National high prevalence, and low awareness, treatment and control of dyslipidaemia among people aged 15–69 years in Mongolia in 2019

The aim of the study was to evaluate the prevalence, distribution and correlates of dyslipidaemia among people (15–69 years) in Mongolia. National data were analyzed from 4,895 individuals (15–69 years, median age = 35 years) that took part in the Mongolia cross-sectional STEPS survey in 2019, and had complete lipid measurements. Dyslipidaemia was defined using the guidelines of the Adult Treatment Panel III. The prevalence of dyslipidaemia was 58.6%, 31.7% high triglycerides (TG), 26.9% high low-density lipoprotein cholesterol (LDL-C), 26.9% high total cholesterol (TC) and 14.6% low high-density lipoprotein cholesterol (HDL-C). Among those with dyslipidaemia, 6.2% were aware. Among those who were aware, the proportion of lipid-lowering drug treatment was 18.9% and among those who took lipid-lowering drugs, 21.5% had their dyslipidaemia controlled. In adjusted logistic regression, older age (40–69 years) (AOR: 1.19, 95% CI 1.02–1.40), urban residence (AOR: 1.24, 95% CI 1.04–1.48), obesity call II (AOR: 2.89, 95% CI 2.29–3.66), hypertension (AOR: 1.33, 95% CI 1.11–1.59), and diabetes (AOR: 1.62, 95% CI 1.20–2.18) were positively, and male sex (AOR: 0.84, 95% CI 0.72–1.00) was negatively associated with dyslipidaemia prevalence. Six in ten Mongolians 15 years and older had dyslipidaemia. Several factors associated with dyslipidaemia that can be used to target public health interventions were identified.


Methods
Participants and procedures. Cross-sectional national data with complete lipid measurements from the 2019 Mongolia STEPS survey 18 were analyzed; the study response rate was 98.1% 19 . According to STEPS survey procedures, "Socio-demographic and behavioural information was collected in Step 1. Physical measurements such as height, weight, and blood pressure were collected in Step 2. Biochemical measurements were collected to assess blood glucose and cholesterol levels in Step 3. A multi-stage stratified sampling process (377 sampling units or clusters selected from 21 provinces and 9 districts of Ulaanbaatar) was carried out to randomly select participants from the target population. One individual within the age range of the survey (15-69 years) was selected per household. If the randomly selected individual had temporarily been out of the range of the survey clusters (soum/khoroo) during the whole period of the field work, he or she was excluded and re-sampling was conducted. Ethics approval was provided by the Ministry of Health Medical Ethical Committee, Mongolia, and written informed consent was obtained from all participants, including from a parent and/or legal guardian 18,19 . " All methods were performed in accordance with the relevant guidelines and regulations. Data collection followed the "WHO three STEPS methodology: step 1 included administration of a structured questionnaire (sociodemographics, medical history, medication use, and health risk behaviour) step 2 consisted of blood pressure and anthropometric measurements, and step 3 included biochemical tests (blood glucose and blood lipids) 18 . " Anthropometric measurements were taken using the "Somatometre-Stanley 04-116 device and electronic scales GIMA") 19 . Of the three blood pressure measurements using "OMRON Model M5 automatic blood pressure monitor 19 , " the last two readings were averaged 18 . "Blood glucose, total cholesterol and triglycerides were measured in peripheral (capillary) blood at the data collection site using dry chemical methods using multi-functional 'Prima home test' diagnostic device, biochemical analysis and automated analyzer 19 . " Serum samples were taken to analyze LDL and HDL cholesterol 19 . Laboratory analysis included blood glucose, TC, TG, HDL, and LDL. Laboratory tests for LDL and HDL in blood, were performed and analyzed in "Gyals" LLC's laboratory using biochemical automated analyzer. HDL and LDL content was measured in serum using a direct or two-point linear method 19 . Measures. Dyslipidaemia was classified 20 as: "being on antilipidemic medication or having one or more of the following: elevated total cholesterol (TC): ≥ 5.17 mmol/l (200 mg/dl), high triglycerides (TG): ≥ 1.70 mmol/l (150 mg/dl), low HDL-C: female ≤ 1.29 mmol/l; male ≤ 1.03 mmol/l (50 mg/dl in women, 40 mg/dl in men) and high LDL-C: ≥3.36 mmol/l (130 mg/dl). " The awareness rate of dyslipidaemia was defined as: "having been diagnosed by a health care provider as having high cholesterol among those with dyslipidaemia. The rate of dyslipidaemia treatment was defined as the self-reported use of lipid lowering drugs among participants who were aware of dyslipidaemia. The control rate of dyslipidaemia was classified as the proportion among those treated for dyslipidaemia who reach the lipid standard: TG < 1.70 mmol/L, TC < 5.18 mmol/L, HDL-C ≥ 1.04 mmol/L and LDL-C < 3.37 mmol/L 20 . " Other biological measures included measured central obesity ("waist circumference ≥ 90 cm in men, ≥ 80 cm in women") 21 ; measured Body Mass Index (BMI) (kg/m 2 ): "normal weight 18.5-22.9 kg/m 2 , underweight < 18.5 kg/ m 2 , overweight 23.0-24.9 kg/m 2 , obesity class I 24.9 kg/m 2 , − 29.9 kg/m 2 , and obesity class II ≥ 30.0 kg/m 222 ", Hypertension/raised blood pressure (BP): "systolic BP ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg or where the www.nature.com/scientificreports/ participant is currently on antihypertensive medication 23 . " Diabetes: "fasting plasma glucose levels ≥ 7.0 mmol/L (126 mg/dl); or using insulin or oral hypoglycaemic drugs; or having a history of diagnosis of diabetes 24 . " Behavioural measures included current tobacco use, current heavy episodic drinking ("six or more standard drinks in a single drinking occasion"), exposure to secondary smoke, daily consumption of fruits and vegetables, and low, moderate and high physical activity and sedentary behaviour (≥ 8 h/day) based on the "Global Physical Activity Questionnaire 25 . " Sociodemographic variables included age (years), sex (male, female), education in years, region, residence status, and ethnic group 19 .
History of CVDs included self-reported "Have you ever had a heart attack or chest pain from heart disease (angina) or a stroke (cerebrovascular accident or incident)? (Yes, No) 19 . " Data analysis. All statistical analyses were conducted with "STATA software version 14.0 (Stata Corporation, College Station, TX, USA). " "Analysis weights were calculated by taking the inverse of the probability of selection of each participant. These weights were adjusted for differences in the age-sex composition of the sample population as compared to the target population 19 . " Descriptive statistics are used to describe lipid profiles. Multivariable logistic regressions were used to assess the associations between sociodemographic (age, gender, education, and residence status) and health factors (BMI, hypertension, diabetes, cardiovascular disease, physical activity, sedentary behaviour, fruit/vegetable intake, current tobacco use, passive smoking, and heavy episodic drinking) and dyslipidaemia profiles as well as awareness and treatment. Afterward, significant variables in unadjusted analyses were included in the multivariate model. Covariates were selected based on previous literature review 2,6,8,[10][11][12][13][14][15][16][17] . To account for the multi-stage sample design, Taylor linearization methods were utilized. P-values < 0.05 were considered significant. Statistical analyses were computed with complete cases of lipid profile measurement. Of the 6654 total study sample, 4895 had complete measures of lipid profile. The 1759 excluded individuals with an incomplete lipid profile were more likely to be younger, but did not differ in terms of residence status, sex, educational level, and ethnicity. Furthermore, sensitivity testing was done using multiple imputation by chained equations to fully impute the dataset. The logistic regression with dyslipidaemia as outcome was conducted with complete imputed data and results were compared with complete case analyses results. The prevalence of dyslipidaemia was 58.6% (54.5% using the restricted lipid profile, including high TC, high TG, and low HDL-C), 26.9% high TC, 31.7% high TG, 26.9% high LDL-C and 14.6% low HDL-C. Among the five regions in Mongolia, the highest proportion of dyslipidaemia was found in the central region (63.4%) and Ulaanbaatar (61.8%) and the lowest in the western region (48.8%). Further sample characteristics are described in Table 1 (see Table 1).

