Factors contributing to neuromuscular impairment and sarcopenia during aging.

Motor disturbances and wasting of skeletal muscles (sarcopenia) causes significant impairment of daily life activities and is a major underlying cause for hospitalization in senescence. Herein we review data and present new findings on aging-specific changes in motoneurons, skeletal muscle and the interplay between motoneurons and target muscle fibers. Although many of the changes occurring during aging may be specific to motoneurons and myofibers, respectively, evidence indicates that myofiber regeneration in sarcopenic muscle is halted at the point where reinnervation is critical for the final differentiation into mature myofibers. Combined, evidence suggests that sarcopenia to a significant extent depend on a decreased capacity among motoneurons to innervate regenerating fibers. There are also conspicuous changes in the expression of several cytokines known to play important roles in establishing and maintaining neuromuscular connectivity during development and adulthood. We also present data showing the usefulness of rodent models in studies of successful and unsuccessful patterns of aging. Finally, we show that not only dietary restriction (DR) but also activity and social environment may modulate the pattern of aging.

Neighbourhood income and anxiety: a study based on random samples of the Swedish population.

BACKGROUND: Few studies have investigated the association between the neighbourhood characteristics and the vast panorama of mental disorders. This study examined whether there is an association between neighbourhood income and anxiety, a common mental disorder. METHODS: A national random sample of the entire Swedish population was used, consisting of 30 884 men and women aged 25-64 years. The sample was obtained from pooled data during the period 1995-2002 from the Swedish Annual Level of Living Survey. Small area market statistics were used in order to define neighbourhoods. The proportion of individuals with incomes in the lowest national income quartile was calculated for each neighbourhood. The distribution was then divided into quartiles. A log binomial model was applied in the estimation of prevalence ratios. Four models were calculated with stepwise inclusion of the variables. Model 4 was adjusted for all the individual variables, i.e. age, gender, marital status, immigrant status, social network, housing tenure, employment status, and income. RESULTS: In neighbourhoods with the highest proportions of individuals with low income the prevalence ratio of anxiety was 1.33 (95% confidence interval 1.24-1.42). The association demonstrated between neighbourhood income and anxiety decreased after stepwise inclusion of the individual variables and disappeared after all the individual variables were accounted for. CONCLUSION: Compositional explanations, rather than contextual explanations, lie behind the association between neighbourhood income and anxiety, a common mental disorder. However, we do not exclude the possibility that there is a contextual effect on severe mental disorders or among children with behavioural problems.