Prevalence of the Metabolic Syndrome and its determinants among Nepalese adults: Findings from a nationally representative cross-sectional study

Metabolic syndrome (MetS) increases the risk of cardiovascular diseases and diabetes mellitus. This study is designed to assess the prevalence and determinants of MetS among Nepalese adults from a nationally representative study. This study is based on Stepwise Approach to Surveillance (STEPS) Survey from Nepal. This survey was done among 4200 adults aged 15–69 years from 210 clusters selected proportionately across Nepal’s three ecological zones (Mountain, Hill and Terai). Subsequently, using systematic sampling, twenty households per cluster and one participant per household were selected. The overall prevalence of MetS is 15% and 16% according to Adult Treatment Panel III (ATP III) and International Diabetes Federation (IDF) criteria respectively. A triad of low HDL-C, abdominal obesity and high BP was the most prevalent (8.18%), followed by abdominal obesity, low HDL-C cholesterol and high triglycerides (8%). Less than two percent of participants had all the five components of the syndrome and 19% of participants had none. The prevalence steadily rose across the age group with adults aged 45–69 years having the highest prevalence (28–30%) and comparable prevalence across two definitions of MetS. A notably high burden for females, urban, hill or Terai resident were seen among other factors.


Results
This secondary-analysis of the data provided by the nationally representive survey (STEPS Survey), provides the first nationally representative prevalence of MetS among adult population of Nepal. A total of 3729 participants aged 15 to 69 years were assessed for physical and biochemical parameters. The prevalence of metabolic syndrome is 15% and 16% according to ATP III and IDF criteria respectively. Overall, 21% of participants had had three or more risk factors. The most predominant component of MetS in this population was low HDL cholesterol (71%), followed by high blood pressure (26%) and raised triglycerides (25%). A significantly high prevalence of abdominal obesity and low HDL cholesterol was observed among female participants; whereas raised triglycerides, fasting blood sugar and high blood pressure was observed among male participants (Table 1).
A triad of low HDL-C, abdominal obesity and high BP was the most prevalent constituting 8.2% of the total participants, followed by abdominal obesity, low HDL-C cholesterol and high triglycerides at 8% of participants. Less than two percent of participants had all the five components of the syndrome (Table 1). Only 19% of participants had zero risk factors (Fig. 1). Table 2 presents the independent effect of various covariates on the clustering of MetS components at the individual level using multivariate Poisson regression. The age, education, caste/ethnicity, abnormal waist hip ratio, BMI and place of residence were independently associated with the number of MetS components. Moreover, the cumulative risk of having x number of MetS risk factors or more versus having fewer were 1.28 times higher among participants aged 30-44 years and 1.52 times higher among participants aged 45-69 years compared to 15-29 years. The cumulative risks increased with increase in age and educational level. Participants those who resides in urban areas were 1.13 times more likely to have x or more risk factors compared to rural residence. Table 3 presents prevalence of MetS assessed using ATP III and IDF criteria. The prevalence was higher among participants aged 45 to 69 years, those who do not have formal education, widowed/divorced/separated, belongs to religious minorities, those who resides in hilly region, and among urban dwellers. Likewise, the higher prevalence was also observed among participants who had abnormal waist hip ratio, and were obese [BMI ≥ 30 kg/m 2 ]. The differences in the prevalence of the MetS using ATP III and IDF criteria can be demonstrated by data from the study. Although both the definition identified approximately 16% of the population as having the MetS, there was a large variability and only 10% of individuals met the criteria for both the definitions (Fig. 2). .60) compared to those who had <25 kg/m 2 BMI. Also, compared to participants who resides in mountains, the higher likelihood of occurrence among the residence who resides in Terai/the plain (AOR: 2.64; 95% CI: 1.14-6.11) and hill (AOR: 2.41; 95% CI: 1.04-5.63). The higher odds of occurrence of MetS was observed among urban dwellers (AOR: 1.56; 95% CI: 1.14-2.13) compared to rural dwellers.

