Milk female hormones > female cancer?

[Guest guest]

Milk female hormones > female cancer?

Hi All,

Could it be that female sex hormones are implicated in female cancers? The

below

suggests the answer is yes.

The study is a population comparison type study. " The correlation of incidence

and

mortality rates with environmental variables in worldwide countries provides

[weak]

clues to the etiology of cancer " ?

Ironically, of the only two prospective studies described in the new Med

Hypotheses

paper below, the only one for which the full-text was available did implicate

dairy

and milk in ovarian cancer reported that it was the lactose component of milk

that

was solely responsible for the positive association. See below the text of the

Med

Hypotheses paper for the appropriate excerpts of the full-text text of the

reference.

Med Hypotheses. 2005 Aug 23; [Epub ahead of print]

The possible role of female sex hormones in milk from pregnant cows in the

development of breast, ovarian and corpus uteri cancers.

Ganmaa D, Sato A.

The continued increase in incidence of some hormone-related cancers worldwide

is

of great concern. Although estrogen-like substances in the environment were

blamed

for this increase, the possible role of endogenous estrogens from food has not

been

widely discussed. We are particularly concerned about cows' milk, which contains

a

considerable quantity of estrogens. When we name cows' milk as one of the

important

routes of human exposure to estrogens, the general response of Western people is

that " man has been drinking cows' milk for around 2000 years without apparent

harm. "

However, the milk that we are now consuming is quite different from that

consumed

100 years ago. Unlike their pasture-fed counterparts of 100 years ago, modern

dairy

cows are usually pregnant and continue to lactate during the latter half of

pregnancy, when the concentration of estrogens in blood, and hence in milk,

increases. The correlation of incidence and mortality rates with environmental

variables in worldwide countries provides useful clues to the etiology of

cancer. In

this study, we correlated incidence rates for breast, ovarian, and corpus uteri

cancers (1993-97 from Cancer Incidence in Five Continents) with food intake

(1961-97

from FAOSTAT) in 40 countries. Meat was most closely correlated with the breast

cancer incidence (r=0.827), followed by milk (0.817) and cheese (0.751).

Stepwise

multiple-regression analysis (SMRA) identified meat as the factor contributing

most

greatly to the incidence of breast cancer ([R]=0.862). Milk was most closely

correlated with the incidence of ovarian cancer (r=0.779), followed by animal

fats

(0.717) and cheese (0.697). SMRA revealed that milk plus cheese make the

greatest

contribution to the incidence of ovarian cancer ([R]=0.767). Milk was most

closely

correlated with corpus uteri cancer (r=0.814), followed by cheese (0.787). SMRA

revealed that milk plus cheese make the most significant contribution to the

incidence of corpus uteri cancer ([R]=0.861). In conclusion, increased

consumption

of animal-derived food may have adverse effects on the development of

hormone-dependent cancers. Among dietary risk factors, we are most concerned

with

milk and dairy products, because the milk we drink today is produced from

pregnant

cows, in which estrogen and progesterone levels are markedly elevated.

PMID: 16125328

… Table 1. Correlation coefficients between female cancer incidence rates

(1993–97)

and food consumption (average values during 1961–97)

.................................

Correlation coefficient

Breast Ovary Corpus uteri

...................................

Animal fats 0.650‡‡ 0.717‡‡ 0.713‡‡

Butter 0.584‡‡ 0.576‡‡ 0.543‡‡

Cheese 0.751‡‡ 0.697‡‡ 0.787‡‡

Eggs 0.660‡‡ 0.589‡‡ 0.703‡‡

Meat 0.827‡‡ 0.575‡‡ 0.782‡‡

Fish 0.055 0.226 0.115

Milk 0.817‡‡ 0.779‡‡ 0.814‡‡

Cereals & #8722;0.467‡‡ & #8722;0.520‡‡ & #8722;0.422‡‡

Pulses & #8722;0.438‡‡ & #8722;0.465‡‡ & #8722;0.437‡‡

Fruits 0.297 0.357‡ 0.297

Vegetables 0.222 0.068 0.211

Vegetable oils 0.515‡‡ 0.396‡ 0.580‡‡

Alcohol 0.517‡‡ 0.399‡ 0.497‡‡

Coffee 0.537‡‡ 0.621‡‡ 0.626‡‡

Tea 0.322‡ 0.045 0.126

.......................................

‡ p < 0.05.

‡‡ p < 0.01.

… Table 2. Stepwise-multiple-regression analysis (forward) on the consumption of

selected food items (independent variablesa) affecting incidence/mortality rates

of

female cancers (dependent variables)

......................................

Coefficient Standard error R2b F-to-remove

......................................

Breast cancer incidence vs. 11 independent variables (1961–1998)

Meat 0.251 0.025 0.862 13.724

Breast cancer mortality vs. 11 independent variables (1961–1998)

Milk and cheese 0.022 0.003 0.814 68.527

Ovary cancer incidence vs. 11 independent variables (1961–1998)

Milk and cheese 0.009 0.001 0.767 48.619

Ovary cancer mortality vs. 11 independent variables (1961–1998)

Fats and butter 0.059 0.008 0.796 60.416

Corpus uteri cancer incidence vs. 11 independent variables (1961–1998)

Milk and cheese 0.014 0.003 0.861 72.242

Corpus uteri cancer mortality vs. 11 independent variables (1961–1998)

Milk and cheese 0.001 0.001 0.517 12.746

...........................................

a Fats and butter, meat, eggs, milk and cheese, cereals, pulses, fruits,

vegetables,

vegetable oils, coffee, and alcohol were used as the independent variables.

b R, standardized regression coefficient.

