The gender gap in mortality: How much is explained by behavior?

In developed countries, women are expected to live about 4–5 years longer than men. In this paper, we develop a novel approach to gauge the extent to which gender differences in longevity can be attributed to gender-specific preferences and health behavior. We set up a physiologically founded model of health deficit accumulation and calibrate it using recent insights from gerontology. From fitting life cycle health expenditure and life expectancy, we obtain estimates of the gender-specific preference parameters. We then perform the counterfactual experiment of endowing women with the preferences of men. In our benchmark scenario, this reduces the gender gap in life expectancy from 4.6 to 1.4 years. When we add gender-specific preferences for unhealthy consumption, the model can motivate up to 89 percent of the gender gap. Our theory offers also an economic explanation for why the gender gap declines with rising income.     

What is the association between sickness absence, mortality and morbidity?

This paper examines the area-level relationships in England and Wales between sickness absence ('incapacity benefit'), mortality and morbidity. It uses a random sample of incapacity benefit claims, and population counts of mortality and Census morbidity for local government districts. Although there is little correspondence between sickness absence claims by specific cause and mortality, all cause sickness absence has a strong relationship with all cause mortality (male r 0.74, p=0.00; female r 0.64, p=0.00) and it also has a very strong relationship with the Census measures of morbidity: LLTI (male r 0.98, p=0.00; female r 0.97, p=0.00) and 'not good health' (male r 0.99, p=0.00; female r 0.96, p=0.00). Incapacity benefit claims by all causes has the potential to provide an ongoing measure of area-level health in England and Wales.     

Does the association between smoking and mortality differ by educational level?

Some researchers suggest that the effect of smoking on health depends on socioeconomic status; while others purport that the effect of smoking on health is similar across all social groups. This question of the interaction between smoking and socioeconomic status is important to an improved understanding of the role of smoking in the social gradient in mortality and morbidity. For this purpose, we examined whether educational level modifies the association between smoking and mortality. Information on smoking by age, gender and educational level was extracted from the Belgian Health Interview Surveys of 1997 and 2001. The mortality follow up of the survey respondents was reported until December 2010. A Poisson regression was used to estimate the hazard ratio of mortality for heavy smokers, light smokers, and former smokers compared with never smokers by educational level controlling for age and other confounders. Among men, we found lower hazard ratios in the lowest educational category compared with the intermediate and high-educated categories. For instance, for heavy smokers, the hazard ratios were 2.59 (1.18-5.70) for those with low levels of education, 4.03 (2.59-6.26) for those with intermediate levels of education and 3.78 (1.52-9.43) for the highly educated. However, the interaction between smoking and education was not statistically significant. For women, the hazard ratios were not significant for any educational category except for heavy smokers with intermediate levels of education. Also here the interaction was not statistically significant. Our results support the hypothesis that educational attainment does not substantially influence the association between smoking and mortality.     

Does the association between self-rated health and mortality vary by social class?

Self-rated health (SRH) predicts future mortality. Individuals in different social classes with similar physical health status may have different reference levels and criteria against which they judge their health, therefore the SRH–mortality relationship may vary according to social class. We examine the relationship between SRH and mortality by occupational social class in a prospective study of 22,457 men and women aged 39–79 years, without prevalent disease, living in the general community in Norfolk, United Kingdom, recruited using general practice age–sex registers in 1993–1997 and followed up for an average of 10 years. As expected, SRH was related to subsequent mortality. The age and sex adjusted hazard ratio for mortality for those with poor compared to those with excellent SRH was 4.35 (95% confidence interval 3.38–5.59, P < 0.001). The prevalence of poor or moderate SRH was higher in manual than in non-manual classes. However, SRH was similarly related to mortality in manual and non-manual classes: when non-manual classes are compared with manual classes for each category of SRH, the 95% confidence intervals for the mortality hazard ratios overlap. There was no evidence of an interaction between social class and SRH in either men or women. Thus in this population, SRH appears to predict mortality in a similar manner in non-manual and manual classes.     

Physical activity and self-reported, physician-diagnosed osteoarthritis: is physical activity a risk factor?

