The Predictive Value of Serum Aldosterone Level for Coronary Artery Calcium Score in Patients with Chronic Kidney Disease: A Single-center Study

Patients with chronic kidney disease (CKD) have high cardiovascular risk (CVR), which is often underestimated by conventional tools. The coronary artery calcium score (CACS) significantly improves CVR stratification by conventional tools, but it is often not available in low-resources settings. Aldosterone may be a cheaper alternative to CACS for CVR assessment in CKD patients. The aim was to assess the ability of serum aldosterone level to predict CACS in patients with CKD in comparison to standard predictors. This single-center study included 57 patients aged 40 to 67 years with CKD (estimated glomerular filtration rate [eGFR] ≥45 ml/min) and arterial hypertension. Serum aldosterone, sex, age, body mass index, blood pressure, total cholesterol, eGFR, and proteinuria were used for prediction of CACS>0 Agatston units (AU) and CACS>100 AU. The area under the curve (AUC) with 95% confidence intervals (CI) and the mean Brier scores were examined for predictors of CACS. Aldosterone predicted a CACS>100 AU (AUC = 0.72, 95% CI: 0.56-0.88), but not a CACS>0 AU. Age predicted a CACS>100 AU (AUC = 0.80, 95% CI: 0.67-0.93) and a CACS>0 AU (AUC = 0.75, 95% CI: 0.62-0.89). The addition of aldosterone to age for prediction of a CACS>100 AU improved the mean Brier score, compared to the model with age alone, from 0.16 to 0.14, but not the AUC (0.83, 95% CI: 0.70-0.95). Aldosterone was a significant predictor of a CACS>100 AU in patients with CKD, but aldosterone was not a better predictor than age alone.

The timeliness of COVID-19 testing and tracing in eight public health regions in the Netherlands

Background

Testing and Contact Tracing (TCT) was a core strategy in the fight against the spread of SARS-CoV-2. However, little is known about the real-world effectiveness of TCT for COVID-19. Because time is an important conditional factor, we aim to study timeliness of TCT in the Netherlands, and its determinants.

Methods

We used routine COVID-19 TCT registry data from all individuals who tested positive for SARS-CoV-2 at 8 Dutch regional public health services from 1-6-2020 to 28-2-2021 (N = 338,066). We calculated median time intervals of TCT stages. Factors associated with the time between test result and completion of TCT, categorised as ≤ 3 days and >3 days, were assessed using logistic regression adjusting for region, testing site, and laboratory. Potential determinants were: gender, age, country of birth, number of close contacts, working in health-care or education, TCT manpower, and the Oxford Covid-19 Government Response Tracker (OxCGRT).

Results

The median time from symptom onset to TCT completion was 6 days (IQR:3-10). Median times between TCT stages were 1 day (IQR:0-3) for symptom onset to test request, 1 day, (IQR:0-1) for test request to sample collection, 1 day, (IQR:1-1) for sample collection to test result, and 2 days (IQR:1-5) for test result to TCT completion. In 31.7% of tests, time between test result and TCT completion was >3 days. This delay was associated with being older (65+), whereas being younger (0-14), a higher OxCGRT, scaling down TCT, and a higher number of TCT employees were associated with a shorter interval.

Conclusions

Over fifty percent of interval times from symptom onset to TCT completion exceeded the median SARS-CoV-2 incubation period of 5 days. There seems to be little room for improvement on the side of the index case, but there are some implications for logistics such as increasing TCT manpower, and better integration of digital systems.

Key messages

Factors Associated With Using the COVID-19 Mobile Contact-Tracing App Among Individuals Diagnosed With SARS-CoV-2 in Amsterdam, the Netherlands: Observational Study

Background

Worldwide, efforts are being made to stop the COVID-19 pandemic caused by SARS-CoV-2. Contact tracing and quarantining are key in limiting SARS-CoV-2 transmission. Mathematical models have shown that the time between infection, isolation of cases, and quarantining of contacts are the most important components that determine whether the pandemic can be controlled. Mobile contact-tracing apps could accelerate the tracing and quarantining of contacts, including anonymous contacts. However, real-world observational data on the uptake and determinants of contact-tracing apps are limited.

Objective

The aim of this paper is to assess the use of a national Dutch contact-tracing app among notified cases diagnosed with SARS-CoV-2 infection and investigate which characteristics are associated with the use of the app.