… Table 3. Correlation coefficients between female cancer mortality rates (2000)

and

food consumption (average values during 1961–97)

...........................................

Correlation coefficient

Breast Ovary Corpus uteri

...........................................

Animal fats 0.670‡‡ 0.818‡‡ 0.403‡‡

Butter 0.595‡‡ 0.651‡‡ 0.330‡

Cheese 0.725‡‡ 0.731‡‡ 0.406‡‡

Eggs 0.615‡‡ 0.655‡‡ 0.223

Meat 0.517‡‡ 0.600‡‡ 0.434‡‡

Fish 0.110 0.047 & #8722;0.140

Milk 0.536‡‡ 0.790‡‡ 0.545‡‡

Cereals & #8722;0.401‡ & #8722;0.391‡‡ & #8722;0.384‡

Pulses & #8722;0.395‡ & #8722;0.367‡ & #8722;0.345‡

Fruits 0.292 0.246‡ 0.381‡

Vegetables 0.189 0.185 & #8722;0.036

Vegetable oils 0.435‡‡ 0.372‡ 0.339‡

Alcohol 0.463‡‡ 0.491‡‡ 0.249

Coffee 0.547‡‡ 0.569‡‡ 0.349‡

Tea 0.316‡ 0.186 0.256

........................................

‡ p < 0.05.

‡‡ p < 0.01.

… [45] Prospective study of diet and ovarian cancer.

Am J Epidemiol. 1999 Jan 1;149(1):21-31.

PMID: 9883790

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve & db=pubmed & dopt=Abstra\

ct & list_uids=9883790 & query_hl=34Kushi

LH, Mink PJ, Folsom AR, KE, Zheng W, Lazovich D, Sellers TA. Related

Articles, Links

.... [51] Larsson SC, Bergkvist L, Wolk A.

Milk and lactose intakes and ovarian cancer risk in the Swedish Mammography

Cohort.

Am J Clin Nutr. 2004 Nov;80(5):1353-7.

PMID: 15531686

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve & db=pubmed & dopt=Abstra\

ct & list_uids=15531686 & query_hl=32

.... TABLE 2 Invasive epithelial ovarian cancer according to consumption of dairy

products1

.......................................

Intake All invasive epithelial tumors Serous epithelial tumors Other epithelial

tumors2

No. of cases RR (95% CI) No. of cases RR (95% CI) No. of cases RR (95%

CI)

.......................................

Total dairy (servings/d)3

<2 61 1.0 24 1.0 37 1.0

2 to <3 71 1.2 (0.9, 1.7) 37 1.6 (0.9, 2.7) 34 1.0 (0.6, 1.6)

3 to <4 65 1.4 (0.9, 2.0) 30 1.6 (0.9, 2.9) 35 1.2 (0.7, 2.0)

4 69 1.6 (1.1, 2.5) 34 2.0 (1.1, 3.7) 35 1.4 (0.8, 2.4)

P for trend4 0.02 0.06 0.15

Total milk (servings/d)5

Never or seldom (1 serving wk) 55 1.0 18 1.0 37 1.0

1 54 1.2 (0.9, 1.8) 22 1.5 (0.8, 2.9) 32 1.1 (0.7, 1.8)

1.1 to <2 86 1.2 (0.9, 1.8) 49 2.1 (1.2, 3.7) 37 0.8 (0.5, 1.3)

2 71 1.3 (0.9, 1.9) 36 2.0 (1.1, 3.7) 35 1.0 (0.6, 1.6)

P for trend4 0.27 0.04 0.70

Total yogurt (servings/d)5

Never or seldom (<1 serving wk) 118 1.0 48 1.0 70 1.0

<1 66 1.0 (0.7, 1.3) 36 1.3 (0.8, 2.0) 30 0.7 (0.5, 1.1)

1 82 1.1 (0.8, 1.5) 41 1.4 (0.9, 2.2) 41 0.9 (0.6, 1.4)

P for trend3 0.42 0.11 0.76

Cheese (servings/d)5

<1 81 1.0 36 1.0 45 1.0

1 to <2 107 0.9 (0.7, 1.3) 55 1.0 (0.7, 1.6) 52 0.9 (0.6, 1.3)

2 78 1.2 (0.9, 1.7) 34 1.1 (0.7, 1.9) 44 1.3 (0.8, 2.1)

P for trend4 0.17 0.69 0.15

.......................................................................

1 Multivariate rate ratios (RRs) were adjusted for age (in 5-y categories), BMI

(kg/m2; in quartiles), education level (ie, less than high school, high school,

and

college), parity (ie, nulliparous, 1–2, and 3 children), oral contraceptive use

(ever or never), and quartiles of fruit, vegetable, and total energy intakes.

2 Includes 48 endometrioid tumors, 21 mucinous tumors, 5 clear cell tumors, and

67

undifferentiated tumors or tumors of unknown histologic subtypes.

3 Total dairy products included total milk (low-fat, medium-fat, and whole

milk),

total yogurt (low-fat and regular yogurt), cheese, and ice cream.

4 Two-sided P values for trend were calculated with the Wald statistic by using

the

median values for each category.

