Prevalence of hypertension and associated risk factors in Chinese Jing compared with Mulao populations

Abstract

Objective

These authors contributed equally to this work. At present, they work at the Hezhou People’s Hospital, Hezhou, China.

To retrospectively compare differences in the prevalence of hypertension and associated risk factors between the Chinese Jing and Mulao populations.

Methods

Subjects of Jing and Mulao ethnicities were surveyed using stratified randomized sampling. Demography, diet and lifestyle data were collected using standardized questionnaires. Several anthropometric parameters, blood pressure (BP) levels and serum lipid concentrations were obtained.

Results

Data from 915 Jing and 911 Mulao subjects aged ≥35 years were included. Diastolic BP levels and prevalence of hypertension were lower, but prevalence of isolated systolic hypertension was higher, in the Jing compared with the Mulao population. Prevalence of hypertension in the age 60–69 years, body mass index (BMI) > 24 kg/m², and smoker subgroups was lower in the Jing compared with the Mulao populations. Prevalence of hypertension correlated with age, cigarette smoking, triglyceride level, waist circumference, sodium intake and total dietary fibre in the Jing population; hypertension prevalence also correlated with age, triglyceride level, BMI, total fat, sodium intake and total dietary fibre in the Mulao population (unconditional logistic regression analyses).

Conclusions

Prevalence of hypertension and associated risk factors were different between the two ethnic minorities, which might result from the combined effects of differences in their geographic, dietary, lifestyle, and genetic backgrounds.

Keywords

Blood pressure hypertension prevalence risk factor lifestyle

Introduction

Hypertension is an important and modifiable risk factor for cardiovascular disease.^1,2 Ethnic/racial differences in blood pressure (BP) and in the prevalence of hypertension have been described, for example hypertension is more prevalent in African–American than in nonHispanic Caucasian populations.^3,4 In China, the prevalence of hypertension in economically developed regions is reported to be significantly higher in rural than in urban residents,⁵ and in northern compared with southern regions.⁶ Data regarding ethnic/racial differences in hypertension are limited and somewhat contradictory, however: some studies show no difference in BP between African–American and Caucasian children;^7,8 others show higher BP levels in Caucasian children.^9,10

China has a majority population of Han ethnicity and 55 officially recognized ethnic minorities.¹¹ The Jing and Mulao ethnic groups are isolated minorities in the Guangxi Zhuang Autonomous Region, China. The Jing population is the only oceanic ethnic group in China, with a very small minority population of 28 199 reported in 2010.¹² In the early 16th century, the Jing ancestors emigrated from Vietnam to China to first settle on the three islands of Wanwei, Wutou and Shanxin in Dongxing city, where almost all of the Jing population now live.¹² Mulao is one of the mountain dwelling minorities, with a population of 216 257 in 2010, and ∼90% of Mulao people live in the Luocheng Mulao Autonomous County, Guangxi. Mulao history can be traced back to the Jin Dynasty (AD 265–420).^11,13

The particular customs and culture (including intraethnic marriages, diet, lifestyle and genetic backgrounds) differ between the Jing and Mulao populations,^12,13 but little is known about differences in the prevalence of hypertension and associated risk factors between the two ethnic minorities. The aim of the present study, therefore, was to compare the prevalence of hypertension and associated risk factors between the Jing and Mulao populations.

Subjects and methods

Study population

The present retrospective cross-sectional study was conducted at the Department of General Practice, Jiangping Health Station of Dongxing City, Dongxing, China and The Disease Control and Prevention Centre of Luocheng Mulao Autonomous County, Hechi, during December 2009 and January 2010. All subjects included in the present study were randomly selected, using a computer-generated randomization schedule, from a group of stratified randomized samples that had been produced for a previous study.^14,15 Exclusion criteria comprised subjects aged <35 years and history and/or evidence of diseases other than hypertension, such as hepatic, renal or thyroid disease, myocardial infarction, stroke, congestive heart failure, diabetes or fasting blood glucose levels >7.0 mmol/l (determined by glucose meter readings). Subjects with a history of hypertension and/or who took antihypertensive drugs were included in the present study.¹⁶

