Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016.

BACKGROUND: Individuals with metabolic syndrome are five times more susceptible to chronic diseases. Assessment of its magnitude, components, and risk factors is essentials to deploy visible interventions needed to avoid further complications. The study aimed to assess magnitude, components, and predictors of metabolic syndrome in Tigray region northern Ethiopia, 2016.
METHODS: Data were reviewed from Tigray region NCDs STEPs survey data base between May to June 2016. A total of 1476 adults aged 18-64 years were enrolled for the study. Multi-variable regression analysis was performed to estimate the net effect of size to risk factors associated with metabolic syndrome. Statistical significance was declared at p-value of ≤0.05 at 95% confidence interval (CI) for an adjusted odds ratio (AOR).
RESULTS: The study revealed that unadjusted and adjusted prevalence rate of Metabolic Syndrome (MetS) were (CPR = 33.79%; 95%CI: 31.29%-36.36%) and (APR = 34.2%; 95% CI: 30.31%-38.06%) respectively. The most prevalent MetS component was low HDL concentration (CPR = 70.91%; 95%CI: 68.47%-73.27%) and (APR = 70.61; 95%CI; 67.17-74.05). While; high fasting blood glucose (CPR = 20.01% (95%CI: 18.03-22.12) and (APR = 21.72; 95%CI; 18.41-25.03) was the least ones. Eating vegetables four days a week, (AOR = 3.69, 95%CI; 1.33-10.22), a salt sauce added in the food some times (AOR = 5.06, 95%CI; 2.07-12.34), overweight (AOR = 24.28, 95%CI; 10.08-58.47] and obesity (AOR = 38.81; 12.20-111.04) had strong association with MetS.
CONCLUSION: The magnitude of metabolic syndrome was found to be close to the national estimate. Community awareness on life style modification based on identified MetS components and risk factors is needed to avoid further complications.

Introduction

Metabolic syndrome (MetS) has received much attention in recent times. It is a cluster of cardiovascular risk factors in the tune of abdominal obesity, hyperglycemia, dyslipidemia and high blood pressure [1-3]. Globally, adult population having MetS ranged from 20–25%. Individuals with metabolic syndrome are five times more susceptible to chronic diseases [3-6] and becoming an important cause of morbidity and mortality in Africa. Pieces of evidences suggested that contributing factors were rapid demographic transition, changing behaviors, and lifestyles [2-5]. The high MetS prevalence was observed in Africa ranged from 17–25% [7]. In particular; North—Western Nigeria (35.1%), South Africa (21.8%), Morocco (35.4%), and Cameroon (38.9%) [8-11].

However, in Sub-Saharan Africa (SSA) its prevalence will be 59% to 179% in 2030 [2-5]. Even though most of the studies on MetS were conducted in North America, Europe, and Asia [12-14], its impact was high in sub-Saharan African; like Kenya (25.6%), and Tanzania (38%) [15-17].

In Ethiopia the change in lifestyle due to the current rapid economic growth increased the burden of MetS [18] with an overall pooled prevalence of 20.3% [18]. Accordingly, evidence from adult treatment panel (ATP III) and international diabetic federation (IDF) showed prevalence of 12.5% and 17.9% [19-21].

Considering the literature gap on MetS prevalence and risk factors, the study aimed to assess the prevalence, components and predictors of metabolic syndrome. The evidence will use as a preliminary report to estimate the epidemiology of metabolic syndrome that will be used to promote health promotion and prevention activities for life style modification and action towards metabolic syndrome control and management.

Materials and methods

Design and setting

The study involved a community based cross-sectional study design. It was conducted in Tigray region Northern Ethiopia located 802KMs from Addis Ababa, the administrative capital city of Ethiopia [22]. Tigray region is the homeland of the Tigrayan, Irob and Kunama peoples. Tigray is also known as Region 1 according to the federal constitution. Its capital and largest city is Mekelle. Tigray norther Ethiopia is the 5th largest by area, the 5th most populous, and the 5th most densely populated of the 10 Regional States. Estimated total population is 7,070,260 [22] The region is further administratively subdivided into seven zones, namely, East, South, South East, Western, Northwestern, Central, and Mekelle which contained the smallest administrative units of 52 districts (34 rural and 18 urban). The study period was between May to June 2016.

