The Effect of Fruit and Vegetable Consumption on Cancer Incidence [1.0]

8/13/2019 The Effect of Fruit and Vegetable Consumption on Cancer Incidence [1.0]

1/30

The Effect of Fruit and Vegetable Consumption on Cancer Incidence:

A Critical Approach to How the Scientific Knowledge Health

!ecommendations and the "ublic "olic# Interact to Con$ert Efficientl#

Knowledge into Social %ains

&os' (a#o)n Santiago Calder*n +,-

Southwestern .ni$ersit#

Fall /0,1 Econometrics


2/30

Santiago Calder*n &os' (a#o)n

Let food be thy medicine and medicine be thy food

Hippocrates

,2 Introduction

The purpose of this stud# is to e$aluate the interaction among the scientific base

recommendations and public polic# in the conte3t of fruits and $egetables consumption on

cancer incidence rates2 Cancer is one of the leading causes of death in the world and the second

leading one in the .nites States2 There are man# pla#ers in the multifaceted struggle to fight this

pandemic2 The scientific communit# medical professionals the pertinent industr# non4

go$ernmental and the State ha$e all been coordinating and de$eloping wa#s to efficientl#

promote the public health and minimi5e the effects of the disease2 In order to do so the# interact

in se$eral wa#s2 6an# of these are based on the scientific understanding: to understand the

nature of the disease wa#s to pre$ent it and wa#s to treat it2 Through this process the scientific

base is con$erted into health recommendations and procedures emplo#ed b# medical

professionals and in turn con$e#ed to the general public b# institutions associations guilds and

agencies2 At this stage the message is redacted into a simpler form such that it can be understood

b# the general public and eas# to communicate2 7astl# public polic# is designed to achie$e set

goals that measure compliance of the recommendations in the public agenda2

This model is toda# more rele$ant than e$er2 In the absence of definite cures and

treatments still with man# limitations pre$ention and alternati$es ha$e been the focus related to

this epidemic2 The scientific understanding in this instance has concluded that the bul8 of the

reasons of wh# cancer de$elops is mostl# contained in e3ogenous factors such as en$ironmental

/


3/30


and beha$ioral concerns rather than more so in genetics2 9ue to this conclusion the

recommendations and public polic# ha$e been dri$en b# the understood ris8 factors of the

condition2 These recommendations comprise dietar# and lifest#le choices2 ut of the dietar#

concerns fruits and $egetables consumption is one widel# accepted and often pursued b# the

public agenda2

;hile there is a solid reasoning at the chemical le$el the effect of fruits and $egetables

consumption on cancer incidence has not been as well established empiricall#2 ;hile there is no


4/30


(eha$ioral !is8 Factor Sur$eillance S#stem b# the Center for 9isease Control2 The regression

used data computed for reported cancer incidence rate and the fruits and $egetables consumption

from the food fre?uenc# ?uestionnaire2 6# control $ariables include the ris8 factors measured b#

the national sur$e# and non4genetic demographic characteristics from the census2

The results pro$ided a significant coefficient for the $ariable of interest @p4$alue

0200/B2 Howe$er the sign of the coefficient suggested the counter intuiti$e result indicating that

the lower the percentage of people who compl# with the recommendation of consuming D or

more rations of fruits and $egetables the higher the predicted cancer incidence rate for the

population2

I concluded that the current polic# and recommendations are incorrectl# e3trapolated

from the underl#ing scientific understanding and cannot predict or be used as tools to achie$e the

desired effect under the established paradigm2 There is a need to harmoni5e our polic# ma8ing

tools with the conclusions actuall# deri$ed from the empirical e$idence rather than wor8ing with

the general recommendation2 7astl# I anal#5e how to impro$e the d#namic among the scientific

base recommendations and public polic# to address these issues and establish better general

recommendations and policies2

/2 7iterature !e$iew

6alignant neoplasm,cancer is the second leading cause of death in the .nited States

@Center for 9isease Control /0,1B2 6alignant neoplasm refers to an# new and abnormal growth

specificall# one in which cell multiplication is uncontrolled and progressi$e2 The four most

, 9efined b# the ;orld Health rgani5ation as the rapid creation of abnormal cells that grow be#ond their usualboundaries2 @http:www2who2intcancerenB

-
http://www.who.int/cancer/en/http://www.who.int/cancer/en/


5/30


prominent cancers nowada#s are: prostate @malesB breast @femalesB lung bronchus and colon

rectum with se3 dependent cancers leading in cancer incidence while lung bronchus cancer

leads in mortalit# rates for both se3es/2 According to the annual publication b# the American

Cancer Societ# @/0,1B the ris8 factors $ar# across t#pe of cancer but some are pre$alent across

