Open Access

Dyslipidemia awareness, treatment, control and influence factors among adults in the Jilin province in China: a cross-sectional study

  • Huan He1,
  • Ya-qin Yu1,
  • Yong Li1,
  • Chang-gui Kou1,
  • Bo Li1,
  • Yu-chun Tao1,
  • Qing Zhen1,
  • Chang Wang1,
  • Joseph Sam Kanu1,
  • Xu-feng Huang2,
  • Mei Han2 and
  • Ya-wen Liu1Email author
Lipids in Health and Disease201413:122

DOI: 10.1186/1476-511X-13-122

Received: 13 May 2014

Accepted: 23 July 2014

Published: 3 August 2014

Abstract

Background

In China, even though the prevalence of dyslipidemia among adults increased yearly and dyslipidemia being an important risk factor for cardiovascular diseases among the Chinese population, however, the awareness, treatment and control of dyslipidemia are at low levels, and only limited studies on the influence factors associated with the awareness, treatment and control dyslipidemia in China have been carried out.

Methods

The analysis was based on a representative sample of 7138 adult subjects aged 18 ~ 79 years recruited from a cross-sectional study of chronic disease and risk factors among adults in the Jilin province in 2012. Chi-square test was used to compare the rates of dyslipidemia awareness, treatment and control between different characteristics of participants. Multiple logistic regression analyses were performed separately for each group to explore the associations between participants’ characteristics and dyslipidemia awareness, treatment and control.

Results

Among participants with dyslipidemia, 11.6% were aware of the diagnosis, 8.4% were receiving treatment, and 34.8% had dyslipidemia controlled. Increase in age and BMI ≥ 24 kg/m2 were by far the strongest risk factors associated with better awareness and treatment of dyslipidemia. Retirees were more likely to be aware of their dyslipidemia condition (OR = 1.255; 95% CI: 1.046, 1.506) and to be receiving treatment (OR = 1.367; 95% CI: 1.114, 1.676) than manual workers. A family history of dyslipidemia increased the likelihood of awareness (OR = 3.620; 95% CI: 2.816, 4.653) and treatment (OR = 3.298; 95% CI: 2.488, 4.371) of dyslipidemia. Alcohol drinking and physical activity were associated with a lower level of awareness and treatment.

Cigarette smokers (OR = 0.501; 95% CI: 0.349, 0.719) and those with BMI ≥ 24 kg/m2 (OR = 0.480; 95% CI: 0.326, 0.706) who received treatment were also associated with poor dyslipidemia control.

Conclusion

Our study highlights low levels of awareness, poor treatment and control of dyslipidemia among adults aged 18 ~ 79 in the Jilin province. Promotion of healthy lifestyles and establishment of a comprehensive strategy of screening, treatment and control of dyslipidemia is needed to reduce or prevent the risk of cardiovascular disease in the Jilin province.

Keywords

Dyslipidemia Awareness, treatment and control Influence factors

Introduction

In China, the prevalence of dyslipidemia among adults increases yearly and dyslipidemia is now an important risk factor for cardiovascular diseases in the Chinese population[1, 2]. The results from the Chinese National and Health Survey in 2002 showed that the prevalence of dyslipidemia in the Chinese population was 18.6%[3]. The study of Wang et al.[4] reported that the prevalence of dyslipidemia in the Beijing adult population was 56.1% in 2006. Luo et al.[5] reported that prevalence of dyslipidemia was 52.72% among adults in northwestern China in 2010. CVD is characterized by high morbidity of stroke and low morbidity of coronary heart disease, but morbidity and mortality of coronary heart diseases have gradually increased in the last 20 years in China[6]. The report of the third recalled sample survey on the causes of death in China showed that in the last 15 years, the proportion of deaths from chronic diseases among residents increased from 76.5% to 82.5% among residents, and cardiovascular death was the first cause[7]. It is apparent that China will continue to experience significant increase in the prevalence of cardiovascular-related morbidity and mortality, which has the potential to create an enormous burden on the health care system in the future[8].