Exclusion criteria

Pregnant women and critically ill patients were excluded from the study.

Sampling and sample size determination

As this study was part of previously published work [22], further details on the sampling technique, data collection procedure were described there. The study subjects were respondents with age categories between 18–64 years. Data were obtained from the 2016 regional STEPs survey data base (S1 Dataset). Sample size was calculated using single proportion formula; where Z-score Z α /2 = 1.96 at 95% confidence level (CL), a margin of error (d) = 5% (0.05) and assuming MetS prevalence of 18.9% (0.189) [19].

The total sample size was 250 by considering a 10% non-response rate. But we included 1476 respondents that had complete list of variables in the data base.

Data collection

Data collection was carried out using a standardized questionnaire (S1 File) adopted from WHO (STEPS) instrument with slight modifications. Items had strong internal consistency (α = 0.925) [23]. Initially, the tool was prepared in English and translated into Tigrigna (local language).Three male and five female nurses with college degree and at least five-year clinical experience were recruited as data collectors. They were trained for five days on interview skills, the standard physical measurements following the WHO guideline, and blood test procedures using portable analysers. During the training, the eight data collectors conducted interviews, physical measurements, and blood tests to each two volunteers. The survey procedure was modified according to the feedback of data collectors and volunteers during the training. Two supervisors monitored the quality of the data collection. The time taken for each interview was 15 minutes. The study protocol was reviewed and approved by Mekelle University School of Public Health ethical review board. Permission was also received from Tigray Regional Health Bureau and respective health facilities. Similarly, data collection was conducted if and only if an informed consent was approved from study participant.

Measurement and classification

After measuring each variable, the classification of MetS risk factors was made based on the cut-off values of diagnosis reference of National Heart, Lung, and Blood Institute (NHLBI) [21, 24–27].

Operational definitions

A waist circumference (WC)

Waist circumference of 35 inches or more for women or 40 for men.

A triglyceride level

Triglyceride level of 150 mg/dl or higher or being on medicine to treat high triglycerides.

Cholesterol (HDL-C)

Sometimes is called "good" cholesterol with a level of less than 50 mg/dl for women and less than 40 mg/dl for men.

Blood pressure (BP)

Blood pressure of 130/85 mmHg or higher or being on medicine to treat high blood pressure.

Fasting blood sugar level

Fasting blood sugar was considered normal for less than 100 mg/dL; pre-diabetic if between 100–125 mg/dL; while a fasting blood sugar level of 126 mg/dL or higher was considered as diabetes and a fasting blood sugar level of 100 mg/dL.

A salt sauce added in the food

Rarely (2 grams/day); sometimes (< 2 grams/day); always; (>2 grams/day).

Physical inactivity

< 600MET-minutes per week.

Low fruit and vegetable consumption

< five servings per day.

Alcohol

≥4 standard drinks per day for men; ≥3 standard drinks per day for women.

Metabolic syndrome

Was considered if at least three metabolic syndromes are present, according to the National Cholesterol Education Program’s Adult Treatment Panel III (NCEP-ATP III).

Data quality assurance

Data collectors were trained for two days. The survey procedure was modified according to the feedbacks provided during training. Completed questionnaires were checked daily by the supervisor and principal investigator.

