Research update on the co-occurrence and clustering model of obesity-related health risky behaviors in children and adolescents
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摘要: 超重肥胖危害着儿童的身心健康, 并且与其成人期高血压和糖尿病等慢性疾病的患病风险增高有关。健康危险行为作为儿童超重肥胖的重要原因, 往往不是单一发生而是表现为多种行为的共存, 且共存的健康效应是协同作用。因此, 提示需要针对健康危险行为综合施策, 同时改善多种可变的行为, 干预措施才可能更具成本效益且能最大限度地扩大影响。通过综述国内外肥胖相关健康危险行为共存及其模式的研究现状, 概述目前研究的不足并讨论未来的研究方向, 为儿童青少年超重肥胖的预防与控制提供研究基础。Abstract: Overweight and obesity among children is not only harmful to physical and mental health, but also associated with an increased risk of chronic diseases such as hypertension and diabetes in adulthood. Health-related behavioral factors are one of the most important causes of child overweight and obesity, which commonly co-occur and show a synergistic negative influence on health. The synergistic effects suggest that interventions are likely to be more cost-effective and to maximize impact by targeting health risk behaviors in combination with the improvement of a variety of modificable behaviors. The present review aims to describe the update of co-occurrence and clustering patterns of obesity-related health risk behaviors, and proposes the future direction for prevention and control of overweight and obesity in children.
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Key words:
- Obesity /
- Dangerous behavior /
- Overweight /
- Child /
- Adolescent
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在过去的30年里,儿童青少年的超重和肥胖患病率在全球范围内大幅上升[1]。儿童青少年时期肥胖不仅危害儿童身心健康,还与成人期患高血压和糖尿病等慢性疾病的风险增高有关[2]。有研究表明,儿童超重肥胖往往是遗传、环境和行为等多种因素相互作用的结果[3],其中行为因素是导致肥胖的重要因素。近年来,越来越多的研究发现,健康危险行为不是单一发生而是表现为多种行为的共存,且其共存的健康效应往往是协同作用[4-7],而非叠加作用。提示对健康危险行为应综合施策,同时改善多种可变的行为,干预措施才可能更具成本效益并能最大限度扩大影响。因此,本文将综述国内外肥胖相关健康危险行为共存及其模式的研究现状,并讨论未来的研究方向。
1. 肥胖相关健康危险行为共存现状
行为共存(co-occurence)指多种健康危险行为往往同时发生,或者一种行为的发生增加另一种行为发生的可能性[8-9]。大量研究发现,肥胖相关健康危险行为包括低摄入蔬菜水果、高摄入含糖饮料、高热量零食的摄入、体力活动不足、久坐行为、睡眠时间缩短等[10-15]。目前,越来越多的研究证据表明以上行为往往同时发生,尤其是在儿童青少年中。如Sanchez等[4]在11~15岁的青少年中发现,近80%有多种饮食和体力活动不足的危险因素。在来自澳大利亚的1 568名六、八和十年级具有代表性的人口样本中,Hardy等[16]发现约51%的男生和43%的女生有3个或更多的肥胖相关健康危险行为,包括低体力活动、高屏幕时间、低蔬菜水果摄入、大量饮用含糖饮料或摄入零食。
肥胖相关健康危险行为发生存在一定的模式。有发达国家已经开始研究健康危险行为共存及行为共存模式。如美国的一项队列研究的基线数据,发现了四年级儿童中“久坐时间长、高糖/高脂零食摄入及无健康意识模式”“体力活动高和健康饮食模式”等多种肥胖相关健康危险行为模式的聚类[17]。日本2018年一项数据研究发现5种行为的聚类模式,分别为高体力活动、非视屏久坐-高质量饮食、低体力活动-长睡眠时间、非视屏久坐-低质量饮食、长时间视屏-低睡眠时间[18]。Nelson等[19]利用聚类分析发现,各种体育活动和久坐行为的模式,如电脑游戏和滑板,是青少年到成人期体力活动下降程度和肥胖发病率的强有力预测因素。不同的健康危险行为以不同的行为模式同时发生,给儿童青少年肥胖的预防和控制带来极大的挑战。
相比国外,国内的研究仍多侧重于单一行为的健康效应。如国内一项15省儿童青少年水果和蔬菜摄入情况研究表明,6~17岁儿童青少年的水果和蔬菜摄入量严重不足[20]。另一项研究表明,青少年每天增加1份含糖饮料, 发生肥胖的风险则会增加1.6倍[21]。仅有少数的学者开始关注肥胖相关健康危险行为共存模式的研究。2019年一项研究探索了长江中下游11市学龄前儿童肥胖相关行为及其聚类性与父母教养行为的关联[22],但是文章仅报告了肥胖相关行为共存的发生率,并未探索相关行为共存模式。综上所述,中国缺乏系统性行为共存模式的研究,仅关注于行为共存的发生率。
2. 行为共存机制作用及理论基础
目前对多种健康危险行为改变的机制了解甚少,仅有部分研究对多种健康行为改变进行了理论建模,还缺乏完整的理论。其中“迁移(Transfer)理论”是目前较为广泛应用于多种行为共存干预的理论之一[23-25]。