Methods

Due to privacy regulations, data from the app could not be used. Instead, we used anonymized SARS-CoV-2 routine contact-tracing data collected between October 28, 2020, and February 26, 2021, in the region of Amsterdam, the Netherlands. Complete case logistic regression analysis was performed to identify which factors (age, gender, country of birth, municipality, number of close contacts, and employment in either health care or education) were associated with using the app. Age and number of close contacts were modelled as B-splines due to their nonlinear relationship.

Results

Of 29,766 SARS-CoV-2 positive cases, 4824 (16.2%) reported app use. Median age of cases was 41 (IQR 29-55) years, and 46.7% (n=13,898) were male. In multivariable analysis, males (adjusted odds ratio [AOR] 1.11, 95% CI 1.04-1.18) and residents of municipalities surrounding Amsterdam were more likely to use the app (Aalsmeer AOR 1.34, 95% CI 1.13-1.58; Ouder-Amstel AOR 1.96, 95% CI 1.54-2.50), while people born outside the Netherlands, particularly those born in non-Western countries (AOR 0.33, 95% CI 0.30-0.36), were less likely to use the app. Odds of app use increased with age until the age of 58 years and decreased sharply thereafter (P<.001). Odds of app use increased with number of contacts, peaked at 8 contacts, and then decreased (P<.001). Individuals working in day care, home care, and elderly nursing homes were less likely to use the app.

Conclusions

Contact-tracing app use among people with confirmed SARS-CoV-2 infection was low in the region of Amsterdam. This diminishes the potential impact of the app by hampering the ability to warn contacts. Use was particularly low among older people, people born outside the Netherlands, and people with many contacts. Use of the app was also relatively low compared to those from some other European countries, some of which had additional features beyond contact tracing, making them potentially more appealing. For the Dutch contact-tracing app to have an impact, uptake needs to be higher; therefore, investing more into promotional efforts and additional features could be considered.

Self-reported symptoms as predictors of SARS-CoV-2 infection in the general population living in the Amsterdam region, the Netherlands

INTRODUCTION

Most COVID-19 symptoms are non-specific and also common in other respiratory infections. We aimed to assess which symptoms are most predictive of a positive test for SARS-CoV-2 in symptomatic people of the general population who were tested.

METHODS

We used anonymised data of all SARS-CoV-2 test results from the Public Health Service of Amsterdam from June 1,2020 through August 31, 2021. Symptoms were self-reported at time of requesting a test. Multivariable logistic regression models with generalized estimating equations were used to identify predictors of a positive test. Included symptoms were: cough, fever, loss of smell or taste, muscle ache, runny nose, shortness of breath, and throat ache; adjustments were made for age and gender, and stratification by month.

RESULTS

Overall, 12.0% of 773,680 tests in 432,213 unique individuals were positive. All symptoms were significantly associated with a positive test result, the strongest positive associations were: cough (aOR = 1.78, 95%CI = 1.75-1.80), fever (aOR = 2.11, 95%CI = 2.07-2.14), loss of smell or taste (aOR = 2.55, 95%CI = 2.50-2.61), and muscle ache (aOR = 2.38, 95%CI = 2.34-2.43). The adjusted odds ratios for loss of smell or taste slightly declined over time, while that for cough increased.

CONCLUSION

Cough, fever, loss of smell or taste, and muscle ache appear to be most strongly associated with a positive SARS-CoV-2 test in symptomatic people of the general population who were tested.

Evidence-based medicine-When observational studies are better than randomized controlled trials

In evidence-based medicine, clinical research questions may be addressed by different study designs. This article describes when randomized controlled trials (RCT) are needed and when observational studies are more suitable. According to the Centre for Evidence-Based Medicine, study designs can be divided into analytic and non-analytic (descriptive) study designs. Analytic studies aim to quantify the association of an intervention (eg, treatment) or a naturally occurring exposure with an outcome. They can be subdivided into experimental (ie, RCT) and observational studies. The RCT is the best study design to evaluate the intended effect of an intervention, because the randomization procedure breaks the link between the allocation of the intervention and patient prognosis. If the randomization of the intervention or exposure is not possible, one needs to depend on observational analytic studies, but these studies usually suffer from bias and confounding. If the study focuses on unintended effects of interventions (ie, effects of an intervention that are not intended or foreseen), observational analytic studies are the most suitable study designs, provided that there is no link between the allocation of the intervention and the unintended effect. Furthermore, non-analytic studies (ie, descriptive studies) also rely on observational study designs. In summary, RCTs and observational study designs are inherently different, and depending on the study aim, they each have their own strengths and weaknesses.

