Our diabetes prevalence estimates for the gender–race groups were similar to a previous review of data from NHANES III (1988–1994), which showed that for both men and women, non-Hispanic blacks had a higher diabetes prevalence than non-Hispanic whites and Mexican Americans (37
). However, we did not find any studies using NHANES data that examined family history of diabetes in relation to diabetes prevalence.
We found that family history of diabetes was a significant predictor of self-reported diabetes among U.S. adults. We estimated that adults with a family history of diabetes in a parent or sibling had four times the odds of having diabetes than adults without a family history of the disease, after adjusting for gender, age, race, PIR, and BMI. These findings are consistent with a recent summary review of 10 studies performed in various countries, which reported that individuals with a positive family history of diabetes had two to six times the risk of type 2 diabetes, compared with individuals without a family history of the disease (19
Moreover, our study demonstrated that adults with two diabetic parents had more than twice the risk of diabetes than adults with only one diabetic parent. This additive risk association has been described previously in a white U.S. population (22
). Through further examination of family history, an elevated diabetes risk was found to be associated with an increased number of first-degree family members affected with diabetes. Among all demographic and risk factors, the presence of three or more diabetic first-degree relatives corresponded to the highest diabetes prevalence and OR for diabetes. With the exception of a few studies, a relatively small amount of literature quantified family history of diabetes in terms of the number of affected relatives.
Because family history was one of the strongest risks for diabetes in our study, individuals with family members who have diabetes should be a screening priority for diabetes. As stated previously, undiagnosed diabetes constitutes approximately 29.3% of total diabetes prevalence (5
). A current study demonstrated that the prevalence of diagnosed diabetes has increased, and the prevalence of undiagnosed diabetes has decreased for severely obese individuals (BMI
35), possibly because of a better awareness of BMI as a risk factor among health care providers and improved screening among these individuals (5
). Similarly, the use of a family history screening tool could capture many more of these undiagnosed individuals who would benefit from early intervention.
Individuals who have close relatives with diabetes may be more motivated to seek early health screening and thus more likely to be diagnosed than individuals without a family history. Because of earlier screening, individuals with a family history would likely be younger at age of diagnosis than individuals without a family history. This likelihood is supported by both our study (44.5 years at diagnosis for individuals with a family history vs 48.5 years at diagnosis for individuals without a family history) and an Australian study, which found a trend of younger age of diabetes diagnoses with increasing number of family members affected (24
). Furthermore, research has shown that individuals with type 2 diabetes are more likely to collect health information from family members (38
). However, our study indicated that a higher proportion of adults who had diabetes did not know their family history of diabetes (2.7%) when compared with adults who did not have diabetes (2.0%), although this difference was not statistically significant.
In addition, proportionately more women reported a father, mother, brother, or sister with diabetes than men, and there were more reports of female relatives with diabetes than male relatives with diabetes. A recent study found that women were slightly more likely than men to regard family history as very important to their own health and were more likely to collect family medical information (38
). Among men in our study, 2.2% did not know their family history of diabetes, compared with 1.8% of women.
Limitations of our study include the inability to discriminate between cases of type 1 and type 2 diabetes. Had stratification been possible, we may have found different relationships among diabetes, family history, and other factors. Subjects in our study were not excluded based on age of diabetes diagnosis; such exclusion could have eliminated many type 1 diabetes cases. It is estimated that approximately one third of children with diabetes aged 12 to 19 years have type 1 diabetes. The prevalence of type 1 diabetes among all ages in the United States is approximately 0.12% (39
). Therefore, the exclusion of individuals with type 1 diabetes from our study population would probably not have affected our results appreciably.
Because diabetes diagnoses of participants and family members were self-reported and not verified, the true diabetes prevalence may be misrepresented. Moreover, diabetes is underdiagnosed in the United States, suggesting that the true prevalence is higher than reported prevalence. Subjects also self-reported age of diabetes diagnosis, creating a potential for recall bias. As previously mentioned, survey participants were not asked about family history of diabetes in children, which limited our definition of first-degree relatives to parents and siblings only. Also, NHANES excludes institutionalized persons, including individuals residing in nursing homes, who are likely to be older adults.
Our findings create several implications for public health. First, diabetes has paralleled the obesity epidemic. Similar to a previous NHANES study (40
), we found that non-Hispanic black women had the highest prevalence of obesity (48.7%) compared with non-Hispanic white women (31.1%), Mexican American women (36.8%), non-Hispanic black men (26.8%), non-Hispanic white men (27.9%), and Mexican American men (25.8%). The prevalence of family history was also highest in women and non-Hispanic blacks among genders and races. Both obesity and diabetes have strong environmental components, such as diet and physical activity. Thus, the presence of family history often reflects the shared environment and health-related behaviors among family members in addition to hereditary factors. The recognition of this high correlation among obesity, diabetes, and family history can help guide population-appropriate health promotion activities.
Second, with the current striving for genetic awareness and competency in public health, this study represents a feasible and inexpensive method of extracting genomic information from existing population-based data sources. NHANES, a validated and well-recognized survey, provides a substantial amount of health information on a national level. Other population-based surveys also offer informative data that may pertain to genomics. There are several steps public health practitioners can take now to access and use genomics and incorporate genomics into programs. Because family history encompasses both genetic and environmental factors, it can be applied to other chronic diseases involving multiple complex etiologies, such as cardiovascular disease. Therefore, knowledge gained from family history and diabetes can be translated into other public health program areas.
Finally, at the primary care and public health level, this study supports the promotion of a family history tool for diabetes prevention and early detection strategies as a valuable measure of diabetes risk. Family history is easily available and inexpensive to obtain yet may be underused in health care practice (31
). The following three criteria are suggested for incorporating a family history tool into public health screening: 1) the disease represents a significant public health burden, 2) family history is an established risk factor, and 3) there are effective interventions for prevention (31
). Type 2 diabetes meets these criteria. It is evident that neither diabetes nor obesity prevalence is decreasing; therefore, it is critical that we use all available resources to quantify individual disease risk as accurately and completely as possible.