The previous stratified randomized sampling of Jing ethnic subjects was performed as follows. First, five ‘teams’ (where one ‘team’ comprised a group of 30–70 families) were randomly selected from each ‘island’ (where one ‘island’ comprised seven to nine teams). Then, subjects in each ‘team’ were separated into sex and age subgroups, which extended beyond the age groups in the present study because several studies were being undertaken using these data: the age groups were 15–19, 20–29, 30–39, 40–49, 50–59, 60–69, 70–79, and >80 years). Finally, the sampled residents were randomly determined from the local population registers. For the group of stratified randomized samples obtained prior to the present study, 1 800 subjects were visited by study investigators or local officials and asked to participate; 1 674 subjects responded (response rate, 93%). A total of 52 participants (3.1%) with a history and/or evidence of diseases other than hypertension, such as hepatic, renal or thyroid disease, myocardial infarction, stroke, congestive heart failure, diabetes or fasting blood glucose >7.0 mmol/l (determined by glucose meter readings) were excluded from this initial bank of stratified randomized samples. Jing subjects for the present study were randomly selected from this sample pool. The Mulao population was sampled using the same method at Luocheng Mulao Autonomous County, Guangxi, China, during December 2009 and January 2010.¹⁵

The protocol was approved by the Ethics Committee of the First Affiliated Hospital, Guangxi Medical University and written informed consent was obtained from each participant.

Epidemiological survey

The present survey was conducted according to standardized methods.^16,17 Data regarding demographic characteristics, cigarette smoking, alcohol intake, education level, physical activity, and medical history were obtained using a standardized questionnaire. Overall physical activity was ascertained using a modified version of the Harvard Alumni Physical Activity Questionnaire,¹⁸ which included questions about the number of hours per day spent sleeping and in sedentary, light, moderate, and vigorous activities. A 24 h dietary recall interview, conducted by a trained physician (L-M.Y.) at the relevant investigation site, was used to determine the dietary intake of each subject. Detailed descriptions of all foods, beverages and supplements consumed during the 24 h period before the interview (including the quantity, cooking method and brand names) were recorded. Intake of macronutrients according to the ingredients was determined using the 2002 Chinese Food Composition Table.¹⁹ Particiants underwent a physical examination at the relevant investigation site that included measurements of body height, weight and waist circumference. Body mass index (BMI) was calculated as weight (kg) divided by height (m)². Sitting BP was measured three times by a trained physician (F.H.) using a standard mercury sphygmomanometer after the subject had rested in the sitting position for 5 min; BP was calculated as the mean of three measurements. Systolic BP and diastolic BP were determined by the first and fifth Korotkoff sounds, respectively.

Determination of serum lipid levels

A 5-ml venous blood sample was obtained from an antecubital vein from each subject, using standard methods, between 08.00 h and 11.00 h, following a ≥12-h fast. For serum collection, 2 ml of each sample was transferred into a glass tube and allowed to clot at room temperature for 30–60 min. Immediately following clotting, serum was separated by centrifugation for 15 min at 1006.2 g at 4℃, then stored at 4℃ for ∼1–3 days prior to analysis. Serum total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels in the samples were determined enzymatically using commercially available kits: Tcho-1, Triglyceride-LH (Randox Laboratories, Ardmore, County Antrim, UK); Cholestest N HDL and Cholestest LDL (Daiichi Pure Chemicals Co., Ltd., Tokyo, Japan), according to the manufacturer’s instructions. Serum apolipoprotein A1 and apolipoprotein B levels were measured using a commercially available immunoturbidimetric assay (Randox Laboratories) according to the manufacturer’s instructions. All assays were quantified using an autoanalyser (Type 7170A; Hitachi Ltd., Tokyo, Japan) in the Clinical Science Experiment Centre of the First Affiliated Hospital, Guangxi Medical University.

Diagnostic criteria

Hypertension was defined as a mean systolic BP of ≥140 mmHg and/or a mean diastolic BP of ≥90 mmHg, and/or self-reported pharmacological treatment for hypertension within 2 weeks prior to interview. Subjects with a mean systolic BP of ≥140 mmHg and a diastolic BP of <90 mmHg were defined as having isolated systolic hypertension. Normal blood lipid ranges at the Clinical Science Experiment Centre of the First Affiliated Hospital, Guangxi Medical University were as follows: serum total cholesterol, 3.10–5.17 mmol/l; triglyceride, 0.56–1.70 mmol/l; HDL-C, 0.91–1.81 mmol/l; LDL-C, 2.70–3.20 mmol/l; apolipoprotein A1, 1.00–1.76 g/l; apolipoprotein B, 0.63–1.14 g/l and the apolipoprotein A1/B ratio, 1.00–2.50. Subjects with total cholesterol >5.17 mmol/l, triglyceride >1.70 mmol/l, and total cholesterol >5.17 mmol/l and/or triglyceride >1.70 mmol/l were defined as having hypercholesterolaemia, hypertriglyceridaemia and hyperlipidaemia; respectively.¹⁹ BMIs of <24, 24–28, and >28 kg/m² were defined as normal weight, overweight and obese, respectively.²⁰

