Health Behaviors

This article defines health behaviors and then overviews data on key health behaviors (smoking, diet, exercise/physical activity, health screening, sexual behaviors, and alcohol use). Variations in these behaviors by sociodemographic factors are then considered. The next section addresses the psychological determinants of health behaviors and considers key models, such as the theory of planned behavior, health belief model, and social cognitive theory, and how these models might be integrated. The final section discusses how health behaviors might be changed to improve health outcomes.


Much of the interest in behaviors that have important impacts on our health and well-being is based upon two assumptions: that a significant proportion of the mortality from the leading causes of death is caused by the behavior of individuals, and that such behavior is modifiable (Conner and Norman, 2005). Behavior is held to exert its influence on health in three basic ways: by producing direct biological changes; by conveying health risks or protecting against them; or by leading to the early detection or treatment of disease (Baum and Posluszny, 1999).

The Definition of Health Behaviors

Health behaviors have been defined in a variety of ways. For example, Conner and Norman (2005) define them as any activity undertaken for the purpose of preventing or detecting disease, or for improving health and well-being. Gochman (1997) in the Handbook of Health Behavior Research defines them as “. behavior patterns, actions and habits that relate to health maintenance, to health restoration and to health improvement” (vol. 1: p. 3). Behaviors within these definitions include medical service usage (e.g., physician visits, vaccination, screening), compliance with medical regimens (e.g., dietary, diabetic, antihypertensive regimens), and self-directed health behaviors (e.g., diet, exercise, smoking, alcohol consumption). Each has received considerable attention from social and behavioral researchers and we now have a growing understanding of the factors determining engagement in such behaviors and ways in which such behavior can be changed.

In describing health behaviors it is common to distinguish health-enhancing from health-impairing behaviors. Health-impairing behaviors have harmful effects on health or otherwise predispose individuals to disease and include smoking, excessive alcohol consumption, and high dietary fat consumption. In contrast, engagement in health-enhancing behaviors convey health benefits or otherwise protect individuals from disease and include physical activity and exercise, fruit and vegetable consumption, and condom use in response to the threat of sexually transmitted diseases. A third set of health behaviors focus on detecting potential health problems and include behaviors such as health screening and testicular/breast self-examination.

Key Health Behaviors

Numerous studies have examined the health-behavior–health-outcome relationship. One of the first such studies identified seven features of lifestyle which were associated with lower morbidity and higher subsequent long-term survival: not smoking, moderate alcohol intake, sleeping 7–8 h per night, exercising regularly, maintaining a desirable body weight, avoiding snacks, and eating breakfast regularly (Belloc and Breslow, 1972). Health behaviors also impact upon individuals’ quality of life by delaying the onset of chronic disease and extending healthy life span. Smoking, alcohol consumption, diet, gaps in primary care services, and low screening uptake are all significant determinants of poor health, and changing such behaviors should lead to improved health. Health recommendations in countries across the Western world currently emphasize the importance of an increase in fruit and vegetable consumption, a reduction in dietary fat consumption, increased physical activity, and reductions in tobacco, alcohol, and drug use as important for health promotion and disease prevention.


Smoking is the health behavior most closely linked with long-term negative health outcomes. Morbidity and mortality from coronary heart disease (CHD) are increased among smokers (Doll et al., 1994). Moreover, there is a strong positive relationship between the number of cigarettes smoked per day and the incidence of CHD (Friedman et al., 1979). Smoking has also been linked to a number of cancers including cancer of the lung, throat, stomach, and bowel as well as a number of more immediate negative health effects such as reduced lung capacity and bronchitis (Royal College of Physicians, 1983). Despite the array of negative health outcomes, smokers often report positive mood effects from smoking and the use of smoking as a strategy for coping with stress.

A variety of studies support the idea that the vast majority of smokers take up this habit as adolescents with 40% of adult smokers having started before they reached 16 years of age (Royal College of Physicians, 1992). The number of people smoking in the USA and UK has shown a steady decline over the past 20 years from over 30% in 1999 to below 20% now (Center for Diseases Control, 2008). Smoking is higher among less educated, lower income, and minority groups (Rigotti, 1989). Those who quit smoking reduce the risk to their health, particularly if they quit before 35 years of age (Doll et al., 1994).


