Metropolitan Area Planning Council, 60 Temple Pl, Boston, MA 02111. E-mail:
Metropolitan Area Planning Council, Boston, Massachusetts.
Prev Chronic Dis. 2014 Feb 13;11:E21. doi: 10.5888/pcd11.130215.
Community-based approaches to preventing chronic diseases are attractive because of their broad reach and low costs, and as such, are integral components of health care reform efforts. Implementing community-based initiatives across Massachusetts' municipalities presents both programmatic and evaluation challenges. For effective delivery and evaluation of the interventions, establishing a community typology that groups similar municipalities provides a balanced and cost-effective approach.
Through a series of key informant interviews and exploratory data analysis, we identified 55 municipal-level indicators of 6 domains for the typology analysis. The domains were health behaviors and health outcomes, housing and land use, transportation, retail environment, socioeconomics, and demographic composition. A latent class analysis was used to identify 10 groups of municipalities based on similar patterns of municipal-level indicators across the domains.
Our model with 10 latent classes yielded excellent classification certainty (relative entropy = .995, minimum class probability for any class = .871), and differentiated distinct groups of municipalities based on health-relevant needs and resources. The classes differentiated healthy and racially and ethnically diverse urban areas from cities with similar population densities and diversity but worse health outcomes, affluent communities from lower-income rural communities, and mature suburban areas from rapidly suburbanizing communities with different healthy-living challenges.
Latent class analysis is a tool that may aid in the planning, communication, and evaluation of community-based wellness initiatives such as Community Transformation Grants projects administrated by the Centers for Disease Control and Prevention.
基于社区的慢性病预防方法具有广泛的覆盖面和低成本的优势，因此是医疗保健改革努力的重要组成部分。在马萨诸塞州的各个城市实施基于社区的倡议既具有项目方面的挑战，也具有评估方面的挑战。为了有效地提供和评估干预措施，建立一个将类似城市分组的社区分类法提供了一种平衡且具有成本效益的方法。
通过一系列关键知情人访谈和探索性数据分析，我们确定了 6 个领域的 55 个市级指标用于进行分类法分析。这些领域包括健康行为和健康结果、住房和土地利用、交通、零售环境、社会经济和人口构成。使用潜在类别分析根据各领域市级指标的相似模式，确定了 10 个城市组。
我们的 10 个潜在类别模型具有出色的分类确定性（相对熵=.995，任何类别最小类别概率=.871），并根据与健康相关的需求和资源区分了不同的城市群体。这些类别区分了健康且种族和族裔多样化的城市地区与人口密度和多样性相似但健康状况较差的城市、富裕社区与低收入农村社区、以及成熟的郊区与具有不同健康生活挑战的快速郊区化社区。
潜在类别分析是一种工具，可用于规划、沟通和评估基于社区的健康倡议，例如疾病控制和预防中心管理的社区转型赠款项目。
