中国职业人群肥胖强化健走处方干预效果评价

郭凯明; 赵一凡; 赵平平; 刘芳; 徐溪; 张朝; 林永青; 周脉耕; 姜莹莹; 蒋炜

doi:10.11847/zgggws1139360

中国职业人群肥胖强化健走处方干预效果评价

doi: 10.11847/zgggws1139360

1.
中国疾病预防控制中心慢性非传染性疾病预防控制中心，北京 100050
2.
中国疾病预防控制中心环境与健康相关产品安全所

详细信息

作者简介:
郭凯明（1996 – ），男，山西运城人，硕士在读，研究方向：慢性病流行病学

通讯作者:
蒋炜，E-mail：jiangwei1980@163.com

中图分类号: R 161
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出版历程
- 接收日期: 2022-06-02
- 网络出版日期: 2022-08-31
- 刊出日期: 2022-12-10

Effect of short-term intensive brisk walking prescription on obesity in Chinese occupational population: a pair matched-control study

1.
Center for the Prevention and Control of Chronic Noncommunicable Diseases, Chinese Center for Disease Control and Prevention, Beijing 100050, China

摘要

摘要: 目的评价中国职业人群肥胖强化健走处方干预效果，为推广适合中国职业人群适宜的体重控制方案提供借鉴。方法基于2021年5 — 8月中国职业人群健走项目，招募来自全国12个省份的31528名在职人员进行为期100 d的健走干预，根据是否接受强化干预分为强化干预组和阳性对照组（强化干预组实施4个健走处方，阳性对照组实行3个健走处方），对完成基线问卷调查和体格检查且健走数据完整的28285名在职人员采用倾向得分匹配，共得到5208对10416名研究对象，比较2组职业人群干预前后体重、体质指数、腰围、臀围和体脂率的变化情况以对中国职业人群肥胖强化健走处方的干预效果进行评价。结果强化干预组职业人群万步率、集中健走率、4个处方完成率、体重监测完成率及阳性对照组万步率、集中健走率、3个处方完成率P₂₅值和平均值均 > 85 %，2组职业人群的干预依从性均较好；强化干预组和阳性对照组职业人群的体重、体质指数、腰围、臀围、体脂率在干预前分别为（65.98 ± 11.86）kg和（65.23 ± 11.87）kg、（23.77 ± 3.29）和（23.78 ± 3.30）、（82.75 ± 10.25）cm和（82.54 ± 10.14）cm、（96.15 ± 7.37）cm和（96.06 ± 7.17）cm、（27.92 ± 6.18）%和（27.75 ± 6.37）%，在干预后分别为（64.18 ± 11.50）kg和（63.86 ± 11.58）kg、（23.18 ± 3.16）和（23.31 ± 3.19）、（81.33 ± 10.05）cm和（81.09 ± 9.99）cm、（95.16 ± 6.88）cm和（94.97 ± 6.70）cm、（26.89 ± 6.11）%和（27.00 ± 6.29）%；干预前后强化干预组和阳性对照组职业人群分别比较，干预前、后2组职业人群的体重、体质指数、腰围、臀围和体脂率差异均有统计学意义（均P < 0.01）；干预前、后2组职业人群比较，干预前强化干预组职业人群的体重高于阳性对照组职业人群（t = – 3.25，P = 0.001）；协方差分析结果显示，干预后强化干预组职业人群的体重、体质指数和体脂率均低于阳性对照组职业人群（均P < 0.01）。通过多水平模型结合倍差法校正性别、年龄、文化程度、职业、居住地、是否患慢性病、慢性病知识得分、心理量表得分和睡眠时间等混杂因素后结果显示，干预后强化干预组职业人群体脂率较阳性对照组多下降了0.29 %（t = – 2.05，P = 0.04）；进一步进行亚组分析结果显示，干预前体质指数水平为超重的职业人群通过强化干预可促进体重、体质指数和体脂率的下降，干预前体质指数水平为肥胖的职业人群通过强化干预可促进体质指数和体脂率的下降，干预前体脂率水平为超重和肥胖的职业人群通过强化干预可促进体脂率的下降。结论 4个健走处方的强化干预模式可进一步降低中国超重和肥胖职业人群的肥胖程度，对体脂率的健康受益更大。
- 强化健走处方 /
- 肥胖 /
- 干预效果 /
- 职业人群
Abstract: Objective To evaluate intervention effect of intensive brisk walking prescription on obesity in Chinese occupational population and to provide a reference for popularizing appropriate weight control program among occupational population in China. Methods All the participants of the study were from a 100-day vigorous walking program conducted among 31 528 in service employees in 12 provincial-level administrative divisions of China during May – August 2021 and the participants were divided into an intervention group required to complete a 4 sets of walking schedule in a day (10, 10, 15, 15 minutes of walking continuously at the speed of 100 – 150 steps per minute) and a positive control group with the same requirement as the intervention group but only 3 sets of waling schedule (10, 10, 15 minutes); the body weight in kg (BW) of the participants were measured at least once a week during the program period. From the 28 285 participants with complete