The ERA-EDTA Registry Annual Report 2017: a summary

Background

This article presents a summary of the 2017 Annual Report of the European Renal Association–European Dialysis and Transplant Association (ERA-EDTA) Registry and describes the epidemiology of renal replacement therapy (RRT) for end-stage renal disease (ESRD) in 37 countries.

Methods

The ERA-EDTA Registry received individual patient data on patients undergoing RRT for ESRD in 2017 from 32 national or regional renal registries and aggregated data from 21 registries. The incidence and prevalence of RRT, kidney transplantation activity and survival probabilities of these patients were calculated.

Results

In 2017, the ERA-EDTA Registry covered a general population of 694 million people. The incidence of RRT for ESRD was 127 per million population (pmp), ranging from 37 pmp in Ukraine to 252 pmp in Greece. A total of 62% of patients were men, 52% were ≥65 years of age and 23% had diabetes mellitus as the primary renal disease. The treatment modality at the onset of RRT was haemodialysis for 85% of patients. On 31 December 2017, the prevalence of RRT was 854 pmp, ranging from 210 pmp in Ukraine to 1965 pmp in Portugal. The transplant rate in 2017 was 33 pmp, ranging from 3 pmp in Ukraine to 103 pmp in the Spanish region of Catalonia. For patients commencing RRT during 2008–12, the unadjusted 5-year patient survival probability for all RRT modalities combined was 50.8%.

Effects of parental sensitivity in different contexts on children's hot and cool effortful control

To thrive as an individual and within society, children need to develop the ability to control their behavior. Using a twin design, we estimated the relative influence of genetic, shared, and unique environmental factors on hot and cool effortful control (EC). Furthermore, we investigated whether parental sensitivity in a play, task, or discipline context when the children were on average 3.78 years old, was differentially related to children's hot and cool EC 1 year later (M_age 4.77 years). We included 476 children from 238 twin pairs (48% boys, 58% monozygotic) and their primary parent. Hot EC (delay of gratification) was measured with the marshmallow test and cool EC (response inhibition) was measured with a stop-signal task. The behavioral genetics analyses showed that individual differences in hot and cool EC were mostly explained by unique environmental factors, whereas their association was mostly explained by shared environmental factors. Controlling for sensitivity in the other contexts, task sensitivity contributed to the prediction of cool EC, and sensitive discipline contributed to both cool and hot EC. Play sensitivity did not contribute to the prediction of hot or cool EC over and above parental sensitivity in the other contexts. Our study contributes to a better understanding of the unique and shared antecedents of hot and cool EC, suggesting parental sensitive discipline as a focus for preventive interventions targeting both hot and cool EC. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

How Heritable are Parental Sensitivity and Limit-Setting? A Longitudinal Child-Based Twin Study on Observed Parenting

We examined the relative contribution of genetic, shared environmental and non-shared environmental factors to the covariance between parental sensitivity and limit-setting observed twice in a longitudinal study using a child-based twin design. Parental sensitivity and parental limit-setting were observed in 236 parents with each of their same-sex toddler twin children (M_age  = 3.8 years; 58% monozygotic). Bivariate behavioral genetic models indicated substantial effects of similar shared environmental factors on parental sensitivity and limit-setting and on the overlap within sensitivity and limit-setting across 1 year. Moderate child-driven genetic effects were found for parental limit-setting in year 1 and across 1 year. Genetic child factors contributing to explaining the variance in limit-setting over time were the same, whereas shared environmental factors showed some overlap.

Did the introduction of pictorial health warnings increase information seeking for smoking cessation?: Time-series analysis of Google Trends data in six countries

INTRODUCTION

Pictorial health warnings (PHW) can influence smoking cessation rates and precursors thereof. However, both the magnitude and duration of their impact, in national populations, remain uncertain because of limitations of the available data. In this study we used Google Trends data from six European countries to evaluate whether the implementation of PHW was followed by a short-term increase in online searches on smoking cessation.