$irtuall# all of them2 These ris8 factors are: age obesit# ph#sical acti$it# consumption of red

meats consumption of fruit and $egetables smo8ing diabetes sunlight e3posure tobacco and

certain 8inds of conditions or infections that wea8ens the immune s#stem such as the emotional

state @high stress shoc8s traumas etcB2

The current medical understanding is that about ,0G of all cancers are probabl# due to

genetics1while 0G are due to en$ironmental factors related beha$ior or lifest#le choices2 nl#

about DG of cancers ma# be strongl# hereditar# @IbidB2 This is the reason wh# the field has

e$ol$ed toward anal#5ing the beha$ior ris8 factors for this chronic epidemic2 The most common

cancers are strongl# associated to aging2 As conse?uence de$eloped countries with longer life4

spans t#picall# ha$e higher cancer rates than countries where the lifespan is comparati$el#

shorter2 Furthermore the older the population the higher the cancer incidence2 Howe$er it is

important to notice that in the wealth# de$eloped world the sur$i$al rate for cancer is

substantiall# higher than in those less economicall# prosperous -2Sur$i$al rates are much higher

in wealth# de$eloped countries not onl# because treatment might be more accessible but

because cancer treatment is regarded as a lu3ur# goodD2

/ American Cancer Societ#


6/30


The .nited Kingdom is one of the countries who has studied cancer with an economic

approach most profoundl# in part due to the Jational Healthcare S#stem>2 !esearch and polic#

on cancer in the .nited States is generall# thought to ha$e started with "resident !ichard Ji3on+s

declaration of war on cancer during the State of the .nion of ,,2 At this moment the Jational

Cancer Act was signed into law2 The bill outlines the battle plan with a combination of different

measures among them research for a cancer cure2

Jutrition and medical research has been disco$ering new wa#s to fight cancer through

a better understanding of cancer biolog#2 Some e3amples include: the role of sugar as the The Jational Health Ser$ice @JHSB is the publicl# funded healthcare s#stem for England2 It is the largest andthe oldest single4pa#er healthcare s#stem in the world2

It was e3pected to find a cure for cancer within fi$e #ears2L These conclusions are widel# accepted in the field and are part of the .S F9A polic# recommendations2

>


7/30


smaller and borderline significant reduction in CH9 ris82

Similar studies such as


8/30


a function of !9 in$estment and from the patientsN $iew in terms of longer life e3pectanc#2

The results support the idea of cancer treatment being a lu3ur# good2 This idea has been

supported b# $arious other publications such as B these implications are the basis for the polic# regarding patents

for cancer treatment and medicines a great deal of contemporar# polic# regarding the cancer

epidemic2

ther researchers focus on the health recommendations for fighting illnesses2


9/30


diabetes patients2 .sing the formula .@h wB O hPu@wB where h represents health w wealth and

u@wB the standard utilit# of wealth the stud# found that the .@hwB O hPlog@awB was the line of

best fit for both samples suffering the different conditions2 The findings are consistent with

pre$ious studies that claim that as health deteriorates the more willingness there is to trade

wealth for health2

presents a time stud# of the relation between education and $arious factors of ris8 @Cutler et2 al2

/0,,B2 The methodolog# of both studies was a part of the construction of the one used in this

paper further e3plained in the methodolog# section2 I obser$ed a mar8ed tendenc# in the

literature for including dietar# concerns to e3plain the ris8 of suffering common diseases or

conditions that are epidemic in our societ#2 In other words diet is understood to be the most

rele$ant factor in the research the health recommendations and the public polic#2

The literature on dietar# choices co$ers multiple dimensions2 Some aspects are:

accessibilit# beha$ior modeling determination factors effect of its consumption etc2


10/30


Some policies aim to create an en$ironment that promotes good li$ing practices2 ne

wa# it has been traditionall# studied are food desserts,/and fast food saturated communities,12

B studies the

presence of food desserts and how the absence of health# food options or restricti$e prices affect

low income groups2 (# stud#ing the different mar8ets in terms of a$ailabilit# and prices the

stud# concluded that the lac8 of small grocer# stores located in low income neighborhoods and

higher costs for health# food bas8ets ma# be deterrents to eating healthier among $er# low

income consumers2

According to the publication


11/30


polic# and health recommendations that the consumption of at least fi$e rations of fruit and

$egetables b# the public would lower the cancer incidence rate obser$ed in the population when

controlling for the calculated ris8 factors2

12 9ata 9escription

The outcome $ariable measures the cancer incidence rate: new cases of cancer per

capita per #ear o$er fi$e #ear inter$als,2 This particular data in the stud# uses the /00>4/0,0

time period2 The t#pes of cancers for calculating new cases of cancer account for all cancer sites

e3cept for bladder cancer2 The incidence rates are age4adMusted to the /000 .S standard

population @, age groups: , ,4- D4 Q L04L- LDRB2 !ates calculated using SEE!PStat,L2

The population data used came from the Census (ureau the ,>4/0,, .S "opulation 9ata File

is used for SEE! and J"C!,incidence rates2

The independent $ariable of Few Fruit and Vegetables is defined as the percentage of

adults reporting an a$erage fruit and $egetable consumption of less than D ser$ings per da#2 In

other words the population percentage who do not abide b# the recommended practice2 This

percentage is calculated b# data collected through the (eha$ioral !is8 Factor Sur$eillance

S#stem @(!FSSB sur$e#2 The data is at the count# le$el and was accessed through the

Communit# Health Status Indicators @CHSIB /00L4/0,1 annual reports2

The control $ariables of the regression were: obesit# ph#sical inacti$it# mental health

smo8ing drin8ing diabetes income and age2 besit# was calculated b# the percentage obese /0

, Standard practice in epidemiolog# and per capita based of ,00000 people2,L The Sur$eillance Epidemiolog# and End !esults @SEE!B "rogram of the Jational Cancer Institute wor8s to

pro$ide information on cancer statistics2, Jational "rogram of Cancer !egistries @J"C!B/0 A calculated (6I greater than 102

