Trading off fish health and safety: female decision-making processes toward the risk of methylmercury in fish.
Fish and shellfish are considered an important part of a healthy diet. The oils in fatty fish contain particular omega-3 fatty acids not found naturally in other foods, contributing to heart health, optimal brain function and cognition, improved eye and skin health, and protection against certain cancers (Din, Newby, and Flapan 2004; Mozaffarian and Rimm 2006; Uauy and Dangour 2006). However, some sources of fish contain environmental contaminants such as methylmercury (MeHg) and polychlorinated biphenyls. Research has shown that high levels of mercury can accumulate in the bodies of fish eaters and can harm the developing nervous system of fetuses and young children (Castoldi, Coccini, and Manzo 2003; Davidson, Myers, and Weiss 2004).
In 2004, the U.S. Food and Drug Administration (FDA) and the Environmental Protection Agency (EPA) issued a joint consumer advisory about mercury in fish and shellfish. The advisory was targeted toward woman of childbearing age, pregnant women, nursing women, and young children. They advised that these women eat up to 12 oz (about 335 g) per week of fish and shellfish that contain low levels of mercury (FDA 2004). This joint advisory supersedes FDA's and EPA's individual agency 2001 advisories.
Although research is under way to better understand the human exposure to mercury content in fish and the risks of contaminants are being communicated to consumers (Anderson et al. 2004; Institute of Medicine 2006), little work has been done to understand how consumers are using this information to trade off a healthy and beneficial protein source with the risks of mercury. This study takes a qualitative in-depth look at women's decision-making processes toward trading off seafood health and safety. Insights into these processes will help in understanding consumer response to this national advisory and may guide those developing survey questions for a regional or national quantitative survey of consumers.
Research has shown fish to be beneficial in reducing inflammation, protect against certain chronic diseases such as coronary heart disease (Mozaffarian and Rimm 2006) and arthritis (Cleland, James, and Proudman 2003), and are important for healthy brain development (Hibbeln et al. 2007; Uauy and Dangour 2006). Given these significant health effects, the American Heart Association and the American Diabetes Association recommend individuals consume at least two servings of fish per week. One serving equals 3 oz (about 90g) cooked or 4 oz (about 120g) raw weight (American Heart Association 2007; Franz 2003). Certain types of fish (those that have more oil, like salmon, compared to leaner fish like cod) are also good sources of omega-3 (n-3) fatty acids. Omega-3 fatty acids are considered essential to human health but cannot be produced by the body. These fatty acids have been linked with optimal brain function and cognition and improved eye and skin health (Nettleton 1995; Akabas and Deckelbaum 2006).
Despite these benefits, nearly all fish and shellfish contain at least some MeHg, and it is distributed in all tissues (Davidson, Myers, and Weiss 2004). As humans consume fish and shellfish, they are exposed to varying amounts of MeHg; there are no food preparations or cooking methods that can remove or reduce the amount of MeHg consumed (Mahaffey, Clickner, and Bodurow 2004). Mercury is a naturally occurring element in the earth's crust, and is found in soil, water, and air. The highly toxic metal can be released into the air from anthropogenic (e.g., coal-burning power plants) or environmental sources (e.g., volcanoes) and accumulates in nearby water sources (Davidson, Myers, and Weiss 2004). Bacteria present in the water convert inorganic mercury to an organic form, primarily MeHg (Clarkson 1997). MeHg is taken up by small organisms, such as plankton, and from there it moves rapidly up the food chain (Castoldi, Coccini, and Manzo 2003). Chronic exposure of MeHg can have toxic effects on the human body in adults and the developing fetus and growing young child. MeHg appears to primarily affect the central nervous system in all human populations (Davidson, Myers, and Weiss 2004). Bioaccumulation of the toxins occurs since the human body has no efficient means of excreting MeHg (Risher, Murray, and Prince 2002). Table 1 lists mercury concentrations for fish and shellfish commonly consumed.