METHODS

We applied an interrupted time-series design using ARIMA models. We used weekly or monthly data on the relative search volume (RSV) for search terms about smoking cessation. First, RSV trends were seasonally adjusted and adjusted for autocorrelation. Next, regression models were fitted that included terms for the potential effect of PHW in month 1, months 2–3, and months 4–6 after implementation.

RESULTS

Our findings for France and the United Kingdom were partly in line with our initial expectations. In France, a 4% increase (95% CI: -2% – 11%) occurred in the first month after implementation, but not later. In the UK, a 3% increase (95% CI: 1% – 6%) in ‘quit smoking’ searches occurred in months 2–3. No increases were observed for any other periods for France, the UK, Ireland, Norway, Denmark or Switzerland.

CONCLUSIONS

We found no consistent support that the implementation of PHW was associated with increased internet searches for smoking cessation. Further studies are needed to assess and understand the magnitude and duration of population-wide impacts of PHW.

Tobacco control policies and smoking among older adults: a longitudinal analysis of 10 European countries

BACKGROUND AND AIMS

The impact of tobacco control on European older adults has not been studied, despite evidence that smoking cessation at old age can bring significant life expectancy gains. Our aim was to evaluate the impact of tobacco control policies on smoking among older adults in Europe from 2004 to 2013.

DESIGN

We used longitudinal data from the Survey of Health, Ageing and Retirement in Europe (SHARE, aged 50+ years) from four waves from 2004 to 2013. We used logistic regression models with clustered standard errors to determine whether the implementation of tobacco control policies was associated with changes in smoking status. Furthermore, we studied whether these associations varied by socio-demographic characteristics. Regression coefficients were converted to changes the probability of smoking [marginal effects (ME)].

MEASUREMENTS

Smoking status was the dependent variable, and the Tobacco Control Scale (TCS) was the explanatory variable, overall and by its main policy components (pricing and smoke-free policies). Covariates included age, sex, education and country and wave fixed-effects.

FINDINGS

A 10-point increase in TCS was associated with a lower probability of smoking by 1.6 percentage points [95% confidence interval (CI) = -3.208, -0.056] for those aged 50-65, but not for older Europeans. Among those with primary school or no education, the associated drop was of 1.5 percentage points (95% CI = -2.751, -0.253). By contrast, no significant relation between TCS and smoking was observed among those with high education. Higher TCS scores for pricing (ME = -0.636, 95% CI = -0.998, -0.275) and smoke-free policies (ME = -0.243, 95% CI = -0.445, -0.041) were associated with a significantly lower probability of smoking (P = 0.001 and P = 0.018, respectively).

CONCLUSION

Increases in tobacco taxes and smoke-free policies are significantly related with a reduction in smoking among European older adults, suggesting potential health gains for this rising share of the population. These policies may be more effective among the lowest educated.

Behavioral genetics of temperament and frontal asymmetry in early childhood

Temperament has been suggested to be influenced by genetic and environmental factors. The current study examined genetic shared environmental and unique environmental factors accounting for variation in Fear, Effortful Control (EC), and Frontal Asymmetry (FA) in 4- to 6-year-old children using bivariate behavioral genetic modeling. We included a total of 214 same-sex twin pairs: 127 monozygotic (MZ) and 87 dizygotic (DZ) pairs. FA was measured during a rest electroencephalogram (EEG) recording, and Fear and EC were measured using parent report. Results show that differences between twins were best explained by genetic factors (about a quarter of the variance) and unique environmental factors (about three quarters of the variance). However, the cross-trait, within-twin correlations were not significant, implying no overlapping genetic or environmental factors on Fear and EC or on Fear and FA. Future research should try to elucidate the large role of unique environmental factors in explaining variance in these temperament-related traits.

The Impact of Tobacco Control Policies on Smoking Among Socioeconomic Groups in Nine European Countries, 1990-2007

Background

It is uncertain whether tobacco control policies have contributed to a narrowing or widening of socioeconomic inequalities in smoking in European countries during the past two decades. This paper aims to investigate the impact of price and non-price related population-wide tobacco control policies on smoking by socioeconomic group in nine European countries between 1990 and 2007.

Methods

Individual-level education, occupation and smoking status were obtained from nationally representative surveys. Country-level price-related tobacco control policies were measured by the relative price of cheapest cigarettes and of cigarettes in the most popular price category. Country-level non-price policies were measured by a summary score covering four policy domains: smoking bans or restrictions in public places and workplaces, bans on advertising and promotion, health warning labels, and cessation services. The associations between policies and smoking were explored using logistic regressions, stratified by education and occupation, and adjusted for age, Gross Domestic Product, period and country fixed effects.

