High Blood Press Cardiovasc Prev DOI 10.1007/s40292-015-0106-3
ORIGINAL ARTICLE
Associations Between Hypertension and Body Mass Index and Waist Circumference in U.S. Adults: A Comparative Analysis by Gender Ranjana Roka1 • Akihiko Michimi1 • Gretchen Macy1
Received: 7 April 2015 / Accepted: 16 May 2015 Ó Springer International Publishing Switzerland 2015
Abstract Introduction The body mass index (BMI) and waist circumference (WC) are a risk of hypertension, but their potentially multiplicative effect on hypertension is underexplored. Aim To examine modifying effects of BMI and WC on hypertension using a nationally representative U.S. adult sample stratified by gender. Methods Data were derived from the 2009–2010 NHANES. Overweight and obesity were based on BMI of 25.0–29.9 and C30 kg/m2, respectively. High-risk WC was based on C102.0 and C88.0 cm for males and females, respectively. Hypertension was determined by systolic/diastolic blood pressure of C140/C90 mmHg, or taking prescribed medications. Logistic regression was used to examine the association between hypertension and BMI and WC by gender. Interaction terms were added to examine if BMI modified the effect of WC on hypertension. Results Both BMI and WC were significant predictors of hypertension in overall population. Gender-specific models indicated that BMI played an important role in hypertension risk among males, but WC in females. The interaction effects were present among males implying that the association of WC with hypertension was stronger if subjects were overweight or obese. This effect, however, was not present in females.
& Akihiko Michimi
[email protected] Ranjana Roka
[email protected] Gretchen Macy
[email protected] 1
Department of Public Health, College of Health and Human Services, Western Kentucky University, 1906 College Heights Blvd., Bowling Green, KY 42101-1038, USA
Conclusion BMI and WC may influence hypertension differently among males and females. Keywords Hypertension Body mass index Waist circumference Obesity Gender
1 Introduction Hypertension (high blood pressure) is one of the most prevalent chronic medical conditions in the United States with 67 million (33 %) or approximately one in three American adults having the condition [1]. The projection shows that by 2030 the prevalence of hypertension will increase 7.2 % from 2013 estimates [2]. Because a large proportion of middle-aged adults are affected by hypertension in their lifetime and uncontrolled hypertension is a powerful risk factor for cardiovascular disease, efforts to prevent hypertension are an ongoing public health challenge [3, 4]. Concurrently, obesity has been increasing rapidly. During 2009–2010, the prevalence of age-adjusted adult obesity is roughly 36 % for both men and women in the U.S [5]. Obesity is recognized as one of the most important risk factors for the risk of hypertension, and the prevalence of obesity and hypertension can predispose one to various other health complications such as diabetes, renal failure, and cardiovascular disease [6, 7]. Thus, obesity should be considered as a chronic medical condition that requires long term treatment along with hypertension [8]. National guidelines recommend lifestyle interventions for prevention and management of hypertension which includes weight reduction and control [9]. Various anthropometric measures, such as the body mass index (BMI), waist circumference (WC), waist-to-hip ratio, and waist-to-stature ratio have been used to examine obesity-
R. Roka et al.
related hypertension [10, 11]. Research findings, however, vary in part due to methodological approaches and different populations being studied. For example, when WC was treated as a dichotomous variable, hypertension was higher in overweight and obese groups compared to the normal BMI but when WC was treated as a continuous variable, the likelihood of hypertension was similar in all BMI categories [12]. The association between abdominal obesity and hypertension depends on age and sex among Chinese population [13]. In addition, hypertension is more strongly associated with WC in men and BMI in women than other obesity measures among Japanese population [14]. Other lifestyle factors, such as smoking, healthy diet, physical activity, and alcohol consumption may also influence the relationship between hypertension and obesity and abdominal obesity in various research settings [15–18]. Population-based research that focuses on the relationship between hypertension and obesity and abdominal obesity is limited and gender-specific approaches are less common. There is some evidence that shows a progressive increase in the odds of hypertension among abdominally obese adults stratified by BMI categories [19]. Health behaviors and practice also greatly differ by gender [20], which may impact hypertension and obesity outcomes differently between men and women [21, 22]. Thus, more research is needed that seeks to explain the relationship between various obesity measures and hypertension by gender. Although obesity and hypertension are a growing epidemic, there is inconsistency as to which anthropometric measure, i.e., BMI or WC, is indicative of an increasing risk of hypertension, and whether potentially multiplicative effects between BMI and WC are present for each gender. The purpose of this research was to examine the association between obesity and hypertension using a nationally representative sample of U.S. adults from the 2009–2010 National Health and Nutrition Examination Survey. Two specific obesity measures were examined: (1) generalized obesity based on the BMI and (2) abdominal obesity based on WC. This research explored the extent to which both obesity measures influenced hypertension, and whether or not WC may influence hypertension based on the levels of BMI measures (overweight and obese). Samples were also stratified by gender to see if genderspecific results were consistent with the overall population.
