Do inhabitants profit from integrating a public health focus in urban renewal programmes? A Dutch case study.

BACKGROUND: Urban renewal traditionally involves policy sectors such as housing, transport, and employment, which potentially can enhance the health of residents living in deprived areas. Additional involvement of the public health sector might increase the health impact of these urban renewal activities. This study evaluates the health impact of an additional focus on health, under the heading of Healthy District Experiments (HDE), within districts where an urban renewal programme was carried out. METHODS: We evaluated changes in health outcomes before the start of the HDE and after implementation, and compared these changes with health changes in control areas, e.g. districts from the urban renewal programme where no additional HDE was implemented. Additionally, we gathered information on the content of the experiments to determine what types of activities have been implemented. RESULTS: The additional activities from the HDE were mostly aimed at strengthening the health care in the districts and at promoting physical activity. When we compared the prevalence in general health, mental health, overweight, obesity, smoking, and physical activity during the study period between the HDE districts and control districts, we found no significant differences in the rate of change. The study is limited by a small sample size and the cross-sectional nature of the data. These and other limitations are discussed. CONCLUSION: We found no evidence for a beneficial health impact of the activities that were initiated with a specific focus on health, within a Dutch urban renewal programme. Specific attention for network management and the integration of such activities in the wider programme, as well as an allocated budget might be needed in order to sort a health impact.

Surrounding green, air pollution, traffic noise exposure and non-accidental and cause-specific mortality.

BACKGROUND: Most previous studies that investigated associations of surrounding green, air pollution or traffic noise with mortality focused on single exposures. OBJECTIVES: The aim of this study was to evaluate combined associations of long-term residential exposure to surrounding green, air pollution and traffic noise with total non-accidental and cause-specific mortality. METHODS: We linked a national health survey (Public Health Monitor, PHM) conducted in 2012 to the Dutch longitudinal mortality database. Subjects of the survey who were 30 years or older on 1 January 2013 (n = 339,633) were followed from 1 January 2013 till 31 December 2017. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 m and 1000 m), annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), nitrogen dioxide (NO2)) and traffic noise with non-accidental, circulatory disease, respiratory disease, lung cancer and neurodegenerative disease mortality. RESULTS: We observed 26,886 non-accidental deaths over 1.627.365 person-years of follow-up. Surrounding green, air pollution and traffic noise exposure were not significantly associated with non-accidental or cause-specific mortality. For non-accidental mortality, we found a hazard ratio (HR) of 0.99 (0.98, 1.01) per IQR increase in NDVI 300 m, a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in NO2, a HR of 0.98 (0.97, 1.00) per IQR increase in PM2.5 and a HR of 0.99 (95% CI: 0.97, 1.01) per IQR increase in road-traffic noise. Analyses restricted to non-movers or excluding subjects aged 85+ years did not change the findings. CONCLUSION: We found no evidence for associations of long-term residential exposures to surrounding green, air pollution and traffic noise with non-accidental or cause-specific mortality in a large population based survey in the Netherlands, possibly related to the relatively short follow-up period.

Residential surrounding green, air pollution, traffic noise and self-perceived general health.

Self-perceived general health (SGH) is one of the most inclusive and widely used measures of health status and a powerful predictor of mortality. However, only a limited number of studies evaluated associations of combined environmental exposures on SGH. Our aim was to evaluate associations of combined residential exposure to surrounding green, air pollution and traffic noise with poor SGH in the Netherlands. We linked data on long-term residential exposure to surrounding green based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and road- and rail-traffic noise with a Dutch national health survey, resulting in a study population of 354,827 adults. We analyzed associations of single and combined exposures with poor SGH. In single-exposure models, NDVI within 300 m was inversely associated with poor SGH [odds ratio (OR) = 0.91, 95% CI: 0.89, 0.94 per IQR increase], while NO2 was positively associated with poor SGH (OR = 1.07, 95% CI: 1.04, 1.11 per IQR increase). In multi-exposure models, associations with surrounding green and air pollution generally remained, but attenuated. Joint odds ratios (JOR) of combined exposure to air pollution, rail-traffic noise and decreased surrounding green were higher than the odds ratios of single-exposure models. Studies including only one of these correlated exposures may overestimate the risk of poor SGH attributed to the studied exposure, while underestimating the risk of combined exposures.

