Next Article in Journal
A Biophysical Analysis on the Arm Stroke Efficiency in Front Crawl Swimming: Comparing Methods and Determining the Main Performance Predictors
Previous Article in Journal
First Description of the Hyperpnea–Hypopnea Periodic Breathing in Patients with Interstitial Lung Disease-Obstructive Sleep Apnea: Treatment Implications in a Real-Life Setting
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 16
Issue 23
10.3390/ijerph16234714
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Associated Factors of Hypertension in Women and Men in Vietnam: A Cross-Sectional Study

by
Tran Quoc Cuong
1,
Le Van Bao
2,
Nguyen Anh Tuan
2,
Vo Van Thang
3,
Nguyen Minh Quan
4,
Shwu-Huey Yang
5,6,7 and
Tuyen Van Duong
5,*
1
Department of Anesthesiology, Thu Duc District Hospital, Ho Chi Minh City 713-11, Vietnam
2
School of Public Health, Military Medical University, Hanoi 121-08, Vietnam
3
Institute of Community Health Research, Faculty of Public Health, College of Medicine and Pharmacy, Hue University, Thua Thien Hue 491-20, Vietnam
4
Director Office, Thu Duc District Hospital, Ho Chi Minh City 713-11, Vietnam
5
School of Nutrition and Health Sciences, Taipei Medical University, Taipei 110-31, Taiwan
6
Research Center of Geriatric Nutrition, Taipei Medical University, Taipei 110-31, Taiwan
7
Nutrition Research Center, Taipei Medical University Hospital, Taipei 110-31, Taiwan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(23), 4714; https://doi.org/10.3390/ijerph16234714
Submission received: 26 September 2019 / Revised: 14 November 2019 / Accepted: 23 November 2019 / Published: 26 November 2019
Versions Notes

Abstract

:
Background: Hypertension is a direct cardiovascular disease risk. It causes a heavy burden on the healthcare system globally. We aim to assess hypertension occurrence and its associated factors among women and men in Vietnam. Methods: A cross-sectional study was conducted from January to February 2019 on 2203 community-dwelling women and men aged 18 years or above. Participants’ characteristics, comorbidity, behaviors, and physical measures were evaluated. Hypertension was classified as systolic/diastolic blood pressure ≥140/90 mmHg or using antihypertensive medication. We analyzed data using logistic regression models. Results: The prevalence of hypertension was 24.3% (20.9% in women, 29.1% in men). For women, older age (odds ratio, OR, 6.80–12.41; p < 0.001), income above the poverty line (OR, 0.64; p = 0.008), diabetes comorbid (OR, 2.98; p < 0.001), added salts consumption (OR, 1.80; p < 0.001), overweight/obesity (OR, 1.64; p = 0.005), abdominal obesity (OR, 2.07; p < 0.001) were associated with hypertension. For men, older age (OR, 2.67–5.92; p < 0.001), diabetes comorbid (OR, 2.25; p = 0.010), smoking (OR, 1.38; p = 0.046), and overweight/obesity (OR, 2.18; p < 0.001) were associated with hypertension. Conclusions: Hypertension is prevalent in Vietnamese people. The associated factors of hypertension are varied by gender.

1. Introduction

Non-communicable diseases (NCDs) place a heavy burden on the healthcare system across the globe [1]. It accounts for 71% of the total burden in Vietnam [2]. Among NCDs, cardiovascular disease (CVD) is a leading cause of premature death worldwide [1,2,3]. Hypertension is the strongest risk factor of CVD and causes a huge financial burden in Vietnam and globally [4,5,6,7]. Strategical interventions to reduce its burden could advance the sustainable development goals (SDGs), especially in low- and middle-income (LMIC) countries [8,9].
Globally, the prevalence of hypertension is high and striking from 28.5% in high-income countries to 31.5% in low- and middle-income countries [10]. Meanwhile, the awareness (46.5%–67.0%) and control (10.2%–37.9%) are inadequate in low-, middle-, and high-income countries [10,11,12]. In the Vietnamese population, blood pressure constantly increased from 2001–2009 [13]. The prevalence of hypertension in Vietnam was 18.4% based on three national surveys and 21.1% based on 10 other studies [14]. The level of hypertension awareness (9.3%–25.9%) and treatment (4.7%–12.2%) were very low [14,15]. In addition, the medication adherence rate (49.8%) was relatively low in hypertensive people [16].
The disease pattern in Vietnam has transited from communicable to non-communicable during the socioeconomic reforms [13,17,18]. Ho Chi Minh city is the most developed one in Vietnam with its fast socioeconomic change, which significantly contributed to this epidemiologic transition. Managing hypertension plays an important role in improving CVD outcomes and reducing its burden [4,5,6,19]. Therefore, it is important to identify the risk factors of hypertension, such as personal characteristics, dietary intake, physical activity, and lifestyle [20,21]. The previous studies in Vietnam were conducted a few years ago, which may not reflect the current status and determinant of hypertension [13,15]. In addition, these factors may influence hypertension differently in women and men, which are scarcely studied. We aim to assess hypertension occurrence and investigate the potential determinants of hypertension among women and men in Ho Chi Minh City, Vietnam.

2. Research Methods

2.1. Study Design and Settings

A cross-sectional study design was conducted between January and February 2019. The study participants were recruited from three communities named Hiep Binh Chanh, Linh Xuan, and Tam Phu communes in Thu Duc District, Ho Chi Minh City, Vietnam.

2.2. Sampling and Sample Size

The sample size was calculated using the formula (1) [22]:
N = Z 2 p 1 − p d 2
where N is the sample size, Z is the level of confidence, p is expected prevalence, and d is the absolute error of precision, corresponding to effect size [22]. The sample of 384 was calculated with Z = 1.96 for type I error of 5%, p = 0.20 as the prevalence of hypertension was ranged from 18.4% to 21.1% in Vietnam [14], and d = 0.04 as suggested for a cross-sectional study design [23]. According to the World Health Organization guideline in the STEPwise approach to surveillance, in order to have an adequate precision level for each sex-age estimate, the sample size must be multiplied by 6 (3 groups of age: 18–44, 45–59, 60–69 years for men and women) [24]. The sample size was 384 × 6 = 2304.
A convenience sampling method was utilized to recruit study participants in the community. People recruited in the current study were of the general public, who were aged 18 to 69 years, without any mental health issues, and able to read and understand the local language. People excluded were those with catastrophic diseases, such as chronic kidney disease, chronic obstructive pulmonary disease, cancer, cirrhosis, stroke, ischemic heart disease, or coronary artery disease.

2.3. Measurements

2.3.1. Participants’ Characteristics

Participants’ characteristics were studied, including age (18–44, 45–59, 60–69 years), gender (men vs. women), marital status (never married vs. ever married), education (elementary school and below, secondary school, high school and above), occupation (retirement, officers/workers/traders, and other), and income. The monthly income was classified into below the poverty line (<2.3 million VND/month), and above the poverty line (≥2.3 million VND/month), with 1 USD = 23,000 VND according to Vietcombank-State Bank of Vietnam [25,26]. In addition, diabetes and high cholesterol comorbidities were also investigated.