,,


12/30


adults in the population2 "h#sical inacti$it# was defined b# the percent of adults that reported no

leisure time ph#sical acti$it# in the past 10 da#s2 9iabetes reflected the percentage of adults

diagnosed with diabetes2 The data for these two $ariables were pro$ided b# the Jational Center

for Chronic 9isease "re$ention and Health "romotion 9i$ision of 9iabetes Translation2

6ental health was described b# the a$erage number of poor mental health da#s in past

10 da#s2 This $ariable onl# pro$ided data if at least D0 respondents answered the sur$e# per

count#2 Smo8ing habits was included in the regression as the percentage of adults that smo8ed

tobacco products2 The drin8ing $ariable was defined as the percentage of adults who reported

hea$# drin8ing/,2 The data for these $ariables was collected from the (eha$ioral !is8 Factor

Sur$eillance S#stem @/00-4/0,0B2

The demographic age $ariable was the percentage of the population with o$er si3t#4

fi$e #ears old accordingl# to the .S Census (ureau in the #ear /002 6edian household income

was measured in .S9 and the data was from the Small Area Income and "o$ert# Estimates

@/0,,B2 7astl# the data set used three I9 $ariables: FI"S State and Count#2 These pro$ided the

name of the count# the state where the count# was located and the Federal Information

"rocessing Standards Code for the count#2

The data sets and sur$e#s primaril# used for the data collection were the (eha$ioral

!is8 Factor Sur$eillance S#stem @(!FSSB the Communit# Health Status Indicators !eport The

Count# Health !an8ings !oadmaps and the State Cancer "rofile2 The (eha$ioral !is8 Factor

Sur$eillance S#stem @(!FSSB is a state4based s#stem of health sur$e#s that collects information

on health ris8 beha$iors pre$enti$e health practices and health care access primaril# related to

/, Hea$# drin8ing defined as: if male two or more dail# drin8s and if female one or more drin8s per da#2

,/


13/30


chronic disease and inMur# @Healthdata2go$B2 The Communit# Health Status Indicators !eport is a

collection of nationall# a$ailable indicators for counties representing se$eral areas of

responsibilit# for public health2 It is the product of the Communit# Health Status Indicators

@CHSIB "roMect a public4pri$ate collaboration of organi5ations committed to national support for

local action to impro$e public health @/00B2 The Count# Health !an8ings !oadmaps program

is a collaboration between the !obert ;ood &ohnson Foundation and the .ni$ersit# of ;isconsin

"opulation Health Institute @www2count#healthran8ings2org AboutB2 The Jational Cancer

Institute @JCIB is part of the Jational Institutes of Health @JIHB which is one of ,, agencies that

compose the 9epartment of Health and Human Ser$ices @HHSB2 The State Cancer "rofile is an

interacti$e data and statistical tool offered at their website2

The obser$ations used for the regression comprise all the counties in the .nited States

for which data for all the selected $ariable was a$ailable in the data sets used2 These accounted

for ,>11 counties out of the total 1,-, counties in the .nited States2 The counties obser$ed come

from across all states and ;ashington 92C2 e3cept for the following: Alas8a Kansas 6innesota

hio and Virginia2

Those states did not ha$e the outcome $ariable data a$ailable2 In order to protect the

research from bias b# ha$ing selected a non representati$e sample of the population I ran a

summar# of statistics on basis of the outcome $ariable being a$ailable or not @Figures D >B2

There were no alarming disparit# among the two summar# statistic present indicating that the

obser$ations in the selection of the data seems to be random and should not bias the results2

The regression included one outcome $ariable one $ariable of interest and eight

,1
http://www.countyhealthrankings.org/http://www.countyhealthrankings.org/http://www.countyhealthrankings.org/


14/30


control $ariables2 9ue to the nature of the $ariable of interest as well as the control $ariables the

data was compiled b# ?uestionnaires2 The data selections rests on the belief that the (!FSS is

the most comprehensi$e and solid national sur$e# for these $ariables2 For an o$er$iew of the

$ariables names definitions sources and co$erage refer to @figure ,B2

Form the summar# statistics @refer to figure /B we can see the profile of the aggregated

counties2 (ased of the mean for the $ariables the a$erage count# could be described as

following: a cancer incidence rate of -D, about ,D of the population does compl# with the

recommendation about , out of ,0 people suffers diabetes about ,DG of the population is >D

#ears old or older the median income is around -1000 , out of D people is a smo8er about /

out of does not e3ercise ,DG are hea$# drin8ers ,1 of the population is obese and in general

people suffer around 1 da#s of poor mental health monthl#2 This statistics somewhat fit within

the national statistics2 For e3ample in the case of the compliance with the recommendation of

FV consumption it has been historicall# low and nationall# less than ,12 Furthermore the

highest le$el of compliance with the recommendation obser$ed did not e3ceed the /D

meanwhile the lowest le$el of compliance obser$ed was 12DG2

Some interesting results can be obser$ed from the co$ariance table @refer to figure 1B2

From the co$ariance summar# it can be seen a strong relation among ris8 factors such as obesit#

diabetes smo8ing poor mental health and ph#sical inacti$it#2 Furthermore the $ariable of

interest is positi$el# correlated to the almost all ris8 factors controlled for2 It has a negati$e

correlation with income which is to be e3pected the higher #our income the more li8el# #ou can

afford and might choose to consume fruits and $egetables2 Drinkacts different than the other