Discussion
This secondary-analysis of the data provided by the nationally represented survey (STEPS Survey), provides the first nationally representative estimates on prevalence, disaggregated by sub-groups, and factors attributed to MetS among adult population of Nepal. The overall prevalence of metabolic syndrome is 15% and 16% according to ATP III and IDF criteria respectively. Based on our findings, the Nepalese population appears to have a relatively lower burden of MetS compared to overall burden of MetS in South Asia (ATPIII 26.1% and IDF 29.8%) reported by a systematic review 15 . A triad of central obesity, low HDL-C, and elevated BP was the most prevalent (8.2%) combination of CVD risk factors constituting the syndrome in this population. This was followed by a triad of CVD risk factors, namely central obesity, low HDL-C and elevated triglycerides found in 7.8% of the total participants. The most common MetS component was low HDL cholesterol.
In a multivariable analysis, the risk of MetS increased steadily with age: participants aged 45-69 were 7.08 (ATP III) and 4.52 (IDF) times more likely to suffer from MetS than those who were in the age group 15-29 years. Similar findings were also seen with BMI: participants with BMI ≥ 30 kg/m 2 were 9.44 (ATP III) and 14.03 (IDF) times more likely to suffer from MetS than those who had BMI < 25 kg/m 2 . The prevalence of MetS is higher in females compared to males in Nepal. The association with age, sex and BMI were consistent with previous studies from different countries 13,16,17 . People living in urban areas were twice more likely to develop MetS compared to rural residents. This might be due to sedentary lifestyles, dietary changes and stress in urban people.
The association of MetS with low physical activity was inconsistent with increased odds of 1.48 and decreased odds of 0.93 according to ATP III and IDP criteria respectively. However, some epidemiologic studies and uncontrolled trials have suggested that increased moderate-to-vigorous physical activity reduces the incidence or prevalence of the MetS 18-21 . Insufficient fruit and vegetable intake and cigarette smoking increased the odds of developing MetS in this study. Consumption of fruits and vegetables has been found to reduce diastolic blood pressure 22 and risk of type II diabetes mellitus 23 and may therefore reduce the risk of MetS. Current smoking was not-significantly associated with lower risk of MetS in our study. Existing evidence for association of MetS with cigarette smoking is inconsistent as well [24][25][26] . In our study, there was inconsistent evidence of association of alcohol intake and MetS with increased risk according to ATP III criteria and reduced risk according to IDP criteria. Various studies have shown that drinking alcohol is harmful at higher doses however, light to moderate doses is beneficial to health and reduces risk of coronary heart disease, diabetes, stroke and total mortality in adults [27][28][29] . A recent academic paper by international experts recommended lifestyle changes comprising of increased intake of fruits and vegetables, quitting smoking, moderate consumption of alcohol and physical activity to prevent MetS and improve cardio metabolic health 30 .
South Asians have a propensity towards less lean muscle mass and more visceral fat mass at a lower BMI and waist circumference compared to western population who tend to carry much of their weight in muscle and subcutaneous fat depots peripherally 31,32 . Thus South Asians with same body mass index are be at higher risk for metabolic syndrome compared to their western counterparts 33 . Moreover, comorbid diseases, including T2DM, occur at lower waist circumference in Asian adults 34 . Thus, ATP III might result in low prevalence figures  Continued in Nepalese population due to use of non-specific cut-offs for waist circumference. Moreover, waist circumference is used as only optimal component in ATP III. IDF criteria with waist circumference thresholds specific to Asian population (men 90 cm and women 80 cm) might be therefore more suitable for estimation of metabolic syndrome among adult Nepalese population. Much of the health care priorities to date in low and middle income countries, including Nepal has been catering to infectious diseases and maternal and child health. A high burden of MetS as we demonstrated in our study and confirmed by other small studies from non-specialist hospital setting necessitates acknowledging the importance of reducing NCD risk factors at population level. The primary goal should be creating environment that facilitates greater physical activity and awareness regarding healthy dietary choices. In addition, the health systems need to be strengthened to reach the populations that are at risk for NCDs. Additionally, alternate models for service delivery and health promotion should be considered to reach unprivileged population with limited access to health care services. These may include mobilization of community health volunteers and mass media campaigns aimed at changing risky lifestyle behaviors.
Nationally, representative data are limited in Nepal and prevalence figures in the earlier studies were estimated using non-comparable sampling design in a section of population. This study is based on a large national sample consisting of both urban and rural populations in Nepal. However, as in any cross-sectional study, we could not establish causality between metabolic syndrome and its determinants. The South Asian population have been shown to be genetically susceptible to central obesity and insulin resistance 35 . However, the absence of genetic studies in Nepal have limited our understanding of the role of genetic factors in the pathogenesis of metabolic syndrome among Nepalese adults. The STEPS survey did not include information on household wealth or monthly income of participants hence an important determinant of metabolic syndrome could not be assessed among Nepalese population in this study.

