## 4 Discussion
### Limitations and Strengths  
The main limitation of our study is the limited knowledge about the life-history of players once they retire. It is well known that some remain active with a healthy lifestyle, while others gain excessive weight. In addition, we did not have access to disease or family data nor the clinical history of the players. Therefore, our results are only suggestive about a general association between mortality and height and ethnicity. We considered the number of games played as a proxy to measure the volume of exercise, but we do not have tracking data that can inform about the intensity, load or density of exercise. We also had information about the number of minutes played and the number of minutes per game played, but all three variables were highly correlated. Further, we had missing data of minutes played for 344 players, so we only analyzed the number of games played. Very extreme or very intense exercise has been related to mortality [24], but we did not find any association between the number of games played and risk of death. However, many of the players in our sample had careers outside the NBA, playing in other leagues inside and outside United States. While some of these competitions are also very demanding (especially the major European competitions), the level of physical requirement is lower than that for the NBA. However, this absent information was a shortcoming for our analysis. A considerable percentage of games in the NBA are considered as \"close games\" [45], where home/away teams are winning by less than 10 points at the end of the 3 rd quarter. Specifically, we explored a large data base provided by www.nbastuffer.com; a sample of 2623 regular season and play-off games between 2009 and 2011. The percentage of \"close games\" was 52.2%. This probably means that the distribution of close games in our whole sample is not homogenous, but these claims should be tested in further research with more comprehensive data. It is known that emotional stressors trigger cardiovascular events [46], but literature has also shown that high drama/intensity experience lived by sports fans can be associated with changes in cardiovascular death rates in the short term, depending on winning (decrease) or losing (increase) [47]. Therefore, it is not clear how highly intense, mentally demanding games in the NBA could influence mortality in the long term, considering the possible moderating factor of winning vs. losing close games. In addition, divergences in intensity between players are not related to the risk of all-cause mortality [48], as has been suggested after comparing National Football League participation as a career player with participation as a replacement player. Finally, regarding ethnicity, we recognize the complexity of considering this variable in our analysis. As [PERSON] pointed out, we have thousands of genes that are invisible except for a few anatomical features such as skin color [49], so categorizing individuals only for one visible feature could be deemed crude. We followed the example of other studies that used the simplistic categorization of White versus African-American using skin color [9]. However, we took precautions to carefully consider and eliminate \"mixed ethnicity\" from the analysis, in order to take into account players with white and African-American parents (56, 1.6%). The aim of our study was to analyze overall mortality, but not specific mortality, as [PERSON] et al. recently did [38]. This requires advanced survival analysis, such as the competing risk method, to analyze the causes of death. However, we believe it would be necessary to reduce the number of missing cases. [PERSON] et al. [38] had 34.7% of missing cases and in a search, we obtained 39.6% of missing cases. However, it is difficult to know the causes of death of players where information is not available from public sources. Regarding methodological considerations, we analyzed survival time, rather than a dichotomous response variable (alive or dead).