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Self-perceived health is an important factor for assessing urban residents’ satisfaction and quality of life. However, few have comprehensively investigated the impact of demographics, lifestyle and health awareness, indoor environment characteristics, and neighborhood features on self-perceived health. To fill this gap, we designed a framework using multivariable regressions to derive odd rations and to analyze the determinants of self-rated health, stratified into different sub-groups divided by gender, age, and neighborhood types. The study area is Chengdu, one of the most populous cities in western China. The results show that: (1) female respondents reported worse health, with household income level and marital status significantly affecting self-rated health; (2) elderly people reported the worst health, while unique factors affected only younger people (18–29 years old), such as gender, smoking, and indoor environment characteristics; and (3) different types of neighborhoods influence their residents’ perception of health differently due to historical establishment, current population composition, and housing conditions. Our study provides new observations on neighborhood types, while agreeing with previous studies on the influences of gender and age. We contribute to the field by providing a more complex understanding of the mechanism by which people rate their own health, which is important for understanding the satisfaction of urban residents and the built environment in which they live.

Self-perceived health is an important factor for assessing urban residents’ satisfaction and quality of life. However, few have comprehensively investigated the impact of demographics, lifestyle and health awareness, indoor environment characteristics, and neighborhood features on self-perceived health. To fill this gap, we designed a framework using multivariable regressions to derive odd rations and to analyze the determinants of self-rated health, stratified into different sub-groups divided by gender, age, and neighborhood types. The study area is Chengdu, one of the most populous cities in western China. The results show that: (1) female respondents reported worse health, with household income level and marital status significantly affecting self-rated health; (2) elderly people reported the worst health, while unique factors affected only younger people (18–29 years old), such as gender, smoking, and indoor environment characteristics; and (3) different types of neighborhoods influence their residents’ perception of health differently due to historical establishment, current population composition, and housing conditions. Our study provides new observations on neighborhood types, while agreeing with previous studies on the influences of gender and age. We contribute to the field by providing a more complex understanding of the mechanism by which people rate their own health, which is important for understanding the satisfaction of urban residents and the built environment in which they live.

The COVID-19 pandemic affected how people interact with the built environment and ways of human habitation are facing significant challenges. However, the existing literature has not adequately addressed how the built environment affected the early prevalence of the pandemic. This research aims to extend the existing literature by relating the initial stage pandemic conditions with more comprehensive measures of the built environment including density, diversity, road network, and accessibility at the county level across the United States and conducting bi-weekly comparisons. We collected infection, death, and mortality data in 3141 counties between 1 March to 8 June 2020 and collected seventeen built environment attributes. Our results show that: (1) Road density and street intersection density were significantly associated with the infection rate; (2) Population density only maintained a positive correlation to the prevalence of COVID-19 during the first two weeks, after which the relationship became negative; and (3) Transit accessibility also contributed significantly to the pandemic and the accessibility of transit-oriented jobs was highly correlated to the infection rate in the first two weeks. The study provides valuable insights for policymakers and stakeholders to adopt resource allocation strategies for context-specific conditions.

The COVID-19 pandemic affected how people interact with the built environment and ways of human habitation are facing significant challenges. However, the existing literature has not adequately addressed how the built environment affected the early prevalence of the pandemic. This research aims to extend the existing literature by relating the initial stage pandemic conditions with more comprehensive measures of the built environment including density, diversity, road network, and accessibility at the county level across the United States and conducting bi-weekly comparisons. We collected infection, death, and mortality data in 3141 counties between 1 March to 8 June 2020 and collected seventeen built environment attributes. Our results show that: (1) Road density and street intersection density were significantly associated with the infection rate; (2) Population density only maintained a positive correlation to the prevalence of COVID-19 during the first two weeks, after which the relationship became negative; and (3) Transit accessibility also contributed significantly to the pandemic and the accessibility of transit-oriented jobs was highly correlated to the infection rate in the first two weeks. The study provides valuable insights for policymakers and stakeholders to adopt resource allocation strategies for context-specific conditions.