,-


15/30


$ariables but is not surprising since it onl# measures e3treme consumption of alcohol2 For the

most part the relations seem to be consistent with what it would be e3pected e3cept for one

instance2 The $ariable of interest is negati$el# correlated with the outcome $ariables2 This hints

to if significant the higher the proportion of people who do not eat as man# fruit and $egetables

the lower the cancer incidence rate foreshadowing counter intuiti$e results2

-2 6ethodolog#

I test whether it is correct to generali5e the scientific 8nowledge some fruits and

$egetables are lin8ed to diminish the probabilit# of certain t#pes of cancer into a broad health

recommendation dail# inta8e of fruit and $egetable of at least D rations2 Furthermore base the

public polic# on compliance of that recommendation as a wa# to predict or foster the

achie$ement of the ultimate goal2 For this purpose I will use cross section data // for a linear

regression/1with the following e?uation:

# O 0R ,a R /b R 1c R -d R De R >f R g R Lh R i R ,0M R U Q where

#:O outcome $ariable cancer incidence rate

0:O intercept

a:O percentage of adults who do not follow the recommendation of a consumption le$el of at

least D dail# rations of fruit and $egetables

b:O percentage of adults diagnosed with diabetes

c:O percentage of adults who are smo8ers of tobacco products

d:O percentage of adults who are ph#sicall# inacti$e

// Time series data would show $er# small $ariation on our interest $ariable since the $alue are historical2 (ecauseof this cross section data was determined to be the optimal choice2

/1 Jo reason or concerns rose up to challenge the assumption that the relation was not linear in nature2

,D


16/30


e:O percentage of adults who reported hea$# drin8ing

f:O a$erage da#s of poor mental health per month

g:O percentage of smo8ers

h:O percentage of adults o$er >D #ears old

i:O percentage of adults obese

M:O median income in

The construction of this regression e?uation too8 into account the obMecti$e of this

stud# and the surrounding scientific understanding2 In other words this regression uses the

$ariables in the industr# standards measures uses the data collection methods that public polic#

ma8er would ha$e access and would use to measure the le$el of compliance and controls for the

current understood factors of ris8 measured within the statistic s#stem in place to address the

issue2 This means that this regression does not tr# to unco$er the underl#ing effect of fruits and

$egetables consumption on cancer incidence rate but to test whether if under the established

framewor8 a higher compliance would predict the desired effect or not2 The control $ariables are

those measured in the reports and understood as cancer ris8 e3cluding those genetic @race

gender etc2B since the polic# and recommendation assume their role in predicting cancer is not

significant/-in general for all cancer sites2

The scientific base has produced numerous stud#ing affirming the probabilit# that

certain fruits and $egetables reduce the ris8 of certain cancers2 ;hile on the scientific

communit# and man# health professionals close to the research can interpret the results into

effecti$e medical ad$ice the public has limited capacities to do so on their own2 Health

/- It is accepted that around 0G of cancer is due to en$ironmental factors and not genetics2

,>


17/30


recommendations are then redacted in a more uni$ersal language so that the public might

understand and commit to such practices2

6ost of the research is done in $itro e3periments while others are done in $i$o

@mainl# in ratsB2 !esearch with humans has guided the medical field into obser$ing certain fruits

for e3ample berries to ha$e an impact in decreasing the probabilit# of de$eloping certain t#pes

of cancer2 It is mostl# for this reason that the go$ernment agencies institutions and professional

guilds ma8e the less specific and more general recommendation of consuming fruits for cancer

pre$ention2 This recommendation is generall# in the form of eating at least D rations of fruits and

$egetables per da#2 nce again the public polic# wor8s to use the recommendation and promote

their implementation2

Following these assumptions I then choose as the $ariable of interest as the same

measurement described b# the health recommendation2 For this stud# I will focus on the claim

that this practice reduces the incidence of cancer2 This approach differs from the classical trial

e3periments as I am not testing the effect of consumption of fruit and $egetables on cancer

incidence but the compliance of the recommendation and its relation to the desired outcome

within the recommendation+s framewor82

In order to control for other factors I will include the accepted ris8 factors of cancer2

From the literature I obser$ed that most cancer t#pes are not geneticall# determined but on the

contrar# for the most part there are a function of en$ironmental factors2 The en$ironmental

factors are then di$ided into choice beha$ior and those who are outside our power2 9ue to the

nature of the disease I account for $ariable of age: those o$er >D #ears old are considered high

,


18/30


ris8 population as cancer is a general age associated disease2 Since tumors grow when the

immune s#stem is hampered I account for $ariables that are lin8ed to wea8ened immune

s#stems namel# poor mental health da#s @stress depression etcB2

An indispensable $ariable to control for is the use of tobacco products and so I include

the percentage of the population who are smo8ers2 For the same reasons I include drin8ing

which is 8nown to increase the ris8 for a $ariet# of t#pes of Cancer/D2 7i8ewise strong e$idence

has cataloged obesit# diabetes and ph#sical inacti$it# as factors of ris8 for man# t#pes of

cancers

/>

2 Ha$ing included the control $ariables I ma8e the 8e# assumptions that cancer is a

function of these accepted ris8 factors included and thus can belie$e that the 5ero conditional

mean assumption will hold2

Howe$er I will address omitted $ariable bias concerns in the following paragraphs2 I

belie$e that e$en to some e3pense other factors e3plain the outcome $ariable and are correlated

to the $ariable of interest such as: famil# histor# e3posure to en$ironmental agents @asbestos air

pollution trihalomethanes etcB second hand smo8ing Mob ha5ard @radiation chemical e3posure

etc2B hormone disorders other immune s#stem debilitating conditions @H"V Herpes Hepatitis