迁移理论,也称为结转机制(Carry-over mechanisms, COM)[23]或溢出(Spill-Over)[26],是指一种将资源从一个领域转移到另一个领域的机制,或者将一种行为看作是另一种行为的网关行为[27-30]。也就是说迁移是将在一个环境中获得的经验应用到另一个环境中的过程。经验、技能、知识和自我效能感可以转化为不同的行为和领域。基于迁移理论多种行为的改变有两种类型[30]:(1)迁移效应同时发生。目标行为和非目标行为的变化同时发生[31],同时改变者在改变相关行为时体验到协同效应,并且对自己改变多个目标的能力更有信心[30, 33];(2)迁移效应相继发生。目标行为的改变先于非目标行为的改变,改变者可以集中资源、感知较少目标冲突,从而产生迁移效应,相继改变行为[32]。目前仅有极少的干预实验调查了这两种行为改变类型的健康影响。虽然有3项研究表明在不同的条件下,这两种行为改变的类型对健康影响无差异,但另外2项研究提供了支持顺序干预的证据。未来的研究应该去探索并建立应用于多种健康危险行为改变的理论模型,并通过不同类型的研究进行验证。
3. 行为共存及其模式分析方法
目前关于行为共存的分析方法大致分为共存分析与聚类分析[8-9]。不同的研究往往会使用不同的分析方法,但是这两种方法并不相互排斥。
共存分析是将行为分为有风险和无风险,主要有两种通用方法:(1)报告不同的健康危险行为组合的流行情况,行为共存模式取决于行为的数量。如Pearson等[34]探索体力活动不足、早餐摄入量及蔬菜摄入3种行为的共存模式,行为的组合模式有8种。研究者往往倾向于报告自己感兴趣的行为组合;(2)按照变量判定标准,将每种危险行为的发生即有危险,记为1分,加和每个研究对象所有的危险行为的个数,形成一个“共存指数”,报告不同行为模式指数的流行程度。如Hausdorf等[35]研究吸烟、饮酒、肥胖、缺乏体育活动、日晒和水果蔬菜摄入不足的行为共存模式,则共存指数为0~6,描述每个指数的发生概率。
聚类分析是探索共同发生的健康相关行为间的潜在关联[9]。也存在两种主要方法:(1)计算行为的发生风险值(prevalence odds ratios, POR),是指在另一种危险行为普遍存在的情况下,存在某种危险行为的相对概率。当危险行为同时发生的概率大于单独发生概率时,即POR>1为行为聚类;(2)通过更高级的统计方法确定行为共存模式,如聚类分析、潜在类别分析、因子分析等,通过数据挖掘潜在的行为共存模式。现在的研究多采用聚类分析来探索多种行为的共存模式[36-37]。
4. 行为共存影响因素
已有研究发现,较大年龄的儿童更易出现健康危险行为的共存且共存模式会随时间改变,如英国[38]和澳大利亚[39]的两项研究结果表明,随着孩子年龄的增长,他们会变得更久坐,更少运动。另外相比于高经济水平的儿童,来自于低经济水平家庭的儿童青少年更易同时出现多种健康危险行为[40-42],其中女生更易出现低体力活动和高静坐时间的行为模式[43]。但是在澳大利亚两项涉及到5~7岁儿童的研究[44-45]中,并没有发现行为共存模式的性别差异。因此未来的研究应关注多种因素如社会人口学因素、家庭因素、社区因素、学校因素等对肥胖相关健康危险行为的影响。
5. 研究局限与不足
尽管国内外学者已经开始关注儿童青少年肥胖相关健康危险行为共存及行为共存模式,但是研究仍存在问题。
5.1 研究主题
健康危险行为共存及其行为模式研究多集中于成人,在儿童青少年人群中的研究较少。2020年一项系统综述在5~12岁儿童的健康危险行为共存的研究中仅发现19篇肥胖相关健康危险行为的研究[46]。此外,该领域的研究多局限于几种特定行为,如部分研究关注于体力活动不足与久坐行为的行为共存模式[19, 47-48],有研究关注于饮食与体力活动的共存及其模式对于肥胖的影响[38],但多种且全面的肥胖相关健康危险行为共存及其模式的研究较少。
5.2 研究类型
研究多为横断面研究,队列研究及干预研究较少。如日本一项研究通过横断面研究确定了8 015名成年人中4种健康危险行为(吸烟状态、饮酒、卡路里摄入量和每天的步数)独特的行为共存模式[49]。队列研究及干预研究可以为个人和社会因素对健康危险行为的影响提供更有力的证据。可以更多地了解潜在的可改变因素如自我控制或父母行为在多种健康风险行为干预中的作用,将有助于针对多种健康风险行为的干预策略构建。Mawditt等[50]通过英国两项出生队列,探索了吸烟、酒精、饮食、体育活动4种行为共存模式的性别差异。Akasaki等[51]利用1970年英国队列研究中8 754名参与者的数据分析了青少年健康危险行为的共存模式及其中年时健康后果,发现青少年参与多种危险行为是晚年健康不平等的一个重要因素。在Mata等[27]的干预研究中,向肥胖女性提供了一种增加体育活动行为的干预,研究发现干预组不仅改善了身体活动,还改善了女性的饮食习惯。与对照组相比,Prochaska等[52]研究发现针对多种行为的干预措施,在改变所有目标行为方面是有效的。
6. 总结与挑战
鉴于肥胖相关健康危险行为的共存对儿童青少年超重肥胖的协同作用,从肥胖相关健康危险行为来开展对儿童超重肥胖的防控就显得十分重要及迫切。未来的研究应专注于以下方向:(1)增加对儿童青少年肥胖相关健康危险行为共存及共存模式的研究,根据中国的文化差异,得出中国儿童青少年肥胖相关健康危险行为的共存模式,为儿童超重肥胖的干预提供思路;(2)拓展研究类型,多采用队列研究及干预研究或是多种研究类型相结合的方法,提供强有力的证据;(3)未来研究应去探索行为共存背后的理论或者是共存行为之间的交互作用的机制,探索行为共存机制,为干预研究提供研究基础。
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[1] HERNÁNDEZ-CORDERO S, CUEVAS-NASU L, MORÁN-RUÁN M C, et al. Overweight and obesity in Mexican children and adolescents during the last 25 years[J]. Nutr Diabet, 2017, 7(3): e247. doi: 10.1038/nutd.2016.52 [2] KUMAR S, KAUFMAN T. Childhood obesity[J]. Panmin Med, 2018, 60(4): 200-212. [3] KUMAR S, KELLY A S. Review of childhood obesity: from epidemiology, etiology, and comorbidities to clinical