Based on recent research of the effects of MeHg on humans, recommendations for fish intake have been established for specific populations, including women of childbearing age, pregnant and lactating women, infants, and children in relation to central nervous system development (FDA 2004). MeHg can easily cross the blood-brain and placental barriers and can be passed from a mother to her infant through breast milk, affecting the rapidly dividing cells of the central nervous system and may ultimately result in varying degrees of damage to the central nervous system (Clarkson 1997, 2002). Currently, approximately 3%-5% of the total U.S. population and 3% of women of child bearing age consume approximately 3.5 oz of fish per day on a routine basis (EPA, Office of Water 2001). For these women, total consumption for one week would be 24.5 oz; the FDA and EPA have recommended limiting fish consumption to no more than 12 ounces per week (FDA 2004).
Scientists remain unclear as to whether the risks of mercury outweigh the health benefits of a seafood diet for adults or children (Oken et al. 2003). Cohen et al. (2005) call this a risk-risk trade-off: by avoiding one risk (exposure to MeHg), consumers who follow these advisories may be incurring another (adverse health consequences associated with lower omega-3 fatty acid intake). Likewise, individuals who increase their consumption of fish because of this food's nutritional benefits may incur risks associated with MeHg exposure.
To quantify this trade-off, the Harvard Center for Risk Analysis convened an expert panel to investigate the aggregated impacts of hypothetical shifts in fish consumption (Cohen et al. 2005). They measured three scenarios of modified fish consumption among women of childbearing age (target population): (1) target population will eliminate consumption of "high" or "medium" MeHg concentrations, but maintain the same level of fish consumption; (2) target population will decrease their total fish consumption by 17% based on Oken et al.'s (2003) study; and (3) target population will reduce consumption by 17% as well as other members of the population. Although Cohen et al. (2005) found that high compliance with recommended fish consumption patterns can improve public health (Scenario 1), if women decreased fish consumption, countervailing risks substantially reduce net benefits.
The findings of Oken et al. (2003) demonstrate responsive behavior changes to the national advisory. In studying the extent to which pregnant women changed fish consumption habits after the national advisory, they found diminished consumption of dark-meat fish, canned tuna, and white-meat fish. Total fish consumption was reduced by approximately 1.4 servings per month from December 2000 to April 2001. In a field experiment conducted with French childbearing women, the impact of MeHg information led to a significant but insufficient change in fish consumption; consumption of the most contaminated fish did not decrease (Roosen et al. 2006). This work differed from Oken et al.'s (2003) as it measured participants' fish consumption over several months and controlled for seasonality. The Center for Food, Nutrition, and Agricultural Policy (2005) conducted a study of American adults to find out how consumers were responding to the conflicting information about the health benefits and mercury levels in seafood. In their opinion poll of 1,040 adults, more than 1 in 10 adults (12%) indicated they were consuming less seafood compared to a year ago. They found a third of their sample to be concerned about the amount of mercury in fish and shellfish. Although these studies indicate changes in consumption patterns of fish in response to national advisories, limited information is available about the decision process behind consumers' fish-related risk behaviors.
The goal of this study was to better understand how female consumers weighed the benefits and risks of consuming seafood. Qualitative techniques were used to collect baseline information and map patterns regarding consumers' decision-making processes toward trading off seafood health and safety. Because relatively little is known about the decision process behind consumers' fish-related risk behaviors, it was useful to begin by interviewing those directly involved with making fish and seafood consumption decisions.
Participant Selection and Recruitment
Twenty-six in-depth interviews were conducted among English-speaking female adults at least 18 years of age who resided in a northwest state, and who consumed fish or seafood at least once per month. In this study, the goal was to explore relevant and possible relationships of risk perception and behavioral influences, and not empirically test these relationships or make generalizations to any specific population (Denzin and Lincoln 2000; Krueger 1988). The sample size of 26 was adequate in that it captured variability within the group of participants along the dimensions we were interested in (e.g., age groups, education, seafood consumption) and within the study's resources. We sought representation of the female gender for several reasons: (1) their traditional role as primary food purchasers and preparers (Davidson and Freudenburg 1996), (2) many of the chronic diseases fish prevents against affect women differently and more predominantly than men (Society for Women's Health Research 2005), and (3) the primary risk of MeHg is to the developing fetus in the stage of pregnancy (Institute of Medicine 2006).