Statistical analyses

All statistical analyses were performed using the SPSS® statistical software package, version 17.0 (SPSS Inc., Chicago, IL, USA). Quantitative variables were presented as mean ± SD. Mean values of general characteristics were compared between Jing and Mulao populations using Student’s unpaired t-test. Comparisons of BP levels between both ethnic groups were tested by analysis of covariance. For statistical analyses, data were adjusted for sex, age, weight, body height, BMI, alcohol intake, cigarette smoking and serum lipid levels. Qualitative variables were presented as n (%) prevalence. Between-group differences were assessed using χ²-test. Logistic regression analyses were performed to evaluate the association between hypertension and ethnic group as follows: ethnic group (Jing = 0; Mulao = 1); sex (male = 0; female = 1); age in years (<40 = 1; 40–49 = 2; 50–59 = 3; 60–69 = 4; 70–79 = 5; and >80 = 6); BMI (≤24 kg/m²= 0; >24 kg/m²= 1); waist circumference (<90 [male]/85 [female] cm = 0; ≥90 [male]/85 [female] cm = 1); total cholesterol (≤5.17 mmol/l = 0; >5.17 mmol/l = 1); triglyceride (≤1.70 mmol/l = 0; >1.70 mmol/l = 1); alcohol consumption (nondrinker = 0; drinker = 1); cigarette smoking (nonsmoker = 0; smoker = 1). Unconditional logistic regression analysis was also performed with Jing alone, Mulao alone, or a combined population of Jing and Mulao. A backward stepwise multiple logistic regression method was used to select the risk factors significantly associated with hypertension. A P value <0.05 was considered statistically significant.

Results

General characteristics

The present study included 915 Jing subjects (3.24% of the total Jing population) and 911 Mulao subjects. The Jing study population comprised 339 (37.05%) male and 576 (62.95%) female subjects, aged 35–92 years (57.51 ± 13.05 years). The Mulao study population comprised 340 (37.32%) male and 571 (62.68%) female subjects, aged 35–93 years (57.51 ± 13.04 years). All subjects were essentially healthy in medical history, physical examination and biochemical analysis, and had no evidence of any chronic illness such as hepatic, renal, thyroid or cardiac dysfunction. A total of 55 (6.01%) Jing subjects and 62 (6.81%) Mulao subjects were treated with antihypertensive drugs.

General characteristics of the Jing and Mulao populations are shown in Table 1. Body height, weight, BMI, waist circumference, prevalence of hypertriglyceridaemia and hyperlipidaemia, and protein intake were significantly higher in the Jing than in the Mulao population (P < 0.05). Duration of physical activity, intake of energy, carbohydrate, total fat, total dietary fibre and the percentage of subjects who consumed alcohol or smoked cigarettes were significantly lower in the Jing compared with Mulao population (P < 0.001). In addition, 95% of the cigarettes smoked by the Mulao subjects consisted of natural tobacco leaves, whereas 95% of the cigarettes smoked by the Jing subjects were commercially available brands. No significant differences in education level, dietary cholesterol, sodium intake, age and sex, or in the prevalence of hypercholesterolemia were observed between the two ethnic populations (P > 0.05).

Table 1.

Comparison of general characteristics between Chinese Jing and Mulao ethnic populations aged ≥ 35 years in a study of hypertension prevalence.

	Population
Parameter	Jing n = 915	Mulao n = 911	t, χ ²	Statistical significance
Age, years	57.51 ± 13.05	57.51 ± 13.04	<0.001	NS
Male/female	339/576	340/571	0.015	NS
Education level, years	4.87 ± 3.38	4.58 ± 3.66	1.759	NS
Physical activity, h/week	43.33 ± 7.44	46.21 ± 8.71	−7.598	P < 0.001
Body height, cm	156.57 ± 7.78	153.86 ± 7.81	7.418	P < 0.001
Body weight, kg	57.51 ± 9.86	52.36 ± 9.39	11.442	P < 0.001
BMI, kg/m²	23.29 ± 3.22	22.06 ± 3.20	7.914	P < 0.001
BMI >24 kg/m², n (%)	284 (31.04)	223 (24.48)	9.794	P = 0.002
Waist circumference, cm	80.00 ± 9.19	75.38 ± 8.69	11.064	P < 0.001
Alcohol consumption, n (%)	105 (11.48)	179 (19.65)	23.219	P < 0.001
Cigarette smoking, n (%)	118 (12.90)	173 (18.99)	12.654	P < 0.001
Energy intake, kJ/day	8838.64 ± 387.44	9131.45 ± 408.17	−15.722	P < 0.001
Carbohydrate intake, g/day	390.23 ± 19.67	420.12 ± 22.68	−30.088	P < 0.001
Protein intake, g/day	52.33 ± 7.88	50.95 ± 6.27	4.140	P < 0.001
Total fat intake, g/day	27.38 ± 4.57	29.77 ± 3.64	−12.358	P < 0.001
Dietary cholesterol, mg/day	197.34 ± 98.49	205.76 ± 96.74	1.843	NS
Total dietary fibre, g/day	8.12 ± 3.03	9.87 ± 4.47	9.796	P < 0.001
Sodium intake, g/day	8.88 ± 3.44	9.19 ± 4.12	1.746	NS
Hypercholesterolaemia, n (%)	429 (46.89)	440 (48.30)	0.366	NS
Hypertriglyceridaemia, n (%)	288 (31.48)	200 (21.95)	21.134	P < 0.001
Hyperlipidaemia, n (%)	553 (60.44)	508 (55.76)	4.097	P = 0.043

