Chantal M. Koolhaas

Levels of ambient air pollution according to mode of transport: a systematic review

BACKGROUND Controversy exists about the differences in air pollution exposure and inhalation dose between mode of transport. We aimed to review air pollution exposure and inhaled dose according to mode of transport and pollutant and their effect in terms of years of life expectancy (YLE). METHODS In this systematic review, we searched ten online databases from inception to April 13, 2016, without language or temporal restrictions, for cohort, cross-sectional, and experimental studies that compared exposure to carbon monoxide, black carbon, nitrogen dioxide, and fine and coarse particles in active commuters (pedestrian or cyclist) and commuters using motorised transport (car, motorcycle, bus, or massive motorised transport [MMT-ie, train, subway, or metro]). We excluded studies that measured air pollution exposure exclusively with biomarkers or on the basis of simulated data, reviews, comments, consensuses, editorials, guidelines, in-vitro studies, meta-analyses, ecological studies, and protocols. We extracted average exposure and commuting time per mode of transport and pollutant to calculate inhaled doses. We calculated exposure and inhaled dose ratios using active commuters as the reference and summarised them with medians and IQRs. We also calculated differences in YLE due to fine particle inhaled dose and physical activity. FINDINGS We identified 4037 studies, of which 39 were included in the systematic review. Overall, car commuters had higher exposure to all pollutants than did active commuters in 30 (71%) of 42 comparisons (median ratio 1·22 [IQR 0·90-1·76]), followed by those who commuted by bus in 57 (52%) of 109 (1·0 [0·79-1·41]), by motorcycle in 16 (50%) of 32 (0·99 [0·86-1·38]), by a car with controlled ventilation settings in 39 (45%) of 86 (0·95 [0·66-1·54]), and by MMT in 21 (38%) of 55 (0·67 [0·49-1·13]). Overall, active commuters had higher inhalation doses than did commuters using motorised transport (median ratio car with controlled ventilation settings 0·16 [0·10-0·28]; car 0·22 [0·15-0·30]; motorcycle 0·38 [0·26-0·78]; MMT 0·49 [0·34-0·81]; bus 0·72 [IQR 0·50-0·99]). Commuters using motorised transport lost up to 1 year in YLE more than did cyclists. INTERPRETATION Proximity to traffic and high air interchange increased the exposure to air pollution of commuters using motorised transport. Larger inhalation rates and commuting time increased inhaled dose among active commuters. Benefits of active commuting from physical activity are larger than the risk from an increased inhaled dose of fine particles. FUNDING Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS), National Health and Medical Research Council, Nestlé Nutrition (Nestec), Metagenics, and AXA.

Physical Activity Types and Coronary Heart Disease Risk in Middle-Aged and Elderly Persons The Rotterdam Study

Physical activity is associated with decreased risk of coronary heart disease (CHD). The specific physical activity types that provide beneficial effects in an older population remain unclear. We assessed the association of total physical activity, walking, cycling, domestic work, sports, and gardening with CHD by using Cox proportional hazard models among 5,901 participants aged >55 (median age, 67) years from the prospective population-based Rotterdam Study, enrolled between 1997 and 2001. Activities were categorized into tertiles, and the lowest tertiles were used as reference. In the multivariable model, we adjusted for age, sex, smoking, alcohol consumption, education, diet, and other physical activity types. During 15 years of follow-up (median, 10.3 (interquartile range, 8.0-11.8) years), 642 participants (10.9%) experienced a CHD event. In the multivariable model, the respective hazard ratios for the medium and high categories compared with the low category were 0.79 (95% confidence interval CI): 0.66, 0.96) and 0.71 (95% CI: 0.58, 0.87) for total physical activity, 0.76 (95% CI: 0.63, 0.92) and 0.70 (95% CI: 0.57, 0.88) for cycling, and 0.81 (95% CI: 0.66, 0.98) and 0.71 (95% CI: 0.56, 0.90) for domestic work. Walking, sports, and gardening were not associated with CHD. In conclusion, in this long-term follow-up study of older adults, domestic work and cycling were associated with reduced CHD risk. Physical activity should be promoted in this population with the aim to prevent CHD.