assessment and treatment[J]. Mayo Clin Proc, 2017, 92(2): 251-265. doi: 10.1016/j.mayocp.2016.09.017 [4] SANCHEZ A, NORMAN G J, SALLIS J F, et al. Patterns and correlates of physical activity and nutrition behaviors in adolescents[J]. Am J Prev Med, 2007, 32(2): 124-130. doi: 10.1016/j.amepre.2006.10.012 [5] OTTEVAERE C, HUYBRECHTS I, BENSER J, et al. Clustering patterns of physical activity, sedentary and dietary behavior among european adolescents: the helena study[J]. BMC Public Health, 2011, 11: 328. doi: 10.1186/1471-2458-11-328 [6] BOONE-HEINONEN J, GORDON-LARSEN P, ADAIR L S. Obesogenic clusters: multidimensional adolescent obesity-related behaviors in the U. S[J]. Ann Behav Med, 2008, 36(3): 217-230. doi: 10.1007/s12160-008-9074-3 [7] DE VRIES H, VAN'T RIET J, SPIGT M, et al. Clusters of lifestyle behaviors: results from the Dutch SMILE study[J]. Prev Med, 2008, 46(3): 203-208. doi: 10.1016/j.ypmed.2007.08.005 [8] MEADER N, KING K, MOE-BYRNE T, et al. A systematic review on the clustering and co-occurrence of multiple risk behaviors[J]. BMC Public Health, 2016, 16(1): 657. doi: 10.1186/s12889-016-3373-6 [9] MCALONEY K, GRAHAM H, LAW C, et al. A scoping review of statistical approaches to the analysis of multiple health-related behaviors[J]. Prev Med, 2013, 56(6): 365-371. doi: 10.1016/j.ypmed.2013.03.002 [10] ROBLIN L. Childhood obesity: food, nutrient, and eating-habit trends and influences[J]. Appl Physiol Nutr Metab, 2007, 32(4): 635-645. doi: 10.1139/H07-046 [11] QIN P, LI Q, ZHAO Y, et al. Sugar and artificially sweetened beverages and risk of obesity, type 2 diabetes mellitus, hypertension, and all-cause mortality: a dose-response Meta-analysis of prospective cohort studies[J]. Eur J Epidemiol, 2020, 35(7): 655-671. doi: 10.1007/s10654-020-00655-y [12] WILLIAMSON V G, DILIP A, DILLARD J R, et al. The influence of socioeconomic status on snacking and weight among adolescents: a scoping review[J]. Nutrients, 2020, 12(1): 167. doi: 10.3390/nu12010167 [13] PETERMANN-ROCHA F, BROWN R E, DIAZ-MARTÍNEZ X, et al. Association of leisure time and occupational physical activity with obesity and cardiovascular risk factors in Chile[J]. J Sports Sci, 2019, 37(22): 2549-2559. doi: 10.1080/02640414.2019.1647738 [14] VAN DE KOLK I, GERARDS S M P L, HARMS L S E, et al. The effects of a comprehensive, integrated obesity prevention intervention approach (super fit) on children's physical activity, sedentary behavior, and BMI Z-score[J]. Int J Environ Res Public Health, 2019, 16(24): 5016. doi: 10.3390/ijerph16245016 [15] WIDOME R, LENK K M, LASKA M N, et al. Sleep duration and weight-related behaviors among adolescents[J]. Child Obes, 2019, 15(7): 434-442. doi: 10.1089/chi.2018.0362 [16] HARDY L L, GRUNSEIT A, KHAMBALIA A, et al. Co-occurrence of obesogenic risk factors among adolescents[J]. J Adolesc