Results
Distribution of dyslipidaemia awareness, treatment, and control. Among those with dyslipidaemia, 6.2% were aware. Among those who knew, the proportion of lipid-lowering drug treatment was 18.9%, and among those taking lipid-lowering drugs, 21.5% had their dyslipidaemia controlled (see Table 2).
Furthermore, testing the consistency of these results using multiple imputation of missing data in the dependent variable were explored. The direction and significance of the relationship between covariates and dyslipidaemia in the two models (complete cases: Table 3 and imputed model: Supplementary Table 1) were similar to except in sex, education, and heavy episodic drinking where the level of significance differed).
Associations with prevalence of dyslipidaemia subcategories. In the adjusted logistic regression analysis, older age was positively associated with high TC, high TG, and low HDL-C, and inversely associated with high LDL-C. Male sex was positively associated with high TC and low HDL-C, and negatively associated with high LDL-C. Higher education was associated with high TC, high TG, and low LDL-C. Belonging to the Khalkh ethnic group was positively associated with high LDL-C. Obesity was associated with the four dyslipidaemia subcategories. Hypertension increased the odds of high TC and low LDL-C, and diabetes increased the odds of high TG and high LDL-C. High physical activity reduced the odds high TC, high TG, and low LDL-C. Current tobacco use was positively associated with high TC, high TG, and high LDL-C, while heavy alcohol use was positively associated with high TG (see Table 4).