Impact of physical activity on the association of overweight and obesity with cardiovascular disease: The Rotterdam Study

Background Being overweight or obese is associated with an increased risk of cardiovascular disease (CVD). Physical activity might reduce the risk associated with overweight and obesity. We examined the association between overweight and obesity and CVD risk as a function of physical activity levels in a middle-aged and elderly population. Design The study was a prospective cohort study. Methods The study included 5344 participants aged 55 years or older from the population-based Rotterdam Study. Participants were classified as having high or low physical activity based on the median of the population. Normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2) and obese participants (≥30 kg/m2) were categorized as having high or low physical activity to form six categories. We assessed the association of the six categories with CVD risk using Cox proportional hazard models adjusted for confounders. High physical activity and normal weight was used as the reference group. Results During 15 years of follow-up (median 10.3 years, interquartile range 8.2–11.7 years), 866 (16.2%) participants experienced a CVD event. Overweight and obese participants with low physical activity had a higher CVD risk than normal weight participants with high physical activity. The HRs and 95% confidence intervals (CIs) were 1.33 (1.07–1.66) and 1.35 (1.04–1.75), respectively. Overweight and obese participants with high physical activity did not show a higher CVD risk (HRs (95%CIs) 1.03 (0.82–1.29) and 1.12 (0.83–1.52), respectively). Conclusions Our findings suggest that the beneficial impact of physical activity on CVD might outweigh the negative impact of body mass index among middle-aged and elderly people. This emphasizes the importance of physical activity for everyone across all body mass index strata, while highlighting the risk associated with inactivity even among normal weight people.

Metabolically Healthy Obesity and the Risk of Cardiovascular Disease in the Elderly Population

Background Whether being metabolically healthy obese (MHO)—defined by the presence of obesity in the absence of metabolic syndrome—is associated with subsequent cardiovascular disease (CVD) remains unclear and may depend on the participants’ age. We examined the association of being MHO with CVD risk in the elderly. Methods and Findings This study included 5,314 individuals (mean age 68 years) from the prospective population-based Rotterdam Study. We categorized our population in groups according to body mass index (BMI) and presence and absence of metabolic syndrome, and estimated the hazard ratio (HR) and 95% confidence interval (95%CI) for every group by using Cox proportional hazard models. Among 1048 (19.7%) obese individuals we identified 260 (24.8%) MHO subjects. Over 14 years of follow-up there were 861 incident CVD cases. In the multivariable adjusted analysis, we did not observe an increased CVD risk in MHO individuals (HR 1.07, 95%CI 0.75–1.53), compared to normal weight individuals without metabolic syndrome. CVD risk was increased by the presence of metabolic syndrome in normal weight (HR 1.35, 95%CI 1.02–1.80), overweight (HR 1.32, 95%CI 1.09–1.60) and obese (HR 1.33, 95%CI 1.07–1.66) individuals, compared to those with normal weight without metabolic syndrome. In a mediation analysis, 71.3% of the association between BMI and CVD was explained by the presence of metabolic syndrome. Conclusions In our elderly population, we found that the presence of obesity without metabolic syndrome did not confer a higher CVD risk. However, metabolic syndrome was strongly associated with CVD risk, and was associated with an increased risk in all BMI categories. Therefore, preventive interventions targeting cardiometabolic risk factors could be considered in elderly, regardless of weight status.

Sedentary time assessed by actigraphy and mortality: The Rotterdam Study.