Nonprobability sampling techniques, sampling procedures that cannot specify the probability that each member of a population has of being selected, were used to identify and recruit participants (Denzin and Lincoln 2000). Individuals were recruited to participate in the study through articles published in local newspapers, notices posted in fish markets, senior centers, county health departments (Women, Infants, and Children offices), natural food stores, grocery stores, and articles released by the university news service. Individuals were asked to call the research office. Staff determined whether they were eligible by having them complete an initial screening instrument and ascertained that they were willing and able to participate in the study. The screening instrument also provided demographic information allowing the selection of a diverse group of female participants.
Each participant took part in a one- to two-hour long, in-depth semi-structured interview. The interviews took place in spring 2005; a year after the release of the FDA/EPA joint advisory. Each interview session consisted of (1) having the participant sign an informed consent document and being assured their responses would remain confidential, (2) completing a demographic questionnaire to acquire additional information not previously obtained on the telephone screener, (3) completing a Block Brief 2000 Food Frequency Questionnaire (1) to provide information on current dietary habits with regard to seafood, and (4) answering nine open-ended information questions (see the appendix for questions). An interview guide was developed to cover these nine informal questions but also provided flexibility allowing participants to introduce other issues and concerns (Marshall and Rossman 1999). The interviewer began with questions about seafood consumption and then moved into questions about perceived benefits and risks of seafood. The interview guide was developed based on a review of literature and refined through pilot testing with five participants. The same interviewer conducted all 26 interviews. The research team debriefed and reviewed the first several interviews in order to evaluate the use of additional probes and any issues that arose throughout the interviews. The interview was audio-recorded for accuracy and transcribed by a transcriptionist. All interviews were conducted in a neutral public location (coffee house, restaurant, library, or university campus). Upon completion, each participant was given a food coupon worth $50 to a local grocery store.
Table 2 summarizes the demographic characteristics of the sample. All participants consumed fish or seafood at least once per month. Of the 26 participants, 10 consumed seafood two to three times per month, 8 consumed seafood four to eight times per month, 6 consumed seafood 9-12 times per month, and 2 consumed seafood more than 12 times per month. The majority (24 out of 26) of participants consumed salmon, followed closely by tuna (n = 21) and shrimp/prawns (n = 19). Halibut, crab, clams, scallops, lobster, cod, and trout were also popular choices (in order from most to least). In addition, 6 of the 26 participants indicated taking a fish oil supplement, 5 of whom took it daily. The average age of the participants was 38.9 years; the youngest was 19 and the oldest was 77 years of age. Half (n = 13) of participants had a bachelors or higher degree. All but one participant was either the primary (n = 21) or dual shopper (n = 4) for the household, and the majority (n = 22) had also been the primary food preparer. A quarter (n = 7) of the sample had children under the age of 17, and five had a child(ren) under age six. Although no participants were currently pregnant or breastfeeding, two had been pregnant within the past two years at the time of the study. The sample was predominantly white (n = 22), with three Asian/Pacific Islander participants and one Hispanic.
The data analysis process followed Huberman and Miles' (1994) description, and included the phases of data reduction, data display, and conclusion drawing/verification. During the data reduction phase, our research questions shaped the questions we asked and emphasis was placed on the experiences and perceptions the participants wanted to share. During the data display phase, the research team read and reread each transcript several times, looking for themes and patterns in the narratives. The software MAXqda, a text-based qualitative data analysis program, was used to assist in coding the transcripts (VERBI Software 2005). Grounded theory methods (Strauss and Corbin 1998) suggest dividing coding into three phases: open coding, axial coding, and selective coding. In open coding, the researchers constantly compared transcripts in which key categories or properties were present with those in which they were not. For example, participants who were knowledgeable about the benefits and mercury risks of seafood were compared to those in which there was little awareness. Similar decision-making processes were compared with those that differed. The second phase, axial coding, according to Strauss (1987), consists of "intense analysis done around one category at a time." This step began when the important categories were identified and resulted in clarity concerning the most important dimensions that relate to the key categories or properties of the study. Examples of codes included codes specific to health perceptions of seafood, mercury knowledge and concerns, consumption changes, and decision processes. The third coding phase, selective coding, was part of the conclusion drawing phase to develop broad conceptual themes and to tell the clearest story that the data present. This process resulted in a "thick" understanding of consumers' fish-related decisions (Denzin and Lincoln 2000).
