Jiesheng Lin1, Jason Leung2, Blanche Yu3, Jean Woo4, Timothy Kwok3, Kevin Ka-Lun Lau5. 1. Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong. Electronic address: linjsh6@mail3.sysu.edu.cn. 2. Jockey Club Centre for Osteoporosis Care and Control, The Chinese University of Hong Kong, Hong Kong. 3. Jockey Club Centre for Osteoporosis Care and Control, The Chinese University of Hong Kong, Hong Kong; Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong. 4. CUHK Jockey Club Institute of Ageing, The Chinese University of Hong Kong, Hong Kong; Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong. 5. Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong; CUHK Jockey Club Institute of Ageing, The Chinese University of Hong Kong, Hong Kong. Electronic address: kevinlau@cuhk.edu.hk.
Abstract
BACKGROUND: Previous studies have focused on associations between individual built environment (BE) characteristics and mortality, and found the BE-mortality associations differed by socioeconomic status (SES). Different individual BE characteristics may have different impacts on health and thus could interact. Combinations of BE characteristics may be a better approach to explore the BE-mortality associations. OBJECTIVES: This study aimed to investigate the associations of BE pattern with mortality in a prospective cohort of elderly Hong Kong Chinese (Mr. OS and Ms. OS Study), and assess whether the BE-mortality association differed by SES. METHODS: Between 2001 and 2003, 3944 participants aged 65-98 years at baseline were included in the present analysis. BE characteristics were assessed via Geographic Information System. Data on all-cause and cause-specific mortality were obtained from the Hong Kong Government Death Registry. Latent profile analysis was used to derive BE class, and the Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Three BE classes were identified. During a total of 53276 person-years of follow-up, 1632 deaths were observed. There were no significant associations of BE class with all-cause and cause-specific mortality. However, we found the associations of BE class with all-cause mortality were modified by SES. In comparison with Class 3 (characterized by greater green space), HRs (95%CIs) were 0.72 (0.54, 0.97) for Class 1 (characterized by greater commercial land use) and 0.77 (0.64, 0.94) for Class 2 (characterized by greater residential land use) among low-SES participants. The associations were stronger among high-SES participants, with 0.55 (0.33, 0.89) for Class 1 and 0.68 (0.48, 0.97) for Class 2. In contrast, Class 2 (HR 1.18, 95%CI 1.01-1.39) had a higher mortality risk compared with Class 3 among middle-SES participants. CONCLUSIONS: Our findings provide new evidence on the role of SES as an effect modifier of BE pattern and mortality. BE pattern has a varied effect on mortality risk for different SES groups.
BACKGROUND: Previous studies have focused on associations between individual built environment (BE) characteristics and mortality, and found the BE-mortality associations differed by socioeconomic status (SES). Different individual BE characteristics may have different impacts on health and thus could interact. Combinations of BE characteristics may be a better approach to explore the BE-mortality associations. OBJECTIVES: This study aimed to investigate the associations of BE pattern with mortality in a prospective cohort of elderly Hong Kong Chinese (Mr. OS and Ms. OS Study), and assess whether the BE-mortality association differed by SES. METHODS: Between 2001 and 2003, 3944 participants aged 65-98 years at baseline were included in the present analysis. BE characteristics were assessed via Geographic Information System. Data on all-cause and cause-specific mortality were obtained from the Hong Kong Government Death Registry. Latent profile analysis was used to derive BE class, and the Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Three BE classes were identified. During a total of 53276 person-years of follow-up, 1632 deaths were observed. There were no significant associations of BE class with all-cause and cause-specific mortality. However, we found the associations of BE class with all-cause mortality were modified by SES. In comparison with Class 3 (characterized by greater green space), HRs (95%CIs) were 0.72 (0.54, 0.97) for Class 1 (characterized by greater commercial land use) and 0.77 (0.64, 0.94) for Class 2 (characterized by greater residential land use) among low-SES participants. The associations were stronger among high-SES participants, with 0.55 (0.33, 0.89) for Class 1 and 0.68 (0.48, 0.97) for Class 2. In contrast, Class 2 (HR 1.18, 95%CI 1.01-1.39) had a higher mortality risk compared with Class 3 among middle-SES participants. CONCLUSIONS: Our findings provide new evidence on the role of SES as an effect modifier of BE pattern and mortality. BE pattern has a varied effect on mortality risk for different SES groups.