Measure and effects of physical activity in patients with Chronic Obstructive Pulmonary Disease (COPD)

Antecedents: La Malaltia Pulmonar Obstructiva Crònica (MPOC) és una de les principals causes de mortalitat i discapacitat a nivell mundial. L'activitat física és un dels pocs factors modificables que desacceleren l'evolució de la MPOC. No obstant, la dosi i les característiques de l'activitat física responsables de la desacceleració són encara desconegudes. En conseqüència, els objectius d'aquesta tesi són avançar i perfeccionar la metodologia i els instruments per avaluar l'activitat física realitzada pels malalts amb MPOC, aprofundir en el coneixement sobre les característiques i els patrons de la seva activitat física i determinar quines característiques de l'activitat física milloren el pronòstic dels malalts amb MPOC. Mètodes: Han participat 177 individus amb MPOC estable seleccionats de 8 hospitals a Espanya (94% homes, edat mitjana±DE 71±8 anys, volum expiratori forçat en 1 s 52±16% i índex de massa corporal 29±5 kg·m-2). L'activitat física va ser mesurada per un acceleròmetre (SenseWear® Pro2 Armband) i per un qüestionari (Yale Physical Activity Survey, YPAS). Les variables sociodemogràfiques (edat, sexe, estat civil, nivell educatiu, nivell socioeconòmic, situació laboral i hàbit tabàquic) i les variables clíniques (limitació al flux d'aire, hiperinsuflació pulmonar, díspnea, intercanvi de gasos, inflamació sistèmica i local, composició corporal, comorbiditats, qualitat de vida i capacitat d'exercici), es van obtenir utilitzant instruments validats i seguint les normes internacionals. La informació sobre l'evolució de la malaltia (els ingressos hospitalaris i la mortalitat) es va obtenir dels registres dels governs. Resultats: (Objectiu 1) El YPAS és una eina vàlida per a la detecció precoç de la inactivitat dels individus amb MPOC [àrea sota la corba ROC (95% IC) = 0.71 (0,63-0,79)]. (Objectiu 2) El 97% dels individus amb MPOC són capaços de realitzar episodis de 10 minuts d'activitat física moderada-vigorosa. Més del 50% dels individus amb MPOC compleixen amb les recomanacions de l'Organització Mundial de la Salut sobre l'activitat física per a la gent gran. La quantitat d'activitat física, la proporció d'aquesta activitat realitzada en episodis de 10 minuts i la freqüència d'aquests episodis va disminuir amb l'augment de la gravetat de la MPOC. (Objectiu 3) La quantitat i la intensitat de l'activitat física són determinants independents de l'evolució de la MPOC. El risc d'hospitalització per MPOC és un 20% menor per cada 1000 passos diaris addicionals realitzats en baixa intensitat. No obstant, una major quantitat de passos diaris a una alta intensitat mitjana no influeix en el risc d'hospitalització per MPOC (HR = 1.01; p = 0,919). Conclusions: El YPAS és una eina vàlida per a la detecció precoç dels individus amb MPOC físicament inactius. Els pacients amb MPOC greu i molt greu realitzen menys episodis i quantitat d'activitat física, i tenen menor la ràtio entre episodis i quantitat que en aquells en estat lleu i moderat. Una major quantitat d'activitat física de baixa intensitat redueix el risc d'hospitalització per MPOC.Antecedentes: La Enfermedad Pulmonar Obstructiva Crónica (EPOC) es una de las principales causas de mortalidad y discapacidad a nivel mundial. La actividad física es uno de los pocos factores modificables que desaceleran la evolución de la EPOC. Sin embargo, la dosis y las características de la actividad física responsables de la desaceleración son todavía desconocidas. En consecuencia, los objetivos de esta tesis son avanzar y perfeccionar la metodología e instrumentos para evaluar la actividad física realizada por los enfermos con EPOC, profundizar en el conocimiento sobre las características y patrones de su actividad física y determinar qué características de la actividad física mejoran el pronóstico de los enfermos con EPOC. Métodos: Han participado 177 individuos con EPOC estable seleccionados de 8 hospitales en España (94% hombre, edad media±DE 71±8 años, volumen espiratorio forzado predicho en 1 s 52±16% e índice de masa corporal 29±5 kg·m-2). La actividad física fue medida por un acelerómetro (SenseWear® Pro2 Armband) y por un cuestionario (Yale Physical Activity Survey, YPAS). Las variables sociodemográficas (edad, sexo, estado civil, nivel educativo, nivel socioeconómico, situación laboral y hábito tabáquico) y las variables clínicas (limitación al flujo aereo, hiperinsuflación pulmonar, disnea, intercambio de gases, inflamación sistémica y local, composición