Associations with dyslipidaemia awareness and treatment.
In the adjusted logistic regression analysis, older age, higher education, urban residence, higher general body weight, hypertension, and cardiovascular disease were positively associated with dyslipidaemia awareness. Among those who were aware of their state of dyslipidaemia, belonging to the Khalkh ethnic group was positively associated and overweight or obesity class I was negatively associated with the treatment of dyslipidaemia (see Table 5).
Consistent with previous research 2,6,8,10-12 , older age, urban residence, obesity, hypertension and diabetes increased the odds of dyslipidaemia. Dyslipidaemia may increase with age because physical activity levels decrease leading to more fat accumulation 2 . Lifestyle changes, such as change in dietary and sedentary behaviour, may explain that with urbanization higher rates of dyslipidaemia were found 9,26 . The tendency to have a higher prevalence dyslipidaemia with higher levels of BMI can be attributed to "global metabolic effects of insulin resistance and an excess of visceral fat 27 . " A nutritional transition in Mongolia may have led to the found high prevalence of central obesity (56.7%) and high levels of body fat 28 , increasing the risk of dyslipidaemia.
Some studies in China 6,10 , found that male sex was positively associated with dyslipidaemia, while our study found a weak negative association between male sex and dyslipidaemia, mainly due to higher high TC and higher low HDL-C in men than women. We did not find a significant association between ethnicity and dyslipidaemia, Table 3. Associations with prevalence of dyslipidaemia. COR crude odds ratio, AOR adjusted odds ratio. ***p < 0.001; **p < 0.01; *p < 0.05. a All variables significant (p < 0.05) in unadjusted analyses were included in the adjusted model. www.nature.com/scientificreports/ contrary to some previous studies 10 . While some research 6 showed a positive association between cardiovascular diseasen] and dyslipidaemia, we did not find this association. In unadjusted analyzes we found that increased physical activity was negatively associated with the prevalence of dyslipidaemia, which is consistent with some previous research 2, 9 . Contrary to previous findings 2,10,13 , we did not find significant associations between tobacco use, passive smoking, alcohol use, and dyslipidaemia. Furthermore, we found regional differences in the prevalence and awareness of dyslipidaemia, such that prevalence and awareness was the lowest in the Western region (48.8%, and 3.3%, respectively) and among the highest in Ulaanbaatar (61.8%, and 8.5%, respectively). The role of geographic determinants of dyslipidaemia and awareness is important in designing effective intervention strategies 17 .
Factors associated with high TC in this study included older age, male sex, higher education, obesity, hypertension, physical inactivity, and current tobacco use. In previous studies 7,9,12,14,16 , older age, female sex, lower education, hypertension, diabetes, and obesity were associated with high TC. Factors associated with high TG in this study included older age, higher education, obesity, diabetes, physical inactivity, heavy episodic drinking, and current tobacco use. In previous studies 7,9,12,14 , male sex, higher education, hypertension, diabetes, obesity, and smoking or current tobacco use were associated with high TG. Factors associated with low HDL-C in this study included older age, male sex, higher education, obesity, hypertension, and physical inactivity. In previous studies, 7,14,15 decreased age, male sex, higher education, hypertension, diabetes, obesity, and smoking were associated with low HDL-C. Factors associated with high LDL-C in this study included lower age, female sex, Table 4. Associations with prevalence of dyslipidaemia subcategories. AOR adjusted odds ratio. ***p < 0.001; **p < 0.01; *p < 0.05.

Variable Subcategory
High  14 , hypertension, diabetes, and obesity were associated with high LDL-C. The prevalence of awareness of dyslipidaemia (6.2%), treatment (18.9%), and control (21.5%) were in terms of awareness and treatment lower than in the 35 LMIC study (31/36% and 29/33%, respectively) but higher in terms of control (7/19%) 5 . Awareness was also much lower than in China (31.0%) but treatment was similar to China (19.5%) and control was higher than in China (8.9%) 6 . In particular, the low awareness of dyslipidaemia emphasizes the need for opportunistic screening in Mongolia. Consistent with previous results 5,11,17 , older age, higher education, urban residence, obesity, hypertension, and cardiovascular disease were associated with increased awareness of dyslipidaemia in this study. The association between higher education, urban residence and higher awareness of dyslipidaemia may be explained by higher health literacy in urban educated Mongolians and better access to health care in urban settings 17 . The association between general obesity and awareness of dyslipidaemia may be attributed to lipids being part of weight management, yet overweight and obesity were negatively associated with dyslipidaemia treatment. Similar results were found for dyslipidaemia control in China, highlighting the greater difficulty of dyslipidaemia control among obese compared to people of normal weight 17 .
The strengths of the study include the use of a large nationally representative sample and standardized STEPS methodology and measures. Some variables were evaluated by self-report, which may have biased responses, and the cross-sectional design precludes causative conclusions between the evaluated variables. The sample was restricted to those with complete lipid measurements. The excluded participants were largely similar to those included in the analysis. We conducted additional analyses with imputed data, which provided similar results.

Conclusion
Six in ten Mongolians 15 years and older had dyslipidaemia. Several factors, including sociodemographic and health factors, were identified for dyslipidaemia. The high prevalence of dyslipidaemia in Mongolia warrants enhanced public health interventions, including screening, better diagnose, treat, and control dyslipidaemia.

Data availability
The data source is publicly available at the World Health Organization NCD Microdata Repository (URL: https:// extra net. who. int/ ncdsm icrod ata/ index. php/ catal og).