information on baseline questionnaire survey and data on physical examination and vigorous waling, 5 208 pairs of intervention and control individuals were matched by tendency scores. The changes in BW, body mass index (BMI), waist circumference in cm (WC), hip circumference in cm (HC) and body fat rate in % (BFR) of the intervention and control individuals before and after the intervention were compared to evaluate the effect of intensive brisk walking prescription on the obesity indicators. Results For both the intervention and positive control group, the percentages and the 25th percentiles of the proportions of individuals having 10 000 steps walking per day, group walking, completing 4/3 sets of walking schedule, and BW measuring once a week were all more than 85%, indicating a good compliance with the program of the participants. Compared to those at the beginning of the intervention program, there were significant differences at the end of the intervention for both the intervention and the positive control groups in the average values of BW (64.18 ± 11.50 vs. 65.98 ± 11.86 and 63.86 ± 11.58 vs. 65.23 ± 11.87), BMI (23.18 ± 3.16 vs. 23.77 ± 3.29 and 23.31 ± 3.19 vs. 23.78 ± 3.30), WC (81.33 ± 10.05 vs. 82.75 ± 10.25 and 81.09 ± 9.99 vs. 82.54 ± 10.14), HC (95.16 ± 6.88 vs. 96.15 ± 7.37 and 94.97 ± 6.70 vs. 96.06 ± 7.17), and BFR (26.89 ± 6.11 vs. 27.92 ± 6.18 and 27.00 ± 6.29 vs. 27.75 ± 6.37), respectively (all P < 0.01). The BW of the intensive intervention group was significantly higher than that of positive control group at the beginning of the intervention (t = – 3.25, P = 0.0012). The results of covariance analysis showed that the BW, BMI and BFR of the intensive intervention group were significantly lower than those of positive control group by the end of intervention (all P < 0.01). After adjusting confounding factors such as sex, age, residence, education, occupation, chronic disease, score for knowledge about chronic disease, psychological scale score and sleeping time, the results of multilevel model combined with multiple difference method revealed a higher decline of 0.29% in BFR of intensive intervention group compared to that of positive control group at the end of intensive intervention (t = – 2.05, P = 0.04). Further subgroup analysis demonstrated that the intensive intervention promoted the decrease of BW, BMI and BFR for the individuals with the BMI indicating overweight status, the decrease of BMI and BFR for the individuals with the BMI indicating obesity status, and the decrease of BFR for the individuals with the BMI indicating both overweight or obesity at the beginning of the intervention. Conclusion The short-term intensive intervention with four sets of vigorous walking schedule could reduce obesity indicators among overweight and obese in service employees in China, especially for the decline of body fat rate.
- intensive walking prescription /
- obesity /
- intervention effect /
- occupational population