corporal, comorbilidades, calidad de la vida y capacidad de ejercicio), se obtuvieron utilizando instrumentos validados y siguiendo las normas internacionales. La información sobre la evolución de la enfermedad (ingresos hospitalarios y mortalidad) se obtuvo de los registros gubernamentales. Resultados: (Objetivo 1) El YPAS es una herramienta válida para la detección precoz de la inactividad de los individuos con EPOC [área bajo la curva ROC (95% IC) = 0.71 (0.63-0.79)]. (Objetivo 2) El 97% de los individuos con EPOC son capaces de realizar episodios de 10 minutos de actividad física moderada-vigorosa. Más del 50% de los individuos con EPOC cumplen con la recomendación de la Organización Mundial de la Salud sobre actividad física para las personas mayores. La cantidad de actividad física, la proporción de ésta realizada en episodios de 10 minutos y la frecuencia de estos episodios disminuyó con el aumento de la gravedad de la EPOC. (Objetivo 3) La cantidad y la intensidad de la actividad física son determinantes independientes de la evolución de la EPOC. El riesgo de hospitalización por EPOC es un 20% menor por cada 1000 pasos adicionales realizados en baja intensidad media. Sin embargo, una mayor cantidad de pasos diarios a una alta intensidad media no influye en el riesgo de hospitalización por EPOC (HR = 1.01; p = 0,919). Conclusiones: El YPAS es una herramienta válida para la detección precoz de los individuos con EPOC físicamente inactivos. Los pacientes con EPOC grave y muy grave realizan menos episodios y cantidad de actividad física, y tienen menor el ratio entre episodios y cantidad que en aquellos en estado leve y moderado. Una mayor cantidad de actividad física de baja intensidad reduce el riesgo de hospitalización por EPOC.Background: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of worldwide mortality and disability. Physical activity is one of the few modifiable factors that decelerate COPD evolution. Nonetheless, the dose and characteristics of physical activity responsible of the deceleration are still unknown. In consequence, the aims of this thesis are to move forward and refine the methodology and instruments to evaluate the physical activity of COPD individuals, go in depth in the knowledge about the characteristics and the pattern of their physical activity, and determine which physical activity characteristics improve the prognosis of COPD patients. Methods: 177 individuals with stable COPD selected from 8 hospitals in Spain have participated (94% male, mean±SD age 71±8 years, forced expiratory volume in 1 s 52±16% predicted and body mass index 29±5 kg·m-2). Physical activity was measured with an accelerometer (SenseWear® Pro2 Armband) and with a questionnaire (Yale Physical Activity Survey, YPAS). The sociodemographic (age, sex, civil status, educational level, socioeconomic status, employment status, and tobacco habit) and clinical variables (airflow limitation, lung hyperinflation, dyspnoea, gas exchange, local and systemic inflammation, body composition, comorbidities, quality of life, and exercise capacity), were obtained using validated tools and following international standards. Information about the evolution of the disease (Hospital Admissions and Mortality) was obtained from government registries. Results: (Objective 1) The YPAS is a valid tool for the detection of COPD individuals’ inactivity [the area under the ROC curve is 0.71 (95% CI: 0.63–0.79)]. (Objective 2) The 97% of COPD individuals are able to perform 10-minutes bouts of moderate-to-vigorous physical activity. More than 50% of the COPD individuals met the World Health Organization recommendation of physical activity for the elderly. The quantity of physical activity, the percentage of activity done in bouts and the frequency of bouts decreased with increasing COPD severity. (Objective 3) The quantity and the intensity of physical activity are independent determinants of the COPD evolution. Every additional 1000 daily steps at low-average intensity reduce by 20% the risk of COPD hospitalisation. However, a greater quantity of daily steps at high-average intensity does not influence the risk of COPD hospitalisation (HR 1.01, p=0.919). Conclusion: The YPAS is a valid instrument for the early screening of COPD patients who run the risk of sedentarism. Patients with severe and very severe COPD perform fewer bouts and less quantity of physical activity, and have lower ratio between bouts and quantity than those in mild and moderate stages. Higher quantity of low-intensity physical activity reduces the risk of COPD hospitalization

