Introduction
There has been increasing research interest in lifestyle risk behaviors that collectively increase health risk. Of particular concern are alcohol misuse, cigarette smoking, poor diet, and physical inactivity—the “Big Four” contributors to mortality [
1] and the leading proximal and modifiable causes of morbidity [
2]—in which their synergistic effects are suggested to be more detrimental to health than their cumulative individual effects [
2]. Still, there is a paucity of information about the specific combinations of them [
3], as studies have focused on quantifying the co-occurrence of these behaviors, mostly using counts of risk behaviors [
4] or lifestyle indices as summary measures of healthfulness of lifestyles [
5,
6].
In the current study, we aim to examine the clustering of these behaviors and its associations with two common chronic conditions, hypertension and diabetes, among White, Black, Hispanic, and Asian American adults. Hypertension is the leading single risk factor for morbidity and mortality, and a major risk factor for cardiovascular disease [
7,
8], the leading cause of death in the United States (US) [
9]. Type 2 diabetes is accompanied by complications like cardiovascular diseases, retinopathy, nephropathy, and cancers, and consequently associated with increased risk for premature death [
5]. Although genetic predisposition partly determines individual susceptibility, these conditions largely are by-products of unhealthy lifestyles featuring health risk behaviors [
10]. Continued engagement in these behaviors while having these conditions increases the risks for complications with greater morbidity and premature mortality.
Of note, race-specific information about the clustering of these behaviors is rare. To our knowledge, our recent study is the first one that has reported on the clustering of the Big Four behaviors among Whites, Blacks, and Hispanics, using the National Alcohol Survey data and validating the clusters using self-rated health as the outcome [
11]. Health behaviors are influenced by the sociocultural and economic circumstances that shape decisions about them [
12,
13]. Racial/ethnic minorities (excepting Asians) tend to have lower SES than Whites in the US [
14]. As past research suggests that individuals of lower SES are more likely to engage in unhealthy behaviors such as tobacco use, physical inactivity, and poor nutrition [
15], more unhealthy clustering of lifestyle behaviors may be observed among Black and Hispanic adults.
There is also evidence that cultural norms and expectations in ethnic minority communities influence health behaviors. For example, in addition to income, prices, and access to quality fresh food (often dictated by one’s SES), dietary patterns are also shaped by individual preferences and beliefs, and sociocultural and ethnic factors [
16,
17], with social norms and modeling exerting powerful influences on food choice and consumption amounts [
18‐
21]. Foods are often used to affirm culture and forge social bonds, and frequent kinship gathering among Blacks and Hispanics around food, where rich, traditional or cultural foods may take precedence over more healthful eating, along with community norms that may dissuade adopting healthier food options [
17,
22], may also result in unhealthier diets being more pervasive in Black and Hispanic communities. Low social support for health-promoting activities in Black communities such as healthy diet or regular exercise has also been noted as a barrier to a healthy lifestyle [
23,
24], and might reflect a lack of neighborhood amenities (e.g., recreational spaces, affordable and accessible fresh foods) fostering this [
25,
26]. Asian cultural values that do not prioritize physical activity [
27] may contribute to a sedentary lifestyle. Additionally, greater exposure to stressors associated with racial minority status such as racial discrimination [
28] and lower access to health-promoting resources such as health care may lead to unhealthier lifestyles among racial minority groups. The clustering of health risk behaviors, therefore, is likely to be ethnically-patterned, and understanding race-specific patterns is critical for informing contextually-relevant interventions.
As these risk behaviors constitute pathways that lead to disparities in these conditions or their management [
29], a better understanding of their clustering, common or varying among these groups, can inform appropriate intervention strategies tailored to each group. As the effects of race and SES on health are confounded in the US [
30], to disentangle the respective effects of race and SES, each of which may engender constraints on health-related behaviors, we also examine whether unhealthier clustering is associated with lower SES in each group.
Three research questions are addressed: 1) What are the common and diverging patterns of clustered risk behaviors across these four racial/ethnic groups?; 2) Is unhealthier clustering associated with lower SES?; and 3) Is unhealthier clustering associated with diabetes and hypertension?
