Literature DB >> 29654838

Neighbourhood safety and smoking in population subgroups: The HELIUS study.

Erik J Timmermans1, Eleonore M Veldhuizen2, Marieke B Snijder3, Martijn Huisman4, Anton E Kunst5.   

Abstract

This study examines the associations between neighbourhood safety and three types of smoking behaviour, and whether these associations differ by sex, age, ethnicity and individual-level socio-economic position. Baseline data (2011-2015) from the The HEalthy LIfe in an Urban Setting (HELIUS) study (Amsterdam, the Netherlands) were used. Smoking behaviour was based on self-report. Heavy smoking was defined as smoking ≥10 cigarettes per day. Nicotine dependence was assessed using the Fagerström questionnaire. Geographic Information System techniques were used to construct local residential areas and to examine neighbourhood safety for these areas using micro-scale environmental data. Multilevel logistic regression analyses with 6-digit zip code area as a second level were used to assess the association between neighbourhood safety and smoking. In our study sample of 22,728 participants (18-70 years), 24.0% were current smokers, 13.7% were heavy smokers and 8.1% were nicotine dependent individuals. Higher levels of neighbourhood safety were significantly associated with less heavy smoking (OR = 0.88, 95% CI = 0.78-0.99) and less nicotine dependence (OR = 0.81, 95% CI = 0.69-0.95), but not with less current smoking (OR = 1.01, 95% CI = 0.91-1.11). The associations between neighbourhood safety and the three types of smoking behaviour varied by ethnicity. For instance, higher levels of neighbourhood safety were associated with less current smoking in participants of African Surinamese origin (OR = 0.71, 95% CI = 0.57-0.89), but not in those of Dutch (OR = 1.13, 95% CI = 0.91-1.39), South-Asian Surinamese (OR = 1.22, 95% CI = 0.95-1.55), Turkish (OR = 1.08, 95% CI = 0.84-1.38), Moroccan (OR = 1.53, 95% CI = 1.12-2.10) or Ghanaian (OR = 1.18, 95% CI = 0.47-2.94) origin. Policies that improve neighbourhood safety potentially contribute to less heavy smoking and nicotine dependence.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Environmental epidemiology; Geographic Information Systems; HELIUS study; Neighbourhood safety; Population subgroups; Smoking

Mesh:

Year:  2018        PMID: 29654838     DOI: 10.1016/j.ypmed.2018.04.012

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  4 in total

1.  Geographic variation in tobacco use in India: a population-based multilevel cross-sectional study.

Authors:  Ankur Singh; Monika Arora; Rebecca Bentley; Matthew J Spittal; Loc G Do; Nathan Grills; Dallas R English
Journal:  BMJ Open       Date:  2020-06-21       Impact factor: 2.692

2.  Effect of characteristics and life in cities in China on residents' smoking behaviour.

Authors:  Yang Chen; Hongsheng Chen; Zhigang Li
Journal:  J Int Med Res       Date:  2018-08-15       Impact factor: 1.671

3.  Is the Association Between Education and Sympathovagal Balance Mediated by Chronic Stressors?

Authors:  Benjamin P van Nieuwenhuizen; Aydin Sekercan; Hanno L Tan; Marieke T Blom; Anja Lok; Bert-Jan H van den Born; Anton E Kunst; Irene G M van Valkengoed
Journal:  Int J Behav Med       Date:  2021-09-27

Review 4.  Classification of Deprivation Indices That Applied to Detect Health Inequality: A Scoping Review.

Authors:  Anastasia Zelenina; Svetlana Shalnova; Sergey Maksimov; Oksana Drapkina
Journal:  Int J Environ Res Public Health       Date:  2022-08-15       Impact factor: 4.614

  4 in total

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