2 Methods 2.1 Study Design and Sample A cross-sectional analysis was conducted using data from the 2009–2010 National Health and Nutrition Examination
Survey (NHANES). NHANES is a large nationwide survey designed to examine the health and nutritional status of adults and children in the United States. This research included a subsample of the NHANES which consisted of 5886 adults aged 21–80 years who provided all information necessary to conduct the analysis. 2.2 Instruments The NHANES provides data from personal interviews, physical examinations, and laboratory tests. Interviews were conducted in participants’ homes where participants were asked about their demographic, socioeconomic, dietary, and health-related questions. Standardized physical examinations were conducted in well-equipped mobile examination centers by a physician, trained medical and health technicians, as well as health interviewers. Laboratory tests were performed during the physical examination. This study used individual-level data from interviews and physical examinations. 2.3 Data In this research, clinically measured hypertension was used as the dependent variable. Three consecutive blood pressure (BP) readings were obtained after resting quietly in a seated position for five minutes by using a standard manual mercury sphygmomanometer. The average of the three readings was calculated. Participants were classified as hypertensive if at least one of the following conditions applied: a systolic BP of 140 mmHg or greater; a diastolic BP of 90 mmHg or greater; or currently taking prescribed medications for high BP. Anthropometric measurements, i.e., body mass index (BMI) and waist circumference (WC), served as the primary independent variables to examine their association with hypertension. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). BMI was categorized into normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2) and obese (C30 kg/m2). WC was used as a surrogate for abdominal obesity. A measurement was taken at the uppermost lateral border of the right ileum to the nearest 0.1 centimeter (cm) at the end of the normal expiration. WC was categorized into high-risk (C102.0 and C88.0 cm for males and females, respectively) and low-risk if below these cutoffs as established standards. Pregnant women were excluded from all analyses. Other independent variables included were sociodemographic (age, sex, race/ethnicity, education, and income) and behavioral risk factors (smoking status and physical activity). Age was categorized into three groups; 21–40, 41–60, and 61–80 years. Race/ethnicity was based on selfreported responses and categorized into non-Hispanic
Associations Between Hypertension and Body Mass Index
whites, non-Hispanic blacks, and Hispanics. All other racial groups were excluded from this study due to small sample sizes. Educational level was categorized into less than high school, high school graduate or GED, some college or associate degree, and college graduate or above. Income status was based on the family income to poverty ratio (IPR). Families that have IPR below 1.00 had incomes that were below the official poverty threshold and IPR of greater than or equal to 1.00 were above the poverty level. IPR was categorized into four levels as poorest (less than 1.0), above poverty (1.0–1.9), middle class (2.0–3.9) and wealthy (more than or equal to 4.0). Smoking status was categorized into current, past, and never smoker. Participants were considered current smokers if they smoked currently, and past smokers if they had smoked at least 100 cigarettes in their entire life but did not smoke currently. Physical activity was classified into vigorous and moderate recreational activities. Vigorous recreational activities were considered any sports, fitness or activities that caused increases in breathing or heart rate like running for at least 10 minutes continuously and moderate recreational activities were considered any sports, fitness or activities that caused a small increase in breathing or heart rate such as swimming, bicycling for at least 10 minutes continuously. 