Data processing and analysis

Data were entered and processed using Epi-Info version 7.1.5 (Center for Disease Control and Prevention, USA) and analyzed using SPSS version 21.0 (SPSS Chicago, IL, USA). Descriptive data were presented in tables. The prevalence was described in terms of Crude & Adjusted Prevalence Rate (APR, CPR). The binary logistic regression model was used to see the net effect size. The net effect size was interpreted at P-value ≤ 0.05. Overall fitness of the model was evaluated for each logit function. The final model fitness was checked using Hosmer and Lemeshow test. Model was considered good and fit since p -value was more than 0.05 from the Hosmer-Lemeshow test. Interactions of variables were assessed at p-value < = 0.05 and confounding of variables were assessed by backward and forward elimination and any variable which had > 20% change of coefficient of the parameters between the reduced and full model was considered as confounder. Similarly, collinearity was checked by Variance Inflation Factor (VIF) and If VIF was greater than 10 it was considered as collinear and removed from the model.

Result

Socio-demographic characteristics

A total of 1476 respondents were enrolled in the study. Of these, 842 (57%) were females. Almost closer to half (42.7%) were age category between 29–39 years. Majorities (94%) were orthodox Christian (Table 1).

Table 1

Frequency distribution of socio-demographic characteristics of respondents in Northern Ethiopia (n = 1476).

Variables	Category	Frequency
		Number	Percent
Sex	Male	842	57
	Female	634	43
Age in years	18–28	240	16.3
	29–39	630	42.7
	40–50	416	28.2
	51–61	162	11
	62+	228	1.8
Marital status	Currently married	366	24.8
	Never married	962	65.2
	Separated/divorced/widowed	148	10
Education level	≤8 Grade level	101	6.8
	9–12 Grade Level	175	11.9
	>12 Grade level	1200	81.3
Religion	Orthodox	1387	94
	Muslim	50	3.4
	Protestant	39	2.6

Prevalence and components of metabolic syndrome

The most prevalent MetS component was low HDL concentration CPR = 70.91% (95%CI: 68.47%–73.27%) and APR = 70.61% (95%CI: 67.17%–74.05%). While; high fasting blood glucose CPR = 20.01% (95%CI: 18.03%–22.12%) and APR = 21.72% (95%CI: 18.41–25.03) was the least one (Table 2).

Table 2

Prevalence of metabolic components and syndromes in Northern Ethiopia (n = 1476].

Metabolic syndromes and components	Metabolic syndrome
	Frequency	Prevalence[95% CI]	Prevalence[95%CI]
		CPR	APR
Large waist circumference	317	21.94[19.85, 24.15]	22.60[19.23–26.00]
Low HDL concentration	1046	70.91[68.47, 73.27]	70.61[67.17, 74.05]
High Tri glyceride concentration	842	57.13[54.60, 59.64]	55.63[51.97, 59.29]
High blood pressure	520	35.21[32.81, 37.67]	39.14[35.46, 42.81]
High fasting blood glucose	297	20.01[18.03, 22.12]	21.72[18.41, 25.03]
At least one metabolic risk factors	1251	90.92[89.27, 92.38]	91.67[90.06, 93.27]
At least two metabolic risk factors	885	64.32[61.72, 66.85]	65.13[61.92, 68.34]
At least three metabolic risk factors	465	33.79[31.29, 36.36]	34.18[30.31, 38.06]
At least four risk factors	174	12.65[10.93, 14.52]	13.63[10.71, 16.55]
All five metabolic risk factors	30	2.18[1.48, 3.10]	3.68[1.32, 6.04]

Note: Abbreviations: CI, Confidence Interval; CPR, Crude Prevalence Rate; APR, Adjusted Prevalence Rate.

Prevalence of metabolic syndrome

The CPR and APR of MetS were 33.79%; (95%CI: 31.29%–36.36%) and 34.2%; (95% CI: 30.31%–38.06%) respectively. The prevalence of four metabolic syndrome components was two times more than those with five components (Table 2).