Data presented as mean ± SD, or n (%) prevalence.

BMI, body mass index; hypercholesterolaemia, total cholesterol >5.17 mmol/l; hypertriglyceridaemia, triglyceride >1.70 mmol/l; hyperlipidaemia, total cholesterol >5.17 mmol/l and/or triglyceride >1.70 mmol/l.

NS, no statistically significant between-group difference (P > 0.05).

BP levels and hypertension prevalence

Levels of diastolic BP were lower and prevalence of isolated systolic hypertension was higher in the Jing than in the Mulao population (P ≤ 0.001; Table 2), but prevalence of hypertension was lower in the Jing than in the Mulao population (P < 0.05). There were no significant differences in systolic BP or pulse pressure levels between the two ethnic groups (P > 0.05).

Table 2.

Comparison of blood pressure levels and prevalence of hypertension between Chinese Jing and Mulao ethnic populations aged ≥35 years.

	Population
Parameter	Jing n = 915	Mulao n = 911	t χ ²	Statistical significance
Systolic blood pressure, mmHg	131.92 ± 22.28	132.58 ± 23.17	−6.262	NS
Diastolic blood pressure, mmHg	80.07 ± 10.58	81.88 ± 12.06	−3.416	P = 0.001
Pulse pressure, mmHg	51.74 ± 17.95	50.70 ± 17.40	1.251	NS
Isolated systolic BP ≥ 140 mmHg, n (%)	149 (16.28)	58 (6.37)	44.671	P < 0.001
Isolated diastolic BP ≥ 90 mmHg, n (%)	67 (7.32)	55 (6.04)	1.209	NS
Systolic BP ≥ 140 and diastolic BP ≥ 90 mmHg, n (%)	132 (14.43)	278 (30.52)	67.872	P < 0.001
Hypertension, n (%)	348 (38.03)	391 (42.92)	4.525	P = 0.033
Hypertension awareness rate, n (%)	80 (22.99)	76 (19.44)	1.394	NS
Hypertension treatment rate, n (%)	48 (13.79)	50 (12.79)	0.162	NS
Hypertension control rate, n (%)	15 (4.31)	10 (2.56)	1.731	NS

Data presented as mean ± SD, or n (%) prevalence.

BP, blood pressure; isolated systolic BP ≥ 140 mmHg, isolated systolic hypertension; hypertension, SBP ≥140 mmHg and/or DBP ≥90 mmHg, and/or self-reported pharmacological treatment for hypertension.

NS, no statistically significant between-group difference (P > 0.05).

There were no differences in the rates of awareness, treatment and control of hypertension between the Jing and Mulao populations (P > 0.05), and the rates of these indices in both ethnic groups were very low (Table 2).

Demographic and lifestyle factors and hypertension prevalence

The prevalence of hypertension at different age ranges in the Chinese Jing and Mulao ethnic populations is shown in Table 3. The prevalence of hypertension was found to be significantly lower in the Jing compared with Mulao ethnic groups in the 60–69 years of age subgroup (P < 0.05).

Table 3.

Comparison of the prevalence of hypertension in different age subgroups between Chinese Jing and Mulao ethnic populations aged ≥35 years.

