LI, Yuyu REN, Xiubao SUN, Yaqing ZHOU, Aiying ZHANG. Adjustment of urbanization bias in surface air temperature over the mainland of China [J]. PROGRESS IN GEOGRAPHY, 2019, 38(4): 600-611.
[14]	DING Kaixi, ZHANG Liping, SONG Xiaomeng, SHE Dunxian, XIA Jun. Temporal and spatial features of precipitation and impact of urbanization on precipitation characteristics in flood season in Beijing [J]. PROGRESS IN GEOGRAPHY, 2019, 38(12): 1917-1932.
[15]	Xuegang CUI, Chuanglin FANG, Jun LI, Haimeng LIU, Qiang ZHANG. Progress in dynamic simulation modeling of urbanization and ecological environment coupling [J]. PROGRESS IN GEOGRAPHY, 2019, 38(1): 111-125.