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A prospective follow up study was conducted in Nahya village (Egypt) in order to identify the growth pattern of infants during the first year of life. A cohort of 170 newborn infants was followed up on a monthly basis to the end of the first year of life. Five anthropometric variables were measured; weight, length, head, chest and arm circumferences. Principal component analysis was used in summarizing the growth data. It effectively reduced the multidimensional growth data to seven orthogonal principal components. The seven components captured 82.7% of the variance. They represented a general size, velocity, acceleration, three physique and seasonal effect factors. The three physique factors differentiated soft from bony tissue, head from length and chest circumference from all other four variables. The first four components alone provided adequate representation of the growth data.The 4-component model explained 73.6% of the variance in the data. As judged by residual analysis, it fitted the data well.