This prospective study evaluated regular physical activity and self-reported physician-diagnosed osteoarthritis of the knee and/or hip joints among 16,961 people, ages 20-87, examined at the Cooper Clinic between 1970 and 1995. Among those aged 50 years and older, osteoarthritis incidence was higher among women (7.0 per 1000 person-years) than among men (4.9 per 1000 person-years, P = 0.001), while among those under 50 years of age, osteoarthritis incidence was similar between men (2.6) and women (2.7). High levels of physical activity (running 20 or more miles per week) were associated with osteoarthritis among men under age 50 after controlling for body mass index, smoking, and use of alcohol or caffeine (hazard ratio = 2.4, 95% CI: 1.5, 3.9), while no relationship was suggested among women or older men. These findings support the conclusion that high levels of physical activity may be a risk factor for symptomatic osteoarthritis among men under age 50.     

Self-assessed health and mortality: could psychosocial factors explain the association?

BACKGROUND: The single-item question of self-assessed health has consistently been reported to be associated with mortality, even after controlling for a wide range of health measurements and known risk factors for mortality. It has been suggested that this association is due to psychosocial factors which are both related to self-assessed health and to mortality. We tested this hypothesis. METHODS: The study was carried out in a subsample (n = 5667) of the GLOBE-population, a prospective cohort study conducted in the southeastern part of the Netherlands. Data on self-assessed health, sociodemographic variables, various aspects of health status, behavioural risk factors, and a number of psychosocial factors (social support, psychosocial stressors, personality traits, and coping styles) were collected by postal survey and structured interview in 1991, and mortality data were collected between 1991 and 1998. Cox proportional hazards analyses were used to calculate the association between self-assessed health and mortality, before and after controlling for the psychosocial variables. RESULTS: After controlling for sociodemographic variables, various aspects of health status, and behavioural risk factors, self-assessed health is still strongly associated with mortality in our dataset (Relative Risk [RR] of dying for 'poor' versus 'very good' self-assessed health = 3.98; 95% CI: 1.65-9.61). After controlling for the same set of confounders, many of the psychosocial variables are statistically significantly associated with a 'less-than-good' self-assessed health, particularly instrumental social support, long-lasting difficulties, neuroticism, and locus of control. However, only 'disclosure of emotions'-coping style has a statistically significant relationship with mortality. Adding the psychosocial variables to a model already containing self-assessed health does not attenuate the association between self-assessed health and mortality. CONCLUSIONS: We did not find indications that the association between self-assessed health and mortality is due to the psychosocial factors included in this analysis. It seems likely that the unexplained mortality effects of self-assessed health are due to the fact that self-assessed health is a very inclusive measure of health reflecting health aspects relevant to survival which are not covered by other health indicators.     

How much of the variation in mortality across Norwegian municipalities is explained by the socio-demographic characteristics of the population?

The goal was to find out whether much of the variation in mortality between the 430 Norwegian municipalities could be attributed to socio-demographic characteristics of the population − operating through individual- or aggregate-level mechanisms. Two-level discrete-time hazard models were estimated for women and men at age 60−89 in 2000−2008, using registers covering the entire population. Year, age and a municipality-level random term were included in the first step. When socio-demographic characteristics of the individual and others in the municipality were added, the variance of the random term was reduced by 73−80% almost exclusively because of aggregate-level effects. Policy implications of these findings are discussed.     

Physical activity and appetite control: can we close the energy gap?

Appetite control can be effectively investigated within an energy balance framework. When people are sedentary, weight gain is favoured because appetite is poorly regulated, and energy expenditure is low. Consequently, people can exist in a chronic state of positive energy balance. This positive energy balance can be construed as an energy gap. This gap that leads to weight gain and maintains the weight different between overweight and lean people is larger than usually recognised. Physical activity can influence body weight by moving people from a sedentary ‘non‐regulated’ zone into a physiologically ‘regulated zone’, where energy expenditure and energy intake are more in equilibrium. In this regulated zone, physical activity improves the sensitivity of appetite control as well as increasing energy expenditure. The effect on body composition is much more important than an effect on bodyweight. Physical activity can reduce fat mass and waist circumference and increase lean (fat‐free) mass. Other health benefits include a decrease in resting heart rate and blood pressure (systolic and diastolic), an increase in cardiovascular fitness and in mood. Consequently, even though there may be some compensation for the energy expended, people have a better regulated appetite and are healthier.     

