Ok., question, you drink say a lot of water, and it goes out the normal way
(trying to use tact) how much fluoride would you absorb then?  UM MOM
Susan,ps Joel please call me Susan I use the UM MOM because there are so
many Susan's.

Simple observation? Manipulated epidemiology!!

Uhhh? 0.5 ppm where ?? - ... if the water contains another 0.5 ppm?
You still compare apples with oranges.

If the water contains 0.5 ppm fluoride, you´ll take up 0.5 mg if you
ingest just one liter (including the amount of water you use for coffee
or cooking your food). If your grapes contain 0.5 ppm fluoride, you´ll
ingest another 0.5 mg fluoride only if you eat one kg of grapes. Not to
speak about tea.

I´m not Jan Drew, anyway. And I wouldn´t say you´re lying. Though you
could know better by now (that concentration and dose are different
things).

Peter

On the right are the references for the study and where it was
published.

In all studies they must describe how they got their samples and how
they measured it. A statistical description is "confidence levels."

PAGE 4

Samples were collected in up to 144 locations
across the country, depending on the level of contribution to fluoride
intake. Since
drinking water accounts for approximately 75% of dietary fluoride
intake, sampling of
drinking water was conducted, with Office of Management and Budget
approval,

PAGE 6

The Confidence Code (CC) was derived from the QI and
is an indicator of relative quality of the data and the reliability of
a given mean. The CC
is assigned as follows:
QI CC
75-100 A
74-50 B
49-25 C
< 25 D
Format of the table
The table contains fluoride values for 400 foods across 23 food
groups. The data were
aggregated where possible to match the foods in the USDA National
Nutrient Database
for Standard Reference (SR). Food groups are presented in alphabetical
order with
beverages and foods arranged in alphabetical order within a food
group. Whenever
possible, a NDB Number (No.) (a five digit numerical code used in the
SR) is provided.
This NDB No. provides the link between values for foods in this
database and SR. As
the data come from a variety of sources or are presented with
specificity not used in SR,
there are a number of beverages and foods which are included without a
NDB No. In
these cases, we assigned a temporary NDB No. which begins with “975.”
These
temporary NDB Nos. are not unique to these beverages and foods and may
be used in
other special interest databases produced by NDL.

PAGE 7

Field Name Description
Food Group Description of food group
Item Description of food or beverage
Mean Amount in 100 grams, edible portion
Std Error Standard error of the mean. Null, if could not be calculated
N Number of data points (samples analyzed). The N=1 on
NFNAP data represents a composite of 12 samples
Min Minimum value
Max Maximum value
Lower EB Lower 95% error bound
Upper EB Upper 95% error bound
CC Confidence code indicating data quality based on
evaluations of sample plan, sample handling, analytical
method, analytical quality control, and number of samples
analyzed
Derivation Code Code giving specific information on how the value was
determined:
A = Analytical data
RPA = Recipe; Known formulation; No adjustments
applied, combination of source codes 1, 12 and/or
6
RPI = Recipe; Known formulation; No adjustments
applied, combination of source codes which
includes codes other than 1, 12 or 6
Source Code Code indicating type of data
1 = Analytical or derived from analytical
6 = Aggregated data involving combinations of source
codes 1 & 12
12 = Manufacturer's analytical; partial documentation
Statistical
Comments
1. The displayed summary statistics were computed
from data containing some less-than values. Lessthan,
trace, and not detected values were calculated
2. The displayed degrees of freedom were computed
using Satterthwaite’s approximation (Korz and
Johnson, 1988)
3. The procedure used to estimate the reliability of the
generic mean requires that the data associated with
each study be a simple random sample from all the
products associated with the given data source (for
example, manufacturer, variety, cultivar, and species)
4. For this nutrient, one or more data sources had only