		Hypertension prevalence, n (%)
Ethnicity and age subgroup	n	Systolic BP ≥140 mmHg	Diastolic BP ≥90 mmHg	Systolic BP ≥ 140 and diastolic BP ≥ 90 mmHg	Prevalence of hypertension
Jing ≤40 years	95	4 (4.21)	6 (6.32)	7 (7.37)	17 (17.89)
Mulao ≤40 years	102	1 (0.98)	11 (10.78)	9 (8.82)	21 (20.59)
χ ²	–	2.075	1.246	0.140	2.229
Statistical significance	–	NS	NS	NS	NS
Jing 40–49 years	225	21 (9.33)	23 (10.22)	23 (10.22)	67 (29.78)
Mulao 40–49 years	220	17 (7.73)	15 (6.82)	36 (16.36)	68 (30.91)
χ ²	–	0.367	1.650	3.648	0.067
Statistical significance	–	NS	NS	NS	NS
Jing 50–59 years	227	33 (14.54)	13 (5.73)	33 (14.54)	79 (34.80)
Mulao 50–59 years	229	28 (12.23)	9 (3.93)	58 (25.33)	95 (41.48)
χ ²	–	0.525	0.801	8.309	2.158
Statistical significance	–	NS	NS	P = 0.004	NS
Jing 60–69 years	183	38 (20.77)	38 (20.77)	1 (0.55)	77 (42.08)
Mulao 60–69 years	174	31 (17.82)	9 (5.17)	55 (31.61)	95 (54.60)
χ ²	–	0.497	18.969	65.072	5.601
Statistical significance	–	NS	P < 0.001	P < 0.001	P = 0.018
Jing 70–79 years	158	49 (31.01)	7 (4.43)	36 (22.78)	92 (58.23)
Mulao 70–79 years	160	39 (24.38)	11 (6.88)	46 (28.75)	96 (60.00)
χ ²	–	1.750	0.890	1.478	0.103
Statistical significance	–	NS	NS	NS	NS
Jing ≥80 years	27	5 (18.52)	4 (14.81)	7 (25.93)	16 (59.26)
Mulao ≥80 years	26	11 (42.31)	0 (0.00)	5 (19.23)	16 (61.54)
χ ²	–	3.557	4.166	0.339	0.029
Statistical significance	–	NS	P = 0.041	NS	NS

Data presented as n (%) prevalence.

BP, blood pressure.

NS, no statistically significant between-group difference (P > 0.05).

In the Jing population, the prevalence of hypertension was higher in the BMI > 24 kg/m², hypertriglyceridaemia, hypercholesterolaemia, hyperlipidaemia, and nonsmoker subgroups than in BMI ≤ 24 kg/m², nonhypertriglyceridaemia, nonhypercholesterolaemia, nonhyperlipidaemia and smoker subgroups, respectively (P < 0.05; Table 4).

Table 4.

Comparison of the prevalence of hypertension in relation to sex, body mass index (BMI), blood lipids, alcohol consumption and cigarette smoking between Chinese Jing and Mulao ethnic populations aged ≥35 years.

		Hypertension prevalence, n (%)
Parameter	n	Systolic BP ≥140 mmHg	Diastolic BP ≥90 mmHg	Systolic BP ≥ 140 and diastolic BP ≥ 90 mmHg	Prevalence of hypertension
Jing ethnicity	915	149 (16.28)	67 (7.32)	132 (14.43)	348 (38.03)
Male	339	42 (12.39)^a	31 (9.14)^a	47 (13.86)	120 (35.40)
Female	576	107 (18.58)	32 (5.56)	89 (15.45)	228 (39.58)
BMI ≤24 kg/m²	631	96 (15.21)	38 (6.02)	61 (9.67)^c	195 (30.90)^c
BMI >24 kg/m²	284	53 (18.66)	25 (8.80)	75 (26.41)	153 (53.87)
Hypertriglyceridaemia, triglyceride >1.70 mmol/l	288	56 (19.44)	19 (6.60)	55 (19.10)^b	130 (45.14)^b
Nonhypertriglyceridaemia, triglyceride ≤1.70 mmol/l	627	96 (15.31)	47 (7.50)	78 (12.44)	218 (34.77)
Hypercholesterolaemia, total cholesterol >5.17 mmol	429	68 (15.85)	33 (7.69)	78 (18.18)^b	179 (41.72)^a
Nonhypercholesterolaemia, total cholesterol ≤5.17 mmol	486	84 (17.28)	33 (6.79)	55 (11.32)	169 (34.77)
Hyperlipidaemia, total cholesterol >5.17 mmol/l and/or triglyceride >1.70 mmol/l	553	97 (17.54)	39 (7.05)	96 (17.36)^b	232 (41.95)^b
Nonhyperlipidaemia, total cholesterol ≤5.17 mmol/l and/or triglyceride ≤1.70 mmol/l	362	55 (15.19)	27 (7.46)	37 (10.22)	116 (32.04)
Alcohol drinker	105	24 (22.86)	12 (11.43)	6 (5.71)^b	42 (40.00)
Nondrinker	810	125 (15.43)	51 (6.30)	130 (16.05)	306 (37.78)
Smoker	118	4 (3.39)	9 (7.63)	7 (5.93)^c	20 (16.95)^c
Nonsmoker	797	45 (5.65)	54 (6.78)	229 (28.73)	328 (41.15)
Mulao ethnicity	911	58 (6.37)^f	55 (6.04)	278 (30.52)^f	391 (42.92)^d
Male	340	38 (11.18)	17 (5.00)^d	88 (25.88)^f	143 (42.06)
Female	571	89 (15.59)	38 (6.65)	121 (21.19)^e	248 (43.43)
BMI ≤24 kg/m²	688	96 (13.95)	34 (4.94)^a	140 (20.35)^b,f	270 (39.24)^c,e
BMI >24 kg/m²	223	31 (13.90)	21 (9.42)	69 (30.94)	121 (54.26)
Hypertriglyceridaemia, triglyceride >1.70 mmol/l	200	36 (18.00)	17 (8.50)	54 (27.00)^a,d	103 (51.50)^b
Nonhypertriglyceridaemia, total cholesterol ≤5.17 mmol	711	102 (14.35)	49 (6.89)	144 (20.25)^f	288 (40.51)
Hypercholesterolaemia, total cholesterol >5.17 mmol	440	73 (16.59)	31 (7.05)	106 (24.09)^e	202 (45.91)
Nonhypercholesterolaemia, total cholesterol ≤ 5.17 mmol	471	65 (13.80)	35 (7.43)	92 (19.53)^e	189 (40.13)
Hyperlipidaemia, total cholesterol >5.17 mmol/l and/or triglyceride >1.70 mmol/l	508	82 (16.14)	38 (7.48)	126 (24.80)^a,e	236 (46.46)^b
Nonhyperlipidaemia, total cholesterol ≤5.17 mmol/l and/or triglyceride ≤1.70 mmol/l	403	56 (13.90)	28 (6.95)	72 (17.87)^e	151 (37.47)
Alcohol drinker	179	19 (10.61)	10 (5.59)	46 (25.70)^f	75 (41.90)
Nondrinker	732	108 (14.75)	45 (6.15)	163 (22.27)^e	316 (43.17)
Smoker	173	15 (8.67)^a	10 (5.78)	41 (23.70)^f	66 (38.15)^f
Nonsmoker	738	112 (15.18)	45 (6.10)	168 (22.76)^e	325 (44.04)