Moreover, the asymptomatic characteristics of dyslipidemia contribute to the increased incidence of CVD and sudden death, thus uncontrolled dyslipidemia is a serious risk factor for cardiovascular events such as coronary heart disease, cerebral ischemic attack, cerebral infarction and peripheral vascular disease[9, 10]. Large clinical trials have demonstrated that the treatment of dyslipidemia is effective in both primary and secondary prevention of CVD[11, 12]. Treating dyslipidemia can reduce the risk of heart diseases by approximately 30% over a 5-year period[12]. Surveys in China have showed that the awareness, treatment and control of dyslipidemia is poor[1, 8, 13], and only limited studies on the influencing factors associated with the awareness, treatment and control of dyslipidemia in China have been carried out.

The aims of this study were: (1) to estimate the awareness, treatment, and control of dyslipidemia in the adult population in the Jilin province; and (2) to determine the influence factors associated with the awareness, treatment and control of dyslipidemia in the adult population in the Jilin province.

Materials and methods

Ethical statement

The study was approved by the Institutional Review Board of the School of Public Health, Jilin University, and all subjects participated in the study after making signed informed consents.

Study population

Data were obtained from the survey of chronic disease and risk factors among adults in the Jilin province of China in 2012. The investigation was a cross-sectional study that aimed to assess chronic disease and associated risk factors among different populations in different regions of the Jilin province in China. The survey used a multistage cluster random sampling method to select a representative sample of permanent residents aged 18 to 79 years in nine different cities in the Jilin province. The detailed sampling process has been published elsewhere[14]. A total of 17,729 participants completed the survey and examination after excluding some participants due to incomplete blood lipid information. Among the 17,729 respondents, a total of 7,138 subjects had dyslipidemia and were included in the study.

Data collection

Questionnaire interview

The study used a personal health survey questionnaire established by the School of Public Health, Jilin University. A direct face-to-face questionnaire interview was carried out by uniformly trained investigators.

The questionnaire provided the demographic information (such as region, age, gender, level of education, occupation), health behaviors (such as smoking, drinking, diet, physical activity), history of dyslipidemia in the past one year, and the current treatment of dyslipidemia.

Anthropometric

After the questionnaire interview, participants underwent anthropometric checks including height and weight. Weight was measured early in the morning before respondents had eaten, and each physical measurement was completed by two people together.

Laboratory assay

Fasting blood samples of each respondent were drawn by venipuncture to measure serum Total Cholesterol (TC), High Density Lipoprotein Cholesterol (HDL-C), Low Density Lipoprotein Cholesterol (LDL-C) and Triglycerides (TG). The tools used for all blood samples collection were from the same source. After collection, the samples were placed in a cold chain system before being collectively transported to a central laboratory. Blood samples were analyzed using MODULE P800 automated biochemistry analyzer (ROCHE, USA).

Definitions

Dyslipidemia was defined according to the Chinese guidelines on the prevention and treatment of dyslipidemia in adults (2007)[6]: TC ≥ 6.22 mmol/L (240 mg/dL) as high; LDL-C ≥ 4.14 mmol/L (160 mg/dL) as high; HDL-C < 1.04 mmol/L (40 mg/dL) as low; and TG ≥ 2.26 mmol/L (200 mg/dL) as high. In this study, high TC, and/or high LDL-C, and/or low HDL-C and/or high TG, and/or having a history of dyslipidemia disease in the past one year, and/or currently receiving treatment with lipid-lowering medications was regarded as dyslipidemia.

Awareness of dyslipidemia was defined as a self-reported diagnosis of dyslipidemia by a healthcare professional or treatment with medications within the population defined as having dyslipidemia. Treatment of dyslipidemia was defined as using medications to treat dyslipidemia among participants with dyslipidemia. Dyslipidemia was considered to be controlled among the population defined as having dyslipidemia and being treated with medication if TC < 6.22 mmol/L, LDL-C < 4.14 mmol/L, HDL-C ≥ 1.04 mmol/L, and TG < 2.26 mmol/L.

Body mass index (BMI) was calculated as weight (kg) divided by height (m2). Using BMI 24 kg/m2 as cut off point, participants were broadly categorized into two main groups: overweight or obesity being defined as BMI ≥ 24 kg/m2, and underweight or normal being defined as BMI < 24 kg/m2. Smoking was defined as having smoked at least one cigarette per day in the past 30 days, or past smokers even if they had exhibited complete abstinence from cigarette use for at least one month[8, 15]. Drinking was defined as drinking any kind of purchased or homemade alcohol-containing beverages on average more than once a week. Physical activity was defined as walking, running, going to the gym or other conscious exercise not less than once a week. Participants with a family history of dyslipidemia and those who like to eat animal-based foods and salted foods were ascertained by questionnaire.