Health, 2012, 51(3): 265-271. doi: 10.1016/j.jadohealth.2011.12.017 [17] HUH J, RIGGS N R, SPRUIJT-METZ D, et al. Identifying patterns of eating and physical activity in children: a latent class analysis of obesity risk[J]. Obesity(Silver Spring), 2011, 19(3): 652-658. [18] CABANAS-SÁNCHEZ V, MARTÍNEZ-GÓMEZ D, IZQUIERDO-GÓMEZ R, et al. Association between clustering of lifestyle behaviors and health-related physical fitness in youth: the UP&DOWN study[J]. J Pediatr, 2018, 199: 41-48. doi: 10.1016/j.jpeds.2018.03.075 [19] NELSON M C, GORDON-LARSEN P, ADAIR L S, et al. Adolescent physical activity and sedentary behavior: patterning and long-term maintenance[J]. Am J Prev Med, 2005, 28(3): 259-266. doi: 10.1016/j.amepre.2004.12.006 [20] 李丽, 欧阳一非, 王惠君, 等. 中国15省儿童青少年蔬菜和水果摄入状况[J]. 中国健康教育, 2020, 36(1): 3-7.LI L, OUYANG Y F, WANG H J, et al. Status of fruit and vegetable intake among children and adolescents in 15 provinces of China[J]. Chin J Health Educ, 2020, 36(1): 3-7. [21] HE B, LONG W, LI X, et al. Sugar-sweetened beverages consumption positively associated with the risks of obesity and hypertriglyceridemia among children aged 7-18 years in south China[J]. J Atheroscl Thromb, 2018, 25(1): 81-89. doi: 10.5551/jat.38570 [22] 江流. 长江中下游11市学龄前儿童肥胖相关行为及其聚集性与父母教养行为的关联性研究[D]. 合肥: 安徽医科大学, 2019.JIANG L. Parenting behaviors and obesogenic behaviors and their clustering: a cross-section study from 11 cities in middle and lower reaches of Yangtze River[D]. Hefei: Anhui Medical University, 2019. [23] BARNETT S M, CECI S J. When and where do we apply what we learn?A taxonomy for far transfer[J]. Psychol Bull, 2002, 128(4): 612-637. doi: 10.1037/0033-2909.128.4.612 [24] LIPPKE S, NIGG C R, MADDOCK J E. Health-promoting and health-risk behaviors: theory-driven analyses of multiple health behavior change in three international samples[J]. Int J Behav Med, 2012, 19(1): 1-13. doi: 10.1007/s12529-010-9135-4 [25] GELLER K, LIPPKE S, NIGG C R. Future directions of multiple behavior change research[J]. J Behav Med, 2017, 40(1): 194-202. doi: 10.1007/s10865-016-9809-8 [26] MATA J, SILVA M N, VIEIRA P N, et al. Motivational "spill-over" during weight control: increased self-determination and exercise intrinsic motivation predict eating self-regulation[J]. Health Psychol, 2009, 28(6): 709-716. doi: 10.1037/a0016764 [27] DUTTON G R, NAPOLITANO M A, WHITELEY J A, et al. Is physical activity a gateway behavior for diet?Findings from a physical activity trial[J]. Prev Med, 2008, 46(3): 216-221. doi: 10.1016/j.ypmed.2007.12.012 [28] FLEIG L, LIPPKE S, POMP S, et al. Intervention effects of exercise self-regulation on physical exercise and eating fruits and vegetables: a longitudinal study in orthopedic and cardiac rehabilitation[J]. Prev Med, 2011, 53(3): 182-187. doi: 10.1016/j.ypmed.2011.06.019 [29] FLEIG L, KERSCHREITER R, SCHWARZER