Source: BMC Public Health
The energy requirement of species at each trophic level in an ecological pyramid is a function of the number of organisms and their average mass. Regarding human populations, although considerable attention is given to estimating the number of people, much less is given to estimating average mass, despite evidence that average body mass is increasing. We estimate global human biomass, its distribution by region and the proportion of biomass due to overweight and obesity.
For each country we used data on body mass index (BMI) and height distribution to estimate average adult body mass. We calculated total biomass as the product of population size and average body mass. We estimated the percentage of the population that is overweight (BMI > 25) and obese (BMI > 30) and the biomass due to overweight and obesity.
In 2005, global adult human biomass was approximately 287 million tonnes, of which 15 million tonnes were due to overweight (BMI > 25), a mass equivalent to that of 242 million people of average body mass (5% of global human biomass). Biomass due to obesity was 3.5 million tonnes, the mass equivalent of 56 million people of average body mass (1.2% of human biomass). North America has 6% of the world population but 34% of biomass due to obesity. Asia has 61% of the world population but 13% of biomass due to obesity. One tonne of human biomass corresponds to approximately 12 adults in North America and 17 adults in Asia. If all countries had the BMI distribution of the USA, the increase in human biomass of 58 million tonnes would be equivalent in mass to an extra 935 million people of average body mass, and have energy requirements equivalent to that of 473 million adults.
Increasing population fatness could have the same implications for world food energy demands as an extra half a billion people living on the earth.
Living alone and antidepressant medication use: a prospective study in a working-age population
Source: BMC Public Health
An increasing proportion of the population lives in one-person households. The authors examined whether living alone predicts the use of antidepressant medication and whether socioeconomic, psychosocial, or behavioral factors explain this association.
The participants were a nationally representative sample of working-age Finns from the Health 2000 Study, totaling 1695 men and 1776 women with a mean age of 44.6 years. In the baseline survey in 2000, living arrangements (living alone vs. not) and potential explanatory factors, including psychosocial factors (social support, work climate, hostility), sociodemographic factors (occupational grade, education, income, unemployment, urbanicity, rental living, housing conditions), and health behaviors (smoking, alcohol use, physical activity, obesity), were measured. Antidepressant medication use was followed up from 2000 to 2008 through linkage to national prescription registers.
Participants living alone had a 1.81-fold (CI = 1.46-2.23) higher purchase rate of antidepressants during the follow-up period than those who did not live alone. Adjustment for sociodemographic factors attenuated this association by 21% (adjusted OR = 1.64, CI = 1.32-2.05). The corresponding attenuation was 12% after adjustment for psychosocial factors (adjusted OR = 1.71, CI = 1.38-2.11) and 9% after adjustment for health behaviors (adjusted OR = 1.74, CI = 1.41-2.14). Gender-stratified analyses showed that in women the greatest attenuation was related to sociodemographic factors and in men to psychosocial factors.
These data suggest that people living alone may be at increased risk of developing mental health problems. The public health value is in recognizing that people who live alone are more likely to have material and psychosocial problems that may contribute to excess mental health problems in this population group.
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See: Home Alone: Depression Highest for Those Living Alone (Science Daily)
Effect of an electronic nicotine delivery device (e-Cigarette) on smoking reduction and cessation: a prospective 6-month pilot study
Cigarette smoking is a tough addiction to break. Therefore, improved approaches to smoking cessation are necessary. The electronic-cigarette (e-Cigarette), a battery-powered electronic nicotine delivery device (ENDD) resembling a cigarette, may help smokers to remain abstinent during their quit attempt or to reduce cigarette consumption. Efficacy and safety of these devices in long-term smoking cessation and/or smoking reduction studies have never been investigated.
In this prospective proof-of-concept study we monitored possible modifications in smoking habits of 40 regular smokers (unwilling to quit) experimenting the ‘Categoria’ e-Cigarette with a focus on smoking reduction and smoking abstinence. Study participants were invited to attend a total of five study visits: at baseline, week-4, week-8, week-12 and week-24. Product use, number of cigarettes smoked, and exhaled carbon monoxide (eCO) levels were measured at each visit. Smoking reduction and abstinence rates were calculated. Adverse events and product preferences were also reviewed.
Sustained 50% reduction in the number of cig/day at week-24 was shown in 13/40(32.5%) participants; their median of 25 cigs/day decreasing to 6 cigs/day (p < 0.001). Sustained 80% reduction was shown in 5/40(12.5%) participants; their median of 30 cigs/day decreasing to 3 cigs/day (p = 0.043). Sustained smoking abstinence at week-24 was observed in 9/40(22.5%) participants, with 6/9 still using the e-Cigarette by the end of the study. Combined sustained 50% reduction and smoking abstinence was shown in 22/40 (55%) participants, with an overall 88% fall in cigs/day. Mouth (20.6%) and throat (32.4%) irritation, and dry cough (32.4%) were common, but diminished substantially by week-24. Overall, 2 to 3 cartridges/day were used throughout the study. Participants’ perception and acceptance of the product was good.
Relationship between commuting and health outcomes in a cross-sectional population survey in southern Sweden
The results of this study are concordant with the few earlier studies in the field, in that associations were found between commutation and negative health outcomes. This further demonstrates the need to consider the negative side-effects of commuting when discussing policies aimed at increasing the mobility of the workforce. Studies identifying population groups with increased susceptibility are warranted.
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See: Commuting – bad for your health? (EurekAlert!)
Hat tip: PW