2.4 Data Analysis NHANES provides sampling weights in order to make estimates nationally representative of the U.S. civilian adults who are non-institutionalized. Sampling weights are provided for interviews and medical examinations separately. Weights are assigned to each sampled person, and weighted samples provide estimates based on the U.S. Census population. Appropriate sampling weights were used in all analyses in this research. In addition, NHANES uses a complex, multistage, probability sampling design. To account for complex sampling design, the SAS SURVEY procedures were used to produce variance estimates and confidence limits, and cluster and stratification parameters were incorporated. Descriptive statistics were calculated for sample characteristics which included demographics and health risk behaviors as well as hypertension status and anthropometric measurements. 95 % confidence intervals (CI) for proportions were calculated to show sampling variability. Histograms of BMI and WC were examined to grasp an overall distribution of the measures. A number of multivariate logistic regression models were developed with hypertension as a dichotomous dependent variable controlling for sociodemographic and behavioral risk factors. First, an overall model was presented including all participants. Second, males and females were modeled
Table 1 Descriptive statistics of sample characteristics, NHANES 2009–2010 n
% [95 % CI]
21–40
1862
36.5 [34.2, 38.7]
41–60
2019
41.5 [40.1, 42.7]
61–80
1609
22.0 [20.4, 23.5]
2879
48.6 [47.5, 49.6]
3007
51.4 [50.3, 52.4]
Non-Hispanic White
2843
73.5 [66.8, 80.2]
Non-Hispanic Black
1063
12.2 [9.98, 14.3]
Hispanic
1659
14.3 [7.88, 20.7]
\High school
1688
19.0 [16.8, 21.1]
High school or GED
1346
22.8 [20.5, 25.1]
Some college
1624
29.8 [28.1, 31.6]
College graduate
1215
28.2 [25.4, 31.0]
Age, years
Sex Male Female Race/ethnicity
Education
Income poverty ratio \1.0
1169
14.7 [12.6, 16.6]
1.0–1.9
1371
19.1 [17.3, 20.7]
2.0–3.9
1334
29.2 [26.0, 32.3]
C4.0
1313
37.0 [34.5, 39.5]
Smoking status Non-smoker
3135
54.9 [51.4, 58.2]
Past smoker
1464
24.7 [22.0, 27.4]
Current smoker
1287
20.4 [18.5, 22.2]
Yes
1065
22.5 [19.9, 24.9]
No
4821
77.5 [75.0, 80.0]
Vigorous recreational activities
Moderate recreational activities Yes
2235
44.2 [42.1, 46.3]
No
3650
55.8 [53.6, 57.8]
Hypertensive
2129
33.4 [30.5, 36.2]
Non-hypertensive
3275
66.6 [63.7, 69.4]
Normal weight
1491
28.9 [26.2, 31.5]
Overweight
1953
33.8 [31.5, 36.1]
2236
37.2 [35.3, 39.1]
Hypertension status
BMI
Obese Waist circumference (WC) High Risk
3193
54.7 [51.6, 57.7]
Low Risk
2346
45.3 [42.2, 48.3]
Proportions were weighted and n indicated raw counts 95 % CI indicates 95 % confidence intervals
separately. Odds ratios (OR) and 95 % CIs were calculated for all three models. Third, the interaction between BMI and WC measures were additionally examined. Because both of these
R. Roka et al.
10 8 6 4 2 0
Ovwgt: 28.7% Obese: 38.1%
N:
2968
Mean: Median:
29.4 28.4
Mode: Std. Dev.:
24 7.1
WC risk: 64.8%
6 4 2
N:
2813
Mean: Median:
97.2 95.6
Mode: Std. Dev.:
94 16.1
0 Ovwgt: 39.2% Obese: 36.2%
N: Mean:
2838 28.8
Median: Mode: Std. Dev.:
28.0 27 5.9
WC risk: 44.2%
6 %
10 8 6 4 2 0
Male
% %
Male
Female
The sample characteristics were summarized in Table 1. The majority of participants were between the ages of 41 and 60 years (41.5 %) and more than half were females (51.4 %). Participants were represented predominantly by non-Hispanic whites (73.5 %) followed by Hispanics (14.3 %). With respect to education, the vast majority of participants had some college (29.8 %) or college education (28.2 %). Our data showed that 14.7 % were below the official poverty threshold whereas 85.3 % were above the poverty level. More than half of the participants (54.9 %) were non-smokers. Some adults had participated in vigorous recreational activities or moderate recreational activities (22.5 and 44.2 %, respectively). The proportion of participants who had hypertension was 33.4 %. The proportion of participants who were considered overweight and obese was 33.8 and 37.2 %, respectively. Approximately 54.7 % were considered abdominally obese according to their waist size. Histograms of BMI and WC depicted that compared to BMI-based
%
3 Results