Built Environment Interventions to Increase Active Travel: a Critical Review and Discussion

Purpose of Review: To review the literature on built environment interventions to increase active travel, focusing on work since 2000 and on methodological choices and challenges affecting studies. Recent Findings: Increasingly, there is evidence that built environment interventions can lead to more walking or cycling. Evidence is stronger for cycling than for walking interventions, and there is a relative lack of evidence around differential impacts of interventions. Some of the evidence remains methodologically weak, with much work in the ‘grey’ literature. Summary: While evidence in the area continues to grow, data gaps remain. Greater use of quasi-experimental techniques, improvements in routine monitoring of smaller schemes, and the use of new big data sources are promising. More qualitative research could help develop a more sophisticated understanding of behaviour change

The neighbourhood environment and profiles of the metabolic syndrome

Background: There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. Methods: We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. Results: LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. Conclusions: This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components

The neighbourhood environment and profiles of the metabolic syndrome

Background There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. Methods We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. Results LCA yielded three latent classes, one including only participants without MetS (“Lower probability of MetS components” profile). The other two classes/profiles, consisting of participants with and without MetS, were “Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure” and “Higher probability of MetS components”. Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. Conclusions This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components

Improving traffic-related air pollution estimates by modelling minor road traffic volumes

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia. We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models' performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman's correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were -0.001 (-0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman's correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data

Improving traffic-related air pollution estimates by modelling minor road traffic volumes

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia. We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models’ performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman’s correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were − 0.001 (− 0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman’s correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data

Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status

Traffic-related air pollution (TRAP) is associated with lower cognitive function and diabetes in older adults, but little is known about whether diabetes status moderates the impact of TRAP on older adult cognitive function. We analysed cross-sectional data from 4141 adults who participated in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study in 2011–2012. TRAP exposure was estimated using major and minor road density within multiple residential buffers. Cognitive function was assessed with validated psychometric scales, including: California Verbal Learning Test (memory) and Symbol–Digit Modalities Test (processing speed). Diabetes status was measured using oral glucose tolerance tests. We observed positive associations of some total road density measures with memory but not processing speed. Minor road density was not associated with cognitive function, while major road density showed positive associations with memory and processing speed among larger buffers. Within a 300 m buffer, the relationship between TRAP and memory tended to be positive in controls (β = 0.005; p = 0.062), but negative in people with diabetes (β = −0.013; p = 0.026) and negatively associated with processing speed in people with diabetes only (β = −0.047; p = 0.059). Increased TRAP exposure may be positively associated with cognitive function among urban-dwelling people, but this benefit may not extend to those with diabetes

Urban and Transport Planning Related Exposures and Mortality: A Health Impact Assessment for Cities