RESULTS AND DISCUSSION
Decision theorists have long been interested in how consumers make decisions under uncertainty. Epstein (1994) argues that people understand reality in two fundamentally different ways. "The rational system is a deliberative, analytical system that functions by way of established rules of logic and evidence (e.g., probability theory). The experiential system is intuitive and encodes reality in images, metaphors, and narratives to which affective feeling have become attached" (Slovic et al. 2004). The affective experiences are "feeling tags" or "somatic markers" that are associated with the images in people's minds (Damasio 1994). When making a judgment or decision, people reference all the positive and negative tags consciously and unconsciously associated with the representations. Consumers may find it easier and more efficient to use a readily available tag than searching their memory for relevant examples or weighing the pros and cons. This is especially true when the decision is complex or mental resources are limited. The extent of analytic versus affective information processing depends on the demands of the task and features of the individual making the judgment or decision. Both modes can be rational depending on the situation.
The decision-making processes of the participants in this study seemed to rely more on affective than analytic information processing. The analyses revealed five different decision processes that provide some understanding of how these 26 women traded off a healthy and beneficial protein source with the risks of mercury. These included (1) benefits of consuming fish outweighed the risks of MeHg, (2) personal risk was perceived to be less than the risk faced by others, (3) perceived risk was reduced through self-protective strategies, (4) they felt conflicted by the health and safety trade-off of fish and reduced fish consumption, and (5) lack of trust in information sources led to ambivalence. This section describes each of these processes and the changes in fish consumption patterns.
Four participants indicated they felt the benefits of consuming fish outweighed the risks. These participants did not change their fish consumption patterns. They perceived fish to be lower in fat, contain fewer calories, have less health risk than red meat, and have fewer antibiotics and hormones than other protein sources. These participants were aware of the mercury issue but were vague on the details and in their understanding of the effects of mercury on humans, consumed seafood often, and spanned the age range of participants. As one participant pointed out "Yeah ... obviously those [risks] don't outweigh the tastiness factor or the beneficial ... the mysterious benefits of omega-3 fatty acids!" (Bachelors degree, age 26, consumed fish once per week). Tangible consumer benefits were seen as positive markers for these participants and played an important role in their decision about the risk of mercury. This is consistent with Alhakami and Slovic's (1994) finding of an inverse relationship between perceived risk and perceived benefit. If consumers like an activity, they are moved toward judging the risks as low and the benefits as high; if they dislike it, they tend to judge the opposite.
Eight of the participants believed that their personal risk was less than the risk faced by others in the same situation, thus did not change their fish consumption behaviors. This is referred to in the literature as "optimistic bias" (Weinstein 1989). Optimism biases have been found to be greatest for risks judged to be controllable by personal action, such as lifestyle risks (Slovic 2000). These participants' decisions about the risk of mercury were based on the following: felt as though they do not consume enough fish for it to affect them, believed the species they ate did not contain mercury, knew where their fish came from and were confident mercury levels were low, felt mercury poisoning was rare, and trusted the sources where they buy fish. Half of these participants consumed seafood two to three times a month and all started consuming fish at a young age. They were aware of the mercury issue but not knowledgeable about the details.
Another seven participants employed self-protective strategies such as eating the fish species recommended by the government or Monterey Bay Aquarium and avoided others such as the large predatory fish and tuna to reduce their chances of an adverse outcome. Given the variety among seafood species, many were able to shift what seafood products they bought. "We have other fish we enjoy so it's not like we're giving up anything that we can't replace with something similar" (Masters degree or above, age 61, consumed fish two to three times per week). The participant's ability or resources to avoid the risk motivated a behavior response. Self-protective behavior is one way to minimize costs associated with a perceived risk. This approach was consistent with the conclusions of the Institute of Medicine (2006) that most people could gain nutritional benefits from seafood while minimizing their risks through the types of fish they selected. These participants were more knowledgeable about the health and safety issues surrounding fish than the other participants, started eating fish at a young age, tend to be older, ate fish because of specific health reasons (decrease cholesterol and ease joint problems), and consumed seafood frequently.