Research suggests that sedentary behavior is a risk factor for mortality. However, most studies rely on questionnaires, which are prone to reporting error. We examined the association between sedentary time assessed by actigraphy and mortality among 1839 participants, aged 45-98years, from the prospective population-based Rotterdam Study, enrolled between 2004 and 2007. Participants wore an actigraph around the wrist for seven days. Sedentary time was evaluated continuously, per 1h/day increase, and categorically in three groups (<8, 8-11, ≥11h/day). The lowest category was used as reference. Mortality risks were examined using Cox proportional hazard models, adjusted for confounders and biological risk factors. We examined the association between sedentary behavior and mortality over and beyond other activity measures (including physical activity (PA) and activities of daily living (ADL)) in a final model. During 11years of follow-up (median: 7.5years, interquartile range: 6.6-8.3years), 212 participants (11.5%) died. In the multivariable model, the hazard ratio (HR) and 95% confidence interval (95% CI) per 1 more hour/day sedentary time was 1.09 (1.00, 1.18). The HR (95% CI) after adjustment for PA and ADL was 1.04 (0.96, 1.13). Participants sedentary for ≥11h/day had a higher mortality risk (HR: 1.80, 95% CI: 1.14, 2.84) than those sedentary <8h/day, in the multivariable model. After adjusting for PA and ADL, this association was clearly attenuated (HR: 1.50, 95% CI: 0.93, 2.41). In conclusion, our study suggests that sedentary behavior is a risk factor for mortality. Further investigation is needed to examine whether this association is distinct from the effect of other measures of activity.

Physical activity types and life expectancy with and without cardiovascular disease: the Rotterdam Study

Background We aimed to determine the contribution of specific physical activity (PA) types (i.e. walking, cycling, domestic work, sports and gardening) on total life expectancy (LE) and LE with and without cardiovascular disease (CVD). Methods We constructed multistate life tables to calculate the effects of total PA and PA types on LE, among individuals older than 55 years from the Rotterdam Study. For the life table calculations, we used sex‐specific prevalences, incident rates and hazard ratios for three transitions (healthy‐to‐CVD, healthy‐to‐death and CVD‐to‐death) by levels of PA and adjusted for confounders. Results High total PA was associated with gains in total and CVD‐free LE. High cycling contributed to higher total LE in men (3.7 years) and women (2.1 years) and higher LE without CVD in men (3.1 years) and women (2.4 years). Total and CVD‐free LE were increased by high domestic work in women (2.6 and 2.4 years, respectively) and high gardening in men (2.7 and 2.0 years, respectively). Conclusions Higher PA levels are associated with increased LE and more years lived without CVD. Of the different PA types, cycling provided high effects in both men and women. Cycling could be more strongly encouraged in activity guidelines to maximize the population benefits of PA.

Seasonality of physical activity, sedentary behavior, and sleep in a middle-aged and elderly population: The Rotterdam study

INTRODUCTION Physical activity (PA) and sedentary behavior (SB) have seasonal patterns. It remains unclear how these patterns are associated with sleep, meteorological factors, and health. METHODS Activity levels were continuously measured with an accelerometer for seven days between July 2011 and May 2016, among middle-aged (50-64 years), young-elderly (65-74 years) and old-elderly (≥75 years) participants of a population-based Dutch cohort study (n = 1116). Meteorological factors (ambient temperature, wind speed, sunlight hours, precipitation, and minimum visibility) were locally recorded. We first examined the seasonality of PA, SB, and nighttime sleep, stratified by age group. Second, we examined the influence of meteorological factors. Third, we modeled the potential seasonality of the all-cause mortality risk due to the seasonality of PA and SB, by using previously published relative risks. RESULTS Levels of light and moderate-to-vigorous PA were higher in summer than in winter among middle-aged (seasonal variation = 18.1 and 14.8 min/day) and young-elderly adults (12.8 and 8.6 min/day). The pattern was explained by ambient temperature and sunlight hours. Nighttime sleep was 31.8 min/day longer in winter among middle-aged adults. SB did not show a seasonal pattern. No seasonality in activity levels was observed among old-elderly adults. The all-cause mortality risk may be higher in winter than in summer due to the accumulation of low levels of moderate to vigorous PA and high levels of SB. CONCLUSION PA has a larger degree of seasonality than SB and nighttime sleep among middle-aged and young-elderly adults. SB appears strongly ingrained in daily routine. Recommending the interruption of SB with light PA might be a good starting point for public health institutions.