BACKGROUND: By 2050, almost 70% of people globally are projected to live in urban areas. As the environments we inhabit affect our health, urban and transport designs that promote healthy living are needed. OBJECTIVE: We estimated the number of premature deaths preventable under compliance with international exposure recommendations for physical activity (PA), air pollution, noise, heat, and access to green spaces. METHODS: We developed and applied the Urban and TranspOrt Planning Health Impact Assessment (UTOPHIA) tool to Barcelona. Exposure estimates and mortality data were available for 1357361 residents. We compared recommended with current exposure levels. We quantified the associations between exposures and mortality and calculated population attributable fractions to estimate the number of premature deaths preventable. We also modeled life-expectancy and economic impacts. RESULTS: We estimated that annually almost 20% of mortality could be prevented if international recommendations for performance of PA, exposure to air pollution, noise, heat, and access to green space were complied with. Estimations showed that the biggest share in preventable deaths was attributable to increases in PA, followed by exposure reductions in air pollution, traffic noise and heat. Access to green spaces had smaller effects on mortality. Compliance was estimated to increase the average life expectancy by 360 (95% CI: 219, 493) days and result in economic savings of 9.3 (95% CI: 4.9; 13.2) billion euro per year. CONCLUSIONS: PA factors and environmental exposures can be modified by changes in urban and transport planning. We emphasize the need for (1) the reduction of motorized traffic through the promotion of active and public transport and (2) the provision of green infrastructure, which are both suggested to provide PA opportunities and mitigation of air pollution, noise, and heat

Factors affecting the relationship between psychological status and quality of life in COPD patients

<p>Abstract</p> <p>Background</p> <p>This study aims to (i) evaluate the association between anxiety and depressive symptoms and health-related quality of life (HRQoL); and (ii) identify the effect modifiers of this relationship in patients with chronic obstructive pulmonary disease (COPD).</p> <p>Methods</p> <p>A total of 337 clinically stable COPD patients answered the St. George's Respiratory Questionnaire (SGRQ) (assessing HRQoL) and the Hospital Anxiety and Depression Scale (HADS). Socio-demographic information, lung function, and other clinical data were collected.</p> <p>Results</p> <p>Most patients (93%) were male; they had a mean (SD) age of 68 (9) years and mild to very severe COPD (post-bronchodilator FEV₁52 (16)% predicted). Multivariate analyses showed that anxiety, depression, or both conditions were associated with poor HRQoL (for all SGRQ domains). The association between anxiety and total HRQoL score was 6.7 points higher (indicating a worse HRQoL) in current workers than in retired individuals. Estimates for patients with "both anxiety and depression" were 5.8 points lower in stage I-II than in stage III-IV COPD, and 10.2 points higher in patients with other comorbidities than in those with only COPD.</p> <p>Conclusions</p> <p>This study shows a significant association between anxiety, depression, or both conditions and impaired HRQoL. Clinically relevant factors affecting the magnitude of this association include work status, COPD severity, and the presence of comorbidities.</p

Positive health effects of the natural outdoor environment in typical populations in different regions in Europe (PHENOTYPE): a study programme protocol

Introduction Growing evidence suggests that close contact with nature brings benefits to human health and well-being, but the proposed mechanisms are still not well understood and the associations with health remain uncertain. The Positive Health Effects of the Natural Outdoor environment in Typical Populations in different regions in Europe (PHENOTYPE) project investigates the interconnections between natural outdoor environments and better human health and well-being. Aims and methods The PHENOTYPE project explores the proposed underlying mechanisms at work (stress reduction/restorative function, physical activity, social interaction, exposure to environmental hazards) and examines the associations with health outcomes for different population groups. It implements conventional and new innovative high-tech methods to characterise the natural environment in terms of quality and quantity. Preventive as well as therapeutic effects of contact with the natural environment are being covered. PHENOTYPE further addresses implications for land-use planning and green space management. The main innovative part of the study is the evaluation of possible short-term and long-term associations of green space and health and the possible underlying mechanisms in four different countries (each with quite a different type of green space and a different use), using the same methodology, in one research programme. This type of holistic approach has not been undertaken before. Furthermore there are technological innovations such as the use of remote sensing and smartphones in the assessment of green space. Conclusions The project will produce a more robust evidence base on links between exposure to natural outdoor environment and human health and well-being, in addition to a better integration of human health needs into land-use planning and green space management in rural as well as urban areas