Statistical analysis

EpiData3.1 was used to establish a database from which and the data was then exported to SPSS 16.0 software for further statistical analyses. Chi-square (χ 2 ) test was used to compare the rates of dyslipidemia awareness, treatment and control between different characteristics of the participants. Multiple logistic regression analyses were performed separately for each group to explore the associations between participants’ characteristics and dyslipidemia awareness, treatment and control. All statistical tests were two-tailed and P-values ≤ 0.05 considered statistically significant.

Results

Characteristics of the study sample

Table 1 presents the characteristics of the dyslipidemia subjects. Out of the 7319 study subjects, 50.1% were from the urban region, 51.1% were men, 48.9% were women, 30.4% were aged between 45 and 54, the mean age was 50.50 ± 12.30 years, 69.0% attained a junior high school or higher education, 88.0% were married, and 52.4% were manual workers. In terms of BMI distribution, 67.9% were BMI ≥ 24 kg/m2. Only 4.9% had a family history of dyslipidemia. The rate of smoking was 44.2%, and drinking was 33.7%, with 9.2% admitted eating more of animal-based foods, 40.4% more of salted foods, and 42.3% of the study subjects reported having regular exercises.
Table 1

Characteristics of the study sample (n = 7319) 2012, Jilin province, China

Variables

N

%

Regions

  

 Urban

3653

50.1

 Rural

3666

49.9

Gender

  

 Male

3740

51.1

 Female

3579

48.9

Age group (years)

  

 18~

821

11.2

 35~

1388

19.0

 45~

2225

30.4

 55~

1987

27.1

 65 ~ 79

898

12.3

Education

  

 Primary school or low

2269

31.0

 Junior high school

2090

28.6

 Senior high school

1956

26.7

 University

1004

13.7

Marital status

  

 Married

6444

88.0

 Single/Divorced/Widowed

875

12.0

Occupation

  

 Manual workers

3832

52.4

 Mental workers

1297

17.7

 Retired

2190

29.9

BMI ≥ 24 kg/m2

  

 No

2346

32.1

 Yes

4973

67.9

Family history of dyslipidemia

  

 No

6959

95.1

 Yes

360

4.9

Smoking

  

 No

4087

55.8

 Yes

3232

44.2

Drinking

  

 No

4853

66.3

 Yes

2446

33.7

Like to eat animal-based foods

  

 No

6647

90.8

 Yes

672

9.2

Like to eat salted foods

  

 No

4363

59.6

 Yes

2956

40.4

Physical activity

  

 No

4222

57.7

 Yes

3097

42.3

Awareness, treatment and control of dyslipidemia

Table 2 shows the prevalence of dyslipidemia awareness, treatment and control. Among participants with dyslipidemia, 852 (11.6%) were aware of the diagnosis of their condition, and the overall rate of dyslipidemia treatment was 8.4%. Among the 615 dyslipidemia patients receiving medical treatment for dyslipidemia, 214 (34.8%) were under control.
Table 2

Awareness, treatment and control of dyslipidemia by characteristics, 2012, Jilin province, China

Variables

Awarenessa

Treatmenta

Controlb

N(%)

P

N(%)

P

N(%)

P

Total

852(11.6)

 

615(8.4)

 

214(34.8)

 

Residential areas

 

0.083

 

0.863

 

0.075

  Urban

449(12.3)

 

309(8.5)

 

97(31.4)

 

  Rural

403(11.0)

 

306(8.3)

 

117(38.2)

 

Gender

 

0.018

 

0.014

 

0.058

  Male

403(10.8)

 

285(7.6)

 

88(30.9)

 

  Female

449(12.5)

 

330(9.2)

 

126(38.2)

 

Age group (years)

 

<0.001

 

<0.001

 

0.886

  18~

24(2.9)

 

15(1.8)

 

4(26.7)

 

  35~

130(9.4)

 

87(6.3)

 

33(37.9)

 

  45~

283(12.7)

 

201(9.0)

 

72(35.8)

 

  55~

285(14.3)

 

211(10.6)

 

70(33.2)

 

  65 ~ 79

130(14.5)

