RESUMO
BACKGROUND: Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments. METHODS: In this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach). RESULTS: The mean exposure to NO2 increases with 1.27 µg/m(3) (4.3%) during the week and with 0.12 µg/m(3) (0.4%) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations. CONCLUSIONS: It is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones).
Assuntos
Poluição do Ar/estatística & dados numéricos , Telefone Celular/estatística & dados numéricos , Interpretação Estatística de Dados , Exposição Ambiental/estatística & dados numéricos , Mapeamento Geográfico , Poluição do Ar/análise , Bélgica/epidemiologia , Humanos , Material Particulado/análiseRESUMO
BACKGROUND: In many countries, financial assistance is awarded to physicians who settle in an area that is designated as a shortage area to prevent unequal accessibility to primary health care. Today, however, policy makers use fairly simple methods to define health care accessibility, with physician-to-population ratios (PPRs) within predefined administrative boundaries being overwhelmingly favoured. Our purpose is to verify whether these simple methods are accurate enough for adequately designating medical shortage areas and explore how these perform relative to more advanced GIS-based methods. METHODS: Using a geographical information system (GIS), we conduct a nation-wide study of accessibility to primary care physicians in Belgium using four different methods: PPR, distance to closest physician, cumulative opportunity, and floating catchment area (FCA) methods. RESULTS: The official method used by policy makers in Belgium (calculating PPR per physician zone) offers only a crude representation of health care accessibility, especially because large contiguous areas (physician zones) are considered. We found substantial differences in the number and spatial distribution of medical shortage areas when applying different methods. CONCLUSIONS: The assessment of spatial health care accessibility and concomitant policy initiatives are affected by and dependent on the methodology used. The major disadvantage of PPR methods is its aggregated approach, masking subtle local variations. Some simple GIS methods overcome this issue, but have limitations in terms of conceptualisation of physician interaction and distance decay. Conceptually, the enhanced 2-step floating catchment area (E2SFCA) method, an advanced FCA method, was found to be most appropriate for supporting areal health care policies, since this method is able to calculate accessibility at a small scale (e.g., census tracts), takes interaction between physicians into account, and considers distance decay. While at present in health care research methodological differences and modifiable areal unit problems have remained largely overlooked, this manuscript shows that these aspects have a significant influence on the insights obtained. Hence, it is important for policy makers to ascertain to what extent their policy evaluations hold under different scales of analysis and when different methods are used.
Assuntos
Área Programática de Saúde/estatística & dados numéricos , Medicina de Família e Comunidade/estatística & dados numéricos , Política de Saúde/economia , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Mão de Obra em Saúde/estatística & dados numéricos , Padrões de Prática Médica/estatística & dados numéricos , Bélgica , Área Programática de Saúde/economia , Medicina de Família e Comunidade/economia , Sistemas de Informação Geográfica , Acessibilidade aos Serviços de Saúde/economia , Necessidades e Demandas de Serviços de Saúde , Pesquisa sobre Serviços de Saúde , Mão de Obra em Saúde/economia , Humanos , Área Carente de Assistência Médica , Padrões de Prática Médica/economia , Fatores SocioeconômicosRESUMO
BACKGROUND: Doing regular physical activity has positive effects on health. Several environmental factors are identified as important correlates of physical activity. However, there seems to be a difference between perceived and objective measures of the environment. This study examines the influence of physical activity, neighbourhood walkability, and socio-demographic characteristics on the correspondence between self-reported and objectively measured walking time to urban destinations of adults in the city of Ghent (Belgium). METHODS: Previously collected survey data was used from 1164 respondents in the city of Ghent who reported walking times to various closest destinations in the neighbourhood of residence. These were compared with corresponding walking times that were objectively measured through geographical information systems. Physical activity was recorded over a 7-day period using accelerometers. Neighbourhood walkability was assessed on the basis of residential density, connectivity, and land-use mix. RESULTS: We observed a relatively poor agreement between objective and perceived walking times. Stronger agreements were noted amongst the most physically active group, while low-level walkers tended to overestimate walking time. Surprisingly, however, people residing in a low-walkable neighbourhood underestimated walking times more frequently relative to those in high-walkable neighbourhoods. CONCLUSIONS: Researchers investigating the influence of environmental attributes on physical activity behavior should thus be cautious when using only self-reported environmental data, since these are a priori influenced by physical activity levels and various socio-demographic factors.
Assuntos
Planejamento Ambiental , Conhecimentos, Atitudes e Prática em Saúde , Atividade Motora , Classe Social , Caminhada , Actigrafia/instrumentação , Adolescente , Adulto , Idoso , Bélgica , Demografia , Feminino , Sistemas de Informação Geográfica , Humanos , Masculino , Pessoa de Meia-Idade , Inquéritos e Questionários , Fatores de Tempo , População Urbana , Adulto JovemRESUMO
Physical activity is an important facilitator for health and wellbeing, especially for late middle-aged adults, who are more susceptible to cardiovascular diseases. Physical activity performed in green areas is supposed to be particularly beneficial, so we studied whether late middle- aged adults are more active in green areas than in non-green areas and how this is influenced by individual characteristics and the level of neighbourhood greenness. We tracked 180 late middle-aged (58 to 65 years) adults using global positioning system and accelerometer data to know whether and where they were sedentary or active. These data were combined with information on land use to obtain information on the greenness of sedentary and active hotspots. We found that late middle-aged adults are more physically active when spending more time in green areas than in non-green areas. Spending more time at home and in non-green areas was found to be associated with more sedentary behaviour. Time spent in non-green areas was found to be related to more moderate-to-vigorous physical activity (MVPA) for males and to less MVPA for females. The positive association between time spent in green areas and MVPA was the strongest for highly educated people and for those living in a green neighbourhood. This study shows that the combined use of global positioning system and accelerometer data facilitates understanding of where people are sedentary or physically active, which can help policy makers encourage activity in this age cohort.