Physical activity types and atrial fibrillation risk in the middle-aged and elderly: The Rotterdam Study

Background The association between physical activity and atrial fibrillation remains controversial. Physical activity has been associated with a higher and lower atrial fibrillation risk. These inconsistent results might be related to the type of physical activity. We aimed to investigate the association of total and types of physical activity, including walking, cycling, domestic work, gardening and sports, with atrial fibrillation. Design Prospective cohort study. Methods Our study was performed in the Rotterdam Study, a prospective population-based cohort. We included 7018 participants aged 55 years and older with information on physical activity between 1997–2001. Cox proportional hazards models were used to examine the association of physical activity with atrial fibrillation risk. Models were adjusted for biological and behavioural risk factors and the remaining physical activity types. Physical activity was categorised in tertiles and the low group was used as reference. Results During 16.8 years of follow-up (median: 12.3 years, interquartile range: 8.7–15.9 years), 800 atrial fibrillation events occurred (11.4% of the study population). We observed no association between total physical activity and atrial fibrillation risk in any model. After adjustment for confounders, the hazard ratio and 95% confidence interval for the high physical activity category compared to the low physical activity category was: 0.71 (0.80–1.14) for total physical activity. We did not observe a significant association between any of the physical activity types with atrial fibrillation risk. Conclusion Our results suggest that physical activity is not associated with higher or lower risk of atrial fibrillation in older adults. Neither total physical activity nor any of the included physical activity types was associated with atrial fibrillation risk.

Erratum to “Association of anthropometric measures with fat and fat-free mass in the elderly: The Rotterdam study” [Maturitas 88 (2016) 96–100]

The publisher regrets that the name of one of the authors was listed incorrectly in the original article. The correct author list appears above. The publisher would like to apologise for any inconvenience caused.

Physical activity derived from questionnaires and wrist-worn accelerometers: comparability and the role of demographic, lifestyle, and health factors among a population-based sample of older adults

Background Agreement between questionnaires and accelerometers to measure physical activity (PA) differs between studies and might be related to demographic, lifestyle, and health characteristics, including disability and depressive symptoms. Methods We included 1,410 individuals aged 51–94 years from the population-based Rotterdam Study. Participants completed the LASA Physical Activity Questionnaire and wore a wrist-worn accelerometer on the nondominant wrist for 1 week thereafter. We compared the Spearman correlation and disagreement (level and direction) for total PA across levels of demographic, lifestyle, and health variables. The level of disagreement was defined as the absolute difference between questionnaire- and accelerometer-derived PA, whereas the direction of disagreement was defined as questionnaire PA minus accelerometer PA. We used linear regression analyses with the level and direction of disagreement as outcome, including all demographic, lifestyle, and health variables in the model. Results We observed a Spearman correlation of 0.30 between questionnaire- and accelerometer-derived PA in the total population. The level of disagreement (ie, absolute difference) was 941.9 (standard deviation [SD] 747.0) minutes/week, and the PA reported by questionnaire was on average 529.4 (SD 1,079.5) minutes/week lower than PA obtained by the accelerometer. The level of disagreement decreased with higher educational levels. Additionally, participants with obesity, higher disability scores, and more depressive symptoms underestimated their self-reported PA more than their healthier counterparts. Conclusion We observed large differences in PA time derived from the LASA Physical Activity Questionnaire and the wrist-worn accelerometer. Differences between the methods were related to body-mass index, level of disability, and presence of depressive symptoms. Future studies using questionnaires and/or accelerometers should account for these differences.