Area deprivation and mortality in the provincial capital cities of Andalusia and Catalonia (Spain)

Objective: To study the linkage between material deprivation and mortality from all causes, for men and women separately, in the capital cities of the provinces in Andalusia and Catalonia (Spain). Methods: A small-area ecological study was devised using the census section as the unit for analysis. 188 983 Deaths occurring in the capital cities of the Andalusian provinces and 109 478 deaths recorded in the Catalan capital cities were examined. Principal components factorial analysis was used to devise a material deprivation index comprising the percentage of manual labourers, unemployment and illiteracy. A hierarchical Bayesian model was used to study the relationship between mortality and area deprivation. Main results: In most cities, results show an increased male mortality risk in the most deprived areas in relation to the least depressed. In Andalusia, the relative risks between the highest and lowest deprivation decile ranged from 1.24 (Malaga) to 1.40 (Granada), with 95% credibility intervals showing a significant excess risk. In Catalonia, relative risks ranged between 1.08 (Girona) and 1.50 (Tarragona). No evidence was found for an excess of female mortality in most deprived areas in either of the autonomous communities. Conclusions: Within cities, gender-related differences were revealed when deprivation was correlated geographically with mortality rates. These differences were found from an ecological perspective. Further research is needed in order to validate these results from an individual approach. The idea to be analysed is to identify those factors that explain these differences at an individual level.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.