Discussion
Our findings partially support our hypotheses: with some exceptions, we found unhealthier clustering of risk behaviors was associated with lower SES, and with chronic conditions. Common and different patterns were found in these relationships across the four racial/ethnic groups. Commonalities include the obese-inactive class among all but Asian adults (who, instead, had the inactivity class) and the clusters that add smoking to this mix in each group. Also common is the smoking-risky-drinking class among Whites and Hispanics, with a variation seen among Blacks and Asians in the addition of inactivity to this cluster. Key differences across racial/ethnic groups, or, to be precise, between Whites and racial minority groups, include: a sizeable relatively-healthy-lifestyle class observed only among Whites; and positive associations of unhealthier clusters with diabetes and hypertension, as well as with income and education, being more consistent for Whites than for others. For racial minority groups, education than income was more consistently associated with unhealthier clusters, and the associations of unhealthier clusters with the two disease conditions were less clear for Blacks and Asians than for Whites, with no significant association observed for Hispanics. As we discuss below, both the commonalities and differences across the groups have important public health implications.
The commonality of the
obese-inactive cluster among Whites, Blacks, and Hispanics in the US suggests that addressing obesity and inactivity should be a key component of lifestyle interventions for these groups. Obesity is a well-recognized health problem in the US that increases risk for morbidity and premature mortality from major illnesses including hypertension, dyslipidemia, type 2 diabetes, cardiovascular diseases, respiratory problems, and some cancers [
46]. As physical inactivity is one of the primary contributors to the obesity epidemic in the US [
72], the common cluster of obesity and physical inactivity is not entirely surprising. However, another common cluster we found that additionally includes smoking is notable. As reported in a study, the joint effects of smoking, physical inactivity, and obesity could increase all-cause and CVD-specific mortality by at least 7.9 years U.S. adults [
73]. The
obese-inactive-smoking class, comprising about one in four adults in each of these three groups, is thus of great public health concerns.
The absence of a healthy lifestyle class among racial/ethnic minority groups does not mean that there were no individuals in these groups showing all four health-promoting behaviors, but the lack of such a class consisting of at least 5% of each minority sample in our LCA. This absence can be attributed to various sociocultural and structural forces. Past research suggests that the commonality of inactivity observed in all unhealthy clusters for Blacks and Asians may be partly attributed to lower social support for regular exercise in some Black communities [
24] and Asian cultural values that place a lower priority on physical activity [
27]. Perhaps more fundamentally, disparities in health-promoting and deleterious resources and environments (e.g., recreational spaces, food deserts, alcohol outlets) combined with differential exposure to chronic stressors such as racial discrimination [
28] and financial strain [
74], may lead to disparities in health behaviors [
25,
26].
Overall, positive associations between unhealthier lifestyle classes and health conditions were more consistent for Whites than for others, with the
relatively-healthy-lifestyle class having lower odds of diabetes and hypertension than the
obese-inactive class (and the
smoking-risky-drinking class, according to our post hoc analysis using the
relatively-healthy-lifestyle class as the referent; results not shown for brevity of recording). Unhealthier clustering that adds smoking to the obesity-inactivity combination for Whites and Blacks (and to inactivity in Asians) was associated with higher odds of disease condition. To the extent these classes capture each respondent’s long-term lifestyle, these findings suggest elevated health risk associated with an additional risk behavior added to the unhealthy cluster. This is consistent with past research showing poorer health associated with larger counts of risk behaviors [
75] or lower healthy lifestyle index scores [
5,
6].
Still, given the cross-sectional design of the present study, strictly speaking, these associations capture continued engagement in risk behaviors while having either or both conditions, rather than the causal effects of the clustered risk behaviors on the conditions. That individuals who already have diabetes or hypertension and who can risk complications are more, not less, likely to (continue to) engage in risk behaviors is a cause for public health concerns. Concerted efforts to address clustered health risk behaviors in most US adults, particularly in those whose health conditions (such as diabetes and hypertension) are adversely affected by them, are warranted.
The
smoking-risky-drinking-inactive class among Blacks and the
smoking-risky-drinking class among Whites were associated with lower odds of disease conditions for Whites and Blacks, compared with the
obese-inactive class. At least for Whites, this may be because of the lower age of the
smoking-risky drinking class than the
obese-inactivity class (Table
3)
, given that these conditions tend to develop later in adulthood. More fine-grained analyses for different age groups among midlife or older adults may shed light on this, which we did not have sufficient statistical power to do.