2.3.2. Health Behaviors

Participants were asked about their current health-related behaviors including tobacco smoking (yes vs. no); alcohol drinking (yes vs. no); fruits and vegetable intake (<5 servings/day vs. ≥5 servings/day), 1 serving is equal to 1 medium size piece of apple, banana, orange, or to ½ cup of chopped or cooked fruit, or to 1 cup of raw green leafy vegetables, or to ½ cup of other vegetables, cooked or chopped raw; added salt consumption (yes vs. no); and physical activity (yes vs. no).

2.3.3. Blood Pressure

The parameters measured were systolic blood pressure (SBP) and diastolic blood pressure (DBP) in mmHg. The SBP and DBP were measured using a standard clinical manual aneroid sphygmomanometer (Yamasu Sphygmomanometer, Yamasu company, Tokyo, Japan). The blood pressure was measured three times with a 30-second interval on all participants after a 10 min rest, in the right arm, and in sitting position. The average value of three measurements was calculated. Participants were also asked whether or not they have been taking antihypertensive medication. Hypertension was classified as systolic blood pressure/diastolic blood pressure ≥140/90 mmHg [27,28,29], or using antihypertensive medication. The antihypertensive drugs commonly used by study participants were angiotensin-converting enzyme inhibitors (e.g., Captorile 25 mg), Ca-Antagonists (e.g., Amlor 5 mg), and β-blockers (Valsartan 80 mg).

2.3.4. Anthropometrics

The anthropometric parameters including height (cm), weight (kg), waist circumference (cm), hip circumference (cm), were measured by doctors or nurses for all participants wearing light clothes and bare feet. Body weight was measured using a weighing scale (CSK-120, Nhon Hoa Scale Company, Ho Chi Minh, Viet Nam), height was reported by participants, waist circumference, and hip circumference were measured using a clinical tape measure. The parameters were recorded to nearest 0.1 kg, or 0.1 cm, appropriately.
The body mass index (BMI) was calculated from weight (kg)/height (m)2. According to WHO classification for the Western Pacific region, BMI was classified as normal weight (<25.0 kg/m2), overweight, and obesity (≥25.0 kg/m2) [30,31]. In addition, abdominal obesity for South Asian people was defined as a waist –hip ratio ≥0.90 for men or ≥0.85 for women, respectively [32].

2.4. Data Collection Procedure

The interviewers (two medical doctors, and eight nurses) were well-trained about data collection by a senior researcher. A two-day training section was conducted in Thu Duc District Hospital. The permission was achieved from the District Health Center. Researchers then contacted local authority people and local volunteers to discuss the study. People satisfied with the recruitment criteria were invited to the survey. The face-to-face interviews were conducted in the participants’ houses using printed questionnaires. The blood pressure, height, weight, waist circumference, and hip circumference were measured by well-trained doctors and nurses. Each interview took about 15–30 min. There were 2203 people who agreed and voluntarily participated in the study and completed the assessment (response rate of 95.6%).

2.5. Ethical Consideration

The study was approved by the institutional review board of the National Institute of Hygiene and Epidemiology in Vietnam (NIHE-IRB-43/2018). All participants voluntarily participated and signed the inform consent form before their participation.

2.6. Data Analysis

The descriptive analysis was used to examine the distribution of hypertension, characteristics, behaviors, and physical parameters. The independent-samples t-test and Chi-square test were used to compare the distribution of hypertension among categories of studied variables, appropriately. Next, the bivariate logistic regression models were run to investigate the associated factors of hypertension. The Spearman correlation was used to check the correlation among predictors to avoid multicollinearity in multivariate regression models. Finally, the factors that showed the association with hypertension at p < 0.20 in the bivariate model were selected into the multivariate model [33]. The p-value < 0.05 was set as significance. We analyzed data using the IBM SPSS Version 20.0 (IBM Corp, Armonk, NY, USA) [34].

3. Results

The average age of the study population was 46.4 ± 13.5 years. The prevalence of hypertension was 24.3% (535 out of 2203 participants) for the total sample, 20.9% (268/1285) for women, and 29.1% (267/918) for men. Among the hypertensive participants, there were 279 (52.1%) using antihypertensive drugs. The proportion of hypertension significantly differed in different groups of age, gender, marital status, education, occupation, monthly income, comorbid diabetes, high cholesterol, smoking, drinking, added salts consumed, BMI, and abdominal obesity (Table 1).
In the total sample, the odds of hypertension were significantly higher in people associated with the factors of older age, men, ever married, comorbid diabetes, high cholesterol, smoking, drinking, consuming added salts, and those with overweight and obesity. The odds of hypertension were significantly lower in people with higher education, a current job, and those above the poverty line (Table 2). To avoid the multicollinearity among the confounders, the correlation among the factors associated with hypertension at p < 0.20 in bivariate regression was examined. The results of the Spearman test showed that age was moderately correlated to marital status and occupation; gender was moderately correlated to smoking, drinking, and abdominal obesity; comorbid diabetes was moderately correlated to comorbid hypercholesterolemia (Table S1). Therefore, age, gender, education, income, comorbid diabetes, added salts, BMI, and abdominal obesity were included in the multivariate regression analysis. The result showed that, as compared with people aged 18–44 years, those aged 45–59 (odds ratio, OR, 3.99; 95% confidence interval, 95% CI, 3.01–5.30; p < 0.001), and aged 60–69 (OR, 8.37; 95% CI, 6.06–11.55; p < 0.001) had higher odds of hypertension. In comparison with women, men had higher odds of hypertension (OR, 2.32; 95% CI, 1.85–2.91; p < 0.001). The odds of hypertension were higher in people with comorbid diabetes (OR, 2.72; 95% CI, 1.85–4.00; p < 0.001). People consumed added salts had higher odds of hypertension (OR, 1.66; 95% CI, 1.33–2.07; p < 0.001) as compared with those who did not consume. Participants with BMI ≥ 25.0 kg/m2 had higher odds of hypertension (OR, 1.90; 95% CI, 1.48–2.44; p < 0.001), as compared with those with BMI < 25.0 kg/m2. People with abdominal obesity had higher odds of hypertension (OR, 1.71; 95% CI, 1.36–2.15; p < 0.001), as compared with normal people (Table 3).
In the women sample, the odds of hypertension were significantly higher in people associated with the factors of older age, ever married, comorbid diabetes, high cholesterol, consuming added salts, and those with overweight and obesity. The odds of hypertension were significantly lower in people with higher education, a current job, and those above the poverty line (Table 2). The results of the Spearman test showed that age was moderately correlated to education and occupation; comorbid diabetes was moderately correlated to high cholesterol (Table S1). Therefore, age, marital status, income, comorbid diabetes, added salts, BMI, and abdominal obesity were included in the multivariate regression analysis. The result showed that, as compared to women aged 18–44 years, those aged 45–59 (OR, 6.80; 95% CI, 4.02–11.49; p < 0.001), and aged 60–69 (OR, 12.41; 95% CI, 7.16–21.52; p < 0.001) had higher odds of hypertension. As compared to women with income at below poverty line level, those with income above the poverty line level had lower odds of hypertension (OR, 0.64; 95% CI, 0.46–0.89; p = 0.008). The odds of hypertension were higher in women with comorbid diabetes (OR, 2.98; 95% CI, 1.81–4.91; p < 0.001). Women who consumed added salts had higher odds of hypertension (OR, 1.80; 95% CI, 1.32–2.45; p < 0.001) as compared to those who did not consume. Women with BMI ≥ 25.0 kg/m2 had higher odds of hypertension (OR, 1.64; 95% CI, 1.16–2.33; p = 0.005), as compared with those with BMI < 25.0 kg/m2. Women with abdominal obesity had higher odds of hypertension (OR, 2.07; 95% CI, 1.49–2.87; p < 0.001), as compared to non-abdominal obesity women (Table 3).
In the men sample, the odds of hypertension were significantly higher in people associated with factors of older age, ever married, diabetes, hypercholesterolemia comorbid, smoking, and those with overweight and obesity. The odds of hypertension were significantly lower in people with higher education and a current job (Table 2). The results of the Spearman test showed that age was moderately correlated to marital status; comorbid diabetes was moderately correlated to high cholesterol (Table S1). Therefore, age, education, occupation, income, comorbid diabetes, smoking, BMI, and abdominal obesity were included in the multivariate regression analysis. The result showed that, as compared to men aged 18–44 years, those aged 45–59 (OR, 2.67; 95% CI, 1.85–3.87; p < 0.001) and aged 60–69 (OR, 5.92; 95% CI, 3.41–10.28; p < 0.001) had higher odds of hypertension. The odds of hypertension were higher in men with comorbid diabetes (OR, 2.25; 95% CI, 1.21–4.18; p = 0.010). Men who smoked had higher odds of hypertension than those who did not smoke (OR, 1.38; 95% CI, 1.01–1.90; p = 0.046). Men with BMI ≥ 25.0 kg/m2 had higher odds of hypertension (OR, 2.18; 95% CI, 1.52–3.13; p < 0.001), as compared to those with BMI < 25.0 kg/m2 (Table 3).