Associations of Combined Exposures to Surrounding Green, Air Pollution, and Road Traffic Noise with Cardiometabolic Diseases.

BACKGROUND: Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures. OBJECTIVES: We aimed to evaluate associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases. METHODS: In this cross-sectional study, we studied associations between self-reported physician-diagnosed diabetes, hypertension, heart attack, and stroke from a Dutch national health survey of 387,195 adults and residential surrounding green, annual average air pollutant concentrations [including particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text]), PM with aerodynamic diameter [Formula: see text] ([Formula: see text]), nitrogen dioxide ([Formula: see text]), and oxidative potential (OP) with the dithiothreitol (DTT) assay ([Formula: see text])] and road traffic noise. Logistic regression models were used to analyze confounding and interaction of surrounding green, air pollution, and noise exposure. RESULTS: In single-exposure models, surrounding green was inversely associated with diabetes, while air pollutants ([Formula: see text], [Formula: see text]) and road traffic noise were positively associated with diabetes. In two-exposure analyses, associations with green and air pollution were attenuated but remained. The association between road traffic noise and diabetes was reduced to unity when adjusted for surrounding green or air pollution. Air pollution and surrounding green, but not road traffic noise, were associated with hypertension in single-exposure models. The weak inverse association of surrounding green with hypertension attenuated and lost significance when adjusted for air pollution. Only [Formula: see text] was associated with stroke and heart attack. CONCLUSIONS: Studies including only one of the correlated exposures surrounding green, air pollution, and road traffic noise may overestimate the association of diabetes and hypertension attributed to the studied exposure. https://doi.org/10.1289/EHP3857.

Associations of combined exposures to surrounding green, air pollution and traffic noise on mental health.

BACKGROUND: Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of single exposures with poor mental health. OBJECTIVES: To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health. METHODS: In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health. RESULTS: In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio [OR] of 0.88 (95% CI: 0.85, 0.92) per interquartile range [IQR] increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios [JOR], based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age. CONCLUSIONS: Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures.

Does selective migration bias the health impact assessment of urban regeneration programmes in cross-sectional studies? Findings from a Dutch case study.

We examined if the assessment of the health impact of a national Dutch regeneration programme depends on using either a repeated cross-sectional or longitudinal study design. This is important as only the latter design can incorporate migration patterns. For both designs, we compared trends in medication use between target and control districts. We found differences in medication use trends to be modest under the longitudinal design, and not demonstrable under the repeated cross-sectional design. The observed differences were hardly influenced by migration patterns. We conclude that in the Netherlands migration patterns had little effect on the health impact assessment of this national urban regeneration programme, so either the cross-sectional or longitudinal evaluation study design will do.

The health of Antillean migrants in the Netherlands: a comparison with the health of non-migrants in both the countries of origin and destination.

Background: This article examines risk factor and health differences between Antillean migrants in the Netherlands and Antillean and Dutch non-migrants, and relates these findings to four commonly used explanations for migrant health disparities. Methods: Nationally representative data from the 2012 Dutch Public Health Monitor and the 2013 National Health Survey Curaçao was used. The weighted rates were calculated and significance assessed using the χ2 test. Logistic regression analyses were used to compare health behaviours and outcomes between Antillean migrants and the non-migrant populations. Results: Overall, Antillean migrants had poorer physical and mental health than Antillean and Dutch non-migrants. For overweight/obesity and tobacco and alcohol use, Antillean migrants had rates in-between those of the Antillean and Dutch non-migrants. The poor health of Antillean migrants persisted in the second generation, who were born in the Netherlands. Conclusions: Patterns of differences in physical and mental health among the study populations were suggestive of a 'stressful environment' effect. The poorer health of Antillean migrants may be partly determined by host-country-specific stressors, such as perceived discrimination, spatial concentration in multi-ethnic neighbourhoods and reduced social mobility.

