This descriptive study is an outcome of an opportunistic Risk Factor Screening (RFS) for NCDs, obesity, and HTN at the Health Promotion Unit of a tertiary Eye and ENT hospital in Bhaktapur, Nepal.
The overall prevalence of obesity using BMI in this study was 16.09%, which is higher than obesity prevalence reported in the 2019 NCD Risk Factors STEPS survey Nepal, where only 5.42% of the same age-group were reported be obese . This might be due to the study setting's difference as this study was done in semi-urban area of Kathmandu valley, whereas STEP survey covered both urban and rural areas. Additionally, using BMI, we found that more than two in ten (21.40%) women and nearly one in ten (9.60%) men coming to the hospital were obese, which is nearly double the previously reported values in the Nepal DHS survey of 2016, for both genders (women: 9.5% and men: 5.1%) . Again, these are not comparable because of the different settings in which these studies were done and also different parameters used.
Using International Diabetes Federation recommended cutoff points for south Asians  (male 90 cm and female 80 cm) for WC, two-thirds (66.76%) of participants were found to be obese as opposed to only 16.09% measured with BMI. More than three-quarters (77.46%) of women and over half (53.73%) of men were obese in our study.
The overall prevalence of abdominal obesity by WHtR was 32.76%, with higher prevalence among women (40.1%) than men (23.8%). This indicates that obesity measured by WHtR missed a significant proportion of the most important CVD risk factor. Also, WC was able to detect more obesity cases than either BMI or WHtR proving itself superior to the other two metrics.
The observed higher prevalence of body fat in women than men, using all three obesity metrics in our study, is supported by other studies [17, 25, 28]. The reported increase in abdominal obesity with each pregnancy independent of total body fat  may explain higher abdominal obesity among women.
Regardless of the metrics used, this study shows a higher prevalence of obesity among Hospital OPD patients, indicating that screening for obesity in this setting has a higher potential to detect a larger number of people with obesity than in community settings; the latter is however, essential for population-based data.
The higher prevalence of obesity in the present study may be due to study design, a selection bias as people reporting to hospitals may also have some or other conditions which could have obesity at the background of their illness. Examined within the larger context of non-utilization of health services, these people may be the ones with better health-seeking behavior, therefore, not truly representative of the community. However, the fact that hospitals draw visitors from their local community would confirm the presence of a high prevalence of this risk factor in the local community. This would need to be confirmed through multi-centric studies in different regions.
To the best of our knowledge, this is the first hospital OPD based data on obesity prevalence from Nepal.
The prevalence of HTN in our study was 40.67%, and men had a slightly higher prevalence of HTN (42.72%) than women (39.00%). Our findings are comparable to the 2019 STEPS survey Nepal and 2016 Nepal DHS, where the prevalence of HTN was 40.91% and 32.6%, respectively . In the present study and the other two nation-wide surveys, the prevalence of HTN increased with increasing age. One in three participants with pre-HTN detected in this study would be an important finding indicating the possible group of patients who could turn into hypertensive in near future if not intervened. A disturbing finding of this study was that 57.6% of hypertensive patients, who presumably had betterhealth-seeking behavior, didn’t know that they had raised BP before this study. This should alert hospital leaders to launch health promotion programs to raise awareness about HTN in hospitals and their surrounding community.
Although the prevalence of obesity was higher in the present study than nation-wide survey; however, the prevalence of HTN is almost similar to community-based national surveys. Obesity is an earlier event in the evolution of HTN, which develops over a period of time with progressive deposition of atheromatous materials in the blood vessels of people who, by and large, have increased body fat, although HTN can occur in thin people as well. It would, therefore be reasonable to assume that obesity is a precursor of non-genetic HTN and therefore develops earlier than HTN. In this regard, we propose to follow a cohort of our participants who have obesity but did not have raised BP.
At our hospital, we refer persons found to be overweight or obese to a counselor in the next room who advises them for appropriate life style modifications and if necessary, refers to Exercise Medicine unit and to an in-house General Practitioner for any associated disease conditions.
Obesity and Hypertension
In the present study, using all metrics, a significantly higher prevalence of HTN was found among participants with either overweight or obesity compared to participants with normal weight. Also, WC participants greater than the cutoff value were twice (2.02; 95% CI: 1.66-2.45) likely to be hypertensive than people with normal WC. This is supported by several studies in different countries (Italy, USA, India) [52-55].
In the present study, we found a statistically significant positive correlation between all the anthropometric metrics and both SBP and DBP. The present study findings are in agreement with other studies with different populations which support a strong relationship between different obesity metrics and BP across developed and developing countries. The Olivetti Heart Study also showed a weak, but significant and positive correlation between WC and SBP (r = 0.191, P < 0.001), and DBP (r = 0.166, P < 0.001) as well .
An important ﬁnding of the present study is that while BMI, WC, and WHtR were all predictors of HTN, WC was the best predictor overall and BMI the least, WHtR being better predictor for males. However, WC was better for females, both genders combined, and the age-group in the present study. Other studies have also shown that both WC or WHtR is a better predictor for HTN than BMI. A Brazilian cohort study also showed that WC and WHtR were better predictors of HTN in adults over 18, with an AUC value of 0.66 and 0.64, respectively, while BMI was 0.62. However, the associations were only significant for women as in our study . The study in India showed AUC values as 0.694, 0.667 and 0.634 for WHtR, WC and BMI respectively . The study done in eastern India also showed AUC values of BMI, WC, and WHtR were 0.654, 0.676, and 0.693, respectively, indicating WC and WHtR as a better predictor for HTN than BMI 
The greater value of this study lies in its ability to signal out very high prevalence of obesity and HTN in people coming to a tertiary care hospital, that is being missed on a day to day basis in clinical setting of busy hospitals of LMIcs.
Limitations of the study
Although prospective, this is still a single-center, observational, cross-sectional study design, hence a causal relationship between an increase in weight over the optimal level and raised BP. The study was performed with the limited objective of finding an inexpensive, simple enough measure of obesity which could be conducted by even non-medical personnel.