Data presented as n (%) prevalence.

BMI, body mass index; BP, blood pressure.

P < 0.05, ^bP < 0.01 and ^cP < 0.001 compared with female subjects, BMI > 24 kg/m², nonhypertriglyceridaemia, nonhypercholesterolaemia, nonhyperlipidaemia, nondrinker, or nonsmoker, as appropriate, in the same population.

P < 0.05, ^eP < 0.01 and ^fP < 0.001 compared with equivalent subgroups of the Jing population.

In the Mulao population, the prevalence of hypertension was higher in the BMI > 24 kg/m², hypertriglyceridaemia and hyperlipidaemia subgroups than in BMI ≤ 24 kg/m², nonhypertriglyceridaemia and nonhyperlipidaemia subgroups, respectively (P < 0.01; Table 4).

The prevalence of hypertension in BMI > 24 kg/m² and smoker subgroups was lower in the Jing than in the Mulao populations (P < 0.01; Table 4).

Risk factors for hypertension

The prevalence of hypertension correlated with age, cigarette smoking, triglyceride levels, waist circumference, sodium intake and total dietary fibre in the Jing population; and with age, triglyceride levels, BMI, total fat, sodium intake and total dietary fibre in the Mulao population (P < 0.05, unconditional logistic regression; Table 5).

Table 5.

Comparison of risk factors for hypertension between the Chinese Jing and Mulao ethnic populations aged ≥35 years.

Ethnicity	Risk factor	Regression coefficient	SE	Wald	Statistical significance	OR	95% CI
Jing plus Mulao
	Cigarette smoking, yes/no	–0.649	0.160	16.466	P < 0.001	0.523	0.382, 0.715
	Age, years	0.412	0.039	112.402	P < 0.001	1.510	1.399, 1.630
	Triglyceride, mmol/l	0.403	0.118	11.724	P = 0.001	1.496	1.188, 1.884
	Ethnic group	0.377	0.104	13.103	P < 0.001	1.457	1.189, 1.787
	Body mass index, kg/m²	0.381	0.132	8.308	P = 0.004	1.464	1.130, 1.897
	Total fat, g/day	0.374	0.158	5.136	P = 0.022	1.452	1.078, 1.844
	Sodium intake, g/day	0.381	0.124	10.341	P = 0.002	1.387	1.246, 2.239
	Total dietary fibre, g/day	–0.331	0.136	8.006	P = 0.005	1.473	1.322, 2.034
Jing
	Age, years	0.361	0.055	43.459	P < 0.001	1.438	1.291, 1.603
	Cigarette smoking, yes/no	–1.090	0.262	17.281	P < 0.001	0.336	0.201, 0.562
	Triglyceride, mmol/l	0.359	0.161	4.977	P = 0.026	1.431	1.045, 1.961
	Waist circumference, cm	0.468	0.169	7.668	P = 0.006	1.597	1.147, 2.224
	Sodium intake, g/day	0.322	0.076	8.791	P = 0.003	1.342	1.117, 1.936
	Total dietary fibre, g/day	–0.386	0.138	5.146	P = 0.023	1.596	1.211, 1.868
Mulao
	Age, years	0.452	0.055	67.444	P < 0.001	1.572	1.411, 1.751
	Triglyceride, mmol/l	0.500	0.173	8.365	P = 0.004	1.649	1.175, 2.315
	Body mass index, kg/m²	0.623	0.165	14.217	P < 0.001	1.864	1.348, 2.576
	Total fat, g/day	0.388	0.194	5.042	P = 0.027	1.476	1.202, 1.878
	Sodium intake, g/day	0.367	0.097	7.778	P = 0.005	1.387	1.265, 2.246
	Total dietary fibre, g/day	–0.401	0.135	10.213	P = 0.002	1.677	1.354, 2.343