Results

The price of popular cigarettes and non-price policies were negatively associated with smoking among men. The price of the cheapest cigarettes was negatively associated with smoking among women. While these favorable effects were generally in the same direction for all socioeconomic groups, they were larger and statistically significant in lower socioeconomic groups only.

Conclusions

Tobacco control policies as implemented in nine European countries, have probably helped to reduce the prevalence of smoking in the total population, particularly in lower socioeconomic groups. Widening inequalities in smoking may be explained by other factors. Policies with larger effects on lower socioeconomic groups are needed to reverse this trend.

Implications

Socioeconomic inequalities in smoking widened between the 1990s and the 2000s in Europe. During the same period, there were intensified tobacco control policies in many European countries. It is uncertain whether tobacco control policies have contributed to a narrowing or widening of socioeconomic inequalities in smoking in European countries. This study shows that tobacco control policies as implemented in the available European countries have helped to reduce the prevalence of smoking in the total population, particularly in lower socioeconomic groups. Widening inequalities in smoking may be explained by other factors.

Effect of Tobacco Control Policies on Information Seeking for Smoking Cessation in the Netherlands: A Google Trends Study

Background

The impact of tobacco control policies on measures of smoking cessation behaviour has often been studied, yet there is little information on their precise magnitude and duration. This study aims to measure the magnitude and timing of the impact of Dutch tobacco control policies on the rate of searching for information on smoking cessation, using Google Trends search query data.

Methods

An interrupted time series analysis was used to examine the effect of two types of policies (smoke-free legislation and reimbursement of smoking cessation support (SCS)) on Google searches for ‘quit smoking’. Google Trends data were seasonally adjusted and analysed using autoregressive integrated moving average (ARIMA) modelling. Multiple effect periods were modelled as dummy variables and analysed simultaneously to examine the magnitude and duration of the effect of each intervention. The same analysis was repeated with Belgian search query data as a control group, since Belgium is the country most comparable to the Netherlands in terms of geography, language, history and culture.

Results

A significant increase in relative search volume (RSV) was found from one to four weeks (21–41%) after the introduction of the smoking ban in restaurants and bars in the Netherlands in 2008. The introduction of SCS reimbursement in 2011 was associated with a significant increase of RSV (16–22%) in the Netherlands after 3 to 52 weeks. The reintroduction of SCS in 2013 was associated with a significant increase of RSV (9–21%) in the Netherlands from 3 to 32 weeks after the intervention. No effects were found in the Belgian control group for the smoking ban and the reintroduction of SCS in 2013, but there was a significant increase in RSV shortly before and after the introduction of SCS in 2011.

Conclusions

These findings suggest that these tobacco control policies have short-term or medium-term effects on the rate of searching for information on smoking cessation, and therefore potentially on smoking cessation rates.

Socioeconomic inequalities in smoking cessation in 11 European countries from 1987 to 2012

BACKGROUND

During the 1990s, inequalities in smoking prevalence by socioeconomic status (SES) have widened in Europe. Since then, many tobacco control policies have been implemented. Yet, European overviews of recent trends in smoking inequalities are lacking. This paper aims to provide an overview of long-term trends of socioeconomic inequalities in smoking cessation in Europe.

METHODS

We used data for 11 countries taken from Eurobarometer surveys from 1987 to 1995 and 2002-2012, with a total study sample of 63 737 respondents. We performed multilevel logistic regression to model associations of the quit ratio (proportion former smokers of ever smokers) with SES, measured by education and occupation separately, with adjustments for age, sex and time.

RESULTS

We found a significant, positive association for education and occupation with the quit ratio. The strength of the association decreased slightly from 1987 to 1995 and increased again from 2002 to 2012. Inequalities increased between the two periods in most countries and decreased in only one country. While in 1987-1995, the quit ratio increased among all SES groups and most strongly among the low SES group, in 2002-2012 it increased only among the high-education group (OR=1.38, 95% CI 1.02 to 1.87), and non-manual occupation group (OR=1.59, 95% CI 1.19 to 2.12).

CONCLUSIONS

Socioeconomic inequalities in smoking cessation rates have strongly increased since the 1990s and during the 2000s. This suggests that the tobacco control policies implemented during the 2000s have not been able to counter the trend in increasing inequalities.

