Occupational physical activity and all-cause and cardiovascular disease mortality: Results from two longitudinal studies in Switzerland.

BACKGROUND: Research regarding the effects of occupational physical activity on health remains inconsistent. We analyzed the association of occupational physical activity with all-cause and cardiovascular disease (CVD) mortality. METHODS: We analyzed two cohorts with baseline assessments from 1977 to 1993 ("National Research Program 1A" (NRP1A) and "MONItoring of trends and determinants in CArdiovascular disease" [MONICA]) and mortality follow-up until 2015 using adjusted Cox regression models. RESULTS: We included 4396 NRP1A participants (137 793 person-years of follow-up, 1541 deaths) and 5780 MONICA participants (135 410 person-years, 1158 deaths). All-cause mortality was higher for men in the high compared with the low occupational physical activity category according to NRP1A (hazard ratio [HR] 1.25, 95% confidence intervals [CI] 1.05-1.50). CVD mortality was higher for men in the moderate compared with the low occupational physical activity category according to MONICA (HR, 1.41; 95% CI, 1.03-1.91). Results for women were not statistically significant. CONCLUSIONS: We observed higher total and CVD mortality risks in men with higher occupational physical activity but inconsistent results for women and across cohorts.

Joints effects of BMI and smoking on mortality of all-causes, CVD, and cancer.

Obesity, underweight, and smoking are associated with an increased mortality. We investigated the joint effects of body mass index and smoking on all-cause and cause-specific mortality. Data of the Third National Health and Nutrition Examination Survey (1988-1994) including mortality follow-up until 2011 were used (n = 17,483). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause, cardiovascular disease (CVD), and cancer mortality with BMI, smoking, and their combinations as exposure, stratified by sex. Normal weight never smokers were considered as reference group. Compared to normal weight never smokers, obese and underweight current smokers were the two combinations with the highest mortality from all-causes, CVD, and cancer. Among underweight current smokers, the HR of death from all-causes was 3.49 (95% CI 2.42-5.02) and for obese current smokers 2.76 (2.12-3.58). All-cause mortality was particularly high in women who were underweight and current smoker (3.88 [2.47-6.09]). CVD mortality risk was the highest among obese current smokers (3.33 [2.98-5.33]). Cancer mortality risk was the highest among underweight current smokers (5.28 [2.68-10.38]). Obese current smokers in the middle age group (between 40 and 59 years old) had the highest risk of all-cause mortality (4.48 [2.94-7.97]). No statistically significant interaction between BMI and smoking on all-cause and cause-specific mortality was found. The current study indicates that obesity and underweight in combination with smoking may emerge as a serious public health problem. Hence, public health messages should stress the increased mortality risk for smokers who are underweight or obese. Also, health messages regarding healthy lifestyle are aimed at maintaining a healthy body weight rather than just "losing weight" and at not starting smoking at all.

Continuous outcome logistic regression for analyzing body mass index distributions.

Body mass indices (BMIs) are applied to monitor weight status and associated health risks in populations.  Binary or multinomial logistic regression models are commonly applied in this context, but are only applicable to BMI values categorized within a small set of defined ad hoc BMI categories.  This approach precludes comparisons with studies and models based on different categories.  In addition, ad hoc categorization of BMI values prevents the estimation and analysis of the underlying continuous BMI distribution and leads to information loss.  As an alternative to multinomial regression following ad hoc categorization, we propose a continuous outcome logistic regression model for the estimation of a continuous BMI distribution.  Parameters of interest, such as odds ratios for specific categories, can be extracted from this model post hoc in a general way.  A continuous BMI logistic regression that describes BMI distributions avoids the necessity of ad hoc and post hoc category choice and simplifies between-study comparisons and pooling of studies for joint analyses.  The method was evaluated empirically using data from the Swiss Health Survey.

Association of household cleaning agents and disinfectants with asthma in young German adults.