Green space definition affects associations of green space with overweight and physical activity.

INTRODUCTION: In epidemiological studies, exposure to green space is inconsistently associated with being overweight and physical activity, possibly because studies differ widely in their definition of green space exposure, inclusion of important confounders, study population and data analysis. OBJECTIVES: We evaluated whether the association of green space with being overweight and physical activity depended upon definition of greenspace. METHODS: We conducted a cross-sectional study using data from a Dutch national health survey of 387,195 adults. Distance to the nearest park entrance and surrounding green space, based on the Normalized Difference Vegetation Index (NDVI) or a detailed Dutch land-use database (TOP10NL), was calculated for each residential address. We used logistic regression analyses to study the association of green space exposure with being overweight and being moderately or vigorously physically active outdoors at least 150min/week (self-reported). To study the shape of the association, we specified natural splines and quintiles. RESULTS: The distance to the nearest park entrance was not associated with being overweight or outdoor physical activity. Associations of surrounding green space with being overweight or outdoor physical activity were highly non-linear. For NDVI surrounding greenness, we observed significantly decreased odds of being overweight [300m buffer, odds ratio (OR) = 0.88; 95% CI: 0.86, 0.91] and increased odds for outdoor physical activity [300m buffer, OR = 1.14; 95% CI: 1.10, 1.17] in the highest quintile compared to the lowest quintile. For TOP10NL surrounding green space, associations were mostly non-significant. Associations were generally stronger for subjects living in less urban areas and for the smaller buffers. CONCLUSION: Associations of green space with being overweight and outdoor physical activity differed considerably between different green space definitions. Associations were strongest for NDVI surrounding greenness.

Long-term exposure to particulate matter, NO2 and the oxidative potential of particulates and diabetes prevalence in a large national health survey.

BACKGROUND: The evidence from observational epidemiological studies of a link between long-term air pollution exposure and diabetes prevalence and incidence is currently mixed. Some studies found the strongest associations of diabetes with fine particles, other studies with nitrogen dioxide and some studies found no associations. OBJECTIVES: Our aim was to investigate associations between long-term exposure to multiple air pollutants and diabetes prevalence in a large national survey in the Netherlands. METHODS: We performed a cross-sectional analysis using the 2012 Dutch national health survey to investigate the associations between the 2009 annual average concentrations of multiple air pollutants (PM10, PM2.5, PM10-2.5, PM2.5 absorbance, OPDTT, OPESR and NO2) and diabetes prevalence, among 289,703 adults. Air pollution exposure was assessed by land use regression models. Diabetes was defined based on a combined measure of self-reported physician diagnosis and medication prescription from an external database. Using logistic regression, we adjusted for potential confounders, including neighborhood- and individual socio-economic status and lifestyle-related risk factors such as smoking habits, alcohol consumption, physical activity and BMI. RESULTS: After adjustment for potential confounders, all pollutants (except PM2.5) were associated with diabetes prevalence. In two-pollutant models, NO2 and OPDTT remained associated with increased diabetes prevalence. For NO2 and OPDTT, single-pollutant ORs per interquartile range were 1.07 (95% CI: 1.05, 1.09) and 1.08 (95% CI: 1.05, 1.10), respectively. Stratified analysis showed no consistent effect modification by any of the included known diabetes risk factors. CONCLUSIONS: Long-term residential air pollution exposure was associated with diabetes prevalence in a large health survey in the Netherlands, strengthening the evidence of air pollution being an important diabetes risk factor. Most consistent associations were observed for NO2 and oxidative potential of PM2.5 measured by the DTT assay. The finding of an association with the oxidative potential of fine particles but not with PM2.5, suggests that particle composition may be important for a potential effect on diabetes.

Estimating the prevalence of 26 health-related indicators at neighbourhood level in the Netherlands using structured additive regression.

