METHOD: Between 1995 and 2000, a standardized 24-h dietary recall was conducted among 36,018 men and women from 27 European Prospective Investigation into Cancer and Nutrition (EPIC) study centres. Adjusted arithmetic means of intakes were estimated in grams (=volume) per day by sex and centre. Means of intake across centres were compared by sociodemographic characteristics and lifestyle factors.
RESULTS: In women, the mean daily intake of coffee ranged from 94 g/day (~0.6 cups) in Greece to 781 g/day (~4.4 cups) in Aarhus (Denmark), and tea from 14 g/day (~0.1 cups) in Navarra (Spain) to 788 g/day (~4.3 cups) in the UK general population. Similar geographical patterns for mean daily intakes of both coffee and tea were observed in men. Current smokers as compared with those who reported never smoking tended to drink on average up to 500 g/day more coffee and tea combined, but with substantial variation across centres. Other individuals' characteristics such as educational attainment or age were less predictive. In all centres, coffee and tea contributed to less than 10% of the energy intake. The greatest contribution to total sugar intakes was observed in Southern European centres (up to ~20%).
CONCLUSION: Coffee and tea intake and their contribution to energy and sugar intake differed greatly among European adults. Variation in consumption was mostly driven by geographical region.
METHODS: Individual participant data from 14 cohorts, involving 59,025 individuals were used in this cross-sectional analysis. We made 15 clusters of four risk factors (current smoking, overweight, elevated blood pressure, elevated total cholesterol). Multilevel age and sex adjusted linear regression models were applied to estimate mean differences in common carotid intima-media thickness (CIMT) between clusters using those without any of the four risk factors as reference group.
RESULTS: Compared to the reference, those with 1, 2, 3 or 4 risk factors had a significantly higher common CIMT: mean difference of 0.026 mm, 0.052 mm, 0.074 mm and 0.114 mm, respectively. These findings were the same in men and in women, and across ethnic groups. Within each risk factor cluster (1, 2, 3 risk factors), groups with elevated blood pressure had the largest CIMT and those with elevated cholesterol the lowest CIMT, a pattern similar for men and women.
CONCLUSION: Clusters of risk factors relate to increased common CIMT in a graded manner, similar in men, women and across race-ethnic groups. Some clusters seemed more atherogenic than others. Our findings support the notion that cardiovascular prevention should focus on sets of risk factors rather than individual levels alone, but may prioritize within clusters.
METHODS: A multi-center retrospective study design was used to collect data from TB patients in four different states of Malaysia, namely Penang, Sabah, Sarawak, and Selangor. The study included medical records of TB patients admitted to the selected hospitals in the period from January 2006 to March 2009. Medical records with incomplete data were not included. Patient demographics and clinical data were collected using a validated data collection form.
RESULTS: Of all patients with TB (9337), the prevalence of smokers was 4313 (46.2%). Among smokers, 3584 (83.1%) were associated with pulmonary TB, while 729 (16.9%) were associated with extrapulmonary TB. Male gender (OR = 1.43, 95% CI 1.30-1.58), Chinese ethnicity (OR = 1.23, 95% CI 1.02-1.49), Sarawak indigenous ethnicity (OR = 0.74, 95% CI 0.58-0.95), urban residents (OR = 1.46, 95% CI 1.33-1.61), employed individuals (OR = 1.21, 95% CI 1.09-1.34), alcoholics (OR = 4.91, 95% CI 4.04-5.96), drug abusers (OR = 7.43, 95% CI 5.70-9.60) and presence of co-morbid condition (OR = 1.27, 95% CI 1.16-1.40) all showed significant association with smoking habits. This study found that 3236 (75.0%) patients were successfully treated in the smokers' group, while 4004 (79.7%) patients were non-smokers. The proportion of deaths (6.6%, n = 283), defaulters (6.6%, n = 284) and treatment interruptions (4.7%, n = 204) was higher in the smokers' group.
CONCLUSIONS: Smoking has a strong influence on TB and is a major barrier towards treatment success (OR = 0.76, 95% CI 0.69-0.84, p