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表 1 中国职业人群干预前、后肥胖相关指标比较（$\bar x \pm s$）

肥胖相关指标	干预前		干预后
肥胖相关指标	强化干预组	阳性对照组	强化干预组	阳性对照组
体重（kg）	65.98 ± 11.86 ^b	65.23 ± 11.87	64.18 ± 11.50 ^ac	63.86 ± 11.58 ^a
体质指数	23.77 ± 3.29	23.78 ± 3.30	23.18 ± 3.16 ^ac	23.31 ± 3.19 ^a
腰围（cm）	82.75 ± 10.25	82.54 ± 10.14	81.33 ± 10.05^a	81.09 ± 9.99 ^a
臀围（cm）	96.15 ± 7.37	96.06 ± 7.17	95.16 ± 6.88 ^a	94.97 ± 6.70 ^a
体脂率（%）	27.92 ± 6.18	27.75 ± 6.37	26.89 ± 6.11 ^ac	27.00 ± 6.29 ^a
注：干预后与干预前同组别比较，a P < 0.01；与干预前阳性对照组比较，b P < 0.01；与干预后阳性对照组比较，c P < 0.01。

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表 2 强化干预对中国职业人群肥胖相关指标效应的亚组分析

亚组		体重	体质指数	腰围	臀围	体脂率
性别	男性	– 0.53（ – 1.35～0.30）	– 0.16（ – 0.42～0.10）	0.11（ – 0.62～0.84）	0.07（ – 0.52～0.65）	– 0.28（ – 0.64～0.09）
	女性	– 0.37（ – 0.93～0.19）	– 0.12（ – 0.32～0.08）	– 0.02（ – 0.58～0.55）	– 0.02（ – 0.49～0.44）	– 0.33（ – 0.68～0.03）
年龄（岁）	20～29	– 0.11（ – 1.30～1.09）	– 0.01（ – 0.43～0.40）	0.03（ – 1.09～1.15）	– 0.14（ – 1.05～0.77）	– 0.02（ – 0.75～0.70）
	30～39	– 0.62（ – 1.56～0.32）	– 0.23（ – 0.55～0.09）	0.07（ – 0.83～0.96）	– 0.10（ – 0.83～0.64）	– 0.49（ – 1.01～0.03）
	40～49	– 0.59（ – 1.32～0.15）	– 0.18（ – 0.43～0.06）	0.07（ – 0.62～0.76）	0.15（ – 0.42～0.72）	– 0.38（ – 0.77～0.01）
	50～65	– 0.12（ – 1.18～0.94）	– 0.02（ – 0.35～0.32）	– 0.11（ – 1.10～0.87）	0.03（ – 0.76～0.83）	– 0.15（ – 0.68～0.38）
干预前体质指数水平	正常	– 0.23（ – 0.64～0.18）	– 0.06（ – 0.18～0.07）	0.13（ – 0.32～0.59）	0.11（ – 0.28～0.51）	– 0.25（ – 0.52～0.01）
	超重	– 0.61（ – 1.15～ – 0.07） ^a	– 0.20（ – 0.33～ – 0.06） ^b	– 0.14（ – 0.75～0.46）	– 0.09（ – 0.61～0.44）	– 0.29（ – 0.51～ – 0.07） ^a
	肥胖	– 1.08（ – 2.18～0.03）	– 0.41（ – 0.74～ – 0.07） ^a	0.45（ – 0.78～1.68）	0.11（ – 0.96～1.18）	– 0.65（ – 1.05～ – 0.25） ^b
干预前腰围水平	正常	– 0.35（ – 0.85～0.15）	– 0.10（ – 0.27～0.07）	– 0.02（ – 0.40～0.37）	0.15（ – 0.27～0.58）	– 0.28（ – 0.60～0.05）
	中心性肥胖前期	– 0.42（ – 1.13～0.30）	– 0.14（ – 0.39～0.11）	– 0.02（ – 0.35～0.31）	– 0.04（ – 0.61～0.53）	– 0.25（ – 0.68～0.17）
	中心性肥胖	– 0.57（ – 1.37～0.23）	– 0.16（ – 0.42～0.11）	0.16（ – 0.42～0.74）	– 0.13（ – 0.71～0.45）	– 0.34（ – 0.72～0.03）
干预前体脂率水平	正常	– 0.29（ – 0.96～0.37）	– 0.05（ – 0.24～0.14）	0.14（ – 0.53～0.81）	0.04（ – 0.52～0.61）	0.06（ – 0.27～0.39）
	超重	– 0.42（ – 0.95～0.11）	– 0.10（ – 0.24～0.04）	0.17（ – 0.44～0.77）	0.16（ – 0.36～0.68）	– 0.36（ – 0.57～ – 0.16） ^b
	肥胖	– 0.53（ – 1.19～0.13）	– 0.20（ – 0.42～0.02）	– 0.22（ – 0.90～0.47）	– 0.19（ – 0.76～0.39）	– 0.49（ – 0.81～ – 0.16） ^b
注：a P < 0.05；b P < 0.01。