HIV etcB other dietar# choices @sugar fat meat processed food inta8eB etc2 Another concern is

the fre?uenc# and ?ualit# of cancer screening that might create data error in our $alues2 The

fre?uenc# and practice of regular cancer screenings among the different counties is probabl# not

without $ariation2

9ata error is bound to be present in the stud# since the data is ?uestionnaires based2

/D Ke# point of the Jational Cancer Institute2/> .nderl#ing science that supports it are the le$els of sugar in the blood and the state of the immune s#stem2

,L


19/30


Specific to this stud# it is well documented that Food Fre?uenc# uestionnaires @FFB


20/30


0200,B and considerable economic effect2 Income on the other hand showed the same le$el of

significance but with an economic effect of $irtuall# 5ero considering the mean of the outcome

$ariable2 7astl# ph#sical inacti$it# showed a considerable economic effect but with a coefficient

less significant @p4$alue 020,B2

"ondering on the possible e3planations for this result is 8e# in accuratel# assessing the

h#pothesis test2 The same drawbac8s that could potentiall# e3plain the sign of the coefficient

could $er# well be the factors that ma8e the public polic# and general recommendation fault#2

The stud# is not accounting for pesticides in fruit and $egetables man# of which are classified as

carcinogen2 Furthermore some studies suggest geneticall# modified products to pose health

concerns2 E$en more other concerns not well addressed in the framewor8 are: whether the

products are fresh or preser$ed in sugar pic8led or other mediums and how are the# prepared2

Eating a salad but drowning it in dressing will not bring the desired effect Must as for e3ample

eating deep fried $egetables2 Some of the most popular fruits are e3tremel# contaminated b#

pesticides in the effort to ma3imi5e their production due to their high demand in the mar8et2

7astl# the t#pe of fruits and $egetables are not being classified and lumped all together2 This is a

concern since the nutritional components of all fruit and $egetables are not the same2 The

pre$ious is an accepted drawbac8s of using FF as opposed to food diaries2

;hile these concerns would $iolate the 5ero mean condition in similar e3periments

since the obMecti$e of this research is to understand whether not controlling for these in the

recommendation affects the predicted outcome it is beneficial not to obser$e them2 This wa# we

are finding out how the le$el of compliance is affecting our outcome $ariable with the

/0


21/30


specifications surrounding the message to the public and the specifications of the

recommendation2

>2 Conclusion

I concluded that the interaction of the scientific base health recommendation and its

transition to public polic# is at least partiall# fault#2 "ublic polic# that focuses in an e3trapolated

recommendation e$en if once based in on empirical data ma# succeed at the compliance of the

recommendation but not necessar# achie$e the desired effect which was the moti$ation2

In more specific terms the recommendations that fruits and $egetables consumption

o$er D dail# ration is an e3trapolated conclusion2 The scientific understanding helps medical

professional educate and treat patients2 Howe$er e$en if well intentioned actors wish to promote

good health b# ma8ing claims e3trapolated from the research such as fruits and $egetables

consumption @implies an# fruits and $egetables and no restrictions on which or how to consume

themB to decrease cancer @impl#ing all t#pesB it does not necessaril# wor8 as intended2 The issue

is more se$ere when it is adopted as a public polic# and the le$el of compliance is used to predict

the outcome as the empirical e$idence showed incorrectl#2

This stud# b# no means discourages the consumption of fruits and $egetables or claims

that the finding hold under a different setting @other condition or certain t#pes of cancer etcB2 It

does howe$er ?uestions the current relationship among the scientific understanding

recommendations and policies2 ne parallel obser$ation is made in


22/30


ad$ocated b# man# national and international bodies no studies that we are aware of ha$e

e3plored associations between $ariet# in inta8e and ris8 of T/9=2

In order to harmoni5e and reconcile the scientific base with effecti$e recommendations

and public polic# there has to be more in social studies in order to transfer the technical into

tangible social e3perimentation2 E$en so there has to be a continuit# in studies that monitor how

the recommendations are well designed in order to be clearl# understood b# the public2 7astl#

there has to be a wa# to implement measure compliance and monitor the effect on the desired

outcome2 That wa# recommendations can be at the border of simplicit# but ne$er step outside of

what is supported b# the empirical e$idence2

If and onl# if this transition is reali5ed then we could accuratel# predict and foster

public health through education and programs efficientl#2 E$en so this does not affect current

policies uniforml#2 ;hile less than one third of the .nited States follows the recommendation

FV inta8e @see figure B achie$ing a higher percentage of people eating health# is a good

public polic#2 The problem arises for e3ample when based on assumptions one would e3pect

such change to ha$e a miscalculated effect on cancer incidence rate2

The good news is that all the scientific 8nowledge alread# a$ailable is Must waiting to

be properl# con$erted into effecti$e recommendations and public polic#2 It should be noted as

well that people are loo8ing for new wa#s to sta# health# and gi$en the opportunit# to learn

how to ta8e care of themsel$es it is $er# li8el# that the# will engage in healthier beha$ior and

enMo# a better happier and longer life2

//


23/30


2 7ist of !eferences

Alemanno A2 CarreWo I2 @/0,1B2 +Fat ta3es+ in Europe 4 A 7egal and "olic#

Anal#sis under E. and ;T 7aw2European Food & Feed Law Review 8@/B 4,,/2

Anand "2 %ra# A2 @/00B2 besit# as 6ar8et Failure: Could a X9eliberati$e

Econom#N $ercome the "roblems of "aternalismY2 Kyklo !"@/B ,L/4,02 doi:,02,,,,M2,->4