OBJECTIVES: We scrutinised the association of private use of household sprays and disinfectants with asthma incidence in young adults in the transition from school to working life. METHODS: Between 2007 and 2009,2051 young adults aged 19-24 years living in two major German cities took part in the Study on Occupational Allergy Risks II. Self-reported exposure to household sprays and disinfectants was characterised according to a composite score for frequency of use as no use (score=0), low use (score between 1 and the median), medium use (score between the median and the 90th percentile) and high use (score above the 90th percentile). Two outcome variables (current asthma and current wheezing) with four mutually exclusive categories (never, incident, persistent and remittent) were used for the risk analyses. Multinomial logistic regression models examined the association between the frequency of using household sprays and disinfectants with asthma and wheezing adjusting for potential confounders. RESULTS: Compared with no use, high use of disinfectants was associated with a more than twofold increased odds of incident asthma (OR 2.79, 95% CI 1.14 to 6.83). In addition, low/medium use of disinfectants was associated with remittent asthma (OR 2.39, 95% CI 1.29 to 4.47). The evidence for an association between high usage of household sprays and asthma incidence was weak (OR 2.79, 95% CI 0.84 to 9.20). CONCLUSION: Our results support the hypothesis of an association between the use of cleaning products and elevated risks for asthma and wheezing in young adults at the start of working life.

Type A personality and mortality: Competitiveness but not speed is associated with increased risk.

BACKGROUND AND AIMS: Type A behavior pattern (TABP) is a possible risk factor for cardiovascular disease (CVD). However, existing evidence is conflicting, also because studies did not examine underlying traits separately. In this study, we investigated whether all-cause and CVD mortality were associated with the Bortner Scale, a measure of TABP, in particular with its subscales competitiveness and speed. METHODS: Information on Bortner Scale and covariates of 9921 participants was collected at baseline in two cross-sectional studies that were linked with mortality information, yielding a follow-up of up to 37 years. We analyzed the Bortner Scale and its two subscales competitiveness and speed. Applying Cox regression models, we investigated the association with all-cause, CVD, and specific CVD type mortality. RESULTS: During follow-up, 3469 deaths were observed (1118 CVD deaths). The total Bortner Scale was not associated with mortality, only its subscales. In women, competitiveness was positively associated with all-cause mortality (highest category vs. the lowest, HR 1.25 [95% CI 1.08,1.44]), CVD mortality (1.39 [1.07,1.81]), and ischemic heart disease mortality (intermediate category vs. the lowest, 1.46 [1.02,2.10]). In men, CVD mortality was inversely associated with speed (highest category vs. the lowest, 0.74 [0.59,0.93]). CONCLUSIONS: The subscales of the Bortner Scale may be associated with CVD in an opposed manner and may therefore have to be analyzed separately. More studies are needed to further investigate this association, also considering differences by sex. Persons scoring high in the competitiveness subscale ought to be screened and counselled in order to reduce their CVD risk.

Is body weight dissatisfaction a predictor of depression independent of body mass index, sex and age? Results of a cross-sectional study.

BACKGROUND: Little is known about the association of dissatisfaction with body weight - a component of body image - with depression in individuals of different sex, age, and with different body mass index (BMI). Hence, the aim of our study was to evaluate the association of body weight dissatisfaction (BWD) with depression in different sub-groups. METHODS: We analyzed data of 15,975 individuals from the cross-sectional 2012 Swiss Health Survey. Participants were asked about their body weight satisfaction. The validated Patient Health Questionnaire (PHQ-9) was used to ascertain depression. Age was stratified into three groups (18-29, 30-59, and ≥60 years). The body mass index (BMI) was calculated from self-reported body height and weight and categorized into underweight (BMI <18.5 kg/m(2)), normal weight (BMI 18.5-24.9 kg/m(2)), overweight (BMI 25.0-29.9 kg/m(2)), and obesity (BMI ≥30 kg/m(2)). The association between body weight dissatisfaction (BWD) and depression was assessed with logistic regression analyses and odds ratios (OR) with 95 % confidence intervals (CI) were computed. RESULTS: BWD was associated with depression in the overall group (OR 2.04, 95 % CI 1.66-2.50) as well as in men (OR 1.85, 95 % CI 1.34-2.56) and women (OR 2.25, 95 % CI 1.71-2.96) independent of BMI. The stratification by age groups showed significant associations of BWD with depression in young (OR 1.78, 95 % CI 1.16-2.74), middle-aged (OR 2.10, 95 % CI 1.61-2.74) and old individuals (OR 2.34, 95 % CI 1.30-4.23) independent of BMI. Stratification by BMI categories resulted in statistically significant positive associations of BWD and depression in underweight, normal weight, overweight and obese individuals. CONCLUSION: BWD was associated with depression independent of BMI, sex and age.