OR, odds ratio; CI, confidence interval.

Discussion

In the current study, levels of diastolic BP and the prevalence of hypertension were shown to be lower in the Jing than in the Mulao population in subjects aged 60–69 years, and also in subgroups with BMI > 24 kg/m² and in smokers. The prevalence of isolated systolic hypertension was, however, higher in the Jing than Mulao population. The prevalence of hypertension was found to be correlated with age, cigarette smoking, triglyceride levels, waist circumference, sodium intake and total dietary fibre in the Jing population; and with age, triglyceride levels, BMI, total fat, sodium intake and total dietary fibre in the Mulao population. Differences in the prevalence of hypertension and associated risk factors between the two ethnic minority groups may be attributed to differences in geographical environment, dietary habits, lifestyle choices and genetic background, and such factors may be more favourable for BP levels in the Jing than in the Mulao population.

The geographical environment and climate differ between the Jing and Mulao ethnic groups. Most of the Jing population lives in the Beibu Gulf coastal region, an abundant fishing area, whereas the majority of the Mulao population lives in mountainous or hilly regions. The altitudes of the Mulao settlements range between 400 m and 1100 m. In studies comparing sea level versus altitudes at or above 2100 m, as altitude increases, BP has been shown to gradually increase,^21–27 and exposure to progressively higher altitude has been associated with a progressive, marked increase in ambulatory BP. In one study, an increase in ambulatory BP occurred immediately after the high altitude was reached; persisted during prolonged altitude exposure; involved daytime ambulatory BP values (but was particularly pronounced for night-time ambulatory BP values), with a consequent reduction in the nocturnal dipping phenomenon at the higher altitude; and disappeared following return to sea level.²⁷ Chronic hypoxia at exposure to high altitude can cause increased BP^21–27 and marked activation of the sympathetic nervous system. The secretion of adrenaline,²² noradrenaline,^21,22,25,27 vasopressin²⁸ and adrenocorticotropin²⁹ are shown to be increased during high-altitude exposure or chronic hypoxia, which may increase BP and promote the development of hypertension. In addition, the climate in the Luocheng Mulao Autonomous County is similar to the Southern subtropics, there is rapid evaporation and the weather is very dry and cold in winter at the highest altitudes.¹⁶ Cold exposure is a risk factor for hypertension, for example, BP was found to be significantly higher in cold-exposed compared with control workers.³⁰ The severity of cold exposure was a significant variable affecting hypertension in logistic regression analysis.³⁰ Gene expression analysis in cold-exposed mice indicated that differentially expressed genes were associated with adaptive thermogenesis, fatty acid metabolism and energy metabolism.³¹ Genes involved in the hypoxia-inducible factor-1 signalling pathway were activated, genes associated with oxidative stress (such as superoxide dismutase 2, mitochondrial and epoxide hydrolase 2, cytoplasmic) were significantly upregulated, whereas genes involved in inflammation-associated pathways were shown to be downregulated in a 4℃ 5-week group.³¹

