Factor loadings for men’s model.

The objectives of this study were to describe regional variation in overweight and to investigate factors associated with overweight at the secondary medical area (SMA) level, accounting for regional economic sector profiles. We utilized data from the specific health checkup, which targets individuals aged 40–74 years. Following descriptive analyses, we employed partial least squares regression analyses using an open-access version of specific health checkup data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. This approach allowed us to identify latent variables related to regional variation in overweight and to examine associated lifestyle and socioenvironmental factors. Identifying these latent variables helps uncover underlying regional or socioeconomic patterns not directly observable, thereby informing more targeted public health interventions. The distinct characteristics of areas associated with a higher proportion of overweight persons were identified—the key latent variable encompassing low socioeconomic status and a high proportion of family workers. Additionally, our findings suggested that the drinking and eating environment may present challenges in regions with a high proportion of workers in the information and real estate sectors. In contrast, reduced walkability of the environment may be problematic in regions with many workers in the manufacturing and transportation sectors. Our study underscores the importance of addressing the unique challenges faced by each area with attention given to their local traits and industrial structures, which may have unconsciously shaped residents’ lifestyles and daily behaviors. As area-level variation in overweight and obesity related to contextual factors, such as economic sector profiles, have not been extensively studied internationally, this study provides a valuable insight into research on factors associated with overweight.本研究旨在描述超重情况的区域差异，并在二级医疗区（Secondary Medical Area, SMA）层面探究与超重相关的影响因素，同时兼顾区域经济产业结构特征。本研究使用了针对40~74岁人群的特定健康体检数据。在完成描述性分析后，我们采用日本健康保险索赔与特定健康体检国家数据库的开源版特定健康体检数据开展偏最小二乘回归分析。该方法可帮助识别与超重区域差异相关的潜变量，并探究与之相关的生活方式与社会环境因素。识别此类潜变量有助于揭示无法直接观测到的潜在区域或社会经济模式，从而为更具针对性的公共卫生干预措施提供科学依据。 本研究明确了与高超重比例人群相关的区域独特特征——该关键潜变量涵盖了低社会经济地位与家庭用工占比高的特征。此外，研究结果显示，在信息产业与房地产业从业者占比较高的区域，饮酒与外出就餐环境可能成为超重相关的不利因素。与之相对，在制造业与交通运输业从业者较多的区域，环境步行可达性不足可能是相关问题。本研究强调，需针对各区域的独特挑战制定应对策略，充分考量其本地特质与产业结构——这些因素可能在潜移默化中塑造了居民的生活方式与日常行为。 由于国际上针对与经济产业结构相关的区域层面超重与肥胖差异的研究尚不多见，本研究为超重相关影响因素的相关研究提供了极具价值的参考视角。