A variety of metrics assessing the environment are frequently showcased in the study of the relationship between the environment and human health. Among them, Land Use and Land Cover (LULC) data are gradually becoming more notable. However, little research has acknowledged the compositional nature of these data. The goal of the present study is to explore, for the first time, the independent effect of eight LULC categories (agricultural land, bare land, coniferous forest, broad-leaved forest, sclerophyll forest, grassland and shrubs, urban areas and waterbodies) on three selected common health conditions: type 2 diabetes mellitus (T2DM), asthma and anxiety, using a compositional methodological approach and leveraging observational health data of Catalonia at area level.

Three covariates (socioeconomic status, age group and sex) were used for segmentation in order to fix the risk exposure scenario and assess the independent effect of the eight LULC categories on the three health conditions. Our results show that each LULC category would affect distinctively on the three health conditions, and that this effect would be clearly mediated by the three covariates.

This compositional approach has led us to plausible results supported by the existing literature, highlighting the relevance of environmental heterogeneity in health studies. In this sense, we argue that different types of environment possess exclusive elements (humidity, temperature, type of flora and fauna, accessibility, walkability, openness, presence of water, sounds, air compounds and air quality, heat, and noise, light contamination and even chemical exposure) affecting distinctively on human health.

We believe that our contribution might help researchers to approach the environment in a more multidimensional scope, allowing environmental heterogeneity to be brought into the equation.

在研究环境与人类健康之间的关系时，经常会展示各种评估环境的指标。其中，土地利用和土地覆盖（LULC）数据逐渐变得更加引人注目。然而，很少有研究承认这些数据的组成性质。本研究的目的是首次探讨 8 个 LULC 类别（农用地、裸地、针叶林、阔叶林、硬叶林、草地和灌木、城市地区和水体）对土地利用的独立影响。三种选定的常见健康状况：2 型糖尿病 (T2DM)、哮喘和焦虑，使用组合方法学方法并利用加泰罗尼亚地区的观察健康数据。

三个协变量（社会经济地位、年龄组和性别）用于细分，以修复风险暴露场景并评估八个 LULC 类别对三种健康状况的独立影响。我们的结果表明，每个 LULC 类别都会对三种健康状况产生不同的影响，并且这种影响显然是由三个协变量介导的。

这种组合方法使我们得到了现有文献支持的似是而非的结果，突出了环境异质性在健康研究中的相关性。从这个意义上说，我们认为不同类型的环境具有独特的元素（湿度、温度、动植物种类、可达性、步行性、开放性、水的存在、声音、空气化合物和空气质量、热量和噪音、光污染甚至化学暴露）对人类健康有显着影响。

我们相信我们的贡献可能会帮助研究人员在更多维度的范围内研究环境，从而将环境异质性纳入等式。