The impacts of diet upon morbidity and mortality are well established (e.g., USDHHS, 1988). In the Third World, the problems related to diet and health are ones of undernutrition; in the First World, the problems are predominantly linked to overconsumption of food. In Western industrialized countries, excessive fat consumption and insufficient fiber, fruit, and vegetable consumption are related to health problems. In addition, excess consumption of calories combined with insufficient exercise has made obesity a major health problem. Diet has been implicated in cardiovascular diseases (CVDs), stroke and high blood pressure, cancer, diabetes, obesity, osteoporosis, and dental disease.

It is generally agreed that elevated blood cholesterol level is a major risk factor for the development of CVD (Consensus Development Conference on Lowering Blood Cholesterol to Prevent Heart Disease, 1985) with significant proportions of the population in countries in the Western world having cholesterol levels higher than the level considered to be healthy. For example, in the USA, it is estimated that 50% of the adult population is at risk of CHD due to elevated blood cholesterol levels (Sampos et al., 1989). The reduction of blood cholesterol via dietary change is now widely accepted as an important way of tackling CHD. Dietary recommendations include reducing fat in the diet and increasing soluble fiber intake. However, their impact upon cholesterol levels may be limited.

Physical Activity/Exercise

The potential health benefits of engaging in physical activity and regular exercise include reduced cardiovascular morbidity and mortality, lowered blood pressure, and the increased metabolism of carbohydrates and fats, as well as a range of psychological benefits such as improved self-esteem, positive mood states, and reduced life stress and anxiety. Nevertheless, many adults in Europe and the US fail to meet physical activity recommendations. For example, the General Household Survey (1989) indicated that only one in three men and one in five women in the UK participate in any sport or recreational physical activity. Moreover, the Allied Dunbar Fitness Survey (1992) of 6000 English adults reported that only one in six adults had engaged in any physical activity that would have been likely to benefit their health (i.e., for 20 min or more at a moderate or vigorous level) in the previous 4 weeks. Participation in regular physical activity and exercise is strongly related to a number of sociodemographic variables. In particular, young people, males, and those from higher socioeconomic status groups are more likely to engage in regular physical activity and exercise.

Health Screening

Individuals may seek to protect their health by participating in various screening programs, which attempt to detect disease at an early, or asymptomatic, stage. In the UK, screening programs have been set up for various diseases including anemia, diabetes, bronchitis, and various cancers (e.g., cervical, bowel, and breast cancers). Taking the example of cervical screening (or PAP testing), it is estimated that if women were screened every 3 years, the cervical cancer mortality rate could be reduced by 70–95% (Greenwald and Sondik, 1986). Research from the UK shows that between 10 and 32% of eligible women remain unscreened (National Audit Office, 1998), while in the USA the number of unscreened women ranges from 13 to 30% (Ruchlin, 1997). Participation tends to be negatively related to age, and positively related to education level and socioeconomic status.

Sexual Behaviors

Sexual behaviors are considered health behaviors because of their impact upon the spread of sexually transmitted infections such as gonorrhea and syphilis. More recently, the role of sexual behaviors in the spread of the human immunodeficiency virus (HIV) has been a focus of attention. While early health education campaigns emphasized the need to reduce the number of sexual partners or avoid particular sexual practices (e.g., anal sex, penetrative sex), more recently the focus has been upon the use of condoms during penetrative sex to reduce the risk of HIV transmission. Condom use is particularly recommended for those with multiple partners or those who do not know their partners’ sexual history. For these reasons, much of the health advice concerning condom use has been focused on young people.

There seems to be considerable variation in the use of condoms in response to the threat of HIV/AIDS, although systematic condom use is not widespread even among single heterosexuals. For example, 78% of respondents in an American study declared they did not always use a condom during sexual intercourse (Choi and Catania, 1996). A Canadian study among a population aged 15 years and older reported similar findings with 28% of respondents reporting not having used a condom during their last sexual intercourse with an occasional partner (Health Canada, 1998). In a European study, among respondents who had more than one partner in the past year, only 52% of the men and 41% of the women declared having used a condom at least once (Guiguet et al., 1994).

Alcohol Use

Moderate alcohol consumption has been linked to positive health outcomes. However, high alcohol consumption has been linked to a range of negative health outcomes including high blood pressure, heart disease, and cirrhosis of the liver. High levels of alcohol consumption have also been associated with accidents, injuries, suicides, crime, domestic violence, rape, murder, and unsafe sex (British Medical Journal, 1982). While many of the adverse effects of high alcohol consumption are due to continued heavy drinking (e.g., cirrhosis of the liver, heart disease), others are more specifically related to excessive alcohol consumption in a single drinking session (e.g., accidents, violence).