5 Total milk, total yogurt, and cheese were mutually adjusted.

.... Lactose intake showed a linear positive association with the risk of serous

ovarian cancer (P for trend = 0.006; Figure 1). The average lactose intake in

the

cohort was 12.2 ± 7.8 g/d; milk was the major source. Relative to women with a

lactose intake of 15 g/d (corresponding to the amount of lactose in 1–2 glasses

of

milk), those with an intake of <2.5 g/d (the amount of lactose in 50 g milk, ie,

3–4

tablespoons, corresponding to the amount usually added to 1–2 cups of coffee or

tea)

were less than half (0.4; 95% CI: 0.1, 0.9) as likely to develop serous ovarian

cancer. When lactose was analyzed as a continuous variable, each 10 g/d increase

in

lactose intake (the amount of lactose in 1 glass milk) was associated with a 20%

greater risk of serous ovarian cancer (multivariate RR: 1.2; 95% CI: 1.0, 1.5).

The

corresponding RRs for total ovarian cancer and nonserous tumors was 1.1 (95% CI:

0.9, 1.3) and 1.0 (95% CI: 0.8, 1.2), respectively.

When we included intakes of lactose and milk simultaneously in the multivariate

model (Pearson's correlation coefficient: r = 0.65), the observed positive

association between total milk consumption and the risk of serous ovarian cancer

was

mostly confined to lactose intake because the relative risk for each 1 glass/d

increment in total milk consumption decreased from 1.2 (95% CI: 1.0, 1.4) to 1.0

(95% CI: 0.8, 1.3), whereas the relative risk for increments of lactose intake

was

essentially unaltered (RR for each 10 g/d increment: 1.2; 95% CI: 0.9, 1.6).

...

Al Pater, PhD; email: old542000@...

__________________________________________________

[Guest guest]

Hi Al:

And milk seems to be implicated in prostate cancer also. As noted in

my long list of ways to help prevent prostate cancer - avoid milk.

Rodney.

--- In , Al Pater <old542000@y...>

wrote:

> Milk female hormones > female cancer?

>

> Hi All,

>

> Could it be that female sex hormones are implicated in female

cancers? The below

> suggests the answer is yes.

>

> The study is a population comparison type study. " The correlation

of incidence and

> mortality rates with environmental variables in worldwide countries

provides [weak]

> clues to the etiology of cancer " ?

>

> Ironically, of the only two prospective studies described in the

new Med Hypotheses

> paper below, the only one for which the full-text was available did

implicate dairy

> and milk in ovarian cancer reported that it was the lactose

component of milk that

> was solely responsible for the positive association. See below the

text of the Med

> Hypotheses paper for the appropriate excerpts of the full-text text

of the

> reference.

>

> Med Hypotheses. 2005 Aug 23; [Epub ahead of print]

> The possible role of female sex hormones in milk from pregnant cows

in the

> development of breast, ovarian and corpus uteri cancers.

> Ganmaa D, Sato A.

> The continued increase in incidence of some hormone-related

cancers worldwide is

> of great concern. Although estrogen-like substances in the

environment were blamed

> for this increase, the possible role of endogenous estrogens from

food has not been

> widely discussed. We are particularly concerned about cows' milk,

which contains a

> considerable quantity of estrogens. When we name cows' milk as one

of the important

> routes of human exposure to estrogens, the general response of

Western people is

> that " man has been drinking cows' milk for around 2000 years

without apparent harm. "

> However, the milk that we are now consuming is quite different from

that consumed

> 100 years ago. Unlike their pasture-fed counterparts of 100 years

ago, modern dairy

> cows are usually pregnant and continue to lactate during the latter

half of

> pregnancy, when the concentration of estrogens in blood, and hence

in milk,

> increases. The correlation of incidence and mortality rates with

environmental

> variables in worldwide countries provides useful clues to the

etiology of cancer. In

> this study, we correlated incidence rates for breast, ovarian, and

corpus uteri

> cancers (1993-97 from Cancer Incidence in Five Continents) with

food intake (1961-97

> from FAOSTAT) in 40 countries. Meat was most closely correlated

with the breast

> cancer incidence (r=0.827), followed by milk (0.817) and cheese

(0.751). Stepwise

> multiple-regression analysis (SMRA) identified meat as the factor

contributing most

> greatly to the incidence of breast cancer ([R]=0.862). Milk was

most closely

> correlated with the incidence of ovarian cancer (r=0.779), followed

by animal fats

> (0.717) and cheese (0.697). SMRA revealed that milk plus cheese

make the greatest

> contribution to the incidence of ovarian cancer ([R]=0.767). Milk

was most closely

> correlated with corpus uteri cancer (r=0.814), followed by cheese

(0.787). SMRA

> revealed that milk plus cheese make the most significant

contribution to the

> incidence of corpus uteri cancer ([R]=0.861). In conclusion,

increased consumption

> of animal-derived food may have adverse effects on the development

of

> hormone-dependent cancers. Among dietary risk factors, we are most

concerned with

> milk and dairy products, because the milk we drink today is

produced from pregnant

> cows, in which estrogen and progesterone levels are markedly

elevated.

> PMID: 16125328

>

> … Table 1. Correlation coefficients between female cancer incidence

rates (1993–97)

> and food consumption (average values during 1961–97)

> .................................

> Correlation coefficient

> Breast Ovary Corpus uteri

> ..................................

