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 Journal Publication

This article was published with modifications in Community Genetics, 2003

Public Knowledge Regarding the Role of Genetic Susceptibility to Environmentally Induced Health Conditions

by Jill Morris, PhD1 , Marta Gwinn, MD, MPH1, Mindy Clyne, MPH1, Muin J. Khoury, MD,PhD1

Affiliations:
1Office of Genetics and Disease Prevention
National Center for Environmental Health
Centers for Disease Control and Prevention
Atlanta, GA 30341-3724

Corresponding author:
Jill Morris, PhD
Office of Genetics and Disease Prevention
National Center for Environmental Health
Centers for Disease Control and Prevention
4770 Buford Highway NE, MS K-89
Atlanta, GA 30341-3724
Phone 770-488-3262
email jmorris1@cdc.gov

Key words: genetics, genetic susceptibility, knowledge, belief, public perception, environment

bullet Abstract
bullet Introduction
bullet Methods
bullet Results
bullet Discussion
bullet Figures and Tables
bullet Appendix
bullet References

Abstract

Objective: Diseases thought to be caused by exposure to environmental factors are also influenced by genetic susceptibility.  It is not clear to what extent the public recognizes the role of genetics in causing these diseases.  
Methods: We asked 2,353 people in a national survey to indicate their level of agreement with statements about the genetic contribution to four health conditions typically considered to be environmentally induced.  
Results: 206 (9%) respondents believed that genetic susceptibility contributes to all four health conditions, while 751 (32%) believed that genetics plays no role in causing any of the conditions.  Respondents were more likely to believe that genetics contributes to adverse drug reactions and smoking-related illnesses than to infectious diseases and diseases resulting from exposure to environmental agents. 
Conclusions:  This study suggests that the public views genetic susceptibility as playing only a limited role in human disease induced by environmental factors.  Increasing awareness of  the role of genetic factors in these diseases will be necessary for translating gene discovery into effective personal and public health actions.

Introduction

The sequencing of the human genome continues to generate exciting new discoveries about the role of genetic variation in human diseases.  Among these discoveries is the recognition that even diseases typically considered to be caused by exposure to environmental factors (broadly defined to include infectious, chemical, physical, nutritional, and behavioral factors) are influenced by genetic susceptibility.  For example, lung cancer from cigarette smoking [1], toxic effects from pesticide exposure [2-4], and lead toxicity [5-7] appear to be influenced by genetic susceptibility.  Susceptibility to infectious diseases such as malaria, tuberculosis, and HIV infection has a genetic basis [8], as do the beneficial and adverse effects of certain drugs [9,10].

To fully translate genetic discoveries into opportunities for disease prevention, health-care providers, policy-makers, the media, and the public need to abandon the outdated notion of “nature versus nurture.”  Genetic and environmental causes of disease are not independent, opposing forces, but the aggregated influences of complex interactions [11,12].  This concept challenges traditional thinking and is difficult to explain, even to experts in medicine and public health [13,14].  Thus, a recently published study of twins to quantify the heritable and environmental causes of cancer [15] generated media headlines emphasizing the significance of genes (e.g. “Study Says Genes Account for More than One-Quarter of Cancer Cases;” [16]), as well as headlines downplaying their role (e.g., “Stop Blaming Your Genes;” [17]).

How do readers interpret such reports?  How do they perceive the role of genetics in common diseases, especially those generally considered to be environmentally induced?  To gain insight into these questions, we asked people participating in a market research survey of health attitudes and behaviors about the contribution of genetics to health conditions for which strong environmental components have been observed.

Methods

Study design.  This cross-sectional study used data from a national, population-based market research survey of health attitudes and behaviors conducted by mail in October 2000.  HealthStyles is a subsample of the annual DDB Needham “LifeStyles” survey, an annual survey of a representative sample of the US population containing several hundred questions on personality traits, media habits, shopping habits, political and religious beliefs, and demographics.  In 2000, the HealthStyles subsample comprised the 3161 (out of 5000) participants who completed and returned the LifeStyles questionnaire.

The HealthStyles survey includes a wide range of questions about health status, health behaviors, and attitudes toward and perceptions of various health topics.  The survey also requests information about demographic characteristics and media use.  Questions are developed by public health agencies, including the Centers for Disease Control and Prevention.  Porter Novelli, a Washington, DC, social marketing and health communications firm, administers the survey.

Six questions about genetics were included in the 2000 HealthStyles survey.  Four of these questions related to the role of genetics in causing health conditions generally considered to be environmentally induced.    For each of the following statements about genetics, participants indicated their agreement with the statement by responding on a scale of one for “strongly disagree” to five for “strongly agree”:

(1) A person’s genes can make them more likely to have side effects from drugs and medication (hereafter referred to as the “DRUGS” statement);

(2) A person’s genes can make them more likely to develop diseases caused by cigarette smoking (hereafter referred to as the “SMOKING” statement);

(3) A person’s genes can make them more likely to get infections such as the flu (hereafter referred to as the “INFECTION” statement); and

(4) A person’s genes can make them more likely to develop illness from environmental exposures such as pesticides  (hereafter referred to as the “ENVIRONMENT” statement).