Who is hurt by procyclical mortality?

There is renewed interest in understanding how fluctuations in mortality and in health are related to fluctuations in economic conditions. The traditional perspective that economic recessions lower health and raise mortality has been challenged by recent findings that reveal mortality is actually procyclical. The epidemiology of the phenomenon - traffic accidents, cardiovascular disease, and smoking and drinking - suggests that socioeconomically vulnerable populations might be disproportionately at risk of "working themselves to death" during periods of heightened economic activity. In this paper, I examine mortality by individual characteristic during the 1980s and 1990s using the U.S. National Longitudinal Mortality Study. I find scant evidence that disadvantaged groups are significantly more exposed to procyclical mortality. Rather, working-age men with more education appear to bear a heavier burden, while those with little education experience countercyclical mortality.     

Is weak association between cigarette smoking and cardiovascular disease mortality observed in Japan explained by low total cholesterol? NIPPON DATA80

BACKGROUND: An international comparison has indicated that the association between smoking and cardiovascular disease (CVD) differs according to total cholesterol (TC) levels. However, little has been published about the relationship between smoking and CVD mortality among populations with various cholesterol levels. METHODS: We calculated the adjusted relative hazard (RH) of smoking for CVD mortality among 8912 Japanese individuals without a history of stroke or heart disease, who were separated according to TC levels of >or=5.40, 4.81-5.39, 4.26-4.80 and <4.25 mmol/l into groups Q4, Q3, Q2 and Q1, respectively. The P-values for multiple interactions between TC and smoking status for CVD mortality were calculated using TC as a continuous variable, dichotomized smoking status (never vs current), and by including cross-product terms in the regression models. RESULTS: After 19 years of follow-up, 313 men and 291 women died of CVD. The RH of CVD mortality among men who currently smoked compared with those who never smoked was increased with higher TC (RH = 2.36 in Q4) and decreased in those with lower TC (RH = 0.85 in Q1) (interaction, P < 0.01). The profiles for coronary heart disease (CHD) mortality and ischaemic CVD (composite endpoint of CHD and ischaemic stroke) in men and for ischaemic CVD mortality in women were identical. The interaction might be explained by a biological mechanism and by frailty of those who have never smoked with lower TC. CONCLUSIONS: Counteractive measures should be implemented against smoking targeted towards Japanese with elevated TC levels.     

Physical activity and low-fat diet: is it enough to maintain weight stability in the reduced-obese individual following weight loss by drug therapy and energy restriction?

OBJECTIVE: The anthropometric and physiological effects of a physical activity (PA) and a mildly energy-restricted low-fat diet (LFD) follow-up program after a long-term dietary restriction were studied in 12 men and 8 women. RESEARCH METHODS AND PROCEDURES: The dietary restriction (approximately 700 kcal/day) was accompanied by a fenfluramine (60 mg/day) or placebo treatment for 15 weeks, whereas the mean duration of the PA-LFD follow-up was 18 weeks. Results: The long-term dietary restriction reduced body weight (-11.9 and -7.6 kg, p<.001), fat mass (FM) (-10.6 and -5.8 kg, p<0.01), resting metabolic rate (RMR) (-304 kcal/day, p<0.01 and -148 kcal/day, NS) in men and women, respectively. A decrease in fat-free mass (FFM) was also observed in women (-1.8 kg, p<0.05). The PA-LFD follow-up preserved weight stability at a reduced body weight and caused an additional significant decrease in FM for men (-3.4 kg, p<0.05). This part of the intervention also caused an increase in daily RMR for men (134 kcal/day, NS) to the point where this value no longer differed from the pre-energy restriction value. In contrast, RMR was further reduced in women (-200 kcal/day) to the point where it significantly differed from initial values (p<0.01). Resting seated heart rate was reduced by the PA-LFD follow-up in men leading it to differ significantly from both pre- and post-energy restriction values (-8.5 and -5.5 bpm, p<0.01). DISCUSSION: In conclusion, these results suggest that a PA-LFD follow-up has the potential to permit body weight stability and may even accentuate fat loss in the reduced-obese state. Moreover, resting energy expenditure is increased under such conditions in men. These stimulating effects seem to be specific to energy metabolism since seated heart rate was either further reduced or remained stable in response to the PA-LFD follow-up.