4. Discussion

In the total sample, men were 2.32 times more likely to have hypertension as compared to women. The prevalence of hypertension was 20.9% for women, and 29.1% for men. This was slightly higher than the finding from the pooled analysis from 200 countries, which showed that the prevalence of raised blood pressure was 20.1% for women and 24.1% for men [35]. In both women and men, those with older age were more likely to have hypertension. It was summarized that age and gender were the major risk factors of hypertension in Vietnam and other countries [15,36,37,38,39,40,41,42].
Women with income above the poverty line had less likelihood of having hypertension as compared to those with income below the poverty line. The association was not found in men. This was similar to the finding of a multilevel analysis in Colombia [43]. In addition, it was summarized that the association between socioeconomic status and hypertension was most consistent for women but less consistent for men [44]. The income/wealth-related inequity was reported as a key factor of hypertension screening, treatment, and control in many low-, middle-, and high-income countries [42,45,46,47]. The appropriate public health interventions are encouraged to narrow down the gap in economic and education that may be the strategical approach to improve public awareness and capacity of public health services in hypertension management.
In both women and men, those with diabetes and hypercholesterolemia comorbidity were more likely to have hypertension. The coexistence of diabetes and hypertension was summarized [48]. Arterial stiffness indices (stiffness index and reflection index) were found to be a strong predictor of future CVD events [49]. In addition, in mothers with gestational diabetes mellitus and dyslipidemia, their child had a higher rate of obesity [50]. Therefore, the management of both blood glucose and blood pressure is a strategical way to prevent cardiovascular events or death [48,51]. The antihypertensive monotherapy with diuretics, Ca-antagonists, or zinc metabolism alterations showed the effect on lipid metabolism and inflammation, which were suggested in managing primary arterial hypertension [52]. The combination of pharmacology and zinc from dietary intake or supplements also showed an effect on hypertension management [53]. Moreover, the management of hypertension with different strategies was summarized as the primary prevention of cardiovascular diseases [54,55,56].
Lifestyle interventions were found as the primary prevention of hypertension and dyslipidemia, which further contributes to preventing cardiovascular diseases [54]. In the current study, smoking was analyzed among men, and the result showed a significantly positive association between smoking and hypertension. Smoking is a strong predictor of hypertension and cardiovascular diseases [57]. In addition, women as passive smokers have also been affected by smoke with a dose-response association [58]. Smoking cessation is a simple and effective lifestyle to prevent hypertension and cardiovascular events [57,59,60].
Salt intake was found as a key factor of hypertension in previous studies [37]. However, in the current study, the association was only found in women, but not in men. In a previous study in Vietnam, salt consumption was not significantly associated with high BP at the national level, but the association differed between urban and rural areas in Vietnam [61]. However, the evidence of this association was consistently found in other countries, namely in Brazil [62], China [63], in Cameroon [37]. Moreover, the long term effect of reduction in salt intake on population BP and CVD was summarized from several randomized trials [64,65,66].
Overweight and obesity classified by BMI showed a positive association with hypertension in both women and men. The abdominal obesity classified by WHR showed the possibility of hypertension in women. The associations of BMI and WHR with hypertension were found in previous studies [13,36,67,68,69]. In the current study, for men, the association of BMI and WHR with hypertension was found in bivariate analysis, but the association between WHR and hypertension was jeopardized in the multivariate analysis. The finding was supported by a previous study that all anthropometric indicators were associated with hypertension in women, but only BMI and its combination with other indicators showed a significant association in men [70].
The current study has some limitations. Firstly, the causality was not drawn as the cross-sectional nature of the design. Secondly, the sample was not a nation-wide one, and the generalizability was limited, even though the sample was adequate to explore the association and contribute to the evidence pool. In the present study, we only asked participants about their vegetables and fruits and salt consumption, which limited the investigation on the association between dietary intake and hypertension. In addition, the quantity of alcohol, salt consumption, and physical activity were not assessed, and the pulse rate was not recorded in the current study. Future studies are suggested to conduct in a larger population and with a longitudinal design in order to have a comprehensive assessment and examine the causal relationship between potential factors and hypertension.

5. Conclusions

Hypertension was prevalent in the study population. The associated factors of hypertension were age, gender, income, diabetes comorbidity, smoking, salt consumption, and obesity. The associations were varied by gender. The associated factors of hypertension in women and men were studied, which provided important evidence for effective screenings and potential interventions for the treatment and control of hypertension.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/16/23/4714/s1, Table S1: The Spearman correlation among the covariates.

Author Contributions

Conceptualization, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.; data curation, T.Q.C., and T.V.D.; formal analysis, T.Q.C., and T.V.D.; funding acquisition, T.Q.C.; investigation, T.Q.C., L.V.B., N.A.T., N.M.Q., S.-H.Y., and T.V.D.; methodology, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.; project administration, T.Q.C.; resources, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.; software, T.Q.C., and T.V.D.; supervision, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.; validation, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.; visualization, T.Q.C., and T.V.D.; writing—original draft preparation, T.Q.C., and T.V.D.; writing—review and editing, T.Q.C., L.V.B., N.A.T., V.V.T., N.M.Q., S.-H.Y., and T.V.D.

