With the increasing use of backpacks on a daily basis, appropriate assessment of shoulder load, which has adverse effects on the body, has become more important. We focused on nociceptive pain, which is a physiological warning signal, and performed a subjective evaluation of loading conditions. In this study, we investigated the relationship between multi-point mechanical stimuli set at38 measuring points on the shoulder, and overall pain. In the experiment, eight subjects rated their pain levels at 24 loading conditions (combinations of 3 weight, 2 weight-distance, 2 weight-height, and 2 padding conditions) using a pain scale. In the statistical analysis, the overall pain intensities at different loading conditions were compared through ANOVA, and weight and distance from body were confirmed as main contributing factors. In the regression analysis, four different models were used to fit the overall data. A generalized linear model (GLM) with polynomial sigmoid function resulted in the best fit. GLM fitting was also performed on the data after these have been divided into 8 groups based on combinations of distance-height-padding. The independent variables, the selected combinations of loads at the measuring points, differed depending on the loading conditions. For more accurate regression, loads that contribute to the determination of overall pain intensity should be appropriately selected according to the loading conditions. These results can be used to comprehensively evaluate backpack design based on shoulder pain.