 

101(11.2)

 

35(34.7)

 

Education

 

0.006

 

0.146

 

0.075

  Primary school or lower

225(9.9)

 

168(7.4)

 

63(37.5)

 

  Junior high school

249(11.9)

 

192(9.2)

 

71(37.0)

 

  Senior high school

238(12.2)

 

163(8.3)

 

59(36.2)

 

  University

140(13.9)

 

92(9.2)

 

21(22.8)

 

Marital status

 

0.058

 

0.328

 

0.993

  Married

767(11.9)

 

549(8.5)

 

191(34.8)

 

  Single

85(9.7)

 

66(7.5)

 

23(34.8)

 

Occupation

 

<0.001

 

<0.001

 

0.529

  Manual workers

351(9.2)

 

253(6.6)

 

92(36.4)

 

  Mental workers

169(13.0)

 

109(8.4)

 

33(30.3)

 

  Retired

332(15.2)

 

253(11.6)

 

89(35.2)

 

BMI ≥ 24 kg/m2

 

<0.001

 

<0.001

 

<0.001

  No

206(8.8)

 

144(6.1)

 

69(47.9)

 

  Yes

646(13.0)

 

471(9.5)

 

145(30.8)

 

Family history of dyslipidemia

 

<0.001

 

<0.001

 

0.948

  No

745(10.7)

 

541(7.8)

 

188(34.8)

 

  Yes

107(29.7)

 

74(20.6)

 

26(35.1)

 

Smokers

 

<0.001

 

0.004

 

<0.001

  No

524(12.8)

 

377(9.2)

 

153(40.6)

 

  Yes

328(10.1)

 

238(7.4)

 

61(25.6)

 

Drinking

 

<0.001

 

<0.001

 

0.082

  No

616(12.7)

 

454(9.4)

 

167(36.8)

 

  Yes

236(9.6)

 

161(6.5)

 

47(29.2)

 

Like to eat animal-based foods

 

0.055

 

0.094

 

0.912

  No

789(11.9)

 

570(8.6)

 

198(34.7)

 

  Yes

63(9.4)

 

45(6.7)

 

16(35.6)

 

Like to eat salted foods

 

0.184

 

0.035

 

0.061

  No

490(11.2)

 

342(7.8)

 

130(38.0)

 

  Yes

362(12.2)

 

273(9.2)

 

84(30.8)

 

Physical activity

 

<0.001

 

<0.001

 

0.689

  No

587(13.9)

 

423(10.0)

 

145(34.3)

 

  Yes

265(8.6)

 

192(6.2)

 

69(35.9)

 

aamong all dyslipidemia subjects.

bamong those who received treatment.

Awareness of dyslipidemia

The awareness of dyslipidemia increased with age (P < 0.001), with the last age group 65 ~ 79 having the highest level of awareness, 130(14.5%). Awareness of dyslipidemia also differed significantly by gender with females being more aware of their dyslipidemia than males (P = 0.018); education with participants who attained university level of education being more aware of their condition compared to lower levels of education (P = 0.006); There were significant differences between the occupations in awareness of dyslipidemia (P < 0.001), with retired having the highest level of awareness, 332(15.2%). BMI with subjects having BMI ≥ 24 kg/m2 being more aware than those with BMI < 24 kg/m2 (P < 0.001); and participants with family history of dyslipidemia had higher levels of awareness of dyslipidemia compared to those without any history of the condition (P < 0.001). Smoking, drinking and physical activity were associated with higher levels of dyslipidemia awareness (all P < 0.01). The awareness of dyslipidemia was not significantly associated with residential area (P = 0.083), marital status (P = 0.058), or whether the participants like more of animal-based foods (P = 0.055) or salted foods (P = 0.184).

Treatment of dyslipidemia

The treatment rate increased with age (P < 0.001), with the last age group 65 ~ 79 having the highest rate of treatment, 101(11.2%); and differed significantly by gender (P = 0.014) and occupation (P < 0.001) with females and retired having higher treatment rates compared to males and manual workers respectively. The level of dyslipidemia treatment was also significantly associated with BMI and a family history of dyslipidemia (all P < 0.001) with subjects with BMI ≥ 24 kg/m2 and those with a family history of dyslipidemia having higher treatment rates as against those with BMI < 24 kg/m2 or without a family history of dyslipidemia respectively. Smoking (P = 0.004), drinking (P < 0.001), liking to eat salted foods (P = 0.035) and physical activity (P < 0.001) were all associated with higher levels of dyslipidemia treatment. In this present study, treatment of dyslipidemia was not found to be significantly associated with residential area (P = 0.863), level of education (P = 0.146), marital status (P = 0.328), or liking to eat animal-based foods (P = 0.094) or salted foods (P = 0.035).