A couple of participants talked about being conflicted by the health and safety trade-off of fish for different reasons. "The benefit of tuna is that it's real easy and the risk is that I'm worried about the mercury so ... I'm trying to cut down on it" (Masters degree or above, age 45, consumed fish two to three times per month). The other made the decision to eat more chicken and switched to wild salmon because of concerns with farm-raised salmon. "We probably eat more chicken than we would if it was healthier to eat fish. But there's so much information out there ... I don't really know exactly how healthy or how unhealthy it [fish] is" (some college, age 36, consumed fish two to three times per week). Young children (ages 0-6 years) were present in both of these households.
Alternatively, lack of trust in information sources left one woman skeptical about the advisory and more ambivalent in her decision making. "It's always interesting when they're saying that something is a problem and they send out a bulletin to people that this is a problem. Then someone comes in and alleges that it's not really a problem--'Oh, don't worry about that.' You know, I always ... I'm always suspicious about that kind of intervention" (bachelors degree, age 43, consumed fish more than three times per week). Although only one participant explicitly discussed a lack of trust, this sentiment has been revealed in other research where consumers lacked trust in regulatory enforcement agencies abilities to set or enforce food safety standards (Hermann 1982; Siegrist 2000; van Ravenswaay 1995).
The final four participants did not express a specific decision-making process and did not alter their fish consumption patterns. They had limited awareness or knowledge about the risks of mercury in fish and indicated they were not concerned or did not worry much about the issue. These participants started eating fish at a young age, consumed seafood two to three times a month, and spanned the ages of 20-52.
Overall, 17 of the 26 participants did not change their fish consumption patterns because of concerns with the risks of mercury. Five of the remaining participants reduced their consumption of specific species but not seafood overall. Four reduced the amount of seafood they consumed. Of the nine who changed their fish consumption in some way, six specifically reduced the amount of tuna they ate. The tuna species has been targeted, in part, because that was what consumers had heard or knew about. Participants knew very little about the mercury concerns with other types of fish or seafood. Participants who were considered most at risk--women of childbearing age and those with young children--expressed fish consumption changes more frequently than others, especially in the amount of tuna they consumed. Other qualitative and quantitative research focusing on women of childbearing age and pregnant women found that participants indicated they would eat less fish as a result of the advisory; some participants specifically mentioned avoiding tuna steaks and albacore tuna (FDA 2005; Oken et al. 2003; Roosen et al. 2006). In this study, there were residual effects of the advisory on participants not targeted in the advisory, but for many this translated into behaviors that did not reduce their fish consumption levels.
This study has considered women's perceptions and behavioral responses to the risk of MeHg in fish. Of particular interest were women's decision-making processes when trading off seafood health and safety. In-depth interviews were conducted with 26 women who consumed fish on a regular basis, thus may be at risk of accumulating mercury in their systems. The qualitative data revealed five different decision-making processes. These included (1) benefits of consuming fish outweighed the risks of MeHg, (2) personal risk was perceived to be less than the risk faced by others, (3) perceived risk was reduced through self-protective strategies, (4) felt conflicted by the health and safety trade-off of fish and reduced fish consumption, and (5) lack of trust in information sources led to ambivalence. Seventeen of the 26 participants did not change their fish consumption patterns because of concerns with the risks of mercury.
One conclusion seems evident from the data; because many of these women did not change their consumption of fish, they still felt the "positive" benefits of fish (variety, protein, omega-3 fatty acids) outweighed the risk of mercury or felt the advisories did not apply to them. Participants who had greater concern levels tended to consume less tuna because that is what they had heard of. This reaction may be due in part to how the risk issue was presented in the advisory or by the mass media, and how these processes affected perceptions and behaviors (Kasperson et al. 2003). The advisory went into effect a year prior to this study.
Another way to view these findings is that the advisory reached its intended audience. In this group of women, participants who were most at risk--women of childbearing age and those with young children--expressed fish consumption changes more frequently than others, especially in the amount of tuna they consumed. Yet, they continued to receive the health benefits of fish by consuming other species such as salmon. There were residual effects of the advisory on participants not targeted in the advisory, but for many, this translated into behaviors that did not reduce their fish consumption levels. Survey data of consumers who consumed seafood on a regular basis would provide a more complete picture of whether these patterns hold true on a regional or national level. The findings from this work could guide the development of survey questions. One could begin by working from the decision processes listed above. For example, it would be informative to ask specifically which benefits of seafood were important and which risks they may be concerned about. Given the complexity of fish consumption, there may be other issues such as farm-raised or depleted fish stock that factor into consumers' decisions. Further research would deepen our understanding of the multifaceted nature of consumer risk behavior to the risk of MeHg in fish and provide information to effectively tailor risk communication.
