Gender and age differences among current smokers in a general population survey

BACKGROUND: Evidence suggests a higher proportion of current smokers among female than among male ever smokers at the age above 50. However, little is known about the proportion of current smokers among ever smokers in old age groups with consideration of women in comparison to men from general population samples. The goal was to analyze the proportions of current smokers among female and among male ever smokers including those older than 80. METHODS: Cross-sectional survey study with a national probability household sample in Germany. Data of 179,472 participants aged 10 or older were used based on face-to-face in-home interviews or questionnaires. The proportions of current smokers among ever smokers were analyzed dependent on age, age of onset of smoking and cigarettes per day including effect modification by gender. RESULTS: Proportions of current smokers tended to be larger among female than among male ever smokers aged 40 or above. Women compared to men showed adjusted odds ratios of 1.7 to 6.9 at ages 40 to 90 or older in contrast to men. No such interaction existed for age of onset of smoking or cigarettes per day. CONCLUSION: Special emphasis should be given to current smokers among the female general population at the age of 40 or above in public health intervention

Smoking, alcohol consumption, physical activity, and family history and the risks of acute myocardial infarction and unstable angina pectoris: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Few studies investigated the association between smoking, alcohol consumption, or physical activity and the risk of unstable angina pectoris (UAP), while the strength of these associations may differ compared to other coronary diseases such as acute myocardial infarction (AMI). Therefore, we investigated whether the associations of these lifestyle factors with UAP differed from those with AMI. Additionally, we investigated whether these effects differed between subjects with and without a family history of myocardial infarction (MI).</p> <p>Methods</p> <p>The CAREMA study consists of 21,148 persons, aged 20-59 years at baseline and randomly sampled from the Maastricht region in 1987-1997. At baseline, all participants completed a self-administered questionnaire. After follow-up of maximally 16.9 years, 420 AMI and 274 UAP incident cases were registered. Incidence rate ratios (RRs) were estimated using Cox proportional hazards models.</p> <p>Results</p> <p>For both diseases, smoking increased the risk while alcohol consumption was associated with a protective effect. Associations with both risk factors were stronger for AMI than UAP, although this difference was only statistically significant for smoking. In men, an inverse association was found with physical activity during leisure time which seemed to be stronger for the risk of UAP than of AMI. On the contrary, physical activity during leisure time was associated with an increased risk of both AMI and UAP in women which seemed to be weaker for UAP than for AMI. Except for occupational physical activity in women, no significant interactions on a multiplicative scale were found between the lifestyle factors and family history of MI. Nevertheless, the highest risks were found in subjects with both a positive family history and the most unfavorable level of the lifestyle factors.</p> <p>Conclusions</p> <p>The strength of the associations with the lifestyle factors did not differ between AMI and UAP, except for smoking. Furthermore, the effects of the lifestyle factors on the risk of both coronary diseases were similar for subjects with and without a positive family history.</p

Methods for dealing with discrepant records in linked population health datasets: a cross-sectional study

BACKGROUND: Linked population health data are increasingly used in epidemiological studies. If data items are reported on more than one dataset, data linkage can reduce the under-ascertainment associated with many population health datasets. However, this raises the possibility of discrepant case reports from different datasets. METHODS: We examined the effect of four methods of classifying discrepant reports from different population health datasets on the estimated prevalence of hypertensive disorders of pregnancy and on the adjusted odds ratios (aOR) for known risk factors. Data were obtained from linked, validated, birth and hospital data for women who gave birth in a New South Wales hospital (Australia) 2000–2002. RESULTS: Among 250173 women with linked data, 238412 (95.3%) women had perfect agreement on the occurrence of hypertension, 1577 (0.6%) had imperfect agreement; 9369 (3.7%) had hypertension reported in only one dataset (under-reporting) and 815 (0.3%) had conflicting types of hypertension. Using only perfect agreement between birth and discharge data resulted in the lowest prevalence rates (0.3% chronic, 5.1% pregnancy hypertension), while including all reports resulted in the highest prevalence rates (1.1 % chronic, 8.7% pregnancy hypertension). The higher prevalence rates were generally consistent with international reports. In contrast, perfect agreement gave the highest aOR (95% confidence interval) for known risk factors: risk of chronic hypertension for maternal age ≥40 years was 4.0 (2.9, 5.3) and the risk of pregnancy hypertension for multiple birth was 2.8 (2.5, 3.2). CONCLUSION: The method chosen for classifying discrepant case reports should vary depending on the study question; all reports should be used as part of calculating the range of prevalence estimates, but perfect matches may be best suited to risk factor analyses. These findings are likely to be applicable to the linkage of any specialised health services datasets to population data that include information on diagnoses or procedures

How to screen for non-adherence to antihypertensive therapy

The quality of assessment of non-adherence to treatment in hypertensive is poor. Within this review, we discuss the different methods used to assess adherence to blood-pressure-lowering medications in hypertension patients. Subjective reports such as physicians’ perceptions are inaccurate, and questionnaires completed by patients tend to overreport adherence and show a low diagnostic specificity. Indirect objective methods such as pharmacy database records can be useful, but they are limited by the robustness of the recorded data. Electronic medication monitoring devices are accurate but usually track adherence to only a single medication and can be expensive. Overall, the fundamental issue with indirect objective measures is that they do not fully confirm ingestion of antihypertensive medications. Detection of antihypertensive medications in body fluids using liquid chromatography–tandem mass spectrometry is currently, in our view, the most robust and clinically useful method to assess non-adherence to blood-pressure-lowering treatment. It is particularly helpful in patients presenting with resistant, refractory or uncontrolled hypertension despite the optimal therapy. We recommend using this diagnostic strategy to detect non-adherence alongside a no-blame approach tailoring support to address the perceptions (e.g. beliefs about the illness and treatment) and practicalities (e.g. capability and resources) influencing motivation and ability to adhere

Comparative quantification of health risks: Conceptual framework and methodological issues

Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability. In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty

A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study.

BACKGROUND: Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated. METHODS AND FINDINGS: We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding. CONCLUSIONS: A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors