Factors associated with secondhand smoke incursion into the homes of non-smoking residents in a multi-unit housing complex: a cross-sectional study in Seoul, Korea

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Abstract Background In a multi-unit housing (MUH) complex, secondhand smoke (SHS) can pass from one living space to another. The aim of this study was to determine the prevalence of SHS incursion, and to establish the relationship between SHS incursion and socio-demographic and built environmental factors in MUH in Korea. Methods A population-based sample of 2600 residents (aged ≥19 years) living in MUH from across the city of Seoul, Korea, was obtained through a web-based selection panel. The residents completed a questionnaire detailing socio-demographic factors, smoking status, frequency of SHS incursion, and built environmental factors. The presence of a personal smoke-free home rule was determined by residents declaring that no one smoked inside the home. Results Of the 2600 participants, non-smoking residents who lived in homes with a personal smoke-free rule were selected for further analysis (n = 1784). In the previous 12 months, 74.7% of residents had experienced SHS incursion ≥1 times. A multivariate ordinal logistic regression analysis indicated that residents who spent more time at home, lived with children, supported the implementation of smoke-free regulations in MUH, lived in small homes, lived in homes with natural ventilation provided by opening a front door or the windows and front door, and lived in homes with more frequent natural ventilation were more likely to report SHS incursion into their homes. Conclusions The majority of the non-smoking residents experienced SHS incursion, even with a personal smoke-free rule in their homes. A smoke-free policy in MUH is needed to protect residents from SHS exposure when they are at home

Trends in the Prevalence of Childhood Asthma in Seoul Metropolitan City, Korea: The Seoul Atopy ∙ Asthma-friendly School Project

Objectives The project Seoul Atopy ∙ Asthma-friendly School investigated the current status of childhood asthma to enable formulation of a preventative policy. We evaluated the current prevalence of childhood asthma in Seoul and its trends and related factors. Methods The project was conducted annually from 2011 to 2016 and involved around 35 000 children aged 1-13 years. Based on the International Study of Asthma and Allergies in Childhood guidelines, the survey involved parents. The associations of the particulate matter (PM10) concentration, and the number of days on which the daily air quality guidance level was exceeded in the 25 districts of Seoul, with the prevalence of asthma were assessed. Results The age-standardized asthma prevalence in 2011 and 2016 was 6.74 and 4.02%, respectively. The prevalence of lifetime asthma treatment and treatment during the last 12 months tended to decrease from 2011 to 2016. Asthma treatment was significantly correlated with the number of days on which the daily air quality guidance level was exceeded, but not with the PM10 concentration. Conclusions This study reports the prevalence of asthma among children in Seoul and confirmed the relationship between childhood asthma and known risk factors in a large-scale survey

Multivariate-adjusted effect estimates (95% CI) of hearing thresholds (dBHL) with IQR increment in occupational noise exposure (dBA), stratified according to participant status.

<p>Models were adjusted for age, age², sex, BMI, and hypertension, defined in Model C, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097538#pone-0097538-t003" target="_blank">Table 3</a>.</p><p>CI, confidence interval.</p><p>^<i>a</i>PTA (dBHL) change per interquartile range (IQR) of occupational noise, 94.26 dBA - 84.74 dBA: 9.52 dBA.</p><p><i>*p<0.05.</i></p

General characteristics of study participants (N = 30,072^a).

<p>^<i>a</i>Participants (N = 33,072) are the individuals having all interest variables in this study: advanced audiometric measurements, age, occupational noise, sex, BMI, and hypertension.</p><p>^<i>b</i>Age-adjusted means were presented.</p><p>^<i>c</i>Occupational noise (a daily 8-hour time weighted average level in each industry).</p><p>^<i>d</i>PTA (pure tone average) of standard threshold at 2, 3, 4 kHz frequencies.</p><p>^<i>e</i>Hearing thresholds at 1 kHz were obtained from primary audiometric tests.</p><p>^<i>f</i>Hearing Loss (PTA at 2, 3, 4 KHz frequencies > 25 dBHL).</p><p>SD, standard deviation.</p

Multivariate-adjusted effect estimates (95% CI) of hearing thresholds (dBHL) with IQR increment in occupational noise exposure (dBA), stratified according to occupational exposure to ototoxic chemicals.