BACKGROUND: Local policy makers increasingly need information on health-related indicators at smaller geographic levels like districts or neighbourhoods. Although more large data sources have become available, direct estimates of the prevalence of a health-related indicator cannot be produced for neighbourhoods for which only small samples or no samples are available. Small area estimation provides a solution, but unit-level models for binary-valued outcomes that can handle both non-linear effects of the predictors and spatially correlated random effects in a unified framework are rarely encountered. METHODS: We used data on 26 binary-valued health-related indicators collected on 387,195 persons in the Netherlands. We associated the health-related indicators at the individual level with a set of 12 predictors obtained from national registry data. We formulated a structured additive regression model for small area estimation. The model captured potential non-linear relations between the predictors and the outcome through additive terms in a functional form using penalized splines and included a term that accounted for spatially correlated heterogeneity between neighbourhoods. The registry data were used to predict individual outcomes which in turn are aggregated into higher geographical levels, i.e. neighbourhoods. We validated our method by comparing the estimated prevalences with observed prevalences at the individual level and by comparing the estimated prevalences with direct estimates obtained by weighting methods at municipality level. RESULTS: We estimated the prevalence of the 26 health-related indicators for 415 municipalities, 2599 districts and 11,432 neighbourhoods in the Netherlands. We illustrate our method on overweight data and show that there are distinct geographic patterns in the overweight prevalence. Calibration plots show that the estimated prevalences agree very well with observed prevalences at the individual level. The estimated prevalences agree reasonably well with the direct estimates at the municipal level. CONCLUSIONS: Structured additive regression is a useful tool to provide small area estimates in a unified framework. We are able to produce valid nationwide small area estimates of 26 health-related indicators at neighbourhood level in the Netherlands. The results can be used for local policy makers to make appropriate health policy decisions.

The impact of urban regeneration programmes on health and health-related behaviour: Evaluation of the Dutch District Approach 6.5 years from the start.

BACKGROUND: Large-scale regeneration programmes to improve the personal conditions and living circumstances in deprived areas may affect health and the lifestyle of the residents. Previous evaluations concluded that a large-scale urban regeneration programme in the Netherlands had some positive effects within 3.5 years. The aim of the current study was to evaluate the effects at the longer run. METHODS: With a quasi-experimental research design we assessed changes in the prevalence of general health, mental health, physical activity, overweight, obesity, and smoking between the pre-intervention (2003-04 -mid 2008) and intervention period (mid 2008-2013-14) in 40 deprived target districts and comparably deprived control districts. We used the Difference-in-Difference (DiD) to assess programme impact. Additionally, we stratified analyses by sex and by the intensity of the regeneration programme. RESULTS: Changes in health and health related behaviours from pre-intervention to the intervention period were about equally large in the target districts as in control districts. DiD impact estimates were inconsistent and not statistically significant. Sex differences in DiD estimates were not consistent or significant. Furthermore, DiD impact estimates were not consistently larger in target districts with more intensive intervention programmes. CONCLUSION: We found no evidence that this Dutch urban regeneration programme had an impact in the longer run on self-reported health and related behaviour at the area level.

Associations between lifestyle and air pollution exposure: Potential for confounding in large administrative data cohorts.