Funding

This research received no external funding.

Acknowledgments

The authors would like to thank the doctors, nurses, and local volunteers who helped with data collection.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Roth, G.A.; Abate, D.; Abate, K.H.; Abay, S.M.; Abbafati, C.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdela, J.; Abdelalim, A.; et al. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018, 392, 1736–1788. [Google Scholar] [CrossRef]
  2. Nhung, N.T.T.; Long, T.K.; Linh, B.N.; Vos, T.; Huong, N.T.; Anh, N.D. Estimation of Vietnam national burden of disease 2008. Asia Pac. J. Public Health 2014, 26, 527–535. [Google Scholar] [CrossRef] [PubMed]
  3. Hoa, N.P.; Rao, C.; Hoy, D.G.; Hinh, N.D.; Chuc, N.T.K.; Ngo, D.A. Mortality measures from sample-based surveillance: Evidence of the epidemiological transition in Viet Nam. Bull. World Health Organ. 2012, 90, 764–772. [Google Scholar] [PubMed]
  4. Nguyen, T.-P.-L.; Nguyen, T.B.Y.; Nguyen, T.T.; Vinh Hac, V.; Le, H.H.; Schuiling-Veninga, C.C.M.; Postma, M.J. Direct costs of hypertensive patients admitted to hospital in Vietnam’ a bottom-up micro-costing analysis. BMC Health Serv. Res. 2014, 14, 514. [Google Scholar] [CrossRef] [PubMed]
  5. Nguyen, T.-P.-L.; Wright, E.P.; Nguyen, T.-T.; Schuiling-Veninga, C.C.M.; Bijlsma, M.J.; Nguyen, T.-B.-Y.; Postma, M.J. Cost-Effectiveness Analysis of Screening for and Managing Identified Hypertension for Cardiovascular Disease Prevention in Vietnam. PLoS ONE 2016, 11, e0155699. [Google Scholar] [CrossRef]
  6. Olsen, M.H.; Angell, S.Y.; Asma, S.; Boutouyrie, P.; Burger, D.; Chirinos, J.A.; Damasceno, A.; Delles, C.; Gimenez-Roqueplo, A.-P.; Hering, D.; et al. A call to action and a lifecourse strategy to address the global burden of raised blood pressure on current and future generations: The Lancet Commission on hypertension. Lancet 2016, 388, 2665–2712. [Google Scholar] [CrossRef]
  7. Yusuf, S.; Joseph, P.; Rangarajan, S.; Islam, S.; Mente, A.; Hystad, P.; Brauer, M.; Kutty, V.R.; Gupta, R.; Wielgosz, A.; et al. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): A prospective cohort study. Lancet 2019. [Google Scholar] [CrossRef]
  8. Nugent, R.; Bertram, M.Y.; Jan, S.; Niessen, L.W.; Sassi, F.; Jamison, D.T.; Pier, E.G.; Beaglehole, R. Investing in non-communicable disease prevention and management to advance the Sustainable Development Goals. Lancet 2018, 391, 2029–2035. [Google Scholar] [CrossRef]
  9. Niessen, L.W.; Mohan, D.; Akuoku, J.K.; Mirelman, A.J.; Ahmed, S.; Koehlmoos, T.P.; Trujillo, A.; Khan, J.; Peters, D.H. Tackling socioeconomic inequalities and non-communicable diseases in low-income and middle-income countries under the Sustainable Development agenda. Lancet 2018, 391, 2036–2046. [Google Scholar] [CrossRef]
  10. Mills Katherine, T.; Bundy Joshua, D.; Kelly Tanika, N.; Reed Jennifer, E.; Kearney Patricia, M.; Reynolds, K.; Chen, J.; He, J. Global Disparities of Hypertension Prevalence and Control: A Systematic Analysis of Population-Based Studies From 90 Countries. Circulation 2016, 134, 441–450. [Google Scholar] [CrossRef]
  11. Lloyd-Sherlock, P.; Beard, J.; Minicuci, N.; Ebrahim, S.; Chatterji, S. Hypertension among older adults in low- and middle-income countries: Prevalence, awareness and control. Int. J. Epidemiol. 2014, 43, 116–128. [Google Scholar] [CrossRef] [PubMed]
  12. Chow, C.K.; Teo, K.K.; Rangarajan, S.; Islam, S.; Gupta, R.; Avezum, A.; Bahonar, A.; Chifamba, J.; Dagenais, G.; Diaz, R.; et al. Prevalence, Awareness, Treatment, and Control of Hypertension in Rural and Urban Communities in High-, Middle-, and Low-Income Countries. JAMA 2013, 310, 959–968. [Google Scholar] [CrossRef] [PubMed]
  13. Nguyen, Q.N.; Pham, S.T.; Nguyen, V.L.; Weinehall, L.; Bonita, R.; Byass, P.; Wall, S. Time Trends in Blood Pressure, Body Mass Index and Smoking in the Vietnamese Population: A Meta-Analysis from Multiple Cross-Sectional Surveys. PLoS ONE 2012, 7, e42825. [Google Scholar] [CrossRef] [PubMed]
  14. Meiqari, L.; Essink, D.; Wright, P.; Scheele, F. Prevalence of Hypertension in Vietnam: A Systematic Review and Meta-Analysis. Asia Pac. J. Public Health 2019, 31, 101–112. [Google Scholar] [CrossRef] [PubMed]
  15. Do, H.T.P.; Geleijnse, J.M.; Le, M.B.; Kok, F.J.; Feskens, E.J.M. National Prevalence and Associated Risk Factors of Hypertension and Prehypertension Among Vietnamese Adults. Am. J. Hypertens. 2014, 28, 89–97. [Google Scholar] [CrossRef] [PubMed]
  16. Nguyen, T.-P.-L.; Schuiling-Veninga, C.C.M.; Nguyen, T.B.Y.; Vu, T.-H.; Wright, E.P.; Postma, M.J. Adherence to hypertension medication: Quantitative and qualitative investigations in a rural Northern Vietnamese community. PLoS ONE 2017, 12, e0171203. [Google Scholar] [CrossRef]
  17. Son, P.T.; Quang, N.N.; Viet, N.L.; Khai, P.G.; Wall, S.; Weinehall, L.; Bonita, R.; Byass, P. Prevalence, awareness, treatment and control of hypertension in Vietnam—Results from a national survey. J. Hum. Hypertens. 2012, 26, 268. [Google Scholar] [CrossRef]
  18. The World Bank. Country Profile: Vietnam; World Bank Group: Washington, DC, USA, 2018. [Google Scholar]
  19. Rosengren, A.; Smyth, A.; Rangarajan, S.; Ramasundarahettige, C.; Bangdiwala, S.I.; AlHabib, K.F.; Avezum, A.; Bengtsson Boström, K.; Chifamba, J.; Gulec, S.; et al. Socioeconomic status and risk of cardiovascular disease in 20 low-income, middle-income, and high-income countries: The Prospective Urban Rural Epidemiologic (PURE) study. Lancet Glob. Health 2019, 7, e748–e760. [Google Scholar] [CrossRef]
  20. Tabrizi, J.S.; Sadeghi-Bazargani, H.; Farahbakhsh, M.; Nikniaz, L.; Nikniaz, Z. Prevalence and Associated Factors of Prehypertension and Hypertension in Iranian Population: The Lifestyle Promotion Project (LPP). PLoS ONE 2016, 11, e0165264. [Google Scholar] [CrossRef]
  21. Peltzer, K.; Pengpid, S.; Sychareun, V.; Ferrer, A.J.G.; Low, W.Y.; Huu, T.N.; Win, H.H.; Rochmawati, E.; Turnbull, N. Prehypertension and psychosocial risk factors among university students in ASEAN countries. BMC Cardiovasc. Disord. 2017, 17, 230. [Google Scholar] [CrossRef]
  22. Daniel, W.W.; Cross, C.L. Biostatistics: A Foundation for Analysis in the Health Sciences, 10th ed.; John Wiley & Sons: New York, NY, USA, 2013; p. 960. [Google Scholar]
  23. Pourhoseingholi, M.A.; Vahedi, M.; Rahimzadeh, M. Sample size calculation in medical studies. Gastroenterol. Hepatol. Bed Bench 2013, 6, 14–17. [Google Scholar] [PubMed]