R, et al. Sticking to a healthy diet is easier for me when I exercise regularly': cognitive transfer between physical exercise and healthy nutrition[J]. Psychol Health, 2014, 29(12): 1361-1372. doi: 10.1080/08870446.2014.930146 [30] FLEIG L, KVPER C, LIPPKE S, et al. Cross-behavior associations and multiple health behavior change: a longitudinal study on physical activity and fruit and vegetable intake[J]. J Health Psychol, 2015, 20(5): 525-534. doi: 10.1177/1359105315574951 [31] ANNESI J J. Supported exercise improves controlled eating and weight through its effects on psychosocial factors: extending a systematic research program toward treatment development[J]. Perm J, 2012, 16(1): 7-18. doi: 10.7812/11-136 [32] NIGG C R, LEE H, HUBBARD A E, et al. Gateway health behaviors in college students: Investigating transfer and compensation effects[J]. J Am Coll Health, 2009, 58(1): 39-44. doi: 10.3200/JACH.58.1.39-44 [33] JUNG M E, BRAWLEY L R. Concurrent self-regulatory efficacy as a mediator of the goal: exercise behavior relationship[J]. J Health Psychol, 2013, 18(5): 601-611. doi: 10.1177/1359105313479238 [34] PEARSON N, ATKIN A J, BIDDLE S J, et al. Patterns of adolescent physical activity and dietary behaviors[J]. Int J Behav Nutr Phys Act, 2009, 6: 45. doi: 10.1186/1479-5868-6-45 [35] HAUSDORF K, EAKIN E, WHITEMAN D, et al. Prevalence and correlates of multiple cancer risk behaviors in an Australian population-based survey: results from the Queensland Cancer Risk Study[J]. Cancer Causes Control, 2008, 19(10): 1339-1347. doi: 10.1007/s10552-008-9205-y [36] NAVARRO SILVERA S A, MAYNE S T, RISCH H A, et al. Principal component analysis of dietary and lifestyle patterns in relation to risk of subtypes of esophageal and gastric cancer[J]. Ann Epidemiol, 2011, 21(7): 543-550. doi: 10.1016/j.annepidem.2010.11.019 [37] LYU J, LIU Q, REN Y, et al. Community Interventions for Health (CIH) collaboration. Socio-demographic association of multiple modifiable lifestyle risk factors and their clustering in a representative urban population of adults: a cross-sectional study in Hangzhou, China[J]. Int J Behav Nutr Phys Act, 2011, 8: 40. doi: 10.1186/1479-5868-8-40 [38] LEECH R M, MCNAUGHTON S A, TIMPERIO A. Clustering of diet, physical activity and sedentary behavior among Australian children: cross-sectional and longitudinal associations with overweight and obesity[J]. Int J Obes(Lond), 2015, 39(7): 1079-1085. doi: 10.1038/ijo.2015.66 [39] JAGO R, FOX K R, PAGE A S, et al. Physical activity and sedentary behavior typologies of 10-11 years old[J]. Int J Behav Nutr Phys Act, 2010, 7: 59. doi: 10.1186/1479-5868-7-59 [40] FERNÁNDEZ-ALVIRA J M, DE BOURDEAUDHUIJ I, SINGH A S, et al. Clustering of energy balance-related behaviors and parental education in European children: the ENERGY-project[J]. Int J Behav Nutr