obesity, generally more subjects were in the risk group for WC, particularly among females (Fig. 1). It should be also noted that females had a larger standard deviation for both BMI and WC measures than did males. Odds ratios (OR) from the overall model including all participants were summarized in Table 2. Older age groups were more likely to have hypertension, compared to the younger group. Compared to non-Hispanic whites, nonHispanic blacks were more likely to have hypertension but Hispanics were less likely to have hypertension. Those who participated in vigorous physical activity were less likely to have hypertension, compared to those who did not. Overweight and obese adults were more likely to have hypertension, compared to normal weight adults. For abdominal obesity, adults who had WC greater than the high-risk cutoff were more likely to have hypertension, compared to those who had below the high-risk cutoff. ORs from gender-specific models were summarized in Table 3. Among males, increased ages, being non-Hispanic black, overweight, obese, and abdominally obese (WC C 102 cm) were associated with having hypertension. Vigorous physical activity, on the other hand, was inversely associated with hypertension. Among females, obesity and abdominal obesity (WC C 88 cm) were associated with hypertension but not overweight status. Increased ages and being non-Hispanic black were also associated with hypertension among females. In addition, Hispanics were less likely to have hypertension, compared to the reference group. The interaction effects between WC and BMI (overweight and obese) were summarized in Table 4. Among males, the interaction effects were present. This implied that the association between WC and hypertension depended on BMI statuses. In other words, the association of WC with hypertension was stronger if subjects were overweight or obese, compared to those with normal
Female
measures are likely to be correlated, one variable may be interacting with the other [23]. For example, the one variable may modify the effect of the other variable on the outcome [24]. To address this potentially multiplicative effect between the two predictor variables, we explored if different levels of BMI (overweight and obese) modified the effect of WC on hypertension by adding an interaction term to each model. An interaction or moderation effect within a correlational framework may occur where the direction and/or strength of the correlation changes [24, 25]. Overall model summaries with regression coefficients were reported to see if interaction effects were present. All analyses were performed using SAS version 9.3.
4 2
N: Mean:
2719 101.4
Median: Mode: Std. Dev.:
100.2 101 15.2
0 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 BMXBMI
60 68 76 84 92 100 108 116 124 132 140 148 156 BMXWAIST
Fig. 1 Histograms of BMI [BMXBMI, (kg/m2)] and WC [BMXWAIST, (cm)] by gender. Overweight (BMI 25–29), obese (BMI C30), and high risk WC (C88 and C102 cm for female and male, respectively) cutoffs are indicated by the vertical line
Associations Between Hypertension and Body Mass Index Table 2 Odds ratios for hypertension including all participants OR [95 % CI] Age, years 21–40 (REF) 41–60
7.09 [5.06, 9.94]**
61–80
29.2 [20.9, 40.9]**
Sex Female (REF) Male
1.21 [0.95, 1.55]
Race/ethnicity Non-Hispanic white (REF) Non-Hispanic black Hispanic Education
1.99 [1.45, 2.72]** 0.67 [0.53, 0.84]**
\High school (REF) High school grad or GED
1.11 [0.88, 1.41]
Some college
0.97 [0.75, 1.25]
College graduate
0.77 [0.54, 1.09]
Income poverty ratio \1.0 (REF) 1.0–1.9
1.01 [0.75, 1.36]
2.0–3.9
0.96 [0.66, 1.39]
C4.0
0.79 [0.56, 1.11]
Smoking status Non-smoker (REF) Past smoker
1.14 [0.98, 1.33]
Current smoker
0.81 [0.65, 1.01]
Vigorous recreational activities No (REF) Yes
0.69 [0.56, 0.86]**
Moderate recreational activities No (REF) Yes
1.01 [0.81, 1.25]
BMI Normal (REF) Overweight
1.35 [1.03, 1.76]*
Obese
2.41 [1.76, 3.30]**
WC Low risk (REF) High risk
1.53 [1.17, 2.00]**
95 % CI indicates 95 % confidence intervals * P \ 0.05, ** P \ 0.01
weight males. Among the general and female population, however, the interaction effects were not present. This implied that the association between WC and hypertension did not depend on whether or not subjects were normal weight, overweight, or obese among general and female populations.