Conclusion
Our study demonstrates a high burden of MetS in Nepalese adults with ten percentage increment in prevalence across each age groups fifteen years apart. The prevalence peaked among those aged 45-69 years such as three in ten in this age-group had MetS. A substantial clustering of risk factors was evident with 80.7% having at least one risk factor. A triad of low HDL-C, abdominal obesity and high BP was the most prevalent (8.18%), followed by abdominal obesity, low HDL-C cholesterol and high triglycerides (8%). Female gender, urban, hill or terai resident were particularly at risk.

Study design and sampling technique. This is a secondary analysis carried out using Non-Communicable
Diseases risk factors 2013 data. The detail methodology and report of the survey has been presented elsewhere 36 . In brief, the survey was a cross sectional study, carried out from January to June 2013, with aim to assesses the risk factors of NCDs at entire population level.  Table 3. Prevalence of metabolic syndrome by demographic and clinical risk factors. Firstly, out of the 921 Ilakas (an administrative unit at the sub-district level) in Nepal, 70 were selected, which were proportionately distributed across Nepal's three ecological zones (Mountain, Hill and Terai/Plains) using probability proportionate to population size (PPS) which served as a primary sampling unit (PSU) of the study. Survey implementation. A total of 26 researchers divided into 2 teams were assigned for data collection.
Each team was composed of field supervisor, medical laboratory technologist, laboratory technician one each, and ten enumerators having nursing, public health or paramedics background. Their major responsibility was to fill out the questionnaires, carry out physical measurements and collect blood samples. The laboratory technicians were assigned for cold chain maintenance, sample processing, and the recording and reporting of biochemical measurements carried out using wet methods. Medical laboratory technologists were responsible for examining and verifying glucose levels and the value of the lipid profile including sending a 10% blood sample to the reference laboratory for external quality control.

Physical measurements
Height and weight were measured and body mass index (BMI) calculated as weight (kg.)/height (m 2 ). Portable standard stature scale was used to measure height. Footwear (shoes, slippers, sandals) and hat were removed while measuring height. Respondents stood on a flat surface facing the interviewer with their feet together and heels against the backboard with knees straight. They were asked to look straight ahead and not tilt their head up, making sure that their eyes were at the same level as their ears. Height was recorded in centimetres. Weight was measured with a portable digital weighing scale (Seca, Germany). The instrument was placed on a firm, flat surface. Participants were requested to remove their footwear and socks, wear light clothes, stand on the scale with one foot on each side of the scale, face forward, place arms at their side and wait until asked to step off. Waist and hip circumference was measured using constant tension tapes (Seca, Germany) in centimeters 37 .

Blood Pressure measurements
Blood pressure was measured with a digital, automated blood pressure monitor (OMRON digital device) with medium cuff. Before taking the measurements, participants were asked to sit quietly and rest for 15 minutes with legs uncrossed. Three readings of the systolic and diastolic blood pressure were obtained using standard protocol. Participants rested for three minutes between each reading. The mean of the second and third readings was calculated.
High blood pressure was defined as having systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥85 mm Hg during the study, or being previously diagnosed as having hypertension determined by sighting documentation such as a treatment record book or by the history of the participant taking medicine for high blood pressure.

Biochemical measurements
A separate mobile laboratory setting was used to collect biochemical data. The mobile laboratory contained all of the logistics and human resources required for the set up including a semi auto analyser and all of the chemicals required for blood glucose testing and lipid profile measurement. To ensure that the cold chain was maintained for the collected samples and for the preservation of the chemicals used for the tests, continuous electricity was ensured with an electric generator and refrigerator. Participants were instructed to fast overnight for 12 hours and diabetic patients on medication were reminded to bring their medicine/insulin with them and take their medicine after providing the blood sample to measure fasting glucose. Wet (liquid) method was used to measure blood lipids. A venous blood sample (4 ml of blood) was taken using a flashback needle with an aseptic technique and kept in plain and fluoride treated tubes. Those samples were kept in an ice pack carrier and brought to the mobile laboratory within an hour. Biochemical measurements of blood glucose and lipids were done using semi-automated procedures (Bioanalyzer, Analyticon, Germany) and commercially available kits (Analyticon, Germany). Plasma glucose was estimated using the GOD-PAP (glucose oxidase/peroxidise -phenol-4-amenophenazone) method. Serum triglycerides were estimated using the GPO-PAP (glycerol-3-phosphate oxidase/peroxidase-4-chlorophenol and 4-aminophenazone) method. HDL cholesterol was determined using the CHOD-PAP (cholesteroloxidase/peroxidase -4-phenol-aminoantipyrine) method 36 . External quality control of these biochemical investigations was performed by sending 10% of the samples to the nearest reference laboratory with standardized fully-automated procedures for biochemical measurement.