> Animal fats 0.650‡‡ 0.717‡‡ 0.713‡‡

> Butter 0.584‡‡ 0.576‡‡ 0.543‡‡

> Cheese 0.751‡‡ 0.697‡‡ 0.787‡‡

> Eggs 0.660‡‡ 0.589‡‡ 0.703‡‡

> Meat 0.827‡‡ 0.575‡‡ 0.782‡‡

> Fish 0.055 0.226 0.115

> Milk 0.817‡‡ 0.779‡‡ 0.814‡‡

> Cereals & #8722;0.467‡‡ & #8722;0.520‡‡ & #8722;0.422‡‡

> Pulses & #8722;0.438‡‡ & #8722;0.465‡‡ & #8722;0.437‡‡

> Fruits 0.297 0.357‡ 0.297

> Vegetables 0.222 0.068 0.211

> Vegetable oils 0.515‡‡ 0.396‡ 0.580‡‡

> Alcohol 0.517‡‡ 0.399‡ 0.497‡‡

> Coffee 0.537‡‡ 0.621‡‡ 0.626‡‡

> Tea 0.322‡ 0.045 0.126

> ......................................

> ‡ p < 0.05.

> ‡‡ p < 0.01.

>

> … Table 2. Stepwise-multiple-regression analysis (forward) on the

consumption of

> selected food items (independent variablesa) affecting

incidence/mortality rates of

> female cancers (dependent variables)

> .....................................

> Coefficient Standard error R2b F-to-remove

> .....................................

> Breast cancer incidence vs. 11 independent variables (1961–1998)

> Meat 0.251 0.025 0.862 13.724

> Breast cancer mortality vs. 11 independent variables (1961–1998)

> Milk and cheese 0.022 0.003 0.814 68.527

> Ovary cancer incidence vs. 11 independent variables (1961–1998)

> Milk and cheese 0.009 0.001 0.767 48.619

> Ovary cancer mortality vs. 11 independent variables (1961–1998)

> Fats and butter 0.059 0.008 0.796 60.416

> Corpus uteri cancer incidence vs. 11 independent variables (1961–

1998)

> Milk and cheese 0.014 0.003 0.861 72.242

> Corpus uteri cancer mortality vs. 11 independent variables (1961–

1998)

> Milk and cheese 0.001 0.001 0.517 12.746

> ..........................................

> a Fats and butter, meat, eggs, milk and cheese, cereals, pulses,

fruits, vegetables,

> vegetable oils, coffee, and alcohol were used as the independent

variables.

> b R, standardized regression coefficient.

>

> … Table 3. Correlation coefficients between female cancer mortality

rates (2000) and

> food consumption (average values during 1961–97)

> ..........................................

> Correlation coefficient

> Breast Ovary Corpus uteri

> ..........................................

> Animal fats 0.670‡‡ 0.818‡‡ 0.403‡‡

> Butter 0.595‡‡ 0.651‡‡ 0.330‡

> Cheese 0.725‡‡ 0.731‡‡ 0.406‡‡

> Eggs 0.615‡‡ 0.655‡‡ 0.223

> Meat 0.517‡‡ 0.600‡‡ 0.434‡‡

> Fish 0.110 0.047 & #8722;0.140

> Milk 0.536‡‡ 0.790‡‡ 0.545‡‡

> Cereals & #8722;0.401‡ & #8722;0.391‡‡ & #8722;0.384‡

> Pulses & #8722;0.395‡ & #8722;0.367‡ & #8722;0.345‡

> Fruits 0.292 0.246‡ 0.381‡

> Vegetables 0.189 0.185 & #8722;0.036

> Vegetable oils 0.435‡‡ 0.372‡ 0.339‡

> Alcohol 0.463‡‡ 0.491‡‡ 0.249

> Coffee 0.547‡‡ 0.569‡‡ 0.349‡

> Tea 0.316‡ 0.186 0.256

> .......................................

> ‡ p < 0.05.

> ‡‡ p < 0.01.

>

> … [45] Prospective study of diet and ovarian cancer.

> Am J Epidemiol. 1999 Jan 1;149(1):21-31.

> PMID: 9883790

>

> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?

cmd=Retrieve & db=pubmed & dopt=Abstract & list_uids=9883790 & query_hl=34Kush

i

> LH, Mink PJ, Folsom AR, KE, Zheng W, Lazovich D, Sellers

TA. Related

> Articles, Links

>

> ... [51] Larsson SC, Bergkvist L, Wolk A.

> Milk and lactose intakes and ovarian cancer risk in the Swedish

Mammography Cohort.

> Am J Clin Nutr. 2004 Nov;80(5):1353-7.

> PMID: 15531686

>

> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?

cmd=Retrieve & db=pubmed & dopt=Abstract & list_uids=15531686 & query_hl=32

>

> ... TABLE 2 Invasive epithelial ovarian cancer according to

consumption of dairy

> products1

> ......................................

> Intake All invasive epithelial tumors Serous epithelial tumors

Other epithelial

> tumors2

> No. of cases RR (95% CI) No. of cases RR (95% CI) No. of

cases RR (95% CI)

> .......................................

> Total dairy (servings/d)3

> <2 61 1.0 24 1.0 37 1.0

> 2 to <3 71 1.2 (0.9, 1.7) 37 1.6 (0.9, 2.7) 34 1.0 (0.6, 1.6)

> 3 to <4 65 1.4 (0.9, 2.0) 30 1.6 (0.9, 2.9) 35 1.2 (0.7, 2.0)

> 4 69 1.6 (1.1, 2.5) 34 2.0 (1.1, 3.7) 35 1.4 (0.8, 2.4)

> P for trend4 0.02 0.06 0.15

> Total milk (servings/d)5

> Never or seldom (1 serving wk) 55 1.0 18 1.0 37 1.0

> 1 54 1.2 (0.9, 1.8) 22 1.5 (0.8, 2.9) 32 1.1 (0.7, 1.8)

> 1.1 to <2 86 1.2 (0.9, 1.8) 49 2.1 (1.2, 3.7) 37 0.8 (0.5, 1.3)