Control of dyslipidemia

Among dyslipidemia patients receiving medical treatment for dyslipidemia, participants with BMI < 24 kg/m2 were more likely to have their dyslipidemia controlled than those with BMI ≥ 24 kg/m2 (P < 0.001). Smoking was associated with a lower level of dyslipidemia control than non-smoking (P < 0.001).

Factors associated with awareness, treatment and control of dyslipidemia

In a multivariate binary logistic regression analysis, awareness, treatment, and control of dyslipidemia were used as dependent variables; and the parameters which were significantly associated with awareness, treatment, and control of dyslipidemia in the χ2 test (P < 0.05 in Table 2), were used as independent variables respectively.

As shown in Table 3, the prevalence of the awareness of dyslipidemia was significantly associated with increasing age, and there was a significant association between education and the awareness of dyslipidemia. Retired participants more likely to aware of their dyslipidemia condition than manual workers (OR = 1.255; 95% CI: 1.046, 1.506). Subjects with BMI ≥ 24 kg/m2 tended to be more aware of their dyslipidemia condition than those with BMI < 24 kg/m2 (OR = 1.547; 95% CI: 1.307,1.832). In addition, having a family history of dyslipidemia increased the tendency of awareness of dyslipidemia (OR = 3.620; 95% CI: 2.816, 4.653). Drinkers (OR = 0.780; 95% CI: 0.658, 0.925) or those who regularly do physical exercises (OR = 0.714; 95% CI: 0.606, 0.842) were unlikely to be aware of their dyslipidemia condition.
Table 3

Multivariate logistic regression analyses on influence factors for awareness of dyslipidemia, 2012, Jilin province, China

Variables

Awarenessa

OR

95% CI

P

Age group (years)

   

  18-

1.000

  

  35-

3.865

2.464,6.062

<0.001

  45-

5.481

3.554,8.453

<0.001

  55-

6.491

4.170,10.105

<0.001

  65-79

6.420

3.989,10.332

<0.001

Education

   

  Primary school or lower

1.000

  

  Junior high school

1.425

1.165,1.743

0.001

  Senior high school

1.361

1.095,1.691

0.005

  University

1.835

1.366,2.466

<0.001

Occupation

   

  Manual workers

1.000

  

  Mental workers

1.083

0.848,1.384

0.521

  Retired

1.255

1.046,1.506

0.014

BMI ≥ 24 kg/m2

   

  No

1.000

  

  Yes

1.547

1.307,1.832

<0.001

Family history of dyslipidemia

   

  No

1.000

  

  Yes

3.620

2.816,4.653

<0.001

Drinking

   

  No

1.000

  

  Yes

0.780

0.658,0.925

0.004

Physical activity

   

  No

1.000

  

  Yes

0.714

0.606,0.842

<0.001

Method: Forward: LR; OR = odds ratio; CI = confidence interval.

aamong all dyslipidemia subjects.

Table 4 illustrates that increasing age was significantly associated with the treatment of dyslipidemia, with retired (OR = 1.367; 95% CI: 1.114, 1.676) being more likely to be treated than manual workers. The higher the level of BMI the more likely that the respondent will receive treatment for dyslipidemia (OR = 1.575; 95% CI: 1.294, 1.918). Subjects with a family history of dyslipidemia were more likely than those without family history to report drug treatment among participants with dyslipidemia (OR = 3.298; 95% CI: 2.488, 4.371).
Table 4

Multivariate logistic regression analyses on influence factors for treatment of dyslipidemia, 2012, Jilin province, China

Variables

Treatmenta

OR

95% CI

P

Age group (years)

   

  18-

1.000

  

  35-

3.816

2.184,6.669

<0.001

  45-

5.338

3.126,9.112

<0.001

  55-

6.043

3.519,10.377

<0.001

  65-79

6.064

3.425,10.727

<0.001

Occupation

   

