In this study, we have shown that DM and ATH cluster as contributing causes of death more strongly in AI as compared to Non-AI. We also found that the difference in the fraction of deaths with DM when ATH was also a contributing cause relative to when ATH did not contribute, was higher for both AI men and women across all age groups but more so among younger AI women (age ≤ 60 years). DM is rarely the primary cause of mortality; it is more likely to serve as an antecedent to vascular dysfunction which can directly cause deaths [18]. In this context, our second finding, though only in mortality data, suggests the interpretation that during life: DM as a risk factor for subsequent ATH and dual DM/ATH contribution to mortality is more salient in AI as compared to a Non-AI for all age groups studied in both men and women. However, the excess contribution of DM in ATH-related deaths in AI was mostly higher among women than men of the same age group and this difference was most apparent at age ≤ 60 years.
Our findings are in line with current literature that suggests the existence of excess dual burden of ATH and DM in AI vs Non-AI [2, 8, 16]. Further evidence regarding the subclinical disease during life comes from a recent study performed in the ongoing Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort which reported that the highest predicted probability for incident coronary artery calcium deposition, a marker of subclinical atherosclerosis, in any US race/ ethnic group with pre-existing diabetes but free from cardiovascular disease at the time initial evaluation, is observed in South Asians [19]. Our first finding takes this understanding a step further by quantitating the excess joint burden of ATH and DM as contributing causes of deaths in AI vs Non-AI. While studies that have relied on electronic health records and health-system based reports for data have reported a higher prevalence of DM and ATH in AI, these contrast with a recent observation by Satish et al who pooled data using self-reported questionnaires [20]. As several AI were potentially under-diagnosed owing to poorer access to healthcare and were, hence, unaware of their condition, Satish et al found a significantly lower prevalence of DM and ATH in AI [20]. This observation is notable in the context of our findings as it highlights the need to step up the detection of DM and ATH in AI. Further, it has been noted that the largest disparities due to poorer healthcare access to immigrants in the US are in the metabolic control of DM and ATH [21]. These compound the risk of progression of undetected DM and ATH in an already genetically predisposed group with lower levels of physical activity coupled with culturally derived dietary practices that fuel the risk of development of these two cardiometabolic co-morbidities [8].
Our second finding that the excess contribution of DM as a co-occurring cause of death in ATH-related versus ATH-unrelated deaths was most apparent in younger AI women (age ≤ 60 years) is consistent with prior reports that the association of DM and mortality is generally higher in females and at younger ages [15, 22], and that it is most pronounced in women of AI national origin [2].
Our study has a major clinical implication which is in line with a recent observation made by Coles et al [23]. Until it is known whether the increased ATH mortality in AI is incited by DM itself or if it is the combined effect of the ‘Asian Indian phenotype’ (‘South Asian phenotype’) and DM, our results indicate that public health strategies should focus on joint prevention and treatment of both ATH and DM in AI, especially in young adulthood and middle age. As suggested by the Emerging Risk Factors Collaboration, in those patients first diagnosed with DM, it is essential to prevent subsequent ATH, and conversely, to prevent DM in those who first develop ATH, because these diseases have multiplicative associations with mortality [22]. Further, our findings quantify the public health implication by quantitating at least a 4% excess co-occurrence of DM and ATH as contributing causes of death in AI versus Non-AI.
Our study has some limitations. Firstly, the data for our study is based on national death certificates, which may contain errors at the time of documentation. Secondly, we were unable to calculate the mortality rate using this dataset compiled by the NCHS as the national origin groups on US Death Certificates are not currently linked to census denominators. Therefore, we can only make indirect inferences about cause-specific rates observed in each subgroup using the cause-specific proportion of overall mortality in that subgroup as a proxy. As a next step to studying the mortality rate owing to concurrent ATH and DM as contributing causes in AI versus Non-AI, mortality data from US Death Certificates could be linked with US Census data. Nevertheless, our results add evidence to the growing field of study of cardiometabolic risk in the South Asian community.
Despite these limitations, our study has notable strengths. While previous studies have characterized mortality related to DM and ATH in Asian American populations using US death certificates [2, 8], to our knowledge, this is the first study to specifically examine DM and ATH clustering as contributing causes of death in AI versus Non-AI using the same mortality data. Our study findings also provide a more informed approach for physicians toward cardiometabolic disease prevention and health promotion in AI.