> 2 71 1.3 (0.9, 1.9) 36 2.0 (1.1, 3.7) 35 1.0 (0.6, 1.6)

> P for trend4 0.27 0.04 0.70

> Total yogurt (servings/d)5

> Never or seldom (<1 serving wk) 118 1.0 48 1.0 70 1.0

> <1 66 1.0 (0.7, 1.3) 36 1.3 (0.8, 2.0) 30 0.7 (0.5, 1.1)

> 1 82 1.1 (0.8, 1.5) 41 1.4 (0.9, 2.2) 41 0.9 (0.6, 1.4)

> P for trend3 0.42 0.11 0.76

> Cheese (servings/d)5

> <1 81 1.0 36 1.0 45 1.0

> 1 to <2 107 0.9 (0.7, 1.3) 55 1.0 (0.7, 1.6) 52 0.9 (0.6, 1.3)

> 2 78 1.2 (0.9, 1.7) 34 1.1 (0.7, 1.9) 44 1.3 (0.8, 2.1)

> P for trend4 0.17 0.69 0.15

> ....................................................................

...

> 1 Multivariate rate ratios (RRs) were adjusted for age (in 5-y

categories), BMI

> (kg/m2; in quartiles), education level (ie, less than high school,

high school, and

> college), parity (ie, nulliparous, 1–2, and 3 children), oral

contraceptive use

> (ever or never), and quartiles of fruit, vegetable, and total

energy intakes.

> 2 Includes 48 endometrioid tumors, 21 mucinous tumors, 5 clear cell

tumors, and 67

> undifferentiated tumors or tumors of unknown histologic subtypes.

> 3 Total dairy products included total milk (low-fat, medium-fat,

and whole milk),

> total yogurt (low-fat and regular yogurt), cheese, and ice cream.

> 4 Two-sided P values for trend were calculated with the Wald

statistic by using the

> median values for each category.

> 5 Total milk, total yogurt, and cheese were mutually adjusted.

>

> ... Lactose intake showed a linear positive association with the

risk of serous

> ovarian cancer (P for trend = 0.006; Figure 1). The average lactose

intake in the

> cohort was 12.2 ± 7.8 g/d; milk was the major source. Relative to

women with a

> lactose intake of 15 g/d (corresponding to the amount of lactose in

1–2 glasses of

> milk), those with an intake of <2.5 g/d (the amount of lactose in

50 g milk, ie, 3–4

> tablespoons, corresponding to the amount usually added to 1–2 cups

of coffee or tea)

> were less than half (0.4; 95% CI: 0.1, 0.9) as likely to develop

serous ovarian

> cancer. When lactose was analyzed as a continuous variable, each 10

g/d increase in

> lactose intake (the amount of lactose in 1 glass milk) was

associated with a 20%

> greater risk of serous ovarian cancer (multivariate RR: 1.2; 95%

CI: 1.0, 1.5). The

> corresponding RRs for total ovarian cancer and nonserous tumors was

1.1 (95% CI:

> 0.9, 1.3) and 1.0 (95% CI: 0.8, 1.2), respectively.

>

> When we included intakes of lactose and milk simultaneously in the

multivariate

> model (Pearson's correlation coefficient: r = 0.65), the observed

positive

> association between total milk consumption and the risk of serous

ovarian cancer was

> mostly confined to lactose intake because the relative risk for

each 1 glass/d

> increment in total milk consumption decreased from 1.2 (95% CI:

1.0, 1.4) to 1.0

> (95% CI: 0.8, 1.3), whereas the relative risk for increments of

lactose intake was

> essentially unaltered (RR for each 10 g/d increment: 1.2; 95% CI:

0.9, 1.6).

>

> ...

>

> Al Pater, PhD; email: old542000@y...

>

> __________________________________________________

>

[Guest guest]

Hi Al:

And milk seems to be implicated in prostate cancer also. As noted in

my long list of ways to help prevent prostate cancer - avoid milk.

Rodney.

--- In , Al Pater <old542000@y...>

wrote:

> Milk female hormones > female cancer?

>

> Hi All,

>

> Could it be that female sex hormones are implicated in female

cancers? The below

> suggests the answer is yes.

>

> The study is a population comparison type study. " The correlation

of incidence and

> mortality rates with environmental variables in worldwide countries

provides [weak]

> clues to the etiology of cancer " ?

>

> Ironically, of the only two prospective studies described in the

new Med Hypotheses

> paper below, the only one for which the full-text was available did

implicate dairy

> and milk in ovarian cancer reported that it was the lactose

component of milk that

> was solely responsible for the positive association. See below the

text of the Med

> Hypotheses paper for the appropriate excerpts of the full-text text

of the

> reference.

>

> Med Hypotheses. 2005 Aug 23; [Epub ahead of print]

> The possible role of female sex hormones in milk from pregnant cows

in the

> development of breast, ovarian and corpus uteri cancers.

> Ganmaa D, Sato A.