The General Household Survey (1992) reported that the average weekly consumption of alcohol in the UK was 15.9 units (1 unit ¼ 1 glass of wine or 1 measure of spirits or 0.5 pints of beer) for men and 5.4 for women. In addition, 27% of men and 11% of women were drinking more than the recommended weekly sensible limits (21 units for men, 14 units for women). Heavy drinking is more likely among younger age groups. In a survey of 12 000 Welsh adults, Moore et al. (1994) reported that 31.1% of drinkers aged 18–24 engaged in binge drinking (i.e., drinking half the recommended weekly consumption of alcohol in a single session) at least once a week.

Relationship of Health Behaviors to Sociodemographic Factors

A clearer understanding of why individuals perform health behaviors might assist in the development of interventions to help individuals gain health benefits. A variety of factors have been found to account for individual differences in the performance of health behaviors. Demographic variables show reliable associations with the performance of health behaviors (e.g., age, gender, ethnic status). For example, there is a nonlinear relationship between many health behaviors and age, with high incidences of many health-risking behaviors such as smoking in young adults and much lower incidences in children and older adults (Blaxter, 1990). Such behaviors also vary by gender, with females being generally less likely to smoke, consume large amounts of alcohol, engage in regular exercise, but more likely to monitor their diet, take vitamins, and engage in dental care (Waldron, 1988). Differences by socioeconomic status are also apparent for behaviors such as diet, exercise, alcohol consumption, and smoking (e.g., Blaxter, 1990) with increases in health-risking behaviors and decreases in health-protective behaviors in lower socioeconomic status groups.

Generally speaking, younger, wealthier, and better-educated individuals are more likely to practice health protective behaviors. Access to medical care has been found to influence the use of such health services (e.g., Black Report, 1988) and may explain some socioeconomic status differences in health behaviors. These factors may interact with other influences such as levels of stress and social support. Higher levels of stress and/ or fewer resources are associated with health-risking behaviors such as smoking and alcohol abuse (Adler and Matthews, 1994). Social factors seem to be important in establishing health behaviors in childhood. Parent, sibling, and peer influences are important, for example, in the initiation of smoking. Cultural values also have a major impact, for instance, in determining the number of women exercising in a particular culture. Steptoe and Wardle (1992) report that between 34 and 95% of women in their European student sample had exercised in the past 14 days.

Understanding the Distribution/Prevalence of Health Behaviors

A considerable body of social and behavioral research has examined individual variables explaining sociodemographic differences in performance of health behaviors. An assumption is that these variables may be more readily modifiable in attempts to change behavior. For example, personality variables such as conscientiousness have been related to mortality. Conscientiousness refers to the ability to control one’s behavior and to complete tasks. Highly conscientious individuals are more organized, careful, dependable, self-disciplined, and achievement-oriented than those low in conscientiousness. There is considerable evidence showing conscientiousness to impact on health behaviors, health outcomes, and even mortality. Friedman et al. (1993) reported that conscientiousness was significantly associated with lower mortality in later life with those high in conscientiousness likely to live longer (by about 2 years), compared to those low in conscientiousness. An important mechanism by which conscientiousness may influence health is through health behaviors. Friedman et al. (1995) showed that the impact of conscientiousness on longevity was partly accounted for by its effect on reducing smoking and alcohol use. A review of work on the relationship between conscientiousness and behavior (Bogg and Roberts, 2004) showed conscientiousness to be positively related to a range of protective health behaviors (e.g., exercise) and negatively related to a range of risky health behaviors (e.g., smoking).

Thoughts and feelings about a health behavior (or health cognitions) also determine whether or not an individual practices health behaviors and may explain how other factors influence behavior. Knowledge about behavior–health links is an important factor in an informed choice concerning health behaviors. Various health cognitions have been studied including perceptions of health risk, efficacy of behaviors in influencing this risk, social pressures to perform the behavior, and control over performance of the behavior. The relative importance of various health cognitions in determining who performs various health behaviors constitutes the basis of several different models. Such models have been labeled social cognition models (SCMs) because of their focus on health cognitions as the primary determinant of individual social behaviors. These SCMs provide a basis for understanding the determinants of behavior and behavior change. Each of these models emphasizes the rationality of human behavior and assumes that behavior is based upon elaborate, but subjective, cost/benefit analysis of the likely outcomes of differing courses of action. It is assumed that individuals generally aim to maximize benefits and minimize costs in selecting a behavior. The effects of sociodemographic variables on health behavior are mediated by health cognitions in these models, although direct and moderated relationships are reported (Conner et al., 2013).

