The public health burden caused by overweight, obesity (OO) and type-2 diabetes (T2D) is very significant and continues to rise worldwide. The causation of OO and T2D is complex and highly multifactorial rather than a mere energy intake (food) and expenditure (exercise) imbalance. But previous research into food and physical activity (PA) neighbourhood environments has mainly focused on associating body mass index (BMI) with proximity to stores selling fresh fruits and vegetables or fast food restaurants and takeaways, or with neighbourhood walkability factors and access to green spaces or public gym facilities, making largely naive, crude and inconsistent assumptions and conclusions that are far from the spirit of 'precision and accuracy public health'. Different people and population groups respond differently to the same food and PA environments, due to a myriad of unique individual and population group factors (genetic/epigenetic, metabolic, dietary and lifestyle habits, health literacy profiles, screen viewing times, stress levels, sleep patterns, environmental air and noise pollution levels, etc.) and their complex interplays with each other and with local food and PA settings. Furthermore, the same food store or fast food outlet can often sell or serve both healthy and non-healthy options/portions, so a simple binary classification into 'good' or 'bad' store/outlet should be avoided. Moreover, appropriate physical exercise, whilst essential for good health and disease prevention, is not very effective for weight maintenance or loss (especially when solely relied upon), and cannot offset the effects of a bad diet. The research we should be doing in the third decade of the twenty-first century should use a systems thinking approach, helped by recent advances in sensors, big data and related technologies, to investigate and consider all these factors in our quest to design better targeted and more effective public health interventions for OO and T2D control and prevention.

中文翻译：

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智慧城市生活方式感知、大数据、地理分析和情报，用于在超重、肥胖和 2 型糖尿病预防方面做出更明智的公共卫生决策：我们应该做的研究


超重、肥胖 (OO) 和 2 型糖尿病 (T2D) 造成的公共卫生负担非常严重，并且在全球范围内持续上升。 OO 和 T2D 的原因是复杂且高度多因素的，而不仅仅是能量摄入（食物）和支出（运动）失衡。但之前对食物和身体活动 (PA) 邻里环境的研究主要集中在将体重指数 (BMI) 与出售新鲜水果和蔬菜的商店或快餐店和外卖店的距离联系起来，或者与邻里步行能力因素和绿地可达性联系起来或公共健身设施，做出的大多是幼稚、粗暴和不一致的假设和结论，与“精确和准确的公共卫生”精神相去甚远。由于无数独特的个人和人群因素（遗传/表观遗传、代谢、饮食和生活习惯、健康素养概况、屏幕观看时间、压力水平、睡眠），不同的人和人群对相同的食物和 PA 环境有不同的反应。模式、环境空气和噪音污染水平等）及其相互之间以及与当地食品和公共场所环境的复杂相互作用。此外，同一食品店或快餐店通常可以销售或提供健康和不健康的选项/部分，因此应避免简单地二元分类为“好”或“坏”商店/店。此外，适当的体育锻炼虽然对于身体健康和预防疾病至关重要，但对于维持或减轻体重并不是非常有效（尤其是仅依靠体育锻炼时），并且不能抵消不良饮食的影响。 我们应该在二十世纪第三个十年进行的研究应该使用系统思维方法，在传感器、大数据和相关技术的最新进展的帮助下，调查和考虑所有这些因素，以设计出更有针对性的产品。以及更有效的公共卫生干预措施来控制和预防 OO 和 T2D。