significant reason for the trend of increasing height in parts of Europe are the egalitarian populations where proper medical care and adequate nutrition are relatively equally distributed. The uneven distribution of nutritional resources makes it more plausible for individuals with better access to resources to grow taller, while individuals with worse access to resources have a lessened chance of growing taller. Average height in a nation is correlated with protein quality. Nations that consume more protein in the form of meat, dairy, eggs, and fish tend to be taller, while those that obtain more protein from cereals tend to be shorter. Therefore, populations with high cattle per capita and high consumption of dairy live longer and are taller. Historically, this can be seen in the cases of the United States, Argentina, New Zealand and Australia in the beginning of the 19th century. Moreover, when the production and consumption of milk and beef is taken to consideration, it can be seen why the Germanic people who lived outside of the Roman Empire were taller than those who lived at its heart. Changes in diet (nutrition) and a general rise in quality of health care and standard of living are the cited factors in the Asian populations. Malnutrition including chronic undernutrition and acute malnutrition is known to have caused stunted growth in various populations. This has been seen in North Korea, parts of Africa, certain historical Europe, and other populations. Developing countries such as Guatemala have rates of stunting in children under 5 living as high as 82.2% in Totonicapán, and 49.8% nationwide. Height measurements are by nature subject to statistical sampling errors even for a single individual. In a clinical situation, height measurements are seldom taken more often than once per office visit, which may mean sampling taking place a week to several months apart. The smooth 50th percentile male and female growth curves illustrated above are aggregate values from thousands of individuals sampled at ages from birth to age 20. In reality, a single individual's growth curve shows large upward and downward spikes, partly due to actual differences in growth velocity, and partly due to small measurement errors. For example, a typical measurement error of plus or minus may completely nullify 0.5 cm of actual growth resulting in either a "negative" 0.5 cm growth (due to overestimation in the previous visit combined with underestimation in the latter), up to a