>-1D2/00200-1023

(e#doun 62 A2 "owell 72 62 ;ang Z2 @/00LB2 The association of fast food fruit

and $egetable prices with dietar# inta8es among .S adults: Is there modification b# famil#

incomeY2 #ocial #cience & $edicine !!@,,B //,L4///2

doi:,02,0,>M2socscimed2/00L20,20,L

Cash S2 (2 Sunding 92 72 [ilberman 92 @/00DB2 Fat ta3es and thin subsidies:

"rices diet and health outcomes2%cta %riculturae #candinavica' #ection () Food Economic

"@1-B ,>4,-2

Clar8e %2 E#re H2 %u# C2 @/00/B2 9eri$ing Indicators of Access to Food !etail

"ro$ision in (ritish Cities: Studies of Cardiff 7eeds and (radford2 *rban #tudie +Routlede,

-.@,,B /0-,4/0>02 doi:,02,0L000-/0L0//0000,,1D1

Cohen &ennifer H2 Kristal A2 !2 Stanford &2 72 @/000B2 Fruit and Vegetable Inta8es

and "rostate Cancer !is82/ournal of the 0ational (ancer 1ntitute Vol2 / Jo2 , &anuar# D

/0002 / @,B: >,4>L2 doi: ,02,01Mnci/2,2>,

Cooper A2 &2 4 riginal !esearch @/0,/B 4 Epidemiolog#Health Ser$ices !esearch:

Andrew &2 Cooper Stephen &2 Sharp 6arleen A2H2 7entMes !obert J2 7uben Ka#4Tee Khaw

/1


24/30


Jicholas &2 ;areham and Jita %2 Forouhi2 A "rospecti$e Stud# of the Association (etween

uantit# and Variet# of Fruit and Vegetable Inta8e and Incident T#pe / 9iabetes2 Diabete (are

&une /0,/ 1D:,/14,100 published ahead of print April 1 /0,/ doi:,02/11dc,,4/1LL

9ana %oldman 9arius 7a8dawalla and Zuhui [heng2 \Food "rices and the 9#namics

of (od# ;eight\ Economic Aspects of besit#2 Ed2 6ichael %rossman Jaci 6ocan2 Chicago:

.ni$ersit# of Chicago "ress /0,,2 >D402 A$ailable at:

http:wor8s2bepress2comdana]goldmanL

9owler E2 @/00LB2 Food and health ine?ualities: the challenge for sustaining Must

consumption2Local Environment 2-@LB D4/2 doi:,02,0L0,1D-L10L0/-L1>

Franc8 C2 %randi S2 62 Eisenberg 62 &2 @/0,1B2 Ta3ing &un8 Food to Counter

besit#2 %merican /ournal 3f 4ublic 5ealth 26-@,,B ,-4,D12

doi:,02/,0DA&"H2/0,1210,/

%riep 72 Verschuren ;2 Kromhout 92 c8' 62 %eleiMnse &2 @/0,,B2 !aw and

processed fruit and $egetable consumption and ,04#ear stro8e incidence in a population4based

cohort stud# in the Jetherlands2 European /ournal 3f (linical 0utrition !7@B ,42

doi:,02,01LeMcn2/0,,21>2

He Feng &2 Jowson C2 A2 6ac%regor %2 A2 @/00>B2 Fruit and $egetable consumption

and stro8e: meta4anal#sis of cohort studies he Lancet) 9olume -!:) 1ue .76:) "8 /anuary;-

February "66! "ages 1/041/> ISSJ 0,-04>1> http:d32doi2org,02,0,>S0,-04

>1>@0>B>L0>402

&ac?uier C2 (onthou3 F2 (aciu 62 !uffieu3 (2 @/0,/B2 Impro$ing the

/-
http://works.bepress.com/dana_goldman/78http://dx.doi.org/10.1016/S0140-6736(06)68069-0http://dx.doi.org/10.1016/S0140-6736(06)68069-0http://works.bepress.com/dana_goldman/78http://dx.doi.org/10.1016/S0140-6736(06)68069-0http://dx.doi.org/10.1016/S0140-6736(06)68069-0


25/30


effecti$eness of nutritional information policies: assessment of unconscious pleasure

mechanisms in$ol$ed in food4choice decisions2 0utrition Review :6@/B ,,L4,1,2

doi:,02,,,,M2,D14-LL2/0,,200--23

&etter K2 62 Cassad# 92 72 @/00>B2 The A$ailabilit# and Cost of Healthier Food

Alternati$es2%merican /ournal 3f 4reventive $edicine -6@,B 1L4--2

doi:,02,0,>M2amepre2/00D2020,>

Klein 6atthew &2 @/0,1B2 9iet and Health Capital: An American Case Stud#

.ndergraduate Economic !e$iew: Vol2 ,0: Iss2 , Article 12

7ee H2 @/0,/B2 The role of local food a$ailabilit# in e3plaining obesit# ris8 among

#oung school4aged children2 #ocial #cience & $edicine :M2socscimed2/0,,2,/201>

6atti &osh and Kim Hansol @/0,1B2 Factors E3plaining besit# in the 6idwest:

E$idence from 9ata .ndergraduate Economic !e$iew: Vol2 ,0: Iss2 , Article ,2 A$ailable at:

http:digitalcommons2iwu2eduuer$ol,0iss,,

"owell 72 62 Chaloup8a F2 &2 @/00B2 Food "rices and besit#: E$idence and

"olic# Implications for Ta3es and Subsidies2 $ilbank =uarterly 8:@,B //4/D2

doi:,02,,,,M2,->L40002/00200DD-23

Sharma S2 "a8serescht 62 Cruic8shan8 K2 %reen 92 62 Kolonel 72 J2 @/0,1B2

Adherence to the .S9A dietar# recommendations for fruit and $egetable inta8e and ris8 of fatal

stro8e among ethnic groups: a prospecti$e cohort stud#2 >$( 0euroloy 2-@,B ,4L2

doi:,02,,L>,-,4/14,14,/0

/D
http://digitalcommons.iwu.edu/uer/vol10/iss1/1http://digitalcommons.iwu.edu/uer/vol10/iss1/1


26/30


Von Tigerstrom (2 @/0,/B2 Ta3ing Sugar4Sweetened (e$erages For "ublic Health:

7egal And "olic# Issues in Canada2%lberta Law Review 76@,B 14>-2

;hite 62 @/00B2 Food access and obesit#2 3beity Review 84,02

doi:,02,,,,M2,->4L^2/002001/23

;rigle# J2 @/00/B2 XFood 9esertsN in (ritish Cities: "olic# Conte3t and !esearch

"riorities2 *rban #tudie +Routlede, -.@,,B /0/4/0-02 doi:,02,0L000-/0L0//0000,,1--

Zang [2 Hall A2 %2 @/00LB2 The Financial (urden of $erweight and besit#

among Elderl# Americans: The 9#namics of ;eight 7onge$it# and Health Care Cost2 5ealth

#ervice Reearch L2 doi:,02,,,,M2,-D4>12/00200L0,23

A$ailable at: http:digitalcommons2iwu2eduuer$ol,0iss,1

L2 Anne3

Figure ,

/>

Jame of Variable 9efinition Co$erage Source

Cancer]!ate Count# _ /00D4/0,0 State Cancer !egistr#

Few]Fruit]Veg Count# _ /0,0 (!FSS

9iabetes "ercentage of adults diagnosed with diabetes Count# _ /0,0 (!FSS

Age "ercentage of residents o$er the age of >D #ears Count# _ /00 .2S2 Census (ureau

Inc Household 6edian Income Count# _ /00

Smo8e "ercentage of adults that smo8e tobacco Count# _ /00/4/00L

"h#s]Inact "ercent of adults that report no leisure time ph#sical acti$it# in past 10 da#s Count# _ /00>4/00L

9rin8 "ercent of adults who report hea$# drin8ing Count# _ /00/4/00L

:bese "ercentage of adults with (6I of o$er 10 Count# _ /00>4/00L

6.9 Count# _ /00 (!FSS

]cons Intercept JA JA

Jew cases of cancer per capita per #ear o$er fi$e #ear for all t#pes ofcancers e3cept bladder

"ercentage of adults reporting an a$erage fruit and $egetable consumption of

less than D ser$ings per da#

SAI"E

(!FSS

(!FSS

(!FSS

(!FSS

A$erage number of poor mental health da#s in past 10 da#s
http://digitalcommons.iwu.edu/uer/vol10/iss1/3http://digitalcommons.iwu.edu/uer/vol10/iss1/3


27/30


Figure /

Figure 1

Figure -

/

Summary of Variables

Variable Obs Mean Std. Dev. Min Max

Cancer_Rate 268 !"#.$2%& "%.!2%$& #2&.# ##6!.2

'e(_'ruit_Ve) #%$! 8.%2 ".#6$%2& 6&.# %6.!

Diabetes !# #$.&8!"% 2.#6%%! & 2$

*)e !# #"."!!&2 !.28"!#" 2.% &6.2

+nc !$ !&86"."" ###$2.%2 2$%%$ ##%"2"

Smo,e 2"&6 2$."2!!" 6.$%&&2 $ !8

-ys_+nact !# 2.%$!8# ".#"%68 #$ !!

Drin, 262& #!.!66 "."%!2# $ &6.8

Obese !# &$.&&82 !.#6$"&! #&. !.6

M/D 2%" &.!86 #.$!2#8! $. %.6

Covariance of variables

Cancer0e 'e(_'r0) Diabetes *)e +nc Smo,e -ys_+0t Drin, Obese M/D

Cancer_Rate #

'e(_'ruit_0) 1$.$2%2 #

Diabetes $.#6% $.&2% #

*)e 1$.$$# $.$$8% $.2$# #

+nc $.$2! 1$.&686 1$."%" 1$.&$"" #

Smo,e $.#%2& $. $."6!2 $.$6 1$."2&% #

-ys_+nact $.#!2 $.!6"6 $.!82 $.2&"8 1$."%!# $.6$&% #Drin, 1$.$626 1$.#8# 1$.!82 $.$2!6 $.&%& 1$.2&2 1$.!#$ #

Obese $.#$%6 $.!6#8 $.&6& $.$$"6 1$."28" $."2$2 $."$ 1$.2%# #

M/D $.#"$# $.#66 $."$#! 1$.$## 1$.!26& $."!6% $.!2# 1$.!!& $.&2!" #

2$$

!$$

6$

$

8$$

#$$$#2$

6$ $ 8$ %$ #$$'e(_'ruit_Ve)

Cancer_Rate 'itted values


28/30


Figure D

Figure >

/L

Summary of variables for observations (it Cancer Rate +ncidence data available

Variable Obs Mean Min Max

'e(_'V #$6 8.%6"!2 ".2#&2"6 6&.# %6.!Diabetes 268 #$.!##2! 2.2"2"&% & 2$

*)e 268 #".!&"6 !.2&" 2.% &6.2

+nc 268 !&262.#! #$8." 2$%%$ ##$2$!