Phys Act, 2013, 10: 5. doi: 10.1186/1479-5868-10-5 [41] GUBBELS J S, KREMERS S P, GOLDBOHM R A, et al. Energy balance-related behavioral patterns in 5-year-old children and the longitudinal association with weight status development in early childhood[J]. Public Health Nutr, 2012, 15(8): 1402-1410. doi: 10.1017/S1368980011003089 [42] LIORET S, TOUVIER M, LAFAY L, et al. Dietary and physical activity patterns in French children are related to overweight and socioeconomic status[J]. J Nutr, 2008, 138(1): 101-107. doi: 10.1093/jn/138.1.101 [43] JAGO R, SALWAY R, LAWLOR D A, et al. Profiles of children's physical activity and sedentary behavior between age 6 and 9: a latent profile and transition analysis[J]. Int J Behav Nutr Phys Act, 2018, 15(1): 103. doi: 10.1186/s12966-018-0735-8 [44] LEECH R M, MCNAUGHTON S A, TIMPERIO A. Clustering of children's obesity-related behaviors: associations with sociodemographic indicators[J]. Eur J Clin Nutr, 2014, 68(5): 623-628. doi: 10.1038/ejcn.2013.295 [45] MAGEE C A, CAPUTI P, IVERSON D C. Patterns of health behaviors predict obesity in Australian children[J]. J Paediatr Child Health, 2013, 49(4): 291-296. doi: 10.1111/jpc.12163 [46] DSOUZA N J, KUSWARA K, ZHENG M, et al. A systematic review of lifestyle patterns and their association with adiposity in children aged 5-12 years[J]. Obes Rev, 2020, 21(8): e13029. [47] TE VELDE S J, DE BOURDEAUDHUIJ I, THORSDOTTIR I, et al. Patterns in sedentary and exercise behaviors and associations with overweight in 9-14-year-old boys and girls-a cross-sectional study[J]. BMC Public Health, 2007, 7: 16. doi: 10.1186/1471-2458-7-16 [48] JONES R A, DOWNING K, RINEHART N J, et al. Physical activity, sedentary behavior and their correlates in children with autism spectrum disorder: a systematic review[J]. PLoS One, 2017, 12(2): e0172482. doi: 10.1371/journal.pone.0172482 [49] MAWDITT C, SASAYAMA K, KATANODA K, et al. The clustering of health-related behaviors in the adult Japanese population[J]. J Epidemiol, 2021, 31(8): 471-479. doi: 10.2188/jea.JE20200120 [50] MAWDITT C, SACKER A, BRITTON A, et al. The clustering of health-related behaviors in a British population sample: testing for cohort differences[J]. Prev Med, 2016, 88: 95-107. doi: 10.1016/j.ypmed.2016.03.003 [51] AKASAKI M, PLOUBIDIS G B, DODGEON B, et al. The clustering of risk behaviors in adolescence and health consequences in middle age[J]. J Adolesc, 2019, 77: 188-197. doi: 10.1016/j.adolescence.2019.11.003 [52] PROCHASKA J O, VELICER W F, ROSSI J S, et al. Multiple risk expert systems interventions: impact of simultaneous stage-matched expert system interventions for smoking, high-fat diet, and sun exposure in a population of parents[J]. Health Psychol, 2004, 23(5): 503-516. doi: 10.1037/0278-6133.23.5.503 期刊类型引用(6)
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