For the present analysis, participants who responded with a four or five were considered to agree with the statement, and those who responded with a one, two, or three were considered to “not agree” with the statement (including those who gave a neutral response).

Characteristics associated with agreement.  Personal characteristics that were examined for association with agreement can be grouped into four categories: (1) demographics, including age, sex, race, level of education, annual household income, and marital status; (2) health status indicators, including self-rated health status and being overweight; (3) health information seeking behaviors, including being a Web user, having a high level of awareness of health information, and relying heavily on physicians as a source of health information; and (4) health beliefs, including feeling a lack of control over one’s health and believing in genetic determinism.  A respondent was said to believe in genetic determinism if he or she agreed with the statement, “A person’s health is determined more by their genes than by their behavior or their environment.”  As described below, we summarized several of these characteristics with composite variables.

Statistical methods.  We conducted univariate, bivariate, and multivariate analyses.  We used univariate analysis to examine crude levels of agreement with each genetics statement and bivariate analysis to assess the relation between the personal characteristics listed above and agreement with each statement.  Associations with a  p value < 0.05 (two-sided) were considered statistically significant.  Adjusted odds ratios for agreement with each of the statements were calculated by multivariate logistic regression. We used SAS 6.12 for Windows [18] for all statistical analysis.

HealthStyles 2000 included over 40 questions related to awareness and comprehension of health information, sources of health information, reliance on physicians for information, quality of relationships with physicians, and feelings of control over one’s health. Because many of these belief statements were highly correlated with one another, principal components analysis was used to group them into three conceptually meaningful composite variables [19].  Two principal components analyses were conducted.  In the first principal components analysis, 30 variables related to health information-seeking behavior and health awareness were summarized into two composite variables called “awareness” and “reliance.”  In the second principal components analysis, five variables were summarized into a composite variable called “health control.” The number of principal components retained in each analysis was determined using a scree plot.  Component rotation and factor analysis did not improve interpretation of the variables and therefore were not used.  Component loadings for each composite variable are given in the appendix. 

Each of the three continuous composite variables was dichotomized for use in the regression models.  The first composite variable, termed “awareness,” was characterized by self-motivated seeking of health information and a good understanding of health information. Respondents with “awareness” scores in the upper quartile of the sample distribution were assigned a value of one for the dichotomous variable “high awareness.”  “Reliance” was characterized by reliance on a physician for health information and difficulty in understanding health information.   Respondents with scores in the upper quartile of “reliance” were assigned a value of one for the dichotomous variable “high reliance.”  “Health control” was characterized by a strong feeling of control over one’s health.  Respondents with scores in the lowest quartile of the sample for “health control” were assigned a value of one for the dichotomous variable “low control.”

Results

Sample characteristics.  Of the 3161 people who received HealthStyles, 2,353 (75%) completed and returned the survey. Of the 2,353 participants, 2,327 (99%) responded to at least one of the genetics questions and 2,223 (95%) responded to all four genetics questions.

Survey participants had a mean age of about 52 years and were predominantly white (79%), female (60%), and married (73%) (Table 1).  The median annual household income ($43,000) and mean years of education (13.9) were slightly above the national averages of $41,000 and 13.2 years, respectively [20].

Agreement with genetics statements.  On the basis of dichotomization of responses into “agree” and “not agree,” 1,138 (49%) respondents agreed with the DRUGS statement, 902 (39%) agreed with the SMOKING statement, 625 (27%) agreed with the INFECTION statement, and 513 (23%) agreed with the ENVIRONMENT statement.  None of the 95% confidence intervals for these percentages overlapped, suggesting that the agreement rates for the four statements are statistically different from one another.  Although the order of the statements was not randomized across respondents, the pattern of agreement across the four statements does not appear to be an artifact of question ordering.

751 (32%) respondents did not agree with any of the four genetics statements, and 691 (29%) agreed with only one of the four statements.  Respondents agreeing with only one statement were  more likely to agree with the DRUGS statement than with one of the other statements.  206 (9%) respondents agreed with all four statements.

Characteristics associated with agreement. We examined the associations between agreement with each of the genetics statements and personal characteristics and health status, behaviors, and beliefs.  The most notable result is remarkable consiste

ncy in the ordinal pattern of agreement across the statements —  that is, the percentage of respondents who agreed with each statement and the resulting ranking of statements within the series was consistent across all groups defined by demographics or personal characteristics.  Across all strata, the pattern of agreement across statements was similar to the overall pattern shown in Figure 1:  agreement with the DRUGS statement exceeded agreement with the SMOKING statement, which exceeded agreement with the INFECTION statement, which exceeded agreement with the ENVIRONMENT statement. Averaged across characteristics, the proportion of respondents who agreed with the DRUGS statement was 2.2 times the proportion of those who agreed with the ENVIRONMENT statement.