> The continued increase in incidence of some hormone-related

cancers worldwide is

> of great concern. Although estrogen-like substances in the

environment were blamed

> for this increase, the possible role of endogenous estrogens from

food has not been

> widely discussed. We are particularly concerned about cows' milk,

which contains a

> considerable quantity of estrogens. When we name cows' milk as one

of the important

> routes of human exposure to estrogens, the general response of

Western people is

> that " man has been drinking cows' milk for around 2000 years

without apparent harm. "

> However, the milk that we are now consuming is quite different from

that consumed

> 100 years ago. Unlike their pasture-fed counterparts of 100 years

ago, modern dairy

> cows are usually pregnant and continue to lactate during the latter

half of

> pregnancy, when the concentration of estrogens in blood, and hence

in milk,

> increases. The correlation of incidence and mortality rates with

environmental

> variables in worldwide countries provides useful clues to the

etiology of cancer. In

> this study, we correlated incidence rates for breast, ovarian, and

corpus uteri

> cancers (1993-97 from Cancer Incidence in Five Continents) with

food intake (1961-97

> from FAOSTAT) in 40 countries. Meat was most closely correlated

with the breast

> cancer incidence (r=0.827), followed by milk (0.817) and cheese

(0.751). Stepwise

> multiple-regression analysis (SMRA) identified meat as the factor

contributing most

> greatly to the incidence of breast cancer ([R]=0.862). Milk was

most closely

> correlated with the incidence of ovarian cancer (r=0.779), followed

by animal fats

> (0.717) and cheese (0.697). SMRA revealed that milk plus cheese

make the greatest

> contribution to the incidence of ovarian cancer ([R]=0.767). Milk

was most closely

> correlated with corpus uteri cancer (r=0.814), followed by cheese

(0.787). SMRA

> revealed that milk plus cheese make the most significant

contribution to the

> incidence of corpus uteri cancer ([R]=0.861). In conclusion,

increased consumption

> of animal-derived food may have adverse effects on the development

of

> hormone-dependent cancers. Among dietary risk factors, we are most

concerned with

> milk and dairy products, because the milk we drink today is

produced from pregnant

> cows, in which estrogen and progesterone levels are markedly

elevated.

> PMID: 16125328

>

> … Table 1. Correlation coefficients between female cancer incidence

rates (1993–97)

> and food consumption (average values during 1961–97)

> .................................

> Correlation coefficient

> Breast Ovary Corpus uteri

> ..................................

> Animal fats 0.650‡‡ 0.717‡‡ 0.713‡‡

> Butter 0.584‡‡ 0.576‡‡ 0.543‡‡

> Cheese 0.751‡‡ 0.697‡‡ 0.787‡‡

> Eggs 0.660‡‡ 0.589‡‡ 0.703‡‡

> Meat 0.827‡‡ 0.575‡‡ 0.782‡‡

> Fish 0.055 0.226 0.115

> Milk 0.817‡‡ 0.779‡‡ 0.814‡‡

> Cereals & #8722;0.467‡‡ & #8722;0.520‡‡ & #8722;0.422‡‡

> Pulses & #8722;0.438‡‡ & #8722;0.465‡‡ & #8722;0.437‡‡

> Fruits 0.297 0.357‡ 0.297

> Vegetables 0.222 0.068 0.211

> Vegetable oils 0.515‡‡ 0.396‡ 0.580‡‡

> Alcohol 0.517‡‡ 0.399‡ 0.497‡‡

> Coffee 0.537‡‡ 0.621‡‡ 0.626‡‡

> Tea 0.322‡ 0.045 0.126

> ......................................

> ‡ p < 0.05.

> ‡‡ p < 0.01.

>

> … Table 2. Stepwise-multiple-regression analysis (forward) on the

consumption of

> selected food items (independent variablesa) affecting

incidence/mortality rates of

> female cancers (dependent variables)

> .....................................

> Coefficient Standard error R2b F-to-remove

> .....................................

> Breast cancer incidence vs. 11 independent variables (1961–1998)

> Meat 0.251 0.025 0.862 13.724

> Breast cancer mortality vs. 11 independent variables (1961–1998)

> Milk and cheese 0.022 0.003 0.814 68.527

> Ovary cancer incidence vs. 11 independent variables (1961–1998)

> Milk and cheese 0.009 0.001 0.767 48.619

> Ovary cancer mortality vs. 11 independent variables (1961–1998)

> Fats and butter 0.059 0.008 0.796 60.416

> Corpus uteri cancer incidence vs. 11 independent variables (1961–

1998)

> Milk and cheese 0.014 0.003 0.861 72.242

> Corpus uteri cancer mortality vs. 11 independent variables (1961–

1998)

> Milk and cheese 0.001 0.001 0.517 12.746

> ..........................................

> a Fats and butter, meat, eggs, milk and cheese, cereals, pulses,

fruits, vegetables,

> vegetable oils, coffee, and alcohol were used as the independent

variables.

> b R, standardized regression coefficient.

>

> … Table 3. Correlation coefficients between female cancer mortality

rates (2000) and

> food consumption (average values during 1961–97)

> ..........................................

> Correlation coefficient

> Breast Ovary Corpus uteri

> ..........................................

> Animal fats 0.670‡‡ 0.818‡‡ 0.403‡‡

> Butter 0.595‡‡ 0.651‡‡ 0.330‡

> Cheese 0.725‡‡ 0.731‡‡ 0.406‡‡

> Eggs 0.615‡‡ 0.655‡‡ 0.223

> Meat 0.517‡‡ 0.600‡‡ 0.434‡‡

> Fish 0.110 0.047 & #8722;0.140

> Milk 0.536‡‡ 0.790‡‡ 0.545‡‡

> Cereals & #8722;0.401‡ & #8722;0.391‡‡ & #8722;0.384‡

> Pulses & #8722;0.395‡ & #8722;0.367‡ & #8722;0.345‡

> Fruits 0.292 0.246‡ 0.381‡

> Vegetables 0.189 0.185 & #8722;0.036

> Vegetable oils 0.435‡‡ 0.372‡ 0.339‡

> Alcohol 0.463‡‡ 0.491‡‡ 0.249

> Coffee 0.547‡‡ 0.569‡‡ 0.349‡

> Tea 0.316‡ 0.186 0.256

> .......................................