Adherence to the cancer prevention recommendations of the World Cancer Research Fund/American Institute for Cancer Research and mortality: a census-linked cohort.

BACKGROUND: Modifiable lifestyle factors linked to cancer offer great potential for prevention. Previous studies suggest an association between adherence to recommendations on healthy lifestyle and cancer mortality. OBJECTIVES: The aim of this study was to examine whether adherence to the cancer prevention recommendations of the World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) is associated with reduced all-cause, total cancer, and specific cancer type mortality. DESIGN: We built a lifestyle score that included 3 categories, based on the recommendations of the WCRF/AICR. Applying Cox regression models, we investigated the association with all-cause, total cancer, and specific cancer type mortality; in addition, we included cardiovascular disease (CVD) mortality. We used census- and death registry-linked survey data allowing a mortality follow-up for ≤32 y. Our analysis included 16,722 participants. Information on lifestyle score components and confounders was collected at baseline. RESULTS: Over a mean follow-up of 21.7 y, 3730 deaths were observed (1332 cancer deaths). Comparing best with poorest category of the lifestyle score showed an inverse association with all-cause (HR: 0.82; 95% CI: 0.75, 0.89) and total cancer (men only, HR: 0.69; 95% CI: 0.57, 0.84) mortality. We estimated that ∼13% of premature cancer deaths in men would have been preventable if lifestyle score levels had been high. Inverse associations were observed for lung, upper aerodigestive tract, stomach, and prostate cancer mortality [men and women combined, HR: 0.72; 95% CI: 0.51, 0.99; HR: 0.49; 95% CI: 0.26, 0.92; HR: 0.34; 95% CI: 0.14, 0.83; HR: 0.48; 95% CI: 0.28, 0.82 (men only), respectively]. CVD mortality was not associated with the lifestyle score (men and women combined, HR: 0.96; 95% CI: 0.82, 1.13). CONCLUSIONS: Our results support the importance of adhering to recommendations for a healthy lifestyle with regard to all-cause and cancer mortality. To reduce the burden of cancer in the population, preventive measures should stress the potential of low-risk health behavior patterns rather than of specific risk factors only.

Heavy Smoking Is More Strongly Associated with General Unhealthy Lifestyle than Obesity and Underweight.

BACKGROUND: Smoking and obesity are major causes of non-communicable diseases. We investigated the associations of heavy smoking, obesity, and underweight with general lifestyle to infer which of these risk groups has the most unfavourable lifestyle. METHODS: We used data from the population-based cross-sectional Swiss Health Survey (5 rounds 1992-2012), comprising 85,575 individuals aged≥18 years. Height, weight, smoking, diet, alcohol intake and physical activity were self-reported. Multinomial logistic regression was performed to analyse differences in lifestyle between the combinations of body mass index (BMI) category and smoking status. RESULTS: Compared to normal-weight never smokers (reference), individuals who were normal-weight, obese, or underweight and smoked heavily at the same time had a poorer general lifestyle. The lifestyle of obese and underweight never smokers differed less from reference. Regardless of BMI category, in heavy smoking men and women the fruit and vegetable consumption was lower (e.g. obese heavy smoking men: relative risk ratio (RRR) 1.69 [95% confidence interval 1.30;2.21]) and high alcohol intake was more common (e.g. normal-weight heavy smoking women 5.51 [3.71;8.20]). In both sexes, physical inactivity was observed more often in heavy smokers and obese or underweight (e.g. underweight never smoking 1.29 [1.08;1.54] and heavy smoking women 2.02 [1.33;3.08]). A decrease of smoking prevalence was observed over time in normal-weight, but not in obese individuals. CONCLUSIONS: Unhealthy general lifestyle was associated with both heavy smoking and BMI extremes, but we observed a stronger association for heavy smoking. Future smoking prevention measures should pay attention to improvement of general lifestyle and co-occurrence with obesity and underweight.