As shown in Table 2, the bivariate analysis suggests that having high income, high education, and a belief in genetic determinism were associated with increased likelihood of agreeing with each of the four statements.  Being male, being a Web user, and having high awareness of health issues were associated with increased likelihood of agreeing with at least three of the four statements.  Having a strong feeling of lack of control over one’s health was associated with decreased likelihood of agreeing with each of the four statements.  Relying heavily on a physician as a source of health information was associated with decreased likelihood of agreeing with three of the four statements (all except INFECTION).

Table 3 presents the final multivariate models, with predictors of agreement with each statement modeled separately (thus yielding four final models).  Smoking status, drinking behavior, and self-rated health status were not significant predictors in any model and were eliminated from the final models.

We observed no strong differences in the characteristics associated with agreement across the four models.  Although only two characteristics —  high education and belief in genetic determinism —  were significant predictors in all four models, the overall trends were similar across the models.  Being male, white, of high income, highly educated, with high awareness, and believing in genetic determinism were associated with increased likelihood of agreeing with each individual statement.  Being a Web user was positively associated with agreement with three of the four statements.  Being married, relying on a physician for health information, and having strong feeling of lack of control over one’s health tended to be associated with decreased likelihood of agreement with each statement.

Agreement across statements was positively correlated, indicating that a respondent who agreed with one statement was more likely to agree with the other statements.  The highest correlation between statements (ρ = 0.43) occurred between the INFECTION and ENVIRONMENT statements, and the lowest correlation occurred between SMOKING and DRUGS and between ENVIRONMENT and DRUGS (both pairs with ρ = 0.27).

Discussion

Given that one third of survey respondents agreed with none of the four survey statements and fewer than 10% agreed with all four statements, the results of this study suggest that the public views genetic susceptibility as playing only a limited role in human disease induced by environmental factors.  Although the “profile” of the person most likely to agree with a specific statement is similar for all statements, the level of agreement between statements differs markedly, ranging from 29% for ENVIRONMENT to 49% for DRUGS. 

Despite this variation, we found a remarkably consistent pattern in the level of agreement across the statements.  In each subgroup (defined by personal characteristics), the proportion of agreement was DRUGS>SMOKING>INFECTION>ENVIRONMENT.  This pattern, although extremely consistent, is difficult to explain.

One hypothesis for this pattern is that perceived controllability of the exposure influences agreement, and that people may consider environmental and infectious exposures less controllable than exposures due to smoking and medication [21]. We were able to test this hypothesis only indirectly by examining the association between agreement and a composite indicator of perceived control over one’s health.  We observed that those who feel a strong lack of control over their health were less likely to agree with the genetics statements.  However, the magnitude of the association was roughly the same for each of the four statements.  Because we would have expected the association to be stronger for the INFECTION and ENVIRONMENT statements, this result does little to explain the pattern of agreement across the statements.

Factors explaining this pattern are probably complex and not easily measured.  Respondents may have been more likely to agree with the DRUGS and SMOKING statements because their awareness of these subjects is enhanced due to recent media coverage of these topics or personal observations, for example, that some people smoke for decades with no obvious ill effects while others become ill at an early age.  Alternatively, people may possess fundamentally different “mental models” of the processes by which these exposures are considered to influence one’s health [22,23].  That is, there may be substantive differences in the mental frameworks used to collect and interpret information from which inferences about disease causation are drawn.

From a broader perspective, the belief by the general public that genetic susceptibility plays a limited role in environmentally induced disease is consistent with the popular view that genes are associated with a small fraction of human diseases that are often severe or incurable (e.g., Tay-Sachs disease; Huntington disease), while environmental factors account for the rest of human disease [24,12].  Indeed, we often consider the spectrum of disease causation as ranging from completely genetic to completely environmental, a unnecessary dichotomy that obscures the fact that most human disease results from the interaction between genetic susceptibility and environmental factors.  As advances in molecular genetics expand our understanding of the genetic basis of disease, it is becoming increasingly misleading to perpetuate the “nature vs. nurture” argument.  As Hoover said [14] in his editorial on the Lichtenstein twins study, “it is time to drop the competition implied by talking about a debate over nature versus nurture in favor of efforts to exploit every opportunity to identify and manipulate both environmental and genetic risk factors [to prevent disease].” 

As the role of genetic susceptibility to environmentally induced diseases is increasingly understood, the scope of  public awareness of genetics needs to be broadened beyond single-gene disorders to include almost all human diseases.  A useful framework upon which to build this awareness starts with the idea that gene-environment interaction is fundamental to nearly all diseases, an idea that is still working its way into the mainstream of medical and public health research.  Providers of health care and health information will need to know more about the role of gene-environment interaction in health and disease to begin translating gene discovery into effective personal and public health action.

Figures and Tables

Appendix

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