4 Discussion Both anthropometric measurements (BMI and WC) were important factors associated with hypertension. In the overall model, BMI, especially for the obese group, played an important role in explaining the prevalence of hypertension due to the relatively higher odds. These findings were generally consistent with other work that reported that the risk of developing hypertension was greater with increased BMI, compared to WC [26, 27]. Although other studies suggest that abdominal fat deposition is generally a stronger predictor of hypertension than BMI-based measures [28, 29], others stress that both BMI and WC should be considered in assessing hypertension risks [30]. Research shows that the relationship between hypertension and BMI as well as WC should take into account gender variations [13, 31]. In the male only model, both BMI (overweight and obese) and WC were significantly associated with hypertension but odds were relatively higher for BMI than WC. In female only model, in contrast, odds of hypertension were relatively higher for WC than BMI. One possible explanation for this gender variability is how subjects are classified into risk and non-risk groups based on the current established guidelines [32]. For example, the WC risk cutoff for females puts a greater proportion of subjects into a risk group than that for males (Fig. 1). Another explanation is that the distribution of subjects on the BMI continuum differs by gender even with the same standard cutoff. Our data showed that the proportion of obesity was similar but the proportion of overweight greatly differed by gender (39.2 and 28.7 % for males and females, respectively). Thus, WC cutoffs and uneven distribution of BMI between males and females may likely respond to hypertension differently. A progressive increase in the odds of hypertension has been reported when adults are stratified by the WC and BMI categories, and the highest risk of hypertension was found among both abdominally obese and BMI-based obese group [19]. Our results from the interaction model indicated similar effects while we applied different statistical methods. Our results, however, emphasize gender variability which suggests that the association of WC with hypertension may likely to be stronger if subjects were also overweight or obese among males. Other research supports that using combined measures of BMI and WC may provide greater insights into identifying various cardiovascular risk factors [33]. Our results also indicated that the interaction effects were present in males, but not in the overall and female models. The absence of interaction effects in the overall population may be in part influenced by an inclusion of females. The interaction effects among males remained when treating adults as normotensive who were
R. Roka et al. Table 3 Odds ratios for hypertension stratified by gender
Male OR [95 % CI]
Female OR [95 % CI]
41–60
5.57 [3.89, 7.97]**
9.78 [6.32, 15.1]**
61–80
19.4 [14.2, 26.3]**
47.6 [26.8, 84.6]**
Non-Hispanic black
2.13 [1.55, 2.91]**
2.07 [1.24, 3.45]**
Hispanic
0.74 [0.53, 1.04]
0.60 [0.44, 0.83]**
Age 21–40 (REF)
Race/ethnicity Non-Hispanic white (REF)
Education \High school (REF) High school grad or GED
1.04 [0.64, 1.68]
1.22 [0.81, 1.82]
Some college
0.83 [0.56, 1.25]
1.14 [0.86, 1.50]
College graduate
0.85 [0.55, 1.32]
0.72 [0.46, 1.15]
1.15 [0.72, 1.62]
0.81 [0.60, 1.37]
Income poverty ratio \1.0 (REF) 1.0–1.9 2.0–3.9
1.30 [0.86, 1.96]
0.75 [0.45, 1.24]
C4.0
1.13 [0.65, 1.97]
0.55 [0.28, 1.08]
Past smoker
1.09 [0.81, 1.46]
1.25 [0.85, 1.84]
Current smoker
0.91 [0.78, 1.08]
0.73 [0.50, 1.06]
0.63 [0.46, 0.87]**
0.74 [0.43, 1.29]
1.13 [0.86, 1.48]
0.90 [0.65, 1.25]
2.05 [1.32, 3.18]** 2.94 [1.84, 4.70]**
0.71 [0.49, 1.01] 1.61 [1.06, 2.42]*
1.56 [1.11, 2.19]**
2.11 [1.40, 3.18]**
Smoking status Non-smoker (REF)
Vigorous recreational activities No (REF) Yes Moderate recreational activities No (REF) Yes BMI Normal (REF) Overweight Obese WC Low risk (REF) High risk 95 % CI indicates 95 % confidence intervals * P \ 0.05, ** P \ 0.01
taking BP medication and whose BP was normal. While the interaction effects among males are noteworthy, mechanisms responsible for this gender variability need further evaluations for more concrete conclusions. Despite the lack of interaction effects in the overall and female models, BMI and WC were independently associated with hypertension. Because of this gender variability, there may be distinct physiological features between males and females with respect to the body fat distribution, and how this gender-based variability in body fat distribution may influence the risk of hypertension differently in men and women [34, 35]. In addition, there
is some physiological evidence from women’s health perspectives that postmenopausal women may increase the risk of developing hypertension [36]. With respect to this notion, we reran models to explore the effects of menopause on BMI and WC and their association with hypertension among females. Although menopause was significantly associated with hypertension (OR 3.21, 95 % CI [1.96, 5.22]), there were no interactions between menopause and BMI or WC that influenced hypertension. More research is encouraged in the area of obesity and hypertension, and how menopause may play a role among obese women.