  24. World Health Organization. Noncommunicable Diseases and Their Risk Factors: STEPwise Approach to Surveillance (STEPS); World Health Organization: Geneva, Switzerland, 2012. [Google Scholar]
  25. Ho Chi Minh City People’s Committee. Decision No. 58/2015/QĐ-UBND Promulgating Poverty Levels Applicable during 2016–2020; Lawsoft: Ho Chi Minh City, Vietnam, 31 December 2015. [Google Scholar]
  26. Ho Chi Minh City People’s Committee. Amended Decision No. 07/2019/QĐ-UBND Promulgating Poverty Levels Applicable during 2016–2020; Lawsoft: Ho Chi Minh City, Vietnam, 15 March 2019. [Google Scholar]
  27. World Health Organization. Global Status Report on Noncommunicable Diseases 2014; World Health Organization: Geneva, Switzerland, 2014. [Google Scholar]
  28. World Health Organization-International Society of Hypertension Writing Group, 2003 World Health Organization (WHO)/International Society of Hypertension (ISH) statement on management of hypertension. J. Hypertens. 2003, 21, 1983–1992. [CrossRef] [PubMed]
  29. Chobanian, A.V.; Bakris, G.L.; Black, H.R.; Cushman, W.C.; Green, L.A.; Izzo, J.; Joseph, L.; Jones, D.W.; Materson, B.J.; Oparil, S.; et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood PressureThe JNC 7 Report. JAMA 2003, 289, 2560–2571. [Google Scholar] [CrossRef] [PubMed]
  30. WHO Consultation on Obesity & World Health Organization. Obesity: Preventing and Managing the Global Epidemic: Report of a WHO Consultation; World Health Organization: Geneva, Switzerland, 2000. [Google Scholar]
  31. World Health Organization. Regional Office for the Western Pacific. Overweight and Obesity in the Western Pacific Region: An Equity Perspective; World Health Organization: Manila, Philippines, 2017. [Google Scholar]
  32. World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation, GENEVA, 8–11 December 2008; World Health Organization: Geneva, Switzerland, 2011. [Google Scholar]
  33. Maldonado, G.; Greenland, S. Simulation Study of Confounder-Selection Strategies. Am. J. Epidemiol. 1993, 138, 923–936. [Google Scholar] [CrossRef]
  34. IBM SPSS. IBM SPSS Statistics for Windows, Version 20.0; IBM Corp.: New York, NY, USA, 2011. [Google Scholar]
  35. Zhou, B.; Bentham, J.; Di Cesare, M.; Bixby, H.; Danaei, G.; Cowan, M.J.; Paciorek, C.J.; Singh, G.; Hajifathalian, K.; Bennett, J.E.; et al. Worldwide trends in blood pressure from 1975 to 2015: A pooled analysis of 1479 population-based measurement studies with 19·1 million participants. Lancet 2017, 389, 37–55. [Google Scholar] [CrossRef]
  36. Bui Van, N.; Vo Hoang, L.; Bui Van, T.; Anh, H.N.S.; Minh, H.T.; Do Nam, K.; Tri, T.N.; Show, P.L.; Nga, V.T.; Thimiri Govinda Raj, D.B.; et al. Prevalence and Risk Factors of Hypertension in the Vietnamese Elderly. High Blood Press. Cardiovasc. Prev. 2019, 26, 239–246. [Google Scholar] [CrossRef]
  37. Lemogoum, D.; Ngatchou, W.; Bika Lele, C.; Okalla, C.; Leeman, M.; Degaute, J.-P.; van de Borne, P. Association of urinary sodium excretion with blood pressure and risk factors associated with hypertension among Cameroonian pygmies and bantus: A cross-sectional study. BMC Cardiovasc. Disord. 2018, 18, 49. [Google Scholar] [CrossRef]
  38. Hien, H.A.; Tam, N.M.; Tam, V.; Derese, A.; Devroey, D. Prevalence, Awareness, Treatment, and Control of Hypertension and Its Risk Factors in (Central) Vietnam. Int. J. Hypertens. 2018, 2018, 12. [Google Scholar] [CrossRef]
  39. Bui Van, N.; Pham Van, Q.; Vo Hoang, L.; Bui Van, T.; Nguyen Hoang, N.; Do Nam, K.; Chu, D.-T. Prevalence and Risk Factors of Hypertension in Two Communes in the Vietnam Northern Mountainous, 2017. Biomed. Res. Int. 2018, 2018, 7. [Google Scholar] [CrossRef]
  40. Jayawardana, N.W.I.A.; Jayalath, W.A.T.A.; Madhujith, W.M.T.; Ralapanawa, U.; Jayasekera, R.S.; Alagiyawanna, S.A.S.B.; Bandara, A.M.K.R.; Kalupahana, N.S. Aging and obesity are associated with undiagnosed hypertension in a cohort of males in the Central Province of Sri Lanka: A cross-sectional descriptive study. BMC Cardiovasc. Disord. 2017, 17, 165. [Google Scholar] [CrossRef]
  41. Echouffo-Tcheugui, J.B.; Batty, G.D.; Kivimäki, M.; Kengne, A.P. Risk Models to Predict Hypertension: A Systematic Review. PLoS ONE 2013, 8, e67370. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Basu, S.; Millett, C. Social Epidemiology of Hypertension in Middle-Income Countries: Determinants of Prevalence, Diagnosis, Treatment, and Control in the WHO SAGE Study. Hypertension 2013, 62, 18–26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Lucumi, D.I.; Schulz, A.J.; Roux, A.V.D.; Grogan-Kaylor, A. Income inequality and high blood pressure in Colombia: A multilevel analysis. Cad. Saude Publica 2017, 33, e00172316. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Leng, B.; Jin, Y.; Li, G.; Chen, L.; Jin, N. Socioeconomic status and hypertension: A meta-analysis. J. Hypertens. 2015, 33, 221–229. [Google Scholar] [CrossRef]
  45. Su, M.; Si, Y.; Zhou, Z.; Shen, C.; Dong, W.; Fan, X.; Wang, X.; Wei, X. Comparing the income-related inequity of tested prevalence and self-reported prevalence of hypertension in China. Int. J. Equity Health 2018, 17, 82. [Google Scholar] [CrossRef]
  46. Huang, X.-B.; Chen, F.; Dai, W.; Song, L.; Tu, J.; Xu, J.-B.; Liu, J.-X.; Yi, Y.-J.; Liu, Y.; Chen, Y.; et al. Prevalence and risk factors associated with hypertension in the Chinese Qiang population. Clin. Exp. Hypertens. 2018, 40, 427–433. [Google Scholar] [CrossRef]
  47. Palafox, B.; McKee, M.; Balabanova, D.; AlHabib, K.F.; Avezum, A., Jr.; Bahonar, A.; Ismail, N.; Chifamba, J.; Chow, C.K.; Corsi, D.J.; et al. Wealth and cardiovascular health: A cross-sectional study of wealth-related inequalities in the awareness, treatment and control of hypertension in high-, middle- and low-income countries. Int. J. Equity Health 2016, 15, 199. [Google Scholar] [CrossRef] [Green Version]
  48. Oktay, A.A.; Akturk, H.K.; Jahangir, E. Diabetes mellitus and hypertension: A dual threat. Curr. Opin. Cardiol. 2016, 31, 402–409. [Google Scholar] [CrossRef]
  49. Tąpolska, M.; Spałek, M.; Szybowicz, U.; Domin, R.; Owsik, K.; Sochacka, K.; Skrypnik, D.; Bogdański, P.; Owecki, M. Arterial Stiffness Parameters Correlate with Estimated Cardiovascular Risk in Humans: A Clinical Study. Int. J. Environ. Res. Public Health 2019, 16, 2547. [Google Scholar] [CrossRef] [Green Version]
  50. Skrypnik, D.; Bogdański, P.; Zawiejska, A.; Wender-Ożegowska, E. Role of gestational weight gain, gestational diabetes, breastfeeding, and hypertension in mother-to-child obesity transmission. Pol. Arch. Intern. Med. 2019, 129, 267–275. [Google Scholar] [CrossRef] [Green Version]