Predictors associated to metabolic syndrome

In the adjusted analysis, currently married (AOR = 1.50; 95%CI: 1.03, 2.19), frequency of alcoholic drink 1–2 day per week (AOR = 0.60; 95%CI: 1.09, 0.71), frequency of alcoholic drink 1–3 days per month (AOR = 0.27; 95%CI:0.1, 0.76), frequency of alcoholic drink less than one per month AOR = 0.28; 95%CI: 0.11, 0.77), eating vegetables four days a week (AOR = 3.69; 95%CI:1.33, 10.22), A salt sauce added in the food sometimes (AOR = 5.06; 95%CI: 5.06 (2.07, 11.34)], heart rate average (AOR = 1.02; 95%CI: 1.01, 1.03), Hemoglobin A1C (AOR = 1.83; 95%CI: 1.49, 2.24), overweight (AOR = 24.28; 95%CI: 10.08, 58.47) and obesity = AOR = 38.81; 95%CI: 12.20, 111.04) showed statistical associations with the MetS (Table 3).

Table 3

Logistic regression analysis of factors associated with pre-diabetes and diabetes for study participants in Northern Ethiopia.

Variables	Metabolic syndrome		OR[95%CI]
	Yes	No	COR	AOR
Sex
Male (Ref)	271	559		NS
Female	194	352	1.14[0.91, 1.43]
Marital status
Never married (Ref)	79	321		NS
Currently married	339	523	2.63[1.99, 3.49]**	1.50[1.03, 2.19]*
Separated	2	3	2.71[0.45, 16.49]
Divorced	30	48	2.54[1.51, 4.26]**
Widowed	15	16	3.30[1.53, 7.15]**
Occupation
Government employees (Ref)	437	821		NS
Farmer	18	49	0.69[0.40, 1.20]
Self employed	4	11	0.68[0.22, 2.16]
Student	1	17	0.11[0.01, 0.83]*
Home marker	13	15	1.13[0.27, 4.74]
Past smoking history
Yes (Ref)	26	30		NS
No	436	875	0.57[0.34, 0.98]*
Frequency of alcoholic drink
Daily (Ref)	24	5		NS
5–6 day per week	6	4	0.31[0.06, 1.53]
1–2 days per week	131	125	0.22[0.08, 0.59]**	0.26[0.09, 0.71]*
1–3 days per month	128	161	0.17[0.06, 0.45]**	0.27[0.1, 0.76]*
Less than one per month	136	351	0.08[0.03, 0.22]**	0.28[0.11, 0.77]*
Frequency of days eating vegetables per week
0 days (Ref)	87	226
2 days	126	214	1.53[1.10, 2.13]*
4days	18	16	2.92[1.43, 5.99]**	3.69[1.33, 10.22]*
7days	102	183	1.45[1.02, 2.05]*
Frequency of days eating meat
Once per month (Ref)	40	117		NS
3–4 times per week	135	227	1.74[1.15, 2.64]**
5–6 times per week	109	120	2.66[1.71, 4.14]**
A salt sauce added in the food
Always (Ref)	396	850
Some times	22	16	2.95[1.53, 5.68]**	5.06[2.07, 12.34]**
Rarely	10	7	3.07[1.16, 8.11]*
Never	32	30	2.29[1.37, 3.82]**
Advised to quite using tobacco
Yes (Ref)	17	16		NS
No	440	884	0.47[0.23, 0.94]*
Advised to eat fruits per day
Yes (Ref)	60	51		NS
No	399	851	0.40[0.27, 0.59]**
Advised to reduced fat in the diet
Yes (Ref)	61	46		NS
No	399	857	0.35[0.24, 0.52]**
Advised to start more physical activity
Yes (Ref)	74	59		NS
No	386	844	0.36[0.25, 0.52]**
Advised to maintain weight lose
Yes (Ref)	51	31
No	48	871	0.28[0.18, 0.45]**
Heart rate average	-	-	1.03[1.01, 1.04]**	1.02[1.007, 1.034]*
Hemoglobin A1C	-	-	2.12[1.78, 2.51]**	1.83[1.49, 2.24]**
BMI
Normal (Ref)	218	571
Under weight	10	187	7.14[3.71, 13.74]**	7.63[3.29, 17.73]**
Overweight	196	136	26.95[13.75, 56.97]**	24.28[10.08, 58.47]**
Obesity	38	15	47.37[19.79, 113.40]**	38.81[12.20, 111.04]**