<p>Models were adjusted for age, age², sex, BMI, and hypertension, defined in Model C, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097538#pone-0097538-t003" target="_blank">Table 3</a>.</p><p>CI, confidence interval.</p><p>^<i>a</i>PTA (dBHL) change per interquartile range (IQR) of occupational noise, 94.26 dBA - 84.74 dBA: 9.52 dBA.</p><p><i>*p<0.05.</i></p

Noise-Induced Hearing Loss in Korean Workers: Co-Exposure to Organic Solvents and Heavy Metals in Nationwide Industries

<div><p>Background</p><p>Noise exposure is a well-known contributor to work-related hearing loss. Recent biological evidence suggests that exposure to ototoxic chemicals such as organic solvents and heavy metals may be additional contributors to hearing loss. However, in industrial settings, it is difficult to determine the risks of hearing loss due to these chemicals in workplaces accompanied by excessive noise exposure. A few studies suggest that the effect of noise may be enhanced by ototoxic chemicals. Therefore, this study investigated whether co-exposure to organic solvents and/or heavy metals in the workplace modifies the risk of noise exposure on hearing loss in a background of excessive noise.</p><p>Methods</p><p>We examined 30,072 workers nationwide in a wide range of industries from the Korea National Occupational Health Surveillance 2009. Data on industry-based exposure (e.g., occupational noise, heavy metals, and organic solvents) and subject-specific health outcomes (e.g., audiometric examination) were collected. Noise was measured as the daily 8-h time-weighted average level. Air conduction hearing thresholds were measured from 0.5 to 6 kHz, and pure-tone averages (PTA) (i.e., means of 2, 3, and 4 kHz) were computed.</p><p>Results</p><p>In the multivariate linear model, PTA increment with occupational noise were 1.64-fold and 2.15-fold higher in individuals exposed to heavy metals and organic solvents than in unexposed individuals, respectively.</p><p>Conclusion</p><p>This study provides nationwide evidence that co-exposure to heavy metals and/or organic solvents may exacerbate the effect of noise exposure on hearing loss in workplaces. These findings suggest that workers in industries dealing with heavy metals or organic solvents are susceptible to such risks.</p></div

Air Pollution Monitoring Design for Epidemiological Application in a Densely Populated City

Introduction: Many studies have reported the association between air pollution and human health based on regulatory air pollution monitoring data. However, because regulatory monitoring networks were not designed for epidemiological studies, the collected data may not provide sufficient spatial contrasts for assessing such associations. Our goal was to develop a monitoring design supplementary to the regulatory monitoring network in Seoul, Korea. This design focused on the selection of 20 new monitoring sites to represent the variability in PM2.5 across people’s residences for cohort studies. Methods: We obtained hourly measurements of PM2.5 at 37 regulatory monitoring sites in 2010 in Seoul, and computed the annual average at each site. We also computed 313 geographic variables representing various pollution sources at the regulatory monitoring sites, 31,097 children’s homes from the Atopy Free School survey, and 412 community service centers in Seoul. These three types of locations represented current, subject, and candidate locations. Using the regulatory monitoring data, we performed forward variable selection and chose five variables most related to PM2.5. Then, k-means clustering was applied to categorize all locations into several groups representing a diversity in the spatial variability of the five selected variables. Finally, we computed the proportion of current to subject location in each cluster, and randomly selected new monitoring sites from candidate sites in the cluster with the minimum proportion until 20 sites were selected. Results: The five selected geographic variables were related to traffic or urbanicity with a cross-validated R2 value of 0.69. Clustering analysis categorized all locations into nine clusters. Finally, one to eight new monitoring sites were selected from five clusters. Discussion: The proposed monitoring design will help future studies determine the locations of new monitoring sites representing spatial variability across residences for epidemiological analyses

Additional file 1: Table S1. of Factors associated with secondhand smoke incursion into the homes of non-smoking residents in a multi-unit housing complex: a cross-sectional study in Seoul, Korea

Fourteen items of socio-demographic information. Table S2. Two items of smoking status. Table S3. Two items of secondhand smoke incursion at home. Table S4. Seven items of built environmental information. (DOCX 26 kb

Association between Secondhand Smoke in Hospitality Venues and Urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol Concentrations in Non-Smoking Staff

The purpose of this study was to determine the relationship between urinary cotinine and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) concentrations in non-smoking staff and the indoor levels of fine particles (PM2.5) in hospitality venues that allow smoking, with respect to demographic and indoor environmental factors. We evaluated 62 hospitality venues that allowed smoking in Seoul, Korea. A real-time aerosol monitor was used to measure indoor PM2.5 concentrations. Field technicians recorded indoor environmental characteristics. One non-smoking staff member in each hospitality venue was tested for urinary cotinine and total NNAL concentrations. Demographic characteristics were obtained from self-reported staff questionnaires. Natural-log (ln)-transformed PM2.5 concentrations were significantly correlated with the ln-transformed cotinine (r = 0.31) and the total NNAL concentrations (r = 0.32). In multivariable regression analysis, the urinary cotinine concentrations of the staff members were significantly correlated with indoor PM2.5 concentrations; those with the highest concentrations were more likely to be women or staff members that worked in venues with a volume &lt;375 m3. Total NNAL concentrations were significantly correlated only with indoor PM2.5 concentrations. Indoor PM2.5 may be used as an indicator for urinary cotinine and total NNAL concentrations in non-smoking staff members in hospitality venues that allow smoking