Health Belief Model

The health belief model (HBM) outlines two types of health beliefs that make a behavior in response to illness more or less likely (Abraham and Sheeran, 2005): perceptions of the threat of illness and evaluation of the effectiveness of behaviors to counteract this threat. Threat perceptions depend upon the perceived susceptibility to the illness and the perceived severity of the consequences of the illness. Together these variables determine the likelihood of the individual following a health-related action, although their effect is modified by demographic variables, social pressure, and personality. The particular action undertaken is determined by the evaluation of the possible alternatives. This behavioral evaluation depends upon beliefs concerning the benefits or efficacy of the health behavior and the perceived costs or barriers to performing the behavior. Hence, individuals are likely to follow a particular health behavior if they believe themselves to be susceptible to a particular condition or illness, which they consider to be serious, and believe the benefits of the behavior undertaken to counteract the condition or illness outweigh the costs. It is assumed that this whole process is set in motion by cues to action. Cues to action include a diverse range of triggers to the individual taking action and are commonly divided into factors that are internal (e.g., physical symptoms) or external (e.g., mass media campaigns, advice from others) to the individual. Other influences upon the performance of health behaviors, such as demographic factors or psychological characteristics (e.g., personality, peer pressure, perceived control over behavior), are assumed to exert their effect via changes in the components of the HBM.

Theory of Planned Behavior

The theory of planned behavior (TPB) was developed by social psychologists and has been widely employed to health behaviors (Ajzen, 1991; McEachan et al., 2011). The TPB specifies the influences that determine the individual’s decision to follow a particular behavior. Within the TPB, the determinants of behavior are intentions to engage in that behavior and perceived behavioral control (PBC) over that behavior. Intentions represent a person’s motivation. The construct is conceptualized as an individual’s conscious plan or decision to exert effort in order to engage in a particular behavior. PBC is a person’s expectancy that performance of the behavior is within his or her control or confidence that he or she can perform the behavior. Intentions are determined by three variables. The first is attitudes, which are an individual’s overall evaluation of the behavior. The second is subjective norms, which consist of a person’s beliefs about whether significant others think he or she should engage in the behavior. The third is PBC. Recent revisions to the TPB have suggested that attitudes may divide into instrumental and affective components and subjective norms may divide into injunctive and descriptive norms while PBC may divide into perceived confidence and perceived control (Conner and Sparks, 2005).

The attitude, subjective norm, and PBC components are determined by underlying beliefs. Attitude is a function of a person’s salient behavioral beliefs, which represent perceived likely consequences of the behavior (e.g., taking exercise will reduce my risk of heart disease). Subjective norm is a function of normative beliefs, which represent perceptions of specific salient others’ preferences about whether one should or should not engage in a behavior (e.g., my family think I should take exercise). PBC is based on beliefs concerning access to the necessary resources and opportunities to perform the behavior successfully (e.g., I have easy access to a place where I can exercise). So, according to the TPB, individuals are likely to engage in a health behavior if they believe that the behavior will lead to particular outcomes which they value, if they believe that people whose views they value think they should carry out the behavior, and if they feel that they have the necessary resources and opportunities to perform the behavior.

Social Cognitive Theory

In social cognitive theory (SCT; Bandura, 1982), behavior is held to be determined by four factors: goals, outcome expectancies, self-efficacy, and sociostructural variables. Goals are plans to act and can be conceived of as intentions to perform the behavior (see Luszczynska and Schwarzer, 2005). Outcome expectancies are similar to behavioral beliefs in the TPB but here are split into physical, social, and self-evaluative depending on the nature of the outcomes considered. Self-efficacy is the belief that a behavior is or is not within an individual’s control and is usually assessed as the degree of confidence the individual has that he or she could still perform the behavior in the face of various obstacles (and is similar to PBC in the TPB; e.g., “I am confident that I can refrain from smoking, even if someone offers me a cigarette”). Sociostructural variables are factors assumed to facilitate or inhibit the performance of a behavior and affect behavior via changing goals (e.g., impediments or opportunities associated with particular living conditions, health systems, political, economic, or environmental systems). They are assumed to inform goal setting and be influenced by self-efficacy.