Smo,e 2#86 2$.8#%& 6.$6!#8 $ !8

268 28.#%$%2 ".2!2&!2 #$ !!

Drin, 228& #!.!$# ".2$%6 $ &6.8

Obese 268 &$.&"6 !.&&$&%! #&. !.6

M/D 2"&6 &."&$28! #.$2888 $. %.6

Std. Dev.

-ys_+nact

Summary of variables for observations (it Cancer Rate +ncidence data not available

Variable Obs Mean Min Max

'e(_'V #%8 8.""%$% !.682#8& 6!.% %&.

Diabetes !"! #$.2268 #.6"!2&" 6 #"

*)e !"! #6.#868 !."22!8& 6.# ."

+nc !"& !!!!.2 #222%.6 28"$2 ##%"2"

Smo,e &"$ #8.68286 ".%&8"$% $ &"

!"! 26.2##!" !.2"!"#& #" &%

Drin, &!$ #!."2%! !.66#!&6 $ 28.8

Obese !"! &$.&!8% 2.%6"62# #%.& &%.

M/D !2# &.22!$& #.$8&868 $. .&

Std. Dev.

-ys_+nact


29/30


Figure

Figure L

/

3inear re)ression

4umber of obs #6&&

' 5% #62&7 #%.$6-rob ' $.$$$$

R1s9uared $.%!&

Root MS: !%.#8!

Cancer_Rate Coef. t -t ;%"< Conf. +nterval=

'e(_'ruit_Ve) 1$.%!#%$$6 $.&$62$ 1&.$6 $.$$2 1#."!"& 1$.&&8"

Diabetes &."&8%8" #.$"!8& &.&6 $.$$# #.!$$ ".6$8$

*)e $.#22"! $.&%%8!& $. $."8 1$.6"8 $.%$&!

+nc $.$$#2$$2 $.$$$#"6 .66 $.$$$ $.$$$% $.$$#"

Smo,e #.28!2# $.&"$86 !.8! $.$$$ #.$28$ 2.!288

-ys_+nact $.%"6!666 $.!!$$!#6 2.# $.$&$ $.$%&! #.8#%6

Drin, 1$.$26$!! $.&6!!# 1$.$ $.%!& 1$.!$6 $.688"

Obese 1$.#628#8 $."2&"8$2 1$. $."6 1#.#8%8 $.86!#

M/D &."6$2& #.%"&8#! #.82 $.$6% 1$.22$ .&%2"

_cons &6%.%#6 2%.$&"#2 #2.! $.$$$ .%66" !26.86$

Robust Std.

:rr.

Variable >y?otesis Si)n and si)nificance

'e(_'ruit_Ve) @ 1 1 1$.%!2AA

5$.$7

Diabetes @ @@@ &."&%AAA

5#.$"$7*)e @ $.#2&

5$.!$$7

+nc @ @@@ $.$$#AAA

5$.$$$7

Smo,e @ @@@ #.28AAA

5$.&6$7

@ @ $.%"6A

5$.!!$7

Drin, @ 1$.$26

5$.&6$7

Obese @ 1$.#6&

5$."2$7M/D @ &."6

5#.%"$7

Constant &6%.%#AAA

52%.$!$7

Bse

-ys_+nact

@ ?$.$" @@ ?$.$# @@@ ?$.$$# and similary for 1


30/30


Figure

Jational Cancer State "rofile

@C9CB generated est2

percentage of population that

consumes D or more rations of

fruit$egetables b# state table

`#ear /00

10

State -ercent State -ercent

District of Columbia ." Eennessee 2&.&

Vermont 2%.& /ta 2&.&

Connecticut 28.& Fyomin) 2&.&

Maine 28 4e( Mexico 2&.2

4e( >am?sire 2.% Fisconsin 22.

California 2. Mici)an 22.6

Maryland 2.6 +llinois 22."

Vir)inia 2.& 4ort Da,ota 22."

4e( Gor, 26.8 Minnesota 2#.%

4e( Hersey 26.! Ientuc,y 2#.#

Ore)on 26.& Oio 2#

Massacusetts 26.2 4ebras,a 2$.%

Rode +sland 26.# +ndiana 2$.6

Montana 2". 4ort Carolina 2$.6Fasin)ton 2".# *r,ansas 2$.!

Dela(are 2" *labama 2$.&

Colorado 2!.8 Missouri #%.%

'lorida 2!.6 Iansas #8.6

+dao 2!.6 +o(a #8."

Jeor)ia 2!." Sout Carolina #.!

*riKona 2!.# 3ouisiana #6.%

-ennsylvania 2!.# Mississi??i #6.8

Eexas 2&.8 Fest Vir)inia #6.2

4evada 2&. Sout Da,ota #".

>a(aii 2&." O,laoma #!.6

*las,a 2&.!

Documents

The Effect of Fruit and Vegetable Consumption on Cancer Incidence [1.0]