Life-course socioeconomic environment and health risk behaviours. A multilevel small-area analysis of young-old persons in an urban neighbourhood in Lausanne, Switzerland

Prediction of cardiovascular disease risk among low-income urban dwellers in metropolitan Kuala Lumpur, Malaysia

We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers.

Lifestyle Health Behaviors of Hong Kong Chinese

Sociodemographics affect health through pathways of lifestyle choices. Using data from a survey of 467 Hong Kong Chinese, this study aims to examine the prevalence of their lifestyle behaviors, identify profiles based on their sociodemographic and lifestyle variables, and compare differences among the profile groups. Two-step cluster analysis was used to identify natural profile groups within the data set: only 37% of the participants engaged in regular physical exercises, and less than 50% monitored their dietary intake carefully. The analysis yields 2 clusters, representing a “healthy” and a “less-healthy” lifestyle group. The “less-healthy” group was predominantly male, younger, employed, and had high-to-middle levels of education. The findings reveal the lifestyle behavior patterns and sociodemographic characteristics of a high-risk group, which are essential to provide knowledge for the planning of health promotion activities.

The effect of neighbourhood unemployment on health-risk behaviours in elderly differs between Slovak and Dutch cities

BACKGROUND

Health-risk behaviours (HRB) increase the risk of disability and chronic diseases at an older age. This study aimed to compare Slovakia and the Netherlands regarding differences in the prevalence of HRB by neighbourhood and individual deprivation and to determine whether area differences could be explained by the socio-economic position (SEP) of the residents.

METHODS

We obtained data on non-institutionalized residents aged ≥ 65 years from the EU-FP7: EURO-URHIS 2 project from Slovak (N = 665, response rate 44.0%) and Dutch cities (N = 795, response rate 50.2%). HRB concerned daily smoking, binge drinking, physical activity, consumption of fruits and vegetables and body mass index. Area deprivation was measured by the neighbourhood unemployment rate. Individual SEP was measured by education and household income with financial strain. We used multilevel logistic regression.

RESULTS

In Slovakia, no HRB was associated with either neighbourhood unemployment or individual SEP. The elderly in the Netherlands from the least favourable neighbourhoods were more likely to be daily smokers [odds ratio (OR) 2.32; 95% confidence interval (CI) 1.25, 4.30] and overweight (OR 1.84; 95% CI 1.24, 2.75) than residents from the most favourable ones. For the Dutch elderly the gradients varied per HRB and per individual-level SEP indicator. Individual SEP explained country differences in the association of area unemployment with smoking and lack of physical activity but not that with overweight.

CONCLUSION

Countries differed in the associations with HRB of both neighbourhood unemployment and individual SEP among the elderly urban residents. The local importance of socio-economic factors on both levels should be considered when developing health-promotion activities for the elderly.

Socioeconomic patterning of excess alcohol consumption and binge drinking: a cross-sectional study of multilevel associations with neighbourhood deprivation

OBJECTIVES

The influence of neighbourhood deprivation on the risk of harmful alcohol consumption, measured by the separate categories of excess consumption and binge drinking, has not been studied. The study objective was to investigate the effect of neighbourhood deprivation with age, gender and socioeconomic status (SES) on (1) excess alcohol consumption and (2) binge drinking, in a representative population survey.

DESIGN

Cross-sectional study: multilevel analysis.

SETTING

Wales, UK, adult population ∼2.2 million.

PARTICIPANTS

58 282 respondents aged 18 years and over to four successive annual Welsh Health Surveys (2003/2004-2007), nested within 32 692 households, 1839 census lower super output areas and the 22 unitary authority areas in Wales.

PRIMARY OUTCOME MEASURE

Maximal daily alcohol consumption during the past week was categorised using the UK Department of Health definition of 'none/never drinks', 'within guidelines', 'excess consumption but less than binge' and 'binge'. The data were analysed using continuation ratio ordinal multilevel models with multiple imputation for missing covariates.

RESULTS

Respondents in the most deprived neighbourhoods were more likely to binge drink than in the least deprived (adjusted estimates: 17.5% vs 10.6%; difference=6.9%, 95% CI 6.0 to 7.8), but were less likely to report excess consumption (17.6% vs 21.3%; difference=3.7%, 95% CI 2.6 to 4.8). The effect of deprivation varied significantly with age and gender, but not with SES. Younger men in deprived neighbourhoods were most likely to binge drink. Men aged 35-64 showed the steepest increase in binge drinking in deprived neighbourhoods, but men aged 18-24 showed a smaller increase with deprivation.

CONCLUSIONS

This large-scale population study is the first to show that neighbourhood deprivation acts differentially on the risk of binge drinking between men and women at different age groups. Understanding the socioeconomic patterns of harmful alcohol consumption is important for public health policy development.