Self-efficacy is one of the most powerful predictors of health behavior (Bandura, 1997). Individuals with a strong sense of self-efficacy are believed to develop stronger intentions to act, to expend more effort to achieve their goals, and to persist longer in the face of barriers and impediments. Perceived self-efficacy is therefore believed to play a crucial role in the determination of health behavior.

Integrated Models of Health Behavior

Models like the HBM, TPB, and SCT show several similarities but also a number of key differences. One approach to combining these models is to consider developing an integrated model. This may be valuable given the overlap in cognitions considered by different models. For example, it is widely accepted that the key cognitions influencing behavior are intention, self-efficacy, and outcome expectancies (or attitudes). One attempt at integration suggested that there were eight key variables determining behavior (Fishbein et al., 2001). The variables are organized into two groups. The first group includes variables viewed as necessary and sufficient determinants of behavior. For behavior to occur an individual must:

  • have a strong intention to perform the behavior;
  • have the necessary skills to perform the behavior; and
  • experience an absence of environmental constraints that could prevent enactment of the behavior.

The second group of variables primarily influences behavior through intention. A strong intention to act is likely to occur when an individual:

  • perceives the advantages (or benefits) of performing the behavior to outweigh the perceived disadvantages (or costs);
  • perceives the social (normative) pressure to perform the behavior to be greater than that not to perform the behavior;
  • believes that the behavior is consistent with his or her self-image;
  • anticipates the emotional reaction to performing the behavior to be more positive than negative; and
  • has high levels of self-efficacy.

Changing Health Behaviors

The above models detail the key social cognitive determinants of health behavior. To the extent that these models outline the key determinants, interventions, which target these variables should lead to associated changes in behavior. For example, enhancing feelings of self-efficacy could be one means to encourage health behavior change. As Bandura (1997) outlines, there are four main sources of self-efficacy, each of which could be addressed in interventions. First, individuals can develop feelings of self-efficacy from personal mastery experience (e.g., it may be possible to split a behavior into various subgoals, such that the easiest subgoals are achieved before more difficult tasks are attempted). Second, individuals may develop feelings of self-efficacy through observing other people succeed on a task (i.e., vicarious experience). Third, it is possible to use standard persuasive techniques to try to instill feelings of self-efficacy. Finally, one’s physiological state may be used as a source of information, such that high levels of arousal or anxiety may indicate to the individual that he or she is not capable of performing a given action (e.g., relaxation techniques may be employed to help maintain feelings of self-efficacy). Alternatively interventions might target changing attitudes as a means to change behavior. This might be achieved using persuasive messages designed, for example, to target behavioral beliefs (e.g., Brubaker and Fowler, 1990). A further approach would be to target the anticipated emotional reactions to a behavior again using persuasive messages (e.g., Conner et al., 2011).

Another interesting approach has focused directly on the immediate determinant of behavior in several of these models, namely intentions. Where individuals do have an intention to engage in a health behavior (goal intentions), but are having trouble implementing their intention, forming a specific plan about where and when to act has been found helpful (Gollwitzer and Sheeran, 2006). For example, Conner and Higgins (2010) got adolescents who did not want to become smokers to repeatedly form plans about how to refuse the offer of a cigarette. This was shown to significantly reduce rates of smoking initiation over the next 4 years.

Over the past few years, research has also sought to develop a taxonomy of the different behavior change techniques (BCTs) that have been used in attempts to change health behavior and relate them to existing theory. For example, Abraham and Michie (2008) set out a total of 26 distinct BCTs used in relation to a range of behaviors. A good number of these relate directly to SCMs described earlier (e.g., provide information about the consequences of the behavior) although others set out alternative means to changing behavior (e.g., motivational interviewing).


Health behaviors have important consequences for both the quality and length of life partly via influencing disease outcomes. Nevertheless, there is still considerable variation in who performs these behaviors. SCMs provide one approach to understanding the variation in who performs health behaviors. These models are also useful because they suggest ways to change health behaviors in order to improve health. Research on BCTs has provided useful information on how to change health behaviors and further insights into why individuals perform these behaviors. The next big challenge for social and behavioral research on health behaviors is to demonstrate how theory-based interventions can produce effective and long-lasting behavior change that results in real benefits in terms of morbidity and mortality.


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