We found unhealthier clustering mostly associated with lower SES. This pattern was the most consistent for Whites, with the other classes having lower income and education than the
relatively-healthy-lifestyle class. This aligns well with prior studies that reported on positive associations between SES and healthier lifestyle using predominantly-White samples [
2,
76]. For racial minority groups, education more than income tended to be associated with unhealthier clusters. For Blacks, for example, the
smoking-risky-drinking-inactive class and the
obese-inactive-smoking class had lower education (and the former had lower income as well) than the
obese-inactive class. Similarly, the
smoking-risky-drinking-inactive class among Asians and the
smoking-risky-drinking-inactive class among Hispanics had lower education than their respective referents featuring fewer risk behaviors. Higher income, on the other hand, was positively associated with the clusters involving smoking and/or risky drinking among Asians and Hispanics, perhaps due to greater affordability of alcohol and tobacco that a higher income allows [
77]. Each SES indicator measures different, often-related aspects of social stratification that may influence health [
52]. Education influences health through a person’s adult occupation and income and the knowledge, health literacy and skills attained through education, which enable or motivate them to have healthier lifestyles [
78]. It has been suggested that education gives individuals the ability to override the ‘default’ American lifestyle characterized by poor diet and inactivity [
79]. Income can influence a wide range of material circumstances that affect health and access to health enhancing resources [
78], but higher income alone may have limited salutogenic effects, particularly for racial minority groups.
That the relationship between higher SES and healthier lifestyle is more pronounced for Whites than other groups may be partly because cultural practices and social support (or the lack thereof for healthy lifestyle) in racial minority groups, which, as we noted above, may also influence lifestyle independently of SES to some degree. Unhealthy lifestyles among racial minority groups may also be attributed to psychosocial stressors such as racial inequities they experience (including low occupational achievements even at the same education level as Whites) [
80], racial prejudice and unfair treatment they encounter in everyday lives [
28], and overall lower subjective social status they may experience [
81,
82], all of which may trigger health risk behaviors to cope with these stressors [
74] or distract individuals from health-seeking behaviors [
25,
26].
Our findings have important implications for future interventions. Given that the
obese-inactive class and the
obesity-inactive-smoking class among White, Black, and Hispanic adults together comprise a large segment of each group—47% of White, 72% of Black, and 80% of Hispanic adults (Fig.
1)—obesity and inactivity should be a central focus of lifestyle interventions for these three groups. Furthermore, in light of the synergistically adverse health effect of obesity, inactivity, and smoking on health noted above [
73], as well as our current findings showing positive associations of the
obese-inactive-smoking class with diabetes and hypertension for Whites and Blacks, preventive and intervention strategies for maintaining good cardio-respiratory health, particularly for these two groups, are warranted. Importantly, it should be emphasized that while clinical patient-oriented interventions are important, multi-level interventions are very likely needed for facilitating behavioral change, as health risk behaviors are related to individual, neighborhood, and environmental conditions as noted above.
In light of the consistently inverse associations between SES and unhealthy lifestyles for White adults, targeting low-SES Whites with these intervention strategies might be fruitful. Interventions to address obesity and inactivity might be directed most adults among Blacks and Hispanics, regardless of their SES. Still, given the significant negative association of the obese-inactive-smoking class and college degree for Blacks, it would be reasonable to target Blacks without a college degree with interventions addressing all three behaviors. The absence of obesity in any unhealthy lifestyle cluster and the commonality of inactivity in unhealthy clusters for Asians calls for a unique strategy to improve their health behaviors. As noted above, physical inactivity may be rooted in Asian cultural values that do not emphasize exercise, and thus interventions to address them could be effective, especially when considering the additional health risks of smoking alongside inactivity. While inactivity is also present in all unhealthy lifestyle classes among Blacks, the high prevalence of obesity among Blacks warrant strategies to address both obesity and inactivity.
We acknowledge several limitations of this study. First, gender differences in the clustering of risk behaviors were not explored in our LCAs to maximize statistical power for racial/ethnic-specific analyses and also to keep the focus on racial/ethnic differences. Still, multinomial regressions captured gendered clustering of risk behaviors (e.g., the
obese-inactive class more likely to be female). Second, though reasonable [
44], the use of obesity as a proxy for unhealthy diet is a limitation. Third, as our LCA models were not specific to gender, we used the cutoff for risky drinking for men (> 14 drinks weekly versus > 7 drinks weekly for women) largely because risky drinking is more pervasive among men than women [
83]. Using a conservative measure for women’s heavy drinking may have underestimated the unhealthy clusters involving risky drinking among them. There may indeed be gender differences in the clustering of risk behaviors, which we did not explore in order to maximize statistical power for racial/ethnic-specific analyses and also to keep the focus on racial/ethnic differences.
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