  Manual workers

1.000

  

  Mental workers

1.183

0.923,1.515

0.184

  Retired

1.367

1.114,1.676

0.003

BMI ≥ 24 kg/m2

   

  No

1.000

  

  Yes

1.575

1.294,1.918

<0.001

Family history of dyslipidemia

   

  No

1.000

  

  Yes

3.298

2.488,4.371

<0.001

Drinking

   

  No

1.000

  

  Yes

0.756

0.620,0.923

0.006

Like to eat salted foods

   

  No

1.000

  

  Yes

1.319

1.110,1.567

0.002

Physical activity

   

  No

1.000

  

  Yes

0.683

0.567,0.824

<0.001

Method: Forward: LR; OR = odds ratio; CI = confidence interval.

aamong all dyslipidemia subjects.

As shown in Table 5, among the study subjects with dyslipidemia who were treated with drugs, BMI ≥ 24 kg/m2 was associated with poor control of dyslipidemia (OR = 0.480; 95% CI: 0.326, 0.706). Smokers were less likely to control their serum lipids at normal levels (OR = 0.501; 95% CI: 0.349, 0.719).
Table 5

Multivariate logistic regression analyses on influence factors for control of dyslipidemia, 2012, Jilin province, China

Variables

Controlb

OR

95% CI

P

BMI ≥ 24 kg/m2

   

  No

1.000

  

  Yes

0.480

0.326,0.706

<0.001

Smoking

   

  No

1.000

  

  Yes

0.501

0.349,0.719

<0.001

Note: Method: Forward: LR; OR = odds ratio; CI = confidence interval.

bamong those who receiving treatment.

Discussions

With economic growth and associated changes in lifestyle and diet, the level of serum cholesterol in the Chinese population has greatly increased[4, 16]. Dyslipidemia is a major pathogenic factor of atherosclerosis, and one of the independent risk factors for cardiovascular disease such as coronary heart disease and stroke[1, 5]. Increasing the awareness and management of patients with dyslipidemia has a positive impact on cardiovascular disease prevention[11]. Despite this, numerous studies have revealed poor awareness and unsatisfactory treatment and control in many European countries[17], and extremely low rates of dyslipidemia in the Chinese population[3, 6, 8, 13]. It has been reported that the awareness, treatment, and control rates of dyslipidemia were comparatively low among Chinese adults aged 18 and above, at 10.93%, 6.84% and 35.3% respectively in 2010[1]. We found similar results in this present study with rates of awareness and treatment among participants being 11.6% and 8.4% respectively. However, the rates in our study were significantly less than the 22.2% awareness of diagnosis and 46.1% receiving treatment among adults in Beijing, China in 2012[8]. Out of the 615 dyslipidemia individuals in our study that were receiving treatment, 34.8% were under control. This is slightly lower than the 37.8% serum lipids control finding of Cai et al.[8] among those with dyslipidemia receiving treatment. This indicates that dyslipidemia is an important health risk factors in the Jilin province. However, only limited studies on the influencing factors associated with awareness, treatment and control of dyslipidemia had been carried out in China. Hence our study aimed to examine the awareness, treatment, and control of dyslipidemia, and their influence factors in the Jilin province.

Because dyslipidemia is almost asymptomatic and its detection requires blood analysis which in most cases requested by a physician, ordinary residents are hardly aware of and being treated for dyslipidemia disease[17]. The results of our study revealed that the awareness and treatment of dyslipidemia among our study population increased concomitantly with age. This is in line with other studies such as the rate of awareness among residents in Beijing being less than 15% among adults aged 45 and above[18], and the awareness rate also increasing with age among residents in Laiwu city, China[19]. This means that as people advance in age, they become more concerned about their health, particularly being concerned about cardiovascular diseases, than younger individuals who are less likely to attach great importance to disease consciousness.

Several recent studies showed that education is positively associated with the awareness of dyslipidemia[10, 18, 20, 21]. The more an individual attains higher levels of education, the more likely awareness about health conditions, including dyslipidemia, increases. Regarding the determinants of awareness in our study, an increasing education level was associated with a higher level of dyslipidemia awareness.

Our study also showed that compared with manual workers, retired participants were more likely to be aware of their dyslipidemia condition and seek treatment. This may be related to retirees, students having more time to focus on their health, and tend to seek early management of any adverse health condition. However, manual workers always appear body fatigue after a whole day’s work, so they easily ignore the condition body health.

