Generation rate, composition, and physical and chemical nature of both feces and urine were recorded as of Table 1. Each recorded datum was the mean of the data from the reported study. Some published papers reported two or more independent studies so these papers contributed more than one value to the data set. The mean and median of each variable were both calculated as measures of central tendency and data were checked for normality by calculating a coefficient of skewness (Young, 1962 ):


Measured variables for feces and urine
 Feces unitUrine unit
Variableof measureof measure
Generationg/cap/dayL/cap/day
Frequency of defecationmotions/24 hrurinations/24 hr
Water content% total mass% total mass
Organic composition% total mass% dry mass
Components of solids% total mass% total mass
Inorganic composition% dry mass% dry mass
Daily excretion of elementsg/cap/dayg/cap/day, mg/L
Chemical nature  
 pHpHpH
 COD and BODmg/g wet massmg/L
Physical form  
 Bristol stool formLinear scale (1–7) 
 Diarrhea prevalence% of population 
σ = Standard deviationn = Valid number of casesBox and whisker plots were created using Statistica 11 software (Statsoft Inc., Tulsa, OK, USA, 2011). Outliers of each data set were defined using a standard default outlier coefficient value (Burns et al., 2005 (link)).

No outliers were removed from the data set but were identified in the graphical output. Full statistical calculations were only conducted on variables that had at least seven values but a median value is given for data when there were less than seven values.
A summary of studies used in the statistical analysis are outlined in Table 2, including the location and number of studies. A large proportion (80%) of the data set was from studies conducted in Europe and North America. A distinction was therefore made between low and high income countries by the measure of development; using the Human Development Index (HDI), a composite index measuring average achievement in three basic dimensions of human development; life expectancy, education, and income (UNDP, 2011 ).
The geographical location and human development index ranking of studies used in statistical analysis
CountrynHDI*References
Africa23/4aCranston and Burkitt (1975 (link)), Burkitt et al. (1980 (link))
Australia21Birkett et al. (1996 (link)), Hovey et al. (2003 (link))
Burma14Myo-Kin et al. (1994 (link))
Canada31Burkitt et al. (1980 (link)), Vuksan et al. (1999 (link))
China32Jie et al. (2000 (link)), Chen et al. (2008 (link)), Bai and Wang (2010 )
Denmark21Maclennan and Jensen (1977 (link)), Jensen et al. (1982 (link))
Developing countries23/4aFeachem et al. (1978 )
Europe and North America11/2bFeachem et al. (1978 )
European11bMykkänen et al. (1998 (link))
Finland41Reddy et al. (1975 (link)), Reddy et al. (1978 (link)), Jensen et al. (1982 (link)), Mykkänen et al. (1998 (link))
Germany11Erhardt et al. (1997 (link))
Guatemala13Calloway and Kretsch (1978 (link))
Holland41Stasse-Wolthuis et al. (1980 (link)), Van Faassen et al. (1993 (link)), Gaillard (2002 ), Wierdsma et al. (2011 (link))
India13Shetty and Kurpad (1986 (link))
Iran12Adibi et al. (2007 (link))
Japan71Glober et al. (1977 ), Polprasert and Valencia (1981 ), Tarida et al. (1984 (link)), Saitoh et al. (1999 (link)), Danjo et al. (2008 (link)), Shinohara et al. (2010 (link)), Hotta and Funamizu (2009 (link))
Kenya14Cranston and Burkitt (1975 (link))
New Zealand11Pomare et al. (1981 )
North America11bVuksan et al. (2008 (link))
Peru12Crofts (1975 (link))
Singapore11Chen et al. (2000 (link))
South Africa23Burkitt et al. (1972 ), Walker (1975 (link))
Spain11Roig et al. (1993 (link))
Sweden41Reddy et al. (1978 (link)), Vinneras (2002 ), Vinnerås et al. (2006 )
Thailand22Danivat et al. (1988 ), Schouw et al. (2002 (link))
Tonga12Pomare et al. (1981 )
UK261Olmsted et al. (1934 ), Connell et al. (1965 (link)), Southgate and Durnin (1970 (link)), Burkitt et al. (1972 ), Goy et al. (1976 (link)), Wyman et al. (1978 (link)), Prynne and Southgate (1979 (link)), Stephen and Cummings (1980 (link)), Eastwood et al. (1984 (link)), Eastwood et al. (1986 (link)), Davies et al. (1986 (link)), Cummings et al. (1987 (link)), Sandler and Drossman (1987 (link)), Cummings et al. (1992 (link)), Murphy et al. (1993 (link)), Cummings et al. (1996 (link)), Lewis and Heaton (1997 (link)), Chen et al. (1998 (link)), Reddy et al. (1998 (link)), Rivero-Marcotegui et al. (1998 (link)), Aichbichler et al. (1998 (link)), Almeida et al. (1999 ), Magee et al. (2000 (link)), Chaplin et al. (2000 (link)), Woodmansey et al. (2004 (link)), Silvester et al. (2011 (link))
USA181Canfield et al. (1963 ), Watts et al. (1963 (link)), Diem and Lentner (1970 ), Goldsmith and Burkitt (1975 (link)), Cummings et al. (1978 ), Glober et al. (1977 ), Goldberg et al. (1977 (link)), Beyer and Flynn (1978 (link)), Reddy et al. (1978 (link)), Calloway and Kretsch (1978 (link)), Kien et al. (1981 (link)), Polprasert and Valencia (1981 ), Tucker et al. (1981 (link)), Schubert et al. (1984 (link)), Parker and Gallagher (1988 ), Zuckerman, et al. (1995 (link)), Aichbichler et al. (1998 (link)), McRorie et al. (2000)

*Human Development Index Classifications (UNDP, 2011 ): 1. Very high, 2. High, 3. Medium, 4. Low.aClassification not available, presumed to be ranking 3 or 4.bClassification not available, presumed to be ranking 1 or 2.

Preliminary data analysis indicated that fiber intake was a major cause of variation in fecal generation and composition. There were a sufficient number of studies that had examined the effects of fiber intake on fecal output to enable further analysis to be undertaken on these data. The total dietary fiber intake was related to the generation of feces in linear and nonlinear regression analyses.
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