Harmful Alcohol consumption
Detailed information on number of standard drinks consumed and frequency of consuming standard drinks in the last 30 days was obtained from current users. One standard drinks was considered as 10 grams of ethanol, the number of standard drinks was calculated using the amount consumed by participants.

Insufficient fruits and vegetable intake
Information on fruit and vegetables consumption in a typical week. Also, the number of servings of fruit and vegetables consumed on average per day. The amount of fruit and vegetables was measured using pictorial show cards and measuring cups (one standard serving of fruit or vegetables equals 80 grams).

Low Physical activity
Global Physical Activity Questionnaire (GPAQ) was used to assess physical activities 39 . The GPAQ asks participants about activities for vigorous and moderate activity at work, and vigorous and moderate activity in leisure time and time spent sitting. Culturally relevant Show-cards with examples were used to classifying activities. Physical activity related to transport and recreation and time spent in sedentary behaviour were also assessed. Physical activity related to transport included travel to work or market by walking or using a bicycle. Recreational activity included two types of activities based on severity, i.e., vigorous and moderate. Vigorous recreational activity was defined as any recreational activity that causes a large increase in heart rate and breathing; for example, games such as football, fast swimming and rapid cycling. Ten minutes of such activity was considered as involvement in vigorous recreational activity. Moderate recreational activity was defined as any kind of recreational activity that causes a moderate increase in heart rate and breathing; examples include yoga and playing basketball. Sedentary behaviour was defined as a behaviour where an individual spends time sitting at a desk, sitting with friends, travelling in a car, bus or train, reading a book, and so on. Analysis and categorization followed existing guidelines 40,41 and the low physical activities were categorized to those who did not meet the criteria for vigorous and moderate intensity activities.
Abnormal waist to hip ratio 42 Abnormal waist to hip ratio is defined as a waist-hip ratio >0.90 for males and >0.85 for females. A week-long training was organised in the two weeks prior to the beginning of data collection. The training was led by a STEPS team from WHO headquarters, Geneva and WHO SEARO, New Delhi. The local investigator team also joined the STEPS team as trainers. Prior to the training, the data collection team were oriented on the tools to be used to collect the data. Training focused on interview techniques, sampling process, household and individual selection, the use of the different kinds of templates and forms in the survey, the use and care of PDAs, a detailed explanation of the questionnaire and the technique to be used for physical measurements. The supervisors were also trained on downloading data from the PDAs as well as the troubleshooting of minor issues with the PDAs.
Overall, field operation and quality control was responsibility of field supervisor including coordinate with respective authorities at the field level, ensure completion of sampling frames, and select 20 households from each cluster. Also, the field supervisors were responsible for aggregating the data from individual PDAs to their laptop and forwarding them to the centre via email or by handing them over to the investigators.
Definition of variables. The dependent variable in this analysis was occurrence of metabolic syndrome. The indicators analysed in this study are defined in Table 5. Two major predictor variables were included: individual characteristics: age in years (15-29, 30-44 and 45-69), gender (male and female), education (no formal schooling, primary, secondary and higher level), marital status (never married, currently married and divorced/widowed/separated) and caste/ethnicity, and community characteristics: ecological zone (mountain, hill and terai/ plains) and place of residence (urban and rural) in this analysis.
Data processing and analysis. In order to obtain nationally representative estimates, the sampling weights were used. Chi-square statistics was used to assess the difference in risk factors by gender. To reflect clustering within individuals, we considered the number of risk factors that each participant had at the time of the survey (from 0 to 5) and examined the mean number and 95%CIs of risk factors by covariates. We examined the independent effects of covariates on risk factor clustering within individuals by modeling a multivariate Poisson regression model, with the number of risk factors as the dependent variable. All the analysis carried out was using complex survey design; wards were considered as cluster and ecological zones as strata.
Univariate and multivariate logistic regression were used to test associations between predictors and outcome variables using Stata SE 14. Adjusted odd ratio (AOR) was calculated using multiple logistic regression, with all predictors (age, gender, education, marital status, ecological zone and place of residence) included simultaneously in the model in order to assess the predictors of MetS. A p-value < 0.05 was considered as statistically significant.

Ethical Considerations. This study was approved by the ethical review board of the Nepal Health Research
Council. An informed written consent was obtained from all the participants. For the participants under the age of 18 years, informed consent from parent/legal guardian was obtained. Waste generated during the laboratory procedures was properly disinfected using aseptic techniques and safely disposed as per protocol. Blood samples were discarded after the biochemical measurements.