Obesity is an independent risk factor of dyslipidemia[17, 22]. Findings from the ORISCAV-LUX study revealed that obese subjects are more conscious of cardiovascular health risks than slim individuals. This is helpful in increase their awareness of the underlying silent metabolic pathologies associated with excess body weight[17]. Our findings are consistent with other studies that overweight or obesity (BMI ≥ 24 kg/m2) is associated with higher levels of dyslipidemia awareness and treatment[19, 20, 23]. Individuals with BMI ≥ 24 kg/m2 tend to control their BMI at 24 kg/m2 or less, which helps in preventing 50-60% risk of hypertriglyceridemia in this population[24]. However, among individuals receiving treatment, individuals with BMI ≥ 24 kg/m2 are less likely to have controlled dyslipidemia. This finding is similar to the results of Long’s study in 2007[22]. The plausible explanation is that weight control is a lengthy process, and it is more difficult to control blood lipids in overweight or obese people.

People with a family history of dyslipidemia have a higher risk of developing dyslipidemia[1]. In this study, we found that family history of dyslipidemia was a strong predictor of dyslipidemia awareness and treatment. Unsurprisingly, having a family member with dyslipidemia would increase the consciousness and alertness of the whole family with regards to dyslipidemia, and physicians tend to pay more attention to patients with a family history of dyslipidemia, as they tend to have increased risk of cardiovascular diseases.

Consistent with other findings[19], our study revealed physical activity is associated with lower levels of awareness and treatment of dyslipidemia. This may be explained by the fact that people who exercise regularly believe they are less likely to become sick, and therefore are less likely to be conscious of dyslipidemia.

Lower levels of awareness and treatment were found among alcohol drinkers and also lower levels of dyslipidemia control among cigarette smokers in the present study. This may be explained that the dyslipidemia patients who are alcohol drinkers and cigarette smokers usually receive advice on drinking and smoking cessation given by physicians, or it may be associated with alcohol drinkers and smokers’ lower level of concern about their own health[18, 25]. Several studies have found that lifestyle changes are effective in controlling serum blood lipids[8, 19, 26]. Thus it is important to emphasize the need for policies that improve healthy lifestyle.

Study limitations

The findings should be interpreted with an understanding of the following potential limitations. The cross-sectional nature of our study design means that causal associations can only be made with caution. As in many surveys, our serum lipid levels and the definitions of dyslipidemia awareness, treatment, and control were based on measurements taken during a single visit. Potential sources of bias include recall bias of self-reported information. Treatment and control rates were based on only pharmacological treatment of dyslipidemia, however, it is possible to control serum lipid by non-pharmacological means, such as diet and/or exercise. The Chinese criteria were adopted to define dyslipidemia; therefore, we could not directly compare our results with those from other countries.

Conclusions

In conclusion, our study highlighted the low rates of awareness, treatment and control of dyslipidemia among adults aged 18–79 in the Jilin province, China. Continuous efforts are needed to increase the awareness, treatment and control of dyslipidemia taking influence factors into account. Our results suggest that the relevant departments should regularly carry out health education programs on dyslipidemia. These departments should also provide guidelines that help promote healthy lifestyles such as increased physical activity, weight control, smoking cessation and cessation of alcohol drinking. Establishment of a comprehensive strategy of screening, treating and controlling of dyslipidemia is needed in the Jilin Province. These interventions will help to reduce the high and increasing burden of cardiovascular disease in the Jilin province, China.

Abbreviations

CVD: 

Cardiovascular disease

TC: 

Total cholesterol

HDL-C: 

HDL cholesterol

LDL-C: 

LDL cholesterol

TG: 

Triglycerides

BMI: 

Body mass index.

Declarations

Acknowledgements

The authors gratefully acknowledge the financial support from the Scientific Research Foundation of the Health Bureau of Jilin Province, China (grant number: 2011Z116). We thank Yan-hua Wu, Yuan Tang, Zhi-hui Yan, Le Lv and Fan-yu Liu who participated in this study. The authors have no competing interests.

Authors’ Affiliations

(1)
Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
(2)
Illawarra Health and Medical Research Institute, University of Wollongong

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© He et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​4.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

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