Associations Between Hypertension and Body Mass Index Table 4 Interaction effects among all subjects (overall) and by gender
Overall
Intercept
Male 2
Female
Estimate
Wald v
Estimate
-2.5906
247.66**
-2.4214
2
Wald v
81.665**
Estimate
Wald v2
-2.6898
71.403**
-0.2171
0.7678
WC low risk (ref.) WC high risk
-0.2839
7.1142**
-0.3394
8.4025**
BMI normal (ref.) Overweight
-0.0863
1.7772
-3.1748
124.04**
0.1980
5.2784*
Obese
-0.2632
6.7861**
-3.2354
161.44**
-0.4752
5.2419*
WC*Overweight
-0.1420
2.5602
2.8004
95.572**
0.0965
0.5142
WC*Obese
-0.0102
0.0111
2.9580
95.413**
-0.1824
0.6436
Interaction terms
All covariates were included in all models which indicated similar results described in Tables 2 and 3 * P \ 0.05, ** P \ 0.01
As for lifestyle factors, the overall model showed that adults who participated in vigorous physical activity had a reduced risk of hypertension. Subsequent gender-specific models revealed that the inverse relationship between vigorous physical activity and hypertension was found in males only. A prospective cohort study showed results similar to our findings which states that vigorously active men are less likely to develop hypertension [37]. The level of human health outcomes is shaped in part by a wide range of social and behavioral factors which may differ by gender [38]. Our data indicated that males were vigorously more active (28.5 %, 95 % CI [25.2, 31.8]) than females (16.7 %, 95 % CI [14.5, 19.0]). If males were more capable of vigorous physical activity than females such as running, their risk of developing hypertension in conjunction with vigorous physical activity would be lower in males than in females [39]. Thus, health interventions may be tailored by capitalizing on gender-specific health risks and behaviors in ways that health is promoted. The strength of this study was the use of the 2009–2010 NHANES which provided a nationally representative adult sample. Blood pressure, WC, weight and height were measured by trained professionals. Thus, it provided credibility to the data and avoided errors that could occur from self-reporting. Gender-specific models may provide additional guidelines to primary care physicians to incorporate BMI for males and WC for females in routine practice in an effort to reduce hypertension. In addition, BMI is likely to modify the effect of WC on hypertension among males, thus, more strict weight control may be recommended for men. 4.1 Limitations Several limitations should be noted. First, cross-sectional data analyzed in this research cannot be used to infer
causality between hypertension and BMI and WC. Hypertension classification was based on BP at the time of screening. Therefore, some participants may have been misclassified if their readings were inconsistent at the time of measurement. Second, this study involved only BMI and WC as obesity measures. Other measurements, such as waist-to-hip ratio and waist-to-stature ratio, were not used to keep the results concise and straightforward. There are also different WC measurement protocols used in other studies, such as WHO and MESA. Using different WC protocols or cutoffs may produce different results. Third, other important factors associated with hypertension were not included due to data limitation, such as alcohol intake and family history of hypertension. Lastly, missing values were excluded which reduced our sample sizes. Individuals who did not provide all information may have different characteristics from those who went through all interviews and physical examinations. Thus, our results may be subject to selfselection bias.
5 Conclusions This research reported both BMI and WC as a risk of hypertension. However, gender-specific analyses found that BMI was a greater risk among men and WC was a greater risk among women in hypertension prevalence. In addition, the association of WC with hypertension was stronger if subjects were also overweight or obese among males. Health interventions may be tailored based on gender since males and females may have different health risks and lifestyle behaviors that may influence hypertension differently. Conflict of interest
The authors declare no conflict of interest.
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