Systematic review into city interventions to address obesity.

Systematic review into city interventions to address obesity.
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对解决肥胖问题的城市干预措施进行系统评价。

DOI:
10.1016/j.eclinm.2020.100710
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发表时间:
2021-03
期刊:
影响因子:
15.1
通讯作者:
Darzi A
Darzi A
中科院分区:
医学1区
文献类型:
--
作者:
Danielli S;Coffey T;Ashrafian H;Darzi A

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肥胖威胁着过去两个世纪在预期寿命方面所取得的进步。它不成比例地影响到较低的社会经济和少数民族群体,并已成为21世纪最重要的全球卫生挑战之一。虽然肥胖并不局限于城市人口,但城市是世界上超过一半的人口的家园,其中集中了肥胖的高风险群体。长期以来,城市也一直是社会和技术变革的前沿,这些变革导致了我们目前的肥胖环境。这项研究的目的是系统地确定解决肥胖问题的全市干预措施,从而为城市的政策制定者、卫生系统领导人和政治领导人提供建议。根据PRISMA指南进行的系统评估,检查Embase、Ovid Medline、Central、Scope us、Campbell图书馆、CINALH、Health Business Elite、Health Management Information Consortium(HMIC)、PYSCHINFO和PROSPERO。没有对物品类型、日期范围或地理位置的限制。除了经典的学术资源,人们还寻找和评论了书籍和政策白皮书。无论研究设计或感知的方法质量如何,都纳入了描述全市范围内为减少肥胖而进行干预的研究。只有英语语言的研究包括在内。寻找和提取的主要结果指标是:肥胖减少、体重减轻和/或BMI减少。在没有说明主要结果指标的情况下,确定并记录任何其他次要影响措施。这篇手稿代表了对Propero研究数据子集的主题分析,注册号:CRD42020166210我们的搜索产生了42,137条原始引用,其中1614条符合纳入标准,96条编码与肥胖有关。从1997年到2019年的96次引用是在36个城市进行的,其中13次引用要么没有说明一个城市,要么覆盖了五大洲的多个城市。出版物比例最高的是北美(59/96),特别是美国(56/96)和纽约市(23/96)。在确定的研究中,只有四分之一说明了主要成果指标(24/96)。总体而言,研究设计、描述方法和出版物类型各不相同,大多数是使用定性评估工具的描述性文本。为了解决肥胖问题,需要在个人、社区和城市层面采取多层次、多组成部分的干预措施。报告提供了城市可以用来解决肥胖问题的一系列干预措施。这些干预措施还将有益于环境,并表明个人健康和地球健康密不可分,应视为一体。无
Obesity threatens to undo the improvements that have been made in life expectancy over the last two centuries. It disproportionately affects lower socioeconomic and ethnic minority groups and has become one of the most important global health challenges of the 21stcentury. Whilst obesity is not confined to city populations, cities are home to more than half of the world's population with concentrated groups at high risk of obesity. Cities have also long been the forefront of social and technological change that has led to our current obesogenic environment. The aim of this study was to systematically identify city-wide interventions to address obesity, from which recommendations for policy makers, health system leaders and political leaders in cities could be made. Systematic review, conducted according to PRISMA guidelines, examining Embase, Ovid Medline, Central, Scopus, Campbell Library, CINALH, Health Business Elite; Health Management Information Consortium (HMIC), PyschINFO and Prospero. No restrictions on article type, date range or geographic location were applied. Along with classic academic sources, books and policy white papers were sought and reviewed. Studies that described a city-wide intervention to reduce obesity were included, irrespective of study design or perceived methodological quality. Only studies in English language were included. The primary outcome indicators that were sought and extracted were: reduction in obesity, reduction in weight and/or reduction in BMI. Where a primary outcome indicator was not stated, any other secondary impact measure was identified and recorded. This manuscript represents thematic analysis of a sub-set of data from the Prospero study, registration number: CRD42020166210 Our search yielded 42,137 original citations of which 1614 met the inclusion criteria and 96 were coded as relating to obesity. The 96 citations, ranging in year of publication 1997 to 2019, were conducted in 36 cities, with 13 citations either not stating a city or covering multiple cities, across 5 continents. The highest proportion of publications were from North America (59 / 96) and in particular the USA (56/96) and New York City (23/96). Primary outcome indicators were only stated in one quarter of the identified studies (24/96). Overall, there was heterogeneity of study design, descriptive methodologies and publication types, with a majority being descriptive texts using qualitative instruments of assessment. Multi-level and multi-component interventions, at the individual, community and city level, done in concert, are needed to address obesity. A composite of interventions that cities can utilise to address obesity is provided. These interventions will also be beneficial to the environment and make the case that personal health and planetary health are inextricably linked and should be considered as one. None
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影响因子: 7.1
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