Note: *p-value<0.05,

** P-value <0.01; Abbreviations: Ref, Reference category; NS, Not statistically significant variable.

Discussion

The study aimed to assess the magnitude, components and predictors of MetS. It revealed that unadjusted and adjusted prevalence rate were (CPR = 33.79%; 95%CI: 31.29%–36.36%) and (APR = 34.2%; 95% CI: 30.31%–38.06%) respectively. The most prevalent component was low HDL concentration (CPR = 70.91%; 95% CI: 68.47–73.27 and APR = 70.61% 95%CI: 67.17%–74.05%). While, high fasting blood glucose was the least prevalent (CPR = 20.01%; 95%CI: 18.03%–22.12% and APR = 21.72% 95%CI: 18.41%–25.03%). eating vegetables four days a week, a salt sauce added in the food sometimes, overweight, obesity had a strong association with MetS.

Unadjusted and adjusted prevalence rate of metabolic syndrome were (CPR = 33.79%; 95%CI: 31.29%–36.36%) and (APR = 34.2%; 95% CI: 30.31%–38.06%) respectively. Several studies reported the prevalence of MetS worldwide including Africa. These shreds of evidences were quite heterogeneous, which can be attributed to a difference definitions and ways of diagnosis and classification. Hence, this limits direct comparisons with the current study. The adjusted prevalence of the current study (34.2%) lies between finding (12–86%) evidenced from sub Saharan Africa [7]. But, it is higher compared to evidence documented in 10 European countries (24%), the UK (32%) [28]. this variation was due to differences in study settings, socio-cultural, and life style modification among the countries. This prevalence is much lower than a report at Ogbera Lagos, Nigeria (86%) [29], national estimate in Ethiopia (45.9%) [19], Ghana (68.6%) [30], and Iran (64.9%) [31]. These differences could be due to the variation in diagnosis and classification criteria of MetS. The other reason for elevated value of MetS observed in Nigeria and Ghana could be due to the fast urbanization and development. Regarding to residency, the association of MetS and urbanization could be as a result of a sedentary life style, increased intake of calorie rich foods and central obesity. This result is supported by other studies [32, 33]. However, the current finding was consistent with findings from Malaysia (37.4%) [34], Germany (33.7%) [35], Korea (36.1%) [36]. These similarities might be due to the use of the same study design, definition and classification criteria.

The most prevalent component of MetS was low HDL concentration (CPR = 70.91%; 95%CI: 68.47%–73.27%) and (APR = 70.61%; 95%CI: 67.17%–74.05%) followed by high tri-glyceride concentration (CPR = 57.13%; 95%CI: 54.60%–59.64%) and (APR = 55.63%; 95%CI: 51.97%–59.29%). Similar to the current study, low HDL-C was found to be the most prevalent MetS components in black African which close (70.1%) to the current finding [37].

According to the NCEP- ATPIII criteria, where the highest prevalence of MetS was observed, high TG and low HDL were the most frequent abnormal MetS components. Even though there were no previous studies which support or contradict the findings of the current study, there were pieces of evidences that indicated abnormal levels of TG and HDL. This has an implication of adverse health effects in which low level of HDL in the body is associated with an increased risk of CVD, coronary heart diseases and death [38]. Thus, interventions focusing on abnormal TG and HDL need to be prioritized [38, 39]. Besides; a pooled prevalence (44%) of high blood pressure reviewed in Africa [7] was relatively high when compared from the current finding (39.4%). However, close to the continental estimate. The difference might be variation in design and study population in which the later was conducted using a longitudinal study design on DM patients. Even though, comparable evidence was found on WC with the current study, evidence suggested that it had the strongest associations with health risk indicators followed by BMI [40, 41].

Respondents who were currently married were significantly associated with MetS, which is also evidenced from Ethiopia [19], Nigeria [29], and Iran [31]. Eating vegetables in a typical four days a week and a salt sauce added in the food sometimes were 3.7 and 5.1 times more protected from metabolic syndrome compared to their counterparts. This evidence was further supported with studies conducted from Ethiopia [42, 43], and Brazil [44]. Besides, the odds of MetS were 24.3 and 38.8 times higher among respondents with overweight and obesity than the normal. This was almost 8 to 9 times higher when compared with the findings from Ethiopia, Nigeria Ghana, Iran, and Malaysia [19, 29, 30, 31, 34]. The difference might be due to sample size, and study setting variation. Those who drink 1–2 days a week, 1–3 days a month, less than once a month were less likely exposed to MetS than those who drink alcohol daily. Nevertheless, physical activity and use of tobacco were tended to none predictors’ of MetS as similarly reported from Southern Ethiopia [45].

The findings from the present study showed MetS is a major burden. Early identification of visible intervention and awareness creation is a great importance to reduce its occurrence and progression [46].

Strengths and limitations

The use of digital device for measured biochemical and physical measurements might increase validity and reliability of study findings. Due to the cross—sectional nature of the study the temporal relationship between the outcome and predictor variables might not powerful. The reliance on self-reported data might lead to incorrect estimates. Non-probability convenience sampling was employed and this might have an effect on generalizability.

Conclusion

The magnitude of MetS was lower than the national estimate but significantly high considering estimations from pocket studies. The predictors were easy to address and targeted interventions of education initiatives, dietary modifications and health screening measures needed to avoid further complications.

Dataset used for the analysis of the study.

(SAV)

Click here for additional data file.

Data collection tool.

(PDF)

Click here for additional data file.

7 Dec 2020

PONE-D-20-16786

Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016

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Reviewer #1: The title of the article is "Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016".

The authors conducted a community based cross sectional study. This study aimed to assess magnitude, components, and predictors of metabolic syndrome in Tigray region northern Ethiopia, 2016.

This is a quite interesting study. However, the manuscript still could be further improved after some revisions.

Specific comments:

1. In Methods section; Statistical analyses, please clarify, what method that used for adjusting in multivariate analysis? Please provide test for interaction between variables, goodness of fit, and multicollinearity. In addition, please demonstrate flowchart of participants. If non-probability convenience sampling was employed. This limitation of the study might affect generalizability.

2. Data collection: Who interviewed the participants? Were they doctors, nurses, medical students, or research investigators? Were they trained before administered the questionnaires? How the authors deal with missing data?

3. Data collection: By how many people, in how long time, where? The time of interview for each person? Missing values?

4. Include full details of how the authors handled missing data and outliers in the ‘Methods’ section.

5. The main concern is that the questionnaires should be validated and have good reliability and validity. Reliability of questionnaires should be mentioned. Please provide citation and reference of the questionnaire. The English peer-review reference should be placed.

6. Please describe the detail of Tigray region northern Ethiopia; such as is it rural or urban community, the number of population and population structure.

7. It is important that within the manuscript, the authors clarify the importance of this work, how it differs from and advances previously published work and how this article can benefit the field and patients in the future etc. Please also add more information from recently published research and offer a more speculative and forward-looking perspective.

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Reviewer #1: Yes: Wisit Kaewput

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21 May 2021

Responses to Reviewer’s and editor comments

Journal name: PLOS ONE

Corresponding Author: Kiros Fenta Ajemu

We would like to express our appreciation to the reviewer for their constructive and supportive comments in the first version of the manuscript entitled “Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016”. This will be an input to improve the quality of the manuscript. We have meticulously revised the manuscript and incorporated all the changes in the revised version of the manuscript based on the suggestions and comments made by the reviewer. We have highlighted these changes in the manuscript. We have listed all the responses for each of the comment/ suggestion made by the reviewer as follows:

Responses to comments Academic Editor: Mr. Paolo Magni

Comment 1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response 1: Thank you for your constructive comment. We crosscheck the manuscript based on the PLOS ONE style requirements in line with the web site you suggested.

Comment 2: We noted that “Figure 1” in your submission contains map images which may be copyrighted.