BACKGROUND: Cohorts based on administrative data have size advantages over individual cohorts in investigating air pollution risks, but often lack in-depth information on individual risk factors related to lifestyle. If there is a correlation between lifestyle and air pollution, omitted lifestyle variables may result in biased air pollution risk estimates. Correlations between lifestyle and air pollution can be induced by socio-economic status affecting both lifestyle and air pollution exposure. OBJECTIVES: Our overall aim was to assess potential confounding by missing lifestyle factors on air pollution mortality risk estimates. The first aim was to assess associations between long-term exposure to several air pollutants and lifestyle factors. The second aim was to assess whether these associations were sensitive to adjustment for individual and area-level socioeconomic status (SES), and whether they differed between subgroups of the population. Using the obtained air pollution-lifestyle associations and indirect adjustment methods, our third aim was to investigate the potential bias due to missing lifestyle information on air pollution mortality risk estimates in administrative cohorts. METHODS: We used a recent Dutch national health survey of 387,195 adults to investigate the associations of PM10, PM2.5, PM2.5-10, PM2.5 absorbance, OPDTT, OPESR and NO2 annual average concentrations at the residential address from land use regression models with individual smoking habits, alcohol consumption, physical activity and body mass index. We assessed the associations with and without adjustment for neighborhood and individual SES characteristics typically available in administrative data cohorts. We illustrated the effect of including lifestyle information on the air pollution mortality risk estimates in administrative cohort studies using a published indirect adjustment method. RESULTS: Current smoking and alcohol consumption were generally positively associated with air pollution. Physical activity and overweight were negatively associated with air pollution. The effect estimates were small (mostly <5% of the air pollutant standard deviations). Direction and magnitude of the associations depended on the pollutant, use of continuous vs. categorical scale of the lifestyle variable, and level of adjustment for individual and area-level SES. Associations further differed between subgroups (age, sex) in the population. Despite the small associations between air pollution and smoking intensity, indirect adjustment resulted in considerable changes of air pollution risk estimates for cardiovascular and especially lung cancer mortality. CONCLUSIONS: Individual lifestyle-related risk factors were weakly associated with long-term exposure to air pollution in the Netherlands. Indirect adjustment for missing lifestyle factors in administrative data cohort studies may substantially affect air pollution mortality risk estimates.

Hierarchy levels, sum score, and worsening of disability are related to depressive symptoms in elderly men from three European countries.

OBJECTIVES: The objectives were to investigate the predictive value of hierarchy levels and sum score of disability and change in disability on depressive symptoms. METHOD: Longitudinal data of 723 men age 70 and older from the Finland, Italy, and the Netherlands Elderly Study were collected in 1990 and 1995. Self-reported disability was based on three disability domains (instrumental activities, mobility, and basic activities) and depressive symptoms on the Zung questionnaire. RESULTS: Severity levels of disability were positively associated with depressive symptoms. Men with no disability scored 5 to 17 points lower (p < .01) on depressive symptoms than did those with disability in all domains. Among men with mild disability, those who had worsening of disability status in the preceding 5 years scored 5 points higher (p = .004) on depressive symptoms than did men who improved. DISCUSSION: Hierarchic severity levels, sum score of disability, and preceding changes in disability status are risk factors for depressive symptoms.

The contribution of self-rated health and depressive symptoms to disability severity as a predictor of 10-year mortality in European elderly men.

OBJECTIVES: To investigate the effect of disability severity and the contribution of self-rated health and depressive symptoms to 10-year mortality. METHODS: Longitudinal data were collected from 1141 men aged 70 to 89 years from the Finland, Italy, and the Netherlands Elderly Study from 1990 to 2000. Disability severity was classified into 4 categories: no disability, instrumental activities, mobility, and basic activities of daily living. Self-rated health and depressive symptoms were classified into 2 and 3 categories, respectively. Multivariate Cox proportional hazard models were used to calculate mortality risks. RESULTS: Men with severe disability had a risk of mortality that was more than 2-fold higher (hazard ratio [HR]=2.41; 95% confidence interval [CI]=1.84, 3.16) than that of men without disability. Men who had severe disability and did not feel healthy had the highest mortality risk (HR = 3.30; 95% CI = 2.52, 4.33). This risk was lower at lower levels of disability and higher levels of self-rated health. The same trend was observed for depressive symptoms. CONCLUSIONS: For adequate prognoses on mortality or for developing intervention strategies, not only physical aspects of health but also other health outcomes should be taken into account.

Duration and intensity of physical activity and disability among European elderly men.

