Muscle strength and physical education: epidemiological studies of factors in adolescence and their association with later morbidity

Although Physical Education (PE) is a part of the school curriculum in many countries, the association between the performance in PE and later morbidity is largely unknown. An important marker of health, cardiorespiratory fitness is inversely associated with future cardiovascular disease (CVD) and mortality. It has been suggested that muscle strength is associated in a similar way. However, whether low muscle strength in youth is a risk factor for CVD independently of cardiorespiratory fitness is not known. In a cohort of men and women, I investigated the association between PE performance in adolescence and morbidity in middle age (paper I and II). In cohorts of adolescent men, I investigated isometric muscle strength as a risk factor for later musculoskeletal pain (paper III), CVD, and mortality (paper IV). In women, low PE performance was associated with having a musculoskeletal diagnosis as well as with increased sick leave and increased number of physician visits. Men with low muscle strength did not have an increased risk for musculoskeletal pain but an increased risk of ischemic CVD as well as middle age CVD mortality. Notably, the associations were independent of cardiorespiratory fitness. In summary, I conclude the following 1) Adolescent girls with low PE performance could be important to target with early interventions to reduce future musculoskeletal illness and health impairment. 2) General isometric muscle strength in youth is not a risk factor for adult musculoskeletal pain in men. 3) The role of muscle strength in the development of CVD warrants further attention

Nonparametric estimation of first passage time distributions in flowgraph models

Statistical flowgraphs represent multistate semi-Markov processes using integral transforms of transition time distributions between adjacent states; these are combined algebraically and inverted to derive parametric estimates for first passage time distributions between nonadjacent states. This dissertation extends previous work in the field by developing estimation methods for flowgraphs using empirical transforms based on sample data, with no assumption of specific parametric probability models for transition times. We prove strong convergence of empirical flowgraph results to the exact parametric results; develop alternatives for numerical inversion of empirical transforms and compare them in terms of computational complexity, accuracy, and ability to determine error bounds; discuss (with examples) the difficulties of determining confidence bands for distribution estimates obtained in this way; develop confidence intervals for moment-based quantities such as the mean; and show how methods based on empirical transforms can be modified to accommodate censored data. Several applications of the nonparametric method, based on reliability and survival data, are presented in detail