Response 2: Thank you for your transparent and constructive comment. Actually we made the map using regional GPS data but as you have said the map is not that much relevant since Mekelle city is already known and everybody can Google it from internet. Therefore we agreed to remove the figure “Figure 1” from the main body of the manuscript. The change made is listed below as per your comments and suggestions in:

- Material and Methods section Line (70), Page (4)].

Responses to reviewer comments

Comment 1: The title of the article is "Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016".The authors conducted a community based cross sectional study. This study aimed to assess magnitude, components, and predictors of metabolic syndrome in Tigray region northern Ethiopia, 2016.This is a quite interesting study.

Response 1: thank you for your acknowledgment that makes me to do more.

Comment 2: in the statistical analyses, please clarify what method that used for adjusting in multivariate analysis? Please provide test for interaction between variables, goodness of fit, and multicollinearity.

Response 2: thank you for your consideration in statical analysis in line with data handling mechanisms since it is the back bone and pillar to find the real evidence and minimize biases and errors. The changes that we made were listed below as per your comments and suggestions in Method section, Line (137-144), Pages (7)].

- Test of interaction, Line (142-143), Pages (7)].

- Goodness of fit, Line (140-142), Pages (7)].

- Multicollinearity, Line (145-146), Pages (7)].

Comment 3: If non-probability convenience sampling was employed. This limitation of the study might affect generalizability.

Response 3: thank you and I accept you fear of generalizability but we put it as a limitation in the:

- Strength and Limitation section, Line (243-244), pages (15)]. As part of the limitation of the study

Comment 4: Who interviewed the participants? Were they doctors, nurses, medical students, or research investigators? Were they trained before administered the questionnaires, by how many people, in how long time, where? The time of interview for each person?

Response 4: thank you your concern for data quality and the changes made were explained in Method section, Line (94- 103] Page (5)]

- Who interviewed, Line (96-97), Pages (5)].

- How many people, Line (96-97), Pages (5)].

- How long and where, Line (102-103), Pages (5)].

Comment 5: The main concern is that the questionnaires should be validated and have good reliability and validity. Reliability of questionnaires should be mentioned Please provide citation and reference of the questionnaire.

Response 5: thank you for your comment and the changes made were listed in Method section Line (94-95] Page (5)]

- Validated questionnaire, Line (94), Pages (5)].

- Reference, Line (95), Pages (5)].

Comment 6: Please describe the detail of Tigray region northern Ethiopia; such as is it rural or urban community, the number of population and population structure.

Response 6: thank you for your concern in the study area and the changes made were listed in Method section Line (70-77] Page (4)]

Comment 7: It is important that within the manuscript, the authors clarify the importance of this work, how it differs from and advances previously published work and how this article can benefit the field and patients in the future etc.

Response 7: the previously published work has different objective and it was a scientific report on prevalence of behavioral characteristics such as alcohol use, eating diet, physical activity, diabetes and pre-diabetes prevalence. The study did not address predictor factors the magnitude of association in respective cardiovascular disease. The current study will provide detail of the risk factors for future deployment of visible intervention. For further information you can access the article on line Journal of scientific report https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6006379/.

Once again thank you for your strong and committed concern for improving the manuscript

Sincerely your’s Kiros Fenta Ajemu (kirosfenta@gmail.com)Researcher, Tigray Health Research Institute, Mekelle, Tigray, Ethiopia

Submitted filename: Response to Reviewers..docx

Click here for additional data file.

3 Jun 2021

Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016

PONE-D-20-16786R1

Dear Dr. Kiros Fenta Ajemu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Paolo Magni

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

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Reviewer #1: Yes: Wisit Kaewput

7 Jun 2021

PONE-D-20-16786R1

Magnitude, components and predictors of metabolic syndrome in Northern Ethiopia: Evidences from regional NCDs STEPS survey, 2016

Dear Dr. Ajemu:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Prof. Paolo Magni

Academic Editor

PLOS ONE