Socioeconomic inequalities in smoking in low and mid income countries: positive gradients among women?

BACKGROUND

In Southern Europe, smoking among older women was more prevalent among the high educated than the lower educated, we call this a positive gradient. This is dominant in the early stages of the smoking epidemic model, later replaced by a negative gradient. The aim of this study is to assess if a positive gradient in smoking can also be observed in low and middle income countries in other regions of the world.

METHODS

We used data of the World Health Survey from 49 countries and a total of 233,917 respondents. Multilevel logistic regression was used to model associations between individual level smoking and both individual level and country level determinants. We stratified results by education, occupation, sex and generation (younger vs. older than 45). Countries were grouped based on GDP and region.

RESULTS

In Eastern Europe and the Eastern Mediterranean, we observed a positive gradient in smoking among older women and a negative gradient among younger women. In Sub-Saharan Africa and Latin America no clear gradient was observed: inequalities were relatively small. In South-East Asia and East Asia a strong negative gradient was observed. Among men, no positive gradients were observed, and like women the strongest negative gradients were seen in South-East Asia and East Asia.

CONCLUSIONS

A positive socio-economic gradient in smoking was found among older women in two regions, but not among younger women. But contrary to predictions derived from the smoking epidemic model, from a worldwide perspective the positive gradients are the exception rather than the rule.

Smoking prevalence among migrants in the US compared to the US-born and the population in countries of origin

OBJECTIVES

Smoking among migrants is known to differ from the host population, but migrants' smoking is rarely ever compared to the prevalence of smoking in their country of origin. The goal of this study is to compare the smoking prevalence among migrants to that of both the US-born population and the countries of origin. Further analyses assess the influence of sex, age at time of entry to the US and education level.

METHODS

Data of 248,726 US-born and migrants from 14 countries were obtained from the Tobacco Use Supplement to the Current Population Survey (TUS-CPS) from 2006-2007. Data on 108,653 respondents from the corresponding countries of origin were taken from the World Health Survey (WHS) from 2002-2005.

RESULTS

The prevalence of smoking among migrants (men: 14.2%, women: 4.1%) was lower than both the US-born group (men: 21.4%, women: 18.1%) and countries of origin (men: 39.4%, women: 11.0%). The gender gap among migrants was smaller than in the countries of origin. Age at time of entry to the US was not related to smoking prevalence for migrants. The risk of smoking for high-educated migrants was closer to their US counterparts.

CONCLUSIONS

The smoking prevalence among migrants is consistently lower than both the country of origin levels and the US level. The theory of segmented assimilation is supported by some results of this study, but not all. Other mechanisms that might influence the smoking prevalence among migrants are the 'healthy migrant effect' or the stage of the smoking epidemic at the time of migration.

The influence of the macro-environment on physical activity: a multilevel analysis of 38 countries worldwide

BACKGROUND

As indicated by the ANGELO framework and similar models, various environmental factors influence population levels of physical activity (PA). To date attention has focused on the micro-level environment, while evidence on the macro-level environment remains scarce and mostly limited to high-income countries. This study aims to investigate whether environmental factors at macro-level are associated with PA among a broader range of countries.

METHODS

Data from the World Health Survey (WHS) was used to analyze 177,035 adults from 38 (mostly low and middle income) countries. The International Physical Activity Questionnaire-Short Form (IPAQ-S) was used to measure PA. Respondents were classified as active or inactive for vigorous PA, moderate PA and walking. Multilevel logistic regression was performed to assess associations between macro-level environmental factors and the prevalence of PA, with control for individual-level socioeconomic factors.

RESULTS

The prevalence of PA varied widely between countries and types of PA (5.0%-93.8%). A negative association was found between gross domestic product and PA, odds ratios for men were 0.76 (95% CI: 0.65-0.89) for moderate PA and 0.79 (95% CI: 0.63-0.98) for walking. A higher temperature was associated with less PA (all types) and higher urbanization was associated with less vigorous and moderate PA. More gender equality was also associated with more walking for women. Governmental functioning and literacy rate were not found to be associated with any type of PA.

CONCLUSIONS

This exploratory study indicates that factors such as climate, economic development and cultural factors are determinants of the level of overall PA at national levels. This underlines the suggestion that the macro-environment should be regarded as an important influence on PA.