Logistic regression will be used to estimate the odds of becoming a case from examination n to n+1 as a function of heavy occupational lifting. For the cross-sectional analysis, there will be a possibility of 3 observations per participant, 1 from each examination. For the prospective analysis, there will be a possibility of 2 observations per participant, 1 from the third to the fourth examination and one from the fourth to the fifth examination. The cross-sectional analysis will be controlled for sex, age, BMI, smoking, and education. The prospective analysis will, in addition to the variables of the cross-sectional analysis, be controlled for self-rated cardiorespiratory fitness, vital exhaustion, and BP at baseline. Self-rated cardiorespiratory fitness and vital exhaustion will only be included as covariates in the prospective analysis where the main point of interest is new cases and not prevalent cases as in the cross-sectional analysis. Generalized estimating equations will be used to estimate the parameters. Observations from the same person will be treated as repeated measurements. A first order autoregressive correlation structure is assumed. Should the estimated covariance matrix fail to converge, then we will resort to a variance component correlation structure.