  51. Cryer, M.J.; Horani, T.; DiPette, D.J. Diabetes and Hypertension: A Comparative Review of Current Guidelines. J. Clin. Hypertens. (Greenwich) 2016, 18, 95–100. [Google Scholar] [CrossRef]
  52. Suliburska, J.; Skrypnik, K.; Szulińska, M.; Kupsz, J.; Markuszewski, L.; Bogdański, P. Diuretics, Ca-Antagonists, and Angiotensin-Converting Enzyme Inhibitors Affect Zinc Status in Hypertensive Patients on Monotherapy: A Randomized Trial. Nutrients 2018, 10, 1284. [Google Scholar] [CrossRef] [Green Version]
  53. Suliburska, J.; Skrypnik, K.; Szulińska, M.; Kupsz, J.; Bogdański, P. Effect of hypotensive therapy combined with modified diet or zinc supplementation on biochemical parameters and mineral status in hypertensive patients. J. Trace Elem. Med. Biol. 2018, 47, 140–148. [Google Scholar] [CrossRef]
  54. Endres, M.; Heuschmann, P.U.; Laufs, U.; Hakim, A.M. Primary prevention of stroke: Blood pressure, lipids, and heart failure. Eur. Heart J. 2011, 32, 545–552. [Google Scholar] [CrossRef] [Green Version]
  55. Sharma, M.; Hakim, A.M. The Management of Hypertension for Primary Stroke Prevention: A Proposed Approach. Int. J. Stroke 2011, 6, 144–149. [Google Scholar] [CrossRef]
  56. Phillips, R.A.; Xu, J.; Peterson, L.E.; Arnold, R.M.; Diamond, J.A.; Schussheim, A.E. Impact of Cardiovascular Risk on the Relative Benefit and Harm of Intensive Treatment of Hypertension. J. Am. Coll. Cardiol. 2018, 71, 1601–1610. [Google Scholar] [CrossRef]
  57. Virdis, A.; Giannarelli, C.; Fritsch Neves, M.; Taddei, S.; Ghiadoni, L. Cigarette Smoking and Hypertension. Curr. Pharm. Des. 2010, 16, 2518–2525. [Google Scholar] [CrossRef]
  58. Wu, L.; Yang, S.; He, Y.; Liu, M.; Wang, Y.; Wang, J.; Jiang, B. Association between passive smoking and hypertension in Chinese non-smoking elderly women. Hypertens. Res. 2017, 40, 399–404. [Google Scholar] [CrossRef]
  59. Polónia, J.; Barbosa, L.; Silva, J.A.; Rosas, M. Improvement of aortic reflection wave responses 6 months after stopping smoking: A prospective study. Blood Press. Monit. 2009, 14, 69–75. [Google Scholar] [CrossRef]
  60. Mills Edward, J.; Thorlund, K.; Eapen, S.; Wu, P.; Prochaska Judith, J. Cardiovascular Events Associated With Smoking Cessation Pharmacotherapies: A Network Meta-Analysis. Circulation 2014, 129, 28–41. [Google Scholar] [CrossRef]
  61. Jensen, P.N.; Bao, T.Q.; Huong, T.T.T.; Heckbert, S.R.; Fitzpatrick, A.L.; LoGerfo, J.P.; Ngoc, T.L.V.; Mokdad, A.H. The association of estimated salt intake with blood pressure in a Viet Nam national survey. PLoS ONE 2018, 13, e0191437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Rodrigues, S.L.; Souza Júnior, P.R.; Pimentel, E.B.; Baldo, M.P.; Malta, D.C.; Mill, J.G.; Szwarcwald, C.L. Relationship between salt consumption measured by 24-h urine collection and blood pressure in the adult population of Vitória (Brazil). Braz. J. Med. Biol. Res. 2015, 48, 728–735. [Google Scholar] [CrossRef] [PubMed]
  63. Xu, J.; Chen, X.; Ge, Z.; Liang, H.; Yan, L.; Guo, X.; Zhang, Y.; Wang, L.; Ma, J. Associations of Usual 24-Hour Sodium and Potassium Intakes with Blood Pressure and Risk of Hypertension among Adults in China’s Shandong and Jiangsu Provinces. Kidney Blood Press. Res. 2017, 42, 188–200. [Google Scholar] [CrossRef]
  64. He, F.J.; Li, J.; MacGregor, G.A. Effect of longer term modest salt reduction on blood pressure: Cochrane systematic review and meta-analysis of randomised trials. BMJ 2013, 346, f1325. [Google Scholar] [CrossRef] [Green Version]
  65. Graudal, N.A.; Hubeck-Graudal, T.; Jurgens, G. Effects of low sodium diet versus high sodium diet on blood pressure, renin, aldosterone, catecholamines, cholesterol, and triglyceride. Cochrane Database Syst. Rev. 2017. [Google Scholar] [CrossRef]
  66. He, F.J.; Li, J.; MacGregor, G.A. Effect of longer-term modest salt reduction on blood pressure. Cochrane Database Syst. Rev. 2013. [Google Scholar] [CrossRef]
  67. Wu, X.; Li, B.; Lin, W.-Q.; Huang, L.-L.; Wang, X.-X.; Fu, L.-Y.; Li, B.-B.; Wang, P.-X. The association between obesity indices and hypertension: Which index is the most notable indicator of hypertension in different age groups stratified by sex? Clin. Exp. Hypertens. 2019, 41, 373–380. [Google Scholar] [CrossRef]
  68. Zhang, Q.; Mahapatra, T.; Huang, F.; Tang, W.; Guo, Y.; Tang, S.; Lei, Y.; Feng, L.; Wang, A.; Zhang, L.; et al. Association between Anthropometric Measures and Indicators for Hypertension Control among Kazakh-Chinese Hypertension Patients in Xinjiang, China: Results from a Cross-sectional Study. PLoS ONE 2017, 12, e0170959. [Google Scholar] [CrossRef]
  69. Taing, K.Y.; Farkouh, M.E.; Moineddin, R.; Tu, J.V.; Jha, P. Age and sex-specific associations of anthropometric measures of adiposity with blood pressure and hypertension in India: A cross-sectional study. BMC Cardiovasc. Disord. 2016, 16, 247. [Google Scholar] [CrossRef] [Green Version]
  70. Luz, R.H.; Barbosa, A.R.; d’Orsi, E. Waist circumference, body mass index and waist-height ratio: Are two indices better than one for identifying hypertension risk in older adults? Prev. Med. 2016, 93, 76–81. [Google Scholar] [CrossRef]
Table
Table 1. Participants’ characteristics, history of diseases, behaviors, and physical parameters.
Table 1. Participants’ characteristics, history of diseases, behaviors, and physical parameters.
VariablesTotal (N = 2203)Non-HTN (N = 1668)HTN (N = 535)p-Value *
Age groups <0.001
  18–44957 (43.4)867 (52.0)90 (16.8)
  45–59820 (37.3)572 (34.3)248 (46.4)
  60–69426 (19.3)229 (13.7)197 (36.8)
Gender <0.001
  Women1285 (58.3)1017 (61.0)268 (50.1)
  Men918 (41.7)651 (39.0)267 (49.9)
Marital status <0.001
  Never married313 (14.2)283 (17.0)30 (5.6)
  Ever married1890 (85.8)1385 (83.0)505 (94.4)
Education <0.001
  Elementary school or below368 (16.7)263 (15.8)105 (19.6)
  Secondary school675 (30.6)483 (29.0)192 (35.9)
  High school and above1160 (52.7)922 (55.2)238 (44.5)
Occupation <0.001
  Retirement421 (19.1)240 (14.4)181 (33.8)
  Officers/Workers/Traders910 (41.3)776 (46.5)134 (25.0)
  Others872 (39.6)652 (39.1)220 (41.1)
Monthly income <0.001
  Below poverty line488 (22.2)337 (20.2)151 (28.2)
  Above poverty line 1715 (77.8)1331 (79.8)384 (71.8)
Comorbidities
Diabetes mellitus <0.001
  No2064 (93.7)1611 (96.6)453 (84.7)
  Yes139 (6.3)57 (3.4)82 (15.3)
Hypercholesterolemia <0.001
  No1920 (87.2)1529 (91.7)391 (73.1)
  Yes283 (12.8)139 (8.3)144 (26.9)