> ‡ p < 0.05.

> ‡‡ p < 0.01.

>

> … [45] Prospective study of diet and ovarian cancer.

> Am J Epidemiol. 1999 Jan 1;149(1):21-31.

> PMID: 9883790

>

> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?

cmd=Retrieve & db=pubmed & dopt=Abstract & list_uids=9883790 & query_hl=34Kush

i

> LH, Mink PJ, Folsom AR, KE, Zheng W, Lazovich D, Sellers

TA. Related

> Articles, Links

>

> ... [51] Larsson SC, Bergkvist L, Wolk A.

> Milk and lactose intakes and ovarian cancer risk in the Swedish

Mammography Cohort.

> Am J Clin Nutr. 2004 Nov;80(5):1353-7.

> PMID: 15531686

>

> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?

cmd=Retrieve & db=pubmed & dopt=Abstract & list_uids=15531686 & query_hl=32

>

> ... TABLE 2 Invasive epithelial ovarian cancer according to

consumption of dairy

> products1

> ......................................

> Intake All invasive epithelial tumors Serous epithelial tumors

Other epithelial

> tumors2

> No. of cases RR (95% CI) No. of cases RR (95% CI) No. of

cases RR (95% CI)

> .......................................

> Total dairy (servings/d)3

> <2 61 1.0 24 1.0 37 1.0

> 2 to <3 71 1.2 (0.9, 1.7) 37 1.6 (0.9, 2.7) 34 1.0 (0.6, 1.6)

> 3 to <4 65 1.4 (0.9, 2.0) 30 1.6 (0.9, 2.9) 35 1.2 (0.7, 2.0)

> 4 69 1.6 (1.1, 2.5) 34 2.0 (1.1, 3.7) 35 1.4 (0.8, 2.4)

> P for trend4 0.02 0.06 0.15

> Total milk (servings/d)5

> Never or seldom (1 serving wk) 55 1.0 18 1.0 37 1.0

> 1 54 1.2 (0.9, 1.8) 22 1.5 (0.8, 2.9) 32 1.1 (0.7, 1.8)

> 1.1 to <2 86 1.2 (0.9, 1.8) 49 2.1 (1.2, 3.7) 37 0.8 (0.5, 1.3)

> 2 71 1.3 (0.9, 1.9) 36 2.0 (1.1, 3.7) 35 1.0 (0.6, 1.6)

> P for trend4 0.27 0.04 0.70

> Total yogurt (servings/d)5

> Never or seldom (<1 serving wk) 118 1.0 48 1.0 70 1.0

> <1 66 1.0 (0.7, 1.3) 36 1.3 (0.8, 2.0) 30 0.7 (0.5, 1.1)

> 1 82 1.1 (0.8, 1.5) 41 1.4 (0.9, 2.2) 41 0.9 (0.6, 1.4)

> P for trend3 0.42 0.11 0.76

> Cheese (servings/d)5

> <1 81 1.0 36 1.0 45 1.0

> 1 to <2 107 0.9 (0.7, 1.3) 55 1.0 (0.7, 1.6) 52 0.9 (0.6, 1.3)

> 2 78 1.2 (0.9, 1.7) 34 1.1 (0.7, 1.9) 44 1.3 (0.8, 2.1)

> P for trend4 0.17 0.69 0.15

> ....................................................................

...

> 1 Multivariate rate ratios (RRs) were adjusted for age (in 5-y

categories), BMI

> (kg/m2; in quartiles), education level (ie, less than high school,

high school, and

> college), parity (ie, nulliparous, 1–2, and 3 children), oral

contraceptive use

> (ever or never), and quartiles of fruit, vegetable, and total

energy intakes.

> 2 Includes 48 endometrioid tumors, 21 mucinous tumors, 5 clear cell

tumors, and 67

> undifferentiated tumors or tumors of unknown histologic subtypes.

> 3 Total dairy products included total milk (low-fat, medium-fat,

and whole milk),

> total yogurt (low-fat and regular yogurt), cheese, and ice cream.

> 4 Two-sided P values for trend were calculated with the Wald

statistic by using the

> median values for each category.

> 5 Total milk, total yogurt, and cheese were mutually adjusted.

>

> ... Lactose intake showed a linear positive association with the

risk of serous

> ovarian cancer (P for trend = 0.006; Figure 1). The average lactose

intake in the

> cohort was 12.2 ± 7.8 g/d; milk was the major source. Relative to

women with a

> lactose intake of 15 g/d (corresponding to the amount of lactose in

1–2 glasses of

> milk), those with an intake of <2.5 g/d (the amount of lactose in

50 g milk, ie, 3–4

> tablespoons, corresponding to the amount usually added to 1–2 cups

of coffee or tea)

> were less than half (0.4; 95% CI: 0.1, 0.9) as likely to develop

serous ovarian

> cancer. When lactose was analyzed as a continuous variable, each 10

g/d increase in

> lactose intake (the amount of lactose in 1 glass milk) was

associated with a 20%

> greater risk of serous ovarian cancer (multivariate RR: 1.2; 95%

CI: 1.0, 1.5). The

> corresponding RRs for total ovarian cancer and nonserous tumors was

1.1 (95% CI:

> 0.9, 1.3) and 1.0 (95% CI: 0.8, 1.2), respectively.