What are the first words that come to mind when you think of fish and/or seafood?
1. When did you first start eating fish and/or seafood?
2. Why do you consume fish and/or seafood?
3. Do you feel there are any particular benefits to consuming fish and/or seafood? If so, what benefits?
4. Do you feel there are risks to consuming fish and/or seafood? If so, what risks?
If they feel there ARE risks, then ask:
Has knowing these risks changed your seafood consumption?
In what ways?
If they feel there are NO risks, then ask:
Are you aware of the mercury issue in seafood?
5. When you are out shopping for fish and/or seafood how do you tradeoff these benefits and risks?
6. Where are you getting your information about the health and safety aspects of seafood?
7. Which sources seem to be the most useful for you? Why?
8. Would you like to see more information on the health and safety aspects of seafood and why?
If Yes, ask the following:
How would you like businesses or government to provide information on the health and safety aspects of seafood?
Is there particular information on labels you would find useful?
What information would you find most helpful?
If No, ask:
9. Do you have anything else you would like to add?
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(1.) For further information go to www.nutritionquest.com.
Deana Grobe is a faculty research associate at the Human Development and Family Sciences, Oregon State University, Corvallis, OR (firstname.lastname@example.org). Melinda M. Manore is a professor at the Nutrition and Exercise Sciences, Oregon State University, Corvallis, OR (melinda.manore@ oregonstate.edu). Elizabeth Still is a graduate student at the Nutrition and Exercise Sciences, Oregon State University, Corvallis, OR (email@example.com).
Financial support for this work was provided by the College of Health and Human Sciences through Oregon State University and the Community Seafood Initiative, Astoria, OR. Any opinions expressed are those of the authors and do not necessarily represent any views or interpretations by the sponsor.
TABLE 1 Mercury Concentrations in Parts per Million (ppm) for Fish/Shellfish Commonly Consumed Species Mercury Concentration (ppm) Tilefish (Gulf of Mexico) (a) 1.45 Shark (a) 0.99 Swordfish (a) 0.97 King mackerel (a) 0.73 Grouper 0.55 Orange roughy 0.54 Marlin 0.49 Tuna (fresh/frozen) 0.38 Tuna (canned, albacore) 0.35 Lobster (Northern/American) 0.31 Halibut 0.26 Snapper 0.19 Tuna (canned, light) 0.12 Cod 0.11 Shrimp ND Lobster (spiny) 0.09 Squid 0.07 Crab (blue, king, snow) 0.06 Pollock 0.06 Scallops 0.05 Herring 0.04 Salmon 0.01 ND = mercury concentration below detection level (<0.01 ppm). (a) Pregnant and nursing women and young children are recommended to avoid these species. Source: U.S. Department of Health and Human Services and EPA. Mercury levels in Commercial Fish and Shellfish. www.cfsan.fda.gov/~frf/sea-mehg.html. May 2001 (updated February 2006). TABLE 2 Characteristics of the Sample (n = 26) Variable Mean (SD)/No. of Participants Seafood consumption 2-3 times per month 10 4-8 times per month 8 9-12 times per month 6 > 12 times per month 2 Age (in years) 38.9 (16.6) Education High school diploma or GED 1 Associates degree 2 Technical certificate 1 Some college 9 Bachelors degree 5 Masters, doctorate, or professional degree 8 Primary shopper No 1 Yes 21 Equal 4 Primary food preparer No 1 Yes 22 Equal 3 Children 0-6 years of age 5 7-17 years of age 2 Ethnicity of family Hispanic 1 Asian/Pacific Islander 3 White 22
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|Author:||Grobe, Deana; Manore, Melinda M.; Still, Elizabeth|
|Publication:||Journal of Consumer Affairs|
|Date:||Dec 22, 2007|
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