Health behaviors
Smoking tobacco <0.001
  No1805 (81.9)1404 (84.2)401 (75.0)
  Yes398 (18.1)264 (15.8)134 (25.0)
Drinking alcohol 0.003
  No1694 (76.9)1308 (78.4)386 (72.1)
  Yes509 (23.1)360 (21.6)149 (27.9)
Consuming added salts 0.046
  No1095 (49.7)858 (51.4)237 (44.3)
  Yes1108 (50.3)810 (48.6)298 (55.7)
Daily intake of fruits and vegetables † 0.831
  <5 servings/day1937 (87.9)1468 (88.0)469 (87.7)
  ≥5 servings/day266 (12.1)200 (12.0)66 (12.3)
Exercise 0.246
  No883 (40.1)680 (40.8)203 (37.9)
  Yes1320 (59.9)988 (59.2)332 (62.1)
Anthropometrics
Height, cm, mean ± SD159.5 ± 7.2159.4 ± 7.1159.9 ± 7.40.229
Weight, kg, mean ± SD58.5 ± 14.257.3 ± 9.062.2 ± 23.7<0.001
BMI, kg/m2, mean ± SD22.9 ± 5.122.5 ± 2.924.3 ± 9.0<0.001
BMI groups <0.001
  Normal (<25.0 kg/m2)1758 (79.5)1390 (83.3)368 (68.8)
  Overweight/obesity (≥25.0 kg/m2)445 (20.2)278 (16.7)167 (31.2)
WC, cm, mean ± SD78.5 ± 10.976.6 ± 10.284.4 ± 10.7<0.001
HC, cm, mean ± SD90.3 ± 8.789.4 ± 8.793.0 ± 8.4<0.001
WHR, %, mean ± SD87.0 ± 9.385.8 ± 9.390.7 ± 8.1<0.001
Abdominal Obesity ‡ <0.001
  Normal1114 (50.6)917 (55.0)197 (36.8)
  Abdominal obesity1089 (49.4)751 (45.0)338 (63.2)
SBP, mmHg, mean ± SD123.3 ± 15.8117.6 ± 10.3140.9 ± 17.0<0.001
DBP, mmHg, mean ± SD77.2 ± 10.174.2 ± 7.586.7 ± 11.0<0.001
Abbreviations: HTN, hypertension; BMI, body mass index; WC, waist circumference; HC, hip circumference; WHR, waist–hip ratio; SBP, systolic blood pressure; DBP, diastolic blood pressure. * Data were presented as frequency and percentage, mean ± SD, and p-values were calculated using Chi-square test, and independent sample t-test, appropriately. † 1 serving is equal to 1 medium size piece of apple, banana, orange, or to ½ cup of chopped or cooked fruit, or to 1 cup of raw green leafy vegetables, or to ½ cup of other vegetables, cooked or chopped raw. ‡ Abdominal obesity was defined as a waist–hip ratio ≥0.90 for men, ≥0.85 for women.
Table
Table 2. The associated factors of hypertension via simple logistic regression models.
Table 2. The associated factors of hypertension via simple logistic regression models.
VariablesOverall (N = 2203) Women (N = 1285)Men (N = 918)
OR (95% CI)p-ValueOR (95% CI)p-ValueOR (95% CI)p-Value
Age groups
18–44Reference Reference Reference
45–594.18 (3.21–5.44)<0.0018.88 (5.39–14.63)<0.0013.21 (2.28–4.51)<0.001
60–698.29 (6.21–11.06)<0.00116.89 (10.08–28.28)<0.0017.75 (5.09–11.81)<0.001
Gender
WomenReference
Men1.56 (1.28–1.89)<0.001
Marital status
Never marriedReference Reference Reference
Ever married3.44 (2.33–5.08)<0.0013.18 (1.73–5.84)<0.0014.18 (2.50–6.97)<0.001
Education
Elementary school or belowReference Reference Reference
Secondary school1.00 (0.75–1.32)0.9760.94 (0.66–1.34)0.7430.95 (0.59–1.54)0.848
High school and above0.65 (0.50–0.85)0.0010.54 (0.38–0.77)0.0010.63 (0.40–0.99)0.043
Occupation
RetirementReference Reference Reference
Officers/Workers/Traders0.23 (0.18–0.30)<0.0010.20 (0.14–0.28)<0.0010.21 (0.14–0.32)<0.001
Others0.45 (0.35–0.57)<0.0010.46 (0.34–0.64)<0.0010.34 (0.23–0.52)<0.001
Monthly income
Below poverty lineReference Reference Reference
Above poverty line0.64 (0.52–0.81)<0.0010.52 (0.39–0.69)<0.0010.79 (0.55–1.13)0.195
Comorbidities
Diabetes
NoReference Reference Reference
Yes5.12 (3.59–7.29)<0.0016.28 (3.97–9.92)<0.0014.03 (2.30–7.06)<0.001
Hypercholesterolemia
NoReference Reference Reference
Yes4.05 (3.13–5.24)<0.0015.18 (3.67–7.32)<0.0013.03 (2.04–4.48)<0.001
Health behaviors
Smoking tobacco
NoReference Reference
Yes1.78 (1.40–2.25)<0.001 1.52 (1.14–2.03)0.004
Drinking alcohol
NoReference Reference
Yes1.40 (1.12–1.75)0.003 1.20 (0.90–1.60)0.208
Consuming added salts
NoReference Reference Reference
Yes1.33 (1.10–1.62)0.0041.54 (1.17–2.02)0.0021.18 (0.89–1.57)0.253
Daily intake of fruits and vegetables *
<5 servings/dayReference Reference Reference
≥5 servings/day1.03 (0.77–1.39)0.8310.80 (0.51–1.26)0.3361.26 (0.84–1.89)0.272
Exercise
NoReference Reference Reference
Yes1.13 (0.92–1.38)0.2461.10 (0.84–1.44)0.5071.07 (0.79–1.45)0.654
Anthropometrics
BMI groups
Normal (<25.0 kg/m2)Reference Reference Reference
Overweight/obesity (≥25.0 kg/m2)2.269 (1.814–2.838)<0.0012.37 (1.73–3.24)<0.0012.08 (1.50–2.86)<0.001
Abdominal Obesity †
NormalReference Reference Reference
Abdominal obesity2.10 (1.71–2.56)<0.0012.53 (1.89–3.38)<0.0011.92 (1.44–2.56)<0.001
Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index. * 1 serving is equal to 1 medium size piece of apple, banana, orange, or to ½ cup of chopped or cooked fruit, or to 1 cup of raw green leafy vegetables, or to ½ cup of other vegetables, cooked or chopped raw. † Abdominal obesity was defined as a waist–hip ratio ≥ 0.90 for men, ≥ 0.85 for women.
Table
Table 3. The associated factors of hypertension via multivariate logistic regression models.
Table 3. The associated factors of hypertension via multivariate logistic regression models.
VariablesOverall (N = 2203) Women (N = 1285)Men (N = 918)
OR (95% CI)p-ValueOR (95% CI)p-ValueOR (95% CI)p-Value
Age groups
  18–44Reference Reference Reference
  45–593.99 (3.01–5.30)<0.0016.80 (4.02–11.49)<0.0012.67 (1.85–3.87)<0.001
  60–698.37 (6.06–11.55)<0.00112.41 (7.16–21.52)<0.0015.92 (3.41–10.28)<0.001
Gender
  WomenReference
  Men2.32 (1.85–2.91)<0.001
Marital status
  Never married Reference
  Ever married 1.05 (0.52–2.12)0.893
Education
  Elementary school or belowReference Reference
  Secondary school1.26 (0.92–1.72)0.147 1.09 (0.65–1.84)0.734
  High school and above1.06 (0.78–1.44)0.700 0.92 (0.55–1.52)0.738
Occupation
  Retirement Reference
  Officers/Workers/Traders 0.69 (0.39–1.21)0.191
  Others 0.88 (0.52–1.48)0.620
Monthly income
  Below poverty lineReference Reference Reference
  Above poverty line0.80 (0.62–1.03)0.0800.64 (0.46–0.89)0.0081.17 (0.77–1.77)0.459
Diabetes comorbidity
  NoReference Reference Reference
  Yes2.72 (1.85–4.00)<0.0012.98 (1.81–4.91)<0.0012.25 (1.21–4.18)0.010
Health behaviors
Smoking tobacco
  No Reference
  Yes 1.38 (1.01–1.90)0.046
Consuming added salts
  NoReference Reference
  Yes1.66 (1.33–2.07)<0.0011.80 (1.32–2.45)<0.001
Anthropometrics
BMI groups
  Normal (<25.0 kg/m2)Reference Reference Reference
  Overweight/obesity (≥25.0 kg/m2)1.90 (1.48–2.44)<0.0011.64 (1.16–2.33)0.0052.18 (1.52–3.13)<0.001
Abdominal Obesity *
  NormalReference Reference Reference
  Abdominal obesity1.71 (1.36–2.15)<0.0012.07 (1.49–2.87)<0.0011.27 (0.92–1.76)0.142
Abbreviations: BMI, body mass index. * Abdominal obesity was defined as a waist–hip ratio ≥ 0.90 for men, ≥ 0.85 for women.

