Were US Asian Indian decedents with atherosclerosis more likely to have concurrent diabetes mellitus? Analysis of national multiple cause of mortality data (2012–2019)

In this study, we have shown that DM and ATH cluster as contributing causes of death more strongly in AI than Non-AI. We also found that the difference in the fraction of deaths with DM when ATH was 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). However, DM is rarely the primary cause of mortality; it is more likely to be an antecedent to vascular dysfunction, which can directly cause death [20]. In this context, our second finding, though only in mortality data, could be interpreted as follows: 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 Non-AI. This contribution was significant for all age groups studied, both men and women. However, the excess contribution of DM in ATH-related deaths in AI was mainly higher among women than men of the same age group, and this difference was most apparent at age ≤ 60.

Our findings are in line with current literature that suggests the existence of excess dual burden of ATH and DM in AI versus 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. In this study, for any US race/ ethnic group with pre-existing diabetes free from cardiovascular disease at the time initial evaluation, the highest predicted probability for incident coronary artery calcium deposition, a marker of subclinical atherosclerosis, was observed in South Asians [21]. Our first finding takes this understanding further by quantitating the excess joint burden of ATH and DM as contributing causes of deaths in AI versus Non-AI.

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; however, these contrast with a recent observation by Satish et al., who pooled data using self-reported questionnaires [22]. As several AI were potentially underdiagnosed 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 [22]. 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. Of note, the largest disparities due to poorer healthcare access to immigrants in the US are in the metabolic control of DM and ATH [23]. Poor healthcare access compounds the risk of undetected DM and ATH progression in AI, who are already genetically predisposed. In addition, their lower physical activity levels and culturally derived dietary practices further fuel the risk of developing these two cardiometabolic co-morbidities [8].

Our second finding is that the excess contribution of DM as a co-occurring cause of death in ATH-related versus ATH-unrelated deaths is most apparent in younger AI women (age ≤ 60). This finding is consistent with prior reports that the association between DM and mortality is generally higher in females and at younger ages [15, 24] and is most pronounced in AI women [2].

Our study has a major clinical implication in line with a recent observation by Coles et al. [25]. Whether DM itself incites the increased ATH mortality in AI or if it is the combined effect of the ‘Asian Indian phenotype’ (‘South Asian phenotype’) and DM is not presently known. Until future studies establish that association, 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 [24]. 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 could not 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.

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