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参考文献(28)

[1]	World Health Organization. Obesity and overweight[EB/OL]. (2021 – 04 – 11)[2022 – 03 – 11]. https://www.who.int/zh/news-room/fact-sheets/detail/obesity-and-overweight.
[2]	Wang LM, Zhou B, Zhao ZP, et al. Body - mass index and obesity in urban and rural China: findings from consecutive nationally represen-tative surveys during 2004 – 18[J]. The Lancet, 2021, 398(10294): 53 – 63. doi: 10.1016/S0140-6736(21)00798-4
[3]	Pan XF, Wang LM, Pan A. Epidemiology and determinants of obesity in China[J]. The Lancet Diabetes and Endocrinology, 2021, 9(6): 373 – 392. doi: 10.1016/S2213-8587(21)00045-0
[4]	Seravalle G, Grassi G. Obesity and hypertension[J]. Pharmacological Research, 2017, 122: 1 – 7. doi: 10.1016/j.phrs.2017.05.013
[5]	Riaz H, Khan MS, Siddiqi TJ, et al. Association between obesity and cardiovascular outcomes: a systematic review and meta-analysis of Mendelian randomization studies[J]. JAMA Network Open, 2018, 1(7): e183788. doi: 10.1001/jamanetworkopen.2018.3788
[6]	Powell-Wiley TM, Poirier P, Burke LE, et al. Obesity and cardio-vascular disease: a scientific statement from the American heart association[J]. Circulation, 2021, 143(21): e984 – e1010.
[7]	Csige I, Ujvárosy D, Szabó Z, et al. The impact of obesity on the cardiovascular system[J]. Journal of Diabetes Research, 2018, 2018: 3407306.
[8]	The Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration (BMI Mediated Effects). Metabolic mediators of the effects of body - mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1·8 million participants[J]. The Lancet, 2014, 383(9921): 970 – 983. doi: 10.1016/S0140-6736(13)61836-X
[9]	Zhou MG, Wang HD, Zeng XY, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990 – 2017: a systematic analysis for the global burden of disease study 2017[J]. The Lancet, 2019, 394(10204): 1145 – 1158. doi: 10.1016/S0140-6736(19)30427-1
[10]	Peñalvo JL, Sagastume D, Mertens E, et al. Effectiveness of work-place wellness programmes for dietary habits, overweight, and cardiometabolic health: a systematic review and meta - analysis[J]. The Lancet Public Health, 2021, 6(9): e648 – e660. doi: 10.1016/S2468-2667(21)00140-7
[11]	Muollo V, Rossi AP, Milanese C, et al. The effects of exercise and diet program in overweight people-Nordic walking versus walk-ing[J]. Clinical Interventions in Aging, 2019, 14: 1555 – 1565. doi: 10.2147/CIA.S217570
