Anthropometric indicators as predictors of high blood pressure among the Ao tribe of North-East India

Abstract

Objective: Hypertension is related to increased body fat, which can be evaluated by anthropometric indicators among the Aos, a tribe of North-East India. Methods: Cross-sectional study with a sample of 1804 Ao adults (male= 890) (females= 914) aged 18 to 70 years. We considered the following anthropometric indicators: body mass index, waist circumference, waist-tohip ratio and waist-to-stature ratio. To identify predictors of high blood pressure, we adopted the analysis of receiver operating characteristic curves with a confidence interval of 95%. Result: For males, the area under curve with confidence intervals were BMI = 0.691 (0.67-0.712); waist circumference=0.757 (0.739-0.775); waist-to-hip ratio=0.692 (0.671-0.713); waist-to-stature ratio = 0.763 (0.745-0.781) and Conicity index = 0.734 (0.716-0.716). For females, the values were BMI = 0.754 (0.732-0.776); waist circumference = 0.762 (0.74-0.784); waist-to-hip ratio = 0.690 (0.668-0.784), waist-to-stature ratio=0.776 (0.753-0.799) and Conicity index=0.722 (0.701-0.743). Different cut off points of anthropometric indicators with better predictive power and their relevant sensitivities and specificities were identified. Conclusion: BMI does not show a very good area under the ROC curve. It seems that waist-to-stature ratio is the best predictor, followed by waist circumference and Conicity index among the males and results in high sensitivity and specificity to hypertension. We suggest the use of both waistto- stature ratio and waist circumference to predict hypertension among males. Among females, waist-to-stature ratio is the best predictor, followed by waist circumference and body mass index. DOI: http://dx.doi.org/10.3126/ajms.v4i3.6275 Asian Journal of Medical Sciences 4(2013) 15-22

Prevalence of hypertension among the indigenous population in North‐East India: Is this a consequence of “nutritional transition”?

“…Appallingly, high prevalence of obesity and hypertension were observed in both Angami males and females across the urban–rural residential areas. Similar high prevalence of non‐communicable disease (NCD) risk factors like obesity and hypertension were reported from the neighboring populations of northeast India, such as Mishing of Assam (Misra et al, 2014), Hmars of Manipur (Lalnuneng, 2022; Lalnuneng & Khongsdier, 2017), tribal population of Mokokchung, Nagaland (Tushi et al, 2018), Tangkhul Naga of Manipur (Mungreiphy et al, 2011), Ao of Mokokchung District, Nagaland (Maken & Varte, 2013), but not among the Rongmei Naga of Manipur (Riamei & Ghosh, 2019). In addition, several recent studies have also reported prevalence of NCD risk factors in tribal populations residing in other part of India (Kandpal et al, 2016; Kshatriya & Acharya, 2016; Reddy & Pranavchand, 2019; Sajeev & Soman, 2018).…”

“…In that case, what could be the reason behind the growing predominance of CVD risk factors among the indigenous populations of northeast India? Several studies have reported prevalence of CVD risk factors in northeast India (Lalnuneng, 2022; Lalnuneng & Khongsdier, 2017; Maken & Varte, 2013; Misra et al, 2014; Mungreiphy et al, 2011; Tushi et al, 2018), where the prevalence is even greater than the national average (IIPS, 2017). Perhaps, we should try to understand this prevalence from an evolutionary view point.…”

“…More specifically, although over‐nutrition is clearly central to the obesity epidemic, the contribution of early‐life under‐nutrition may trigger elevated obesity susceptibility in several populations (Wells, 2012), as mentioned earlier. In this context, indigenous populations of northeast India might provide a classic example of such adaptive mechanism due to nutritional transition and intensified in their predominance of adiposity (Lalnuneng, 2022; Lalnuneng & Khongsdier, 2017; Maken & Varte, 2013; Misra et al, 2014; Mungreiphy et al, 2011; Tushi et al, 2018). In this backdrop, the present study aims to examine prevalence of obesity and hypertension among adult Angami Naga of Nagaland, with special emphasis on the urban‐ rural dichotomy.…”

Prevalence of obesity and hypertension among the adult Angami Naga of Nagaland, Northeast India

“…Several recent studies, in this regard, have reported on the prevalence of NCD risk factors in tribal populations residing in different parts of India (Kandpal et al 2016;Kshatriya et al 2016;Sajeev and Soman 2018;Tripathi 2020). Furthermore, a high prevalence of NCD risk factors like obesity and hypertension was also reported from the neighboring populations of North-East India, such as the Padam (Adi) of Arunachal Pradesh (Limbu and Khual 2020), the Mishing of Assam (Misra et al 2014), the Hmars of Manipur (Lalnuneng and Khongsdier 2017), the tribal populations of Mokokchung, Nagaland (Tushi et al 2018), Tangkhul Naga of Manipur (Mungreiphy et al 2011), and the Ao of the Mokokchung District, Nagaland (Maken and Varte 2013). It is alarming to note that indigenous or tribal populations, including the present population, who were known for undernutrition, now suffer from NCD risk factors like obesity and hypertension.…”

“…The National Family Health Survey (NFHS-4) reported that for both males and females, the North-Eastern states (except Meghalaya for men) have a higher prevalence of hypertension than the national average (IIPS and ICF 2017). More specifically, studies among the North-East Indians have reported a high prevalence of hypertension and obesity in different tribal populations of the region (Khual and Limbu 2019;Lalnuneng 2022;Limbu and Khual 2020;Maken and Varte 2013;Marbaniang et al 2021;Meshram et al 2021) which according to these studies may be because of the impact of urbanization and modernization processes that have led to a major transition in diet and lifestyle of many tribal communities. This is in contradiction with the studies reported on the tribal or indigenous populations of other parts of India, who are known for a prevalence of undernutrition and CED (Bose et al 2006;Chakrabarty and Bharati 2010;Das et al 2008;Ghosh and Bhatrati 2005;Ghosh 2017;Mittal and Srivastava 2006).…”