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Conference Paper: Residential density and adiposity: Findings from the UK Biobank
Title | Residential density and adiposity: Findings from the UK Biobank |
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Authors | |
Issue Date | 2017 |
Citation | Lancet Public Health Science Conference, London, UK, 24 November 2017 How to Cite? |
Abstract | Background Obesity has emerged as a global pandemic, however the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. High residential density may be hypothesized to constitute leptogenic multi-functional environments promoting active living. We examine the association between adiposity and housing unit density. Methods This cross-sectional study involved 450,433 adults from the UK Biobank aged 38-73 years with full data. Residential unit density was objectively assessed within one-kilometer street catchment of participants' residence. Other activity-influencing built environment included density of retail, public transport and street movement density modelled from network analyses of through-movement of street links within the defined catchment. Adiposity is expressed in-terms of measured body mass index (BMI; Kg/m²), waist circumference (WC; cm), whole body fat (WBF; Kg), and obesity as defined by WHO. We fitted linear and non-linear (restrictedcubic-spline) models after adjusting for activity-influencing built environment, neighbourhood deprivation, socio-demographics, lifestyle and co-morbidities and investigated effect modification by gender, age, and physical activity. Findings Restricted-cubic-spline model with three knots best fitted the data identifying two inflexion points at residential densities of 1600 and 3400 units/Km². Below a density of 1600 units/Km², increment of 1000 units/Km² was significantly associated with higher BMI (βBMI=0.24, 95% CI: 0.19 to 0.30), WC (βWC=0.55, 0.40 to 0.69), WBF (βWBF=0.57, 0.46 to 0.68) and odds of obesity (ORObesity=1.13, 1.09 to 1.13). Between 1600-3400 units/Km², it was associated with lower BMI (βBMI=-0.13, -0.18 to -0.08), WC (βWC=-0.19, -0.32 to -0.07), WBF (βWBF=-0.20, -0.30 to -0.10) and obesity (ORObesity=0.96, 0.94 to 0.99). Above 3400 units/Km², each increment of 1000 units/Km2 was leptogenic, being associated with lower BMI (βBMI=-0.15, -0.19 to -0.11), WC (βWC=-0.50, -0.60 to -0.40), WBF (βWBF=-0.26, -0.34 to -0.18) and obesity (ORObesity= 0.93, 0.91 to 0.95). Stronger leptogenic effects of housing density were observed among younger, female and participants doing higher physical activity. Interpretation High residential density is associated with lower adiposity in a large and diverse population sample. The evidence point to the value of housing-level policy related to densification as an upstream-level candidate for public health intervention against adiposity. Further longitudinal evidence are needed to establish causality. |
Description | Poster Presentation -Diet, diabetes and obesity: Manuscript No. THELANCET-D-17-04013R1 |
Persistent Identifier | http://hdl.handle.net/10722/248271 |
DC Field | Value | Language |
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dc.contributor.author | Sarkar, C | - |
dc.contributor.author | Webster, CJ | - |
dc.contributor.author | Gallacher, JEJ | - |
dc.date.accessioned | 2017-10-18T08:40:35Z | - |
dc.date.available | 2017-10-18T08:40:35Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Lancet Public Health Science Conference, London, UK, 24 November 2017 | - |
dc.identifier.uri | http://hdl.handle.net/10722/248271 | - |
dc.description | Poster Presentation -Diet, diabetes and obesity: Manuscript No. THELANCET-D-17-04013R1 | - |
dc.description.abstract | Background Obesity has emerged as a global pandemic, however the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. High residential density may be hypothesized to constitute leptogenic multi-functional environments promoting active living. We examine the association between adiposity and housing unit density. Methods This cross-sectional study involved 450,433 adults from the UK Biobank aged 38-73 years with full data. Residential unit density was objectively assessed within one-kilometer street catchment of participants' residence. Other activity-influencing built environment included density of retail, public transport and street movement density modelled from network analyses of through-movement of street links within the defined catchment. Adiposity is expressed in-terms of measured body mass index (BMI; Kg/m²), waist circumference (WC; cm), whole body fat (WBF; Kg), and obesity as defined by WHO. We fitted linear and non-linear (restrictedcubic-spline) models after adjusting for activity-influencing built environment, neighbourhood deprivation, socio-demographics, lifestyle and co-morbidities and investigated effect modification by gender, age, and physical activity. Findings Restricted-cubic-spline model with three knots best fitted the data identifying two inflexion points at residential densities of 1600 and 3400 units/Km². Below a density of 1600 units/Km², increment of 1000 units/Km² was significantly associated with higher BMI (βBMI=0.24, 95% CI: 0.19 to 0.30), WC (βWC=0.55, 0.40 to 0.69), WBF (βWBF=0.57, 0.46 to 0.68) and odds of obesity (ORObesity=1.13, 1.09 to 1.13). Between 1600-3400 units/Km², it was associated with lower BMI (βBMI=-0.13, -0.18 to -0.08), WC (βWC=-0.19, -0.32 to -0.07), WBF (βWBF=-0.20, -0.30 to -0.10) and obesity (ORObesity=0.96, 0.94 to 0.99). Above 3400 units/Km², each increment of 1000 units/Km2 was leptogenic, being associated with lower BMI (βBMI=-0.15, -0.19 to -0.11), WC (βWC=-0.50, -0.60 to -0.40), WBF (βWBF=-0.26, -0.34 to -0.18) and obesity (ORObesity= 0.93, 0.91 to 0.95). Stronger leptogenic effects of housing density were observed among younger, female and participants doing higher physical activity. Interpretation High residential density is associated with lower adiposity in a large and diverse population sample. The evidence point to the value of housing-level policy related to densification as an upstream-level candidate for public health intervention against adiposity. Further longitudinal evidence are needed to establish causality. | - |
dc.language | eng | - |
dc.relation.ispartof | Lancet Public Health Science Conference, 2017 | - |
dc.title | Residential density and adiposity: Findings from the UK Biobank | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Sarkar, C: csarkar@hku.hk | - |
dc.identifier.email | Webster, CJ: cwebster@hku.hk | - |
dc.identifier.authority | Sarkar, C=rp01980 | - |
dc.identifier.authority | Webster, CJ=rp01747 | - |
dc.identifier.hkuros | 280915 | - |
dc.identifier.hkuros | 282058 | - |