Dietary patterns differ between the Jing and Mulao populations. Rice, corn and seafood are the staple foods of the Jing population;¹² sweet potato and taro are consumed occasionally. Marine fish and fish oils contain n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFAs) including eicosapentaenoic acid and docosahexaenoic acid. Regular supplementation with n-3 LCPUFAs, fish consumption, or fish oil intake in the general population can reduce systolic BP,³² diastolic BP^32,33 and the incidence of hypertension,³⁴ and significant hypotensive action in response to these products has been observed in hypertensive subjects.^35–38 In contrast, rice, corn and potatoes are the staple foods of the Mulao population,¹³ but with improvement of living standards and changes in lifestyle, the intake of animal (mainly pork) fat is higher in the Mulao than in the Jing population.^12,13 The Mulao population also cooks food using animal oil and eats fatty meat, animal offal and other organs that contain abundant levels of saturated fatty acids.¹⁵ A high intake of animal fat and saturated fatty acid has been shown to have an unfavourable effect on BP in an animal model.³⁹ In addition, animal protein and vegetable protein differ in their predominant amino acids. In animal protein, alanine, arginine, aspartic acid, glycine, histidine, lysine, methionine and threonine predominate; in vegetable protein, cysteine, glutamic acid, phenylalanine, proline and serine predominate.^40–42 Several studies have indicated that intake of animal protein, in particular red meat, directly relates to heightened BP levels, whereas intake of vegetable protein and vegetarian eating patterns relate inversely to BP levels.^40–43 Individuals with low vegetable and high animal protein intake consume greater proportions of tryptophan, leucine, arginine, valine, aspartic acid, tyrosine, glycine, isoleucine, alanine, histidine, threonine, methionine, and lysine, and they consume smaller proportions of glutamic acid, cystine, proline, phenylalanine and serine compared with persons with higher vegetable and lower animal protein intake.⁴⁰ Available data indicate that intake of one of cysteine, glutamic acid, phenylalanine, proline and serine, with a predominant intake of vegetable protein, has a significant independent inverse relation to BP,⁴¹ whereas dietary glycine may have an independent adverse effect on BP, which possibly contributes to a direct relationship between BP level and animal protein and meat consumption.⁴²

Lifestyle differs between the Jing and Mulao populations, and the percentages of subjects who consumed alcohol or smoked cigarettes were found to be lower in the Jing than in Mulao populations in the present study. Consuming large amounts of alcohol and cigarette smoking are known to increase BP and overall mortality.^16,17 In the present study, however, the prevalence of hypertension in both ethnic groups was found to be lower in smoker than in nonsmoker subgroups, and the prevalence of hypertension was negatively correlated with cigarette smoking in the Jing but not in the Mulao population. The reasons for these discrepancies remain unclear, but the interactions of other factors with cigarette smoking on BP levels should be considered.

In addition, the effect of different types of cigarettes on BP levels is not well known. In the present study, 95% of the cigarettes smoked by the Mulao subjects contained natural tobacco leaves, whereas 95% of the cigarettes smoked by the Jing subjects were commercially available cigarettes, and the toxin contents between the different types of cigarettes may be different.

Blood pressure is known to be regulated by multiple environmental and genetic factors and their interactions.^{15,17,44–46} Recent genome-wide association studies in different populations have explored over 160 candidate genes associated with BP and hypertension.^47–49 Genetic approaches have advanced the understanding of biological pathways underlying interindividual variations in BP. It is most likely that there are several causal genes, which together account for 30–50% of the BP variation found among individuals.⁵⁰ The Chinese Jing population is a branch of the Yue population of Vietnam, and their ancestors formerly lived in Jipo, Vietnam and migrated to China in the early 16th century.¹² The Mulao people are a mountain-dwelling minority who have, according to historical records, lived in the Luocheng Mulao Autonomous County since the Jin Dynasty (AD 265–420), and are believed to be the descendants of the ancient Ling and Liao tribes. The geographical distance between the two ethnic groups is ∼480 km, therefore, the authors hypothesize that hereditary characteristics and genetic variations in some candidate hypertension-susceptibility genes may be different between both populations.

The results of the present study have several limitations. First, the sample size was small, and fewer male than female subjects responded to the request to participate in the study. The age and sex distribution in the present study, however, was not different between the two ethnic groups. Secondly, a 24 h dietary recall may be inaccurate and not representative when diets are highly variable; however, the diet in an ethnic group is consistent throughout the year and among individuals due to the reliance on a limited number of locally available foods.^14,15 Thirdly, oestrogen and menopause are known to have potential influence on BP levels. In the present study, however, the pre- and postmenopausal female subjects were not distinguished in either ethnic group because of the relatively small sample sizes. Finally, BP is known to be modulated by multiple environmental factors and genetic loci, and their interactions.^{16,17,44–46} Although the effect of several environmental factors on BP were investigated in the present study, many environmental and genetic factors and their interactions remain unmeasured.

In conclusion, the present study showed that diastolic BP levels, and the prevalence of hypertension and associated risk factors, were different between the Jing and Mulao populations. These differences may result from the combined effects of different geographic, dietary, lifestyle and genetic backgrounds.

Footnotes

Declaration of conflicting interest

The authors declare that there are no conflicts of interest

Funding

Support for this study was provided by the National Natural Science Foundation of China (No. 30960130 and No. 81160111).

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