PURPOSE: To investigate the relationship between duration and intensity of physical activity and disability 10 years later, and to investigate the possible effect of selective mortality. METHOD: Longitudinal data of 560 men aged 70?-?89 years, without disability at baseline from the Finland, Italy and The Netherlands Elderly (FINE) Study was used. Physical activity in 1990 was based on activities like walking, bicycling and gardening. Disability severity (three categories) in 1990 and 2000 was based on instrumental activities, mobility and basic activities of daily living. RESULTS: Men in the highest tertile of total physical activity had a lower risk of disability than men in the lowest tertile (odds ratio (OR) 0.46; 95% confidence interval (CI): 0.26-0.84). This was due to duration of physical activity (OR highest tertile 0.42; 95% CI: 0.23-0.78 compared to the lowest tertile). Intensity of physical activity was not associated with disability. Addition of deceased men as fourth category leaded to weaker associations between physical activity and disability (OR highest tertile 0.67; 95% CI: 0.44-1.02). CONCLUSIONS: Even in old age among relatively healthy men, a physically active lifestyle was inversely related to disability. To prevent disability duration of physical activity seems to be more important than intensity.

Effect of widowhood on disability onset in elderly men from three European countries.

OBJECTIVES: To investigate in different countries the effects of becoming widowed, duration of widowhood, and household composition of widowed men on disability onset in different disability domains. DESIGN: Longitudinal data from a cohort study collected around 1990, 1995, and 2000. SETTING: Three cohorts from Finland, The Netherlands, and Italy. PARTICIPANTS: Seven hundred thirty-six men, aged 70 and older at baseline. MEASUREMENTS: Disability was measured using standardized questionnaire on activities of daily living (ADLs). Three domains were assessed: instrumental ADLs (IADLs), mobility, and basic ADLs (BADLs). Duration of widowhood was divided into less than 5 years and 5 or more years and household composition into living alone and living with family or in an institution. RESULTS: Men who became widowed developed more IADL disabilities (odds ratio (OR)=2.15; 95% confidence interval (CI)=1.22-3.81) and mobility (OR=1.84; 95% CI=1.15-2.96) than men who were still married. Men who had been widowed for less than 5 years developed more IADL disabilities than those who had been widowed for 5 years or more (OR=2.27; 95% CI=1.14-4.54). Widowed men living alone showed fewer disabilities in mobility (OR=0.25; 95% CI=0.09-0.73) and BADLs (OR=0.02; 95% CI=0.001-0.33) than those living with others. The effects on disability onset did not differ between countries. CONCLUSION: Widowhood in elderly men is a risk factor for dependency in IADLs and mobility. The growth in the number of widowers may lead to higher demands on family care and professional care.

Self-reported disability and its association with performance-based limitation in elderly men: a comparison of three European countries.

OBJECTIVES: To compare self-reported disability and performance-based limitation and their association in elderly men from three European countries. DESIGN: Cross-sectional data from a cohort study collected around 1990. SETTING: Three cohorts from Finland, the Netherlands, and Italy. PARTICIPANTS: One thousand one hundred sixty-one men aged 70 and older. MEASUREMENTS: Disability and functional limitation were measured in a standardized way in three countries. Self-reported disability was estimated by questionnaire, assessing three domains of activities of daily living: instrumental activities of daily living, mobility, and activities of daily living (score 0-3). Functional limitation was measured by performance tests (score 0-16), with 0 indicated the healthiest score. RESULTS: Self-reported disability and performance-based limitation scores differed between countries. Mean self-reported disability score was worse in Italy (0.72) and the Netherlands (0.70) than in Finland (0.54). Italian men scored worst on the performance-based tests (mean 4.80 vs 4.04 for Finland and 3.74 for the Netherlands). Differences in self-reported disability remained after adjusting for performance scores: Dutch men reported more disabilities (odds ratio (OR) = 1.66, 95% confidence interval (CI) = 1.23-2.25) than men in Finland (reference group) and Italy (OR = 1.08, 95% CI = 0.77-1.53). Self-reported disability was positively associated with performance-based score (OR = 1.28, 95% CI = 1.21-1.35) and did not differ between countries. CONCLUSION: Cross-cultural variation was noted in self-reported disability adjusted for performance score. These differences may be due to sociocultural and physical environmental factors. Self-reported disability was consistently associated with performance-based limitation in Finland, the Netherlands, and Italy.