>

> When we included intakes of lactose and milk simultaneously in the

multivariate

> model (Pearson's correlation coefficient: r = 0.65), the observed

positive

> association between total milk consumption and the risk of serous

ovarian cancer was

> mostly confined to lactose intake because the relative risk for

each 1 glass/d

> increment in total milk consumption decreased from 1.2 (95% CI:

1.0, 1.4) to 1.0

> (95% CI: 0.8, 1.3), whereas the relative risk for increments of

lactose intake was

> essentially unaltered (RR for each 10 g/d increment: 1.2; 95% CI:

0.9, 1.6).

>

> ...

>

> Al Pater, PhD; email: old542000@y...

>

> __________________________________________________

>

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Re: [ ] Re: Milk female hormones > female cancer?

Hi JW:

Funny you should send this to me today. I have been thinking the past couple of days that I should post asking for people's thoughts about how to boost immune system effectiveness.

My contribution would be to suggest drinking tea which, as I posted some months ago, appears to boost one aspect of immune response by an astonishing factor of five!!!

But what else can we do to get greater benefits beyond those of CR? The following extract from the article you sent me seems like it might be especially enlightening?

"This article reviews techniques for reversing immune senescence and improving immune responses, including immune reconstitution, restoration of thymus function, vaccination in the elderly, intravenous immunoglobulin, nutritional interventions, and vitamin supplementation, as well as other lifestyle changes that may restore immune function."

Is there any chance we could get a copy of that full article? (Salvador, , Ershler, Ershler.)

From reading what you sent it is clear that immunity is a very complicated and not-well-understood topic. But if we could find a source listing practical, 'proven', interventions to improve immunity, that each of us can apply to our lives, it would help a lot to plug a hole in our plans to live to 120. Pneumonia is perhaps the most obvious immunity issue - how many of the people who die from pneumonia might have lived ten or more years longer had they been able to fight it off and survive?

Rodney.jwwright <jwwright@...> wrote:

The only problem I have with generalizations is, eg, IL-6 which I'm looking at now, if too low causes you to accumulate fat, if too high promotes CVD.

Another hormone, amongst 100's that we don't know well enough.

If we knew we were short IL-6 would we ingest it or inject it? Better not do either because it's probably just responding to the system, which is somehow changed.

It wasn't changed by what we eat, IMO. At least not foods, maybe additives.

I'd vote for immune senescence, for want of a better reason.complex issue of age-related tumors resulting from a decreased immune response is not supported in the literature as clearly as commonly thought. Combined studies of cancer incidence and immune risk phenotypes may resolve these controversies.

Drs Salvador, , Ershler, and Ershler elegantly review several changes that occur in the immune system with age, including increased risk of infection (eg, influenza, Herpes zoster, HIV) and cancer. This article reviews techniques for reversing immune senescence and improving immune responses, including immune reconstitution, restoration of thymus function, vaccination in the elderly, intravenous immunoglobulin, nutritional interventions, and vitamin supplementation, as well as other lifestyle changes that may restore immune function and enhance health in the elderly.

Click here to donate to the Hurricane Katrina relief effort.

[Guest guest]

http://intapp.medscape.com/px/medlineapp/getdoc?ord=16 & searchid=1 & have_local_holdings_file=1 & local_journals_only=0 & searchstring=immunity

Re: [ ] Re: Milk female hormones > female cancer?

Hi JW:

Funny you should send this to me today. I have been thinking the past couple of days that I should post asking for people's thoughts about how to boost immune system effectiveness.

My contribution would be to suggest drinking tea which, as I posted some months ago, appears to boost one aspect of immune response by an astonishing factor of five!!!

But what else can we do to get greater benefits beyond those of CR? The following extract from the article you sent me seems like it might be especially enlightening?

"This article reviews techniques for reversing immune senescence and improving immune responses, including immune reconstitution, restoration of thymus function, vaccination in the elderly, intravenous immunoglobulin, nutritional interventions, and vitamin supplementation, as well as other lifestyle changes that may restore immune function."

Is there any chance we could get a copy of that full article? (Salvador, , Ershler, Ershler.)

From reading what you sent it is clear that immunity is a very complicated and not-well-understood topic. But if we could find a source listing practical, 'proven', interventions to improve immunity, that each of us can apply to our lives, it would help a lot to plug a hole in our plans to live to 120. Pneumonia is perhaps the most obvious immunity issue - how many of the people who die from pneumonia might have lived ten or more years longer had they been able to fight it off and survive?

Rodney.jwwright <jwwright@...> wrote:

The only problem I have with generalizations is, eg, IL-6 which I'm looking at now, if too low causes you to accumulate fat, if too high promotes CVD.

Another hormone, amongst 100's that we don't know well enough.

If we knew we were short IL-6 would we ingest it or inject it? Better not do either because it's probably just responding to the system, which is somehow changed.

It wasn't changed by what we eat, IMO. At least not foods, maybe additives.

I'd vote for immune senescence, for want of a better reason.complex issue of age-related tumors resulting from a decreased immune response is not supported in the literature as clearly as commonly thought. Combined studies of cancer incidence and immune risk phenotypes may resolve these controversies.

Drs Salvador, , Ershler, and Ershler elegantly review several changes that occur in the immune system with age, including increased risk of infection (eg, influenza, Herpes zoster, HIV) and cancer. This article reviews techniques for reversing immune senescence and improving immune responses, including immune reconstitution, restoration of thymus function, vaccination in the elderly, intravenous immunoglobulin, nutritional interventions, and vitamin supplementation, as well as other lifestyle changes that may restore immune function and enhance health in the elderly.

Click here to donate to the Hurricane Katrina relief effort.