[12]	Runenko SD, Achkasov EE, Volodina KA, et al. Nordic walking as an effective physical activity for weight loss among overweight young adults in high schools[J]. The Journal of Sports Medicine and Physical Fitness, 2020, 60(2): 294 – 301.
[13]	Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure[J]. Journal of General Internal Medicine, 2001, 16(9): 606 – 613. doi: 10.1046/j.1525-1497.2001.016009606.x
[14]	Spitzer RL, Kroenke K, Williams JBW, et al. A brief measure for assessing generalized anxiety disorder: the GAD - 7[J]. Archives of Internal Medicine, 2006, 166(10): 1092 – 1097. doi: 10.1001/archinte.166.10.1092
[15]	祁冰洁, 胥馨尹, 张新, 等. 四川省慢性病核心信息知晓情况分析[J]. 现代预防医学, 2022, 49(5): 918 – 921.
[16]	中华人民共和国国家卫生和计划生育委员会. WS/T 428 — 2013成人体重判定[S]. 北京: 中国标准出版社, 2013.
[17]	郭吟, 陈文鹤. 肥胖症与运动减肥效果的影响因素[J]. 上海体育学院学报, 2010, 34(3): 64 – 66,94. doi: 10.3969/j.issn.1000-5498.2010.03.016
[18]	蒋炜, 赵一凡, 杨幸子, 等. 2016年中国职业人群健走激励效果及相关因素分析[J]. 中华预防医学杂志, 2018, 52(5): 517 – 523. doi: 10.3760/cma.j.issn.0253-9624.2018.05.011
[19]	宋俊辰, 李红娟, 蒋玖君, 等. 健步走对职业人群健康相关指标干预效果及影响因素研究[J]. 中国慢性病预防与控制, 2020, 28(7): 518 – 523.
[20]	徐海峰, 汤海英, 罗卫平, 等. 不同健走强度对职业人群身体指标变化的影响[J]. 中国预防医学杂志, 2021, 22(6): 451 – 454.
[21]	李镒冲, 赵一凡, 杨幸子, 等. 短期健走干预对职业人群体重指数、腰围及其相关指标的影响[J]. 中华预防医学杂志, 2019, 53(2): 212 – 217.
[22]	陈先献, 徐聪, 任杰, 等. 健步走对职业人群慢性病相关健康指标的影响[J]. 中国慢性病预防与控制, 2021, 29(10): 786 – 789.
[23]	李智文, 任爱国. 倾向评分法在SAS软件中的实现[J]. 中国生育健康杂志, 2010, 21(5): 320,封3,封4,297.
[24]	Mache S, Jensen S, Linnig S, et al. Do overweight workers profit by workplace health promotion, more than their normal - weight peers? Evaluation of a worksite intervention[J]. Journal of Occupa-tional Medicine and Toxicology, 2015, 10(1): 28. doi: 10.1186/s12995-015-0068-3
[25]	Melam GR, Alhusaini AA, Buragadda S, et al. Impact of brisk walking and aerobics in overweight women[J]. Journal of Physical Therapy Science, 2016, 28(1): 293 – 297. doi: 10.1589/jpts.28.293
[26]	Estrada RK, Bacardí-Gascon M, Jiménez-Cruz A. Efficacy of self - monitoring in weight loss: a systematic review of randomized con-trolled studies[J]. Nutricion Hospitalaria, 2015, 32(6): 2472 – 2477.
[27]	Berry R, Kassavou A, Sutton S. Does self - monitoring diet and physical activity behaviors using digital technology support adults with obesity or overweight to lose weight? A systematic literature review with meta-analysis[J]. Obesity Reviews, 2021, 22(10): e13306.
[28]	Painter SL, Ahmed R, Hill JO, et al. What matters in weight loss? An in - depth analysis of self - monitoring[J]. Journal of Medical Inter-net Research, 2017, 19(5): e160. doi: 10.2196/jmir.7457