Share and Cite

MDPI and ACS Style

Quoc Cuong, T.; Van Bao, L.; Anh Tuan, N.; Van Thang, V.; Minh Quan, N.; Yang, S.-H.; Duong, T.V. Associated Factors of Hypertension in Women and Men in Vietnam: A Cross-Sectional Study. Int. J. Environ. Res. Public Health 2019, 16, 4714. https://doi.org/10.3390/ijerph16234714

AMA Style

Quoc Cuong T, Van Bao L, Anh Tuan N, Van Thang V, Minh Quan N, Yang S-H, Duong TV. Associated Factors of Hypertension in Women and Men in Vietnam: A Cross-Sectional Study. International Journal of Environmental Research and Public Health. 2019; 16(23):4714. https://doi.org/10.3390/ijerph16234714

Chicago/Turabian Style

Quoc Cuong, Tran, Le Van Bao, Nguyen Anh Tuan, Vo Van Thang, Nguyen Minh Quan, Shwu-Huey Yang, and Tuyen Van Duong. 2019. "Associated Factors of Hypertension in Women and Men in Vietnam: A Cross-Sectional Study" International Journal of Environmental Research and Public Health 16, no. 23: 4714. https://doi.org/10.3390/ijerph16234714

APA Style

Quoc Cuong, T., Van Bao, L., Anh Tuan, N., Van Thang, V., Minh Quan, N., Yang, S. -H., & Duong, T. V. (2019). Associated Factors of Hypertension in Women and Men in Vietnam: A Cross-Sectional Study. International Journal of Environmental Research and Public Health, 16(23), 4714. https://doi.org/10.3390/ijerph16234714

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop