Distribution characteristics of Lipoprotein (a) and non-genetic factors in Chinese Han population

Distribution characteristics of Lipoprotein (a) and non-genetic factors in Chinese Han population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Distribution characteristics of Lipoprotein (a) and non-genetic factors in Chinese Han population Cong Ma, Linggen Gao, Yifan Que, Libo Zhao, Tianzhi Li, Guogang Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4154807/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective : To explore the distribution characteristics and influencing factors of Lipoprotein (a) [Lp(a)] in Chinese Han population. Methods: In total, 2135 Chinese Han individuals who received physical examinations and lab tests from June 2019 to January 2020 in Health Management Institute, Chinese PLA General Hospital were enrolled in the current study. Basic clinical characteristics including disease history, family history, diet habit, blood lipid were collected. Results: A total of 1459 males and 676 females were finally enrolled to this research, with an average age of 48.09±7.98 years old and an overall level of LP (a) of 12.46±17.58 mg/dl. LP(a) increased gradually in 20-60 years. Women presented with a higher LP(a) than that of men in all age groups. The multivariate logistic regression revealed that the influencing factors of LP(a) varied with different cut-off points. Hypertension acted as the risk factor (P < 0.05), while fish consumption acted as the protective factor for the increase of LP (a) (P = 0.001) when the cut-off point was 30mg/dl. However, women and hypertension acted as the risk factors for the increase of LP (a) (P< 0.05) when the cut-off point was 50mg/dl. Conclusion: This research analyzed the clinical characteristics of Chinese Han population and investigated the potential influencing factors. Fish consumption is conducive to the decrease of LP(a). However, women and patients with hypertension should put more emphasis on the monitor of LP(a) and be wary of cardiovascular disease. This study may provide some evidence on the lifestyle management of Chinese Han population. Health sciences/Cardiology Health sciences/Health care Health sciences/Risk factors lipoprotein (a) Chinese Han population diet Introduction Lipoprotein a (LP(a)) is an LDL-like lipoprotein that connected with large glycoproteins known as ApoA to exert biological activity and is first discovered in 1963 by Kare Berg[ 1 ]. In recent years, it has been reported that LP (a) is more associated with atherosclerosis than low-density lipoprotein cholesterol (LDL-C). LP (a) has been reported to be risk factors of cardiovascular events and some inflammatory progression[ 2 – 6 ]. Therefore, more and more attention has been paid on the effect of LP (a). At present, most studies believe that the level of circulating LP (a) is mainly determined by the LPA gene encoding ApoA, and is less affected by age, gender, exercise, diet and nutrition[ 7 – 9 ]. However, some studies still showed that low-fat diet can increase the concentration of plasma Lp (a)[ 10 ], and the concentration of plasma Lp (a) varies with the content of cellulose in the diet. Besides, the concentration of plasma LP (a) varies greatly in the population, especially in different races[ 11 , 12 ]. At present, there is a lack of investigation on the distribution characteristics and influencing factors of LP (a) in the Han population in China. Thus, this research investigates the level and influencing factors of Chinese Han population in order to better understand LP (a) and provide theoretical basis for the prevention and management of cardiovascular events. Materials and Methods Population All participants enrolled to this study were recruited between June 2019 and January 2020 in Health Management Institute, Chinese PLA General Hospital. All the subjects were Han Chinese aged from 30 to 60 years old. Patient with the following conditions were excluded, including myocardial infarction within half a year, cerebrovascular accident, severe trauma, severe diseases of liver, kidney and hematopoietic system, psychosis, pregnant and lactating women. Clinical assessment Baseline clinical characteristics about disease history, LP(a) results and health-associated behaviors were collected for further analysis. Laboratory examinations Venous blood samples were collected after an overnight fast of at least 12 h. Serum Lp(a) levels were measured by latex immune turbidimetry (LP (a) Assay Kit, Liderman Biochemical Co., Ltd., Beijing). Self-administrated questionnaire All selected subjects were required to complete self-administrated questionnaires at the first physical examination to collect information including demographic characteristics, family medical records and history, height, weight, smoking and drinking history. Food frequency questionnaires were performed to collect dietary habits, including 10 single food items as cereals, fishes, milk and products, bean products, fried foods, meat product, fresh vegetables and fruits, eggs, sweetmeats and smoked foods. Statistical analysis Continuous variables were presented as mean ± SD or median (interquartile range), while categorical variables were presented as percentages. The students t-test or one-way ANOVA and the chi-square test or fisher exact test were applied to compare differences of continuous variables and categorical variables between groups, respectively. Logistic regression analysis was applied to investigate the independent association of Lp(a) with other relevant factors. SPSS software version 24.0 was used for all analysis. P-values < 0.05 were considered significantly different. Results Among 2135 participants, 68.3% were men and 31.7% were women, with a mean age of 48.09 ± 7.98 years. Take Serum Lp(a) levels 30mg/dl as the cutoff point, there were significant differences in male, smoking and drinking proportion (P < 0.05), while no significant difference was observed based on age, BMI, combined diseases such as hypertension, coronary heart disease, stroke, diabetes. If take Serum Lp(a) levels 50mg/dl as the cutoff point, there were no significant differences based on age, BMI, drinking proportion,combined diseases such as coronary heart disease, stroke, diabetes. Furthermore, there were significant differences in male, smoking and hypertension proportion (P < 0.05). Table 1 shows the baseline characteristics of the participants based on serum Lp(a). Table 1 Baseline characteristics of study participants based on serum Lp(a) Item Apoa 30mg/dl Apoa 50mg/dl 300 P OR(95%CI) 500 P OR(95%CI) Age 47.99 ± 7.99 48. 94 ± 7.80 0.08 1.015(0.10-1.033) 48.00 ± 8.00 49.50 ± 7.67 0.04 1.02 (1.00-1.045) Sex(male) 1336(69.9%) 133(55.9%) 0.000 1.84(1.40–2.41) 1391(69.3%) 68(53.5%) 0.000 1.96(1.36–2.81) BMI 25.47 ± 3.42 25.06 ± 3.27 0.081 0.97(0.93–1.004) 25.44 ± 3.40 25.17 ± 3.45 0.39 0.98(0.73–1.03) Smoking 789(41.6%) 72(30.3%) 0.01 0.61(0.46–0.81) 825(41.1) 36(28.3) 0.005 0.57(0.38–0.84) Drinking 1270(67%) 132(55.5%) 0.000 0.61(0.47–0.81) 1329(66.2%) 74(58.3%) 0.07 0.71(0.48–1.03) Hypertension 536(28.31%) 76(31.9%) 0.24 1.19(0.89–1.59) 564(28.1%) 48(37.8%) 0.02 1.56(1.07–2.26) CHD 93(4.9%) 16(6.7%) 0.23 1.40(0.81–2.42) 100(5%) 9(7.1%) 0.30 1.46(0.72–2.95) Stroke 16(0.8%) 2(0.8%) 1.0 1.0(0.23–4.36) 17(0.8%) 1(0.8%) 0.94 0.93(0.12–7.04) Diabetes 251(13.2%) 24(10.1%) 0.17 0.74(0.47–1.14) 262(13%) 13(10.2%) 0.36 0.76(0.42–1.37) Abbreviations: BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; OR, odds ratio; Continuous data are expressed as mean ± SD or median (interquartile range) and categorical variables were expressed as percentages. OR and P value were obtained from a univariate logistic regression analysis Distribution of LP (a) in different age groups The 2135 participants ranged in age from 21 to 79 years old. All the participants were divided into five groups by every 10 years as a group (Table 2 ). According to our study, serum Lp(a) increases with age from 21 to 60 years old. One-way ANOVA analysis showed that serum Lp(a) levels varied among the age groups. Individuals in 51–60 age group presented with significantly higher serum Lp(a) levels than those in 31–40 age group and 41–50 age group (P < 0.05). Table 2 Distribution of LP (a) in different age groups Age N Median Mean ± standard deviation 5th percentile 95th percentile Maximum minimum 21–30 54 4.94 9.62 ± 13.21 0.71 41.81 60.68 0.32 31–40 254 4.7 10.91 ± 15 + .44 1 43.7 99.6 0 41–50 1014 5.16 11.85 ± 17.27+ 0.96 54.92 124.72 0.82 51–60 694 6.32 14.02 ± 18.90 1.11 58.75 104.16 0.32 61–79 119 5.52 13.06 ± 17.80 1.36 57.96 83.12 0.84 Total 2135 5.36 12.46 ± 17.58 1 94.68 124.72 0 The unit of lipoprotein a is Milligrams per deciliter Distribution of LP (a) in different gender groups Table 3 shows the sex distribution of LP (a) for each age group. In both men and women aged 21 to 60, serum Lp(a) increases with age. Within each age group, the effect of gender was assessed. We observed a significant difference in LP (a) between sexes, showing a higher LP (a) value of females in the 21–50 age group (P < 0.05). No sex distribution differences were found for the 51–79 age group, which implies that age effects of LP (a) are different for males and females. Table 3 Distribution of LP (a) in different ages and sexes groups Age sex N Median Mean ± standard deviation 5th percentile 95th percentile Maximum minimum P 21–30 Male 27 3.56 6.87 ± 8.47 0.46 32.62 35.64 0.32 0.022 Female 27 5.68 12.36 ± 16.39 0.86 60.54 60.68 0.8 31–40 Male 168 3.58 8.91 ± 12.28 1.05 29.55 99.6 0.68 0.000 Female 86 6.26 14.81 ± 19.76 0.97 64.62 86.72 0 41–50 Male 721 4.36 10.19 ± 15.27 0.88 45.89 103.16 0.28 0.000 Female 293 7.44 15.94 ± 20.89 1.23 68.89 124.72 0.6 51–60 Male 479 5.24 12.94 ± 17.81 1 56.24 90.16 0.48 0.069 Female 215 7.72 16.43 ± 20.98 1.28 72.23 104.16 0.32 61–79 Male 64 5.58 12.56 ± 17.61 1.13 66.6 83.12 0.84 0.812 Female 55 5.52 13.64 ± 18.16 1.64 60.17 83.12 1.08 The unit of lipoprotein a is Milligrams per deciliter Non genetic factors at different cutoff points of LP (a): A Multivariate Logistic Regression Analysis for relevant factors of LP (a) As shown in Table 4 , 11.1% of all subjects presented with Lp(a) level of ≥ 30 mg/dL, which refers to hyperlipoproteinemia(a). According to logistic regression analysis, patient complicated hypertension shows an independent association with elevated Lp(a) level(Lp(a) ≥ 30 mg/dl); whereas eating more fish was negatively correlated with the elevated Lp(a) level. Table 4 Correlation regression analysis of non-genetic factors at different cutoff points of LP (a) Item Apoa 30mg/dL Apoa 50mg/dl P-value OR(95%CI) P-value OR(95%CI) Age 0.18 1.01 (0.99–1.03) 0.14 1.02(0.99–1.04) Sex 0.08 1.42(0.96–2.08) 0.03 1.78 (1.06–2.98) BMI 0.28 0.98(0.93–1.02) 0.57 0.98 (0.92–1.04) Hypertenison 0.031 1.44(1.03–1.99) 0.003 1.90 (1.25–2.91) Diabetes 0.17 0.72(0.45–1.15) 0.27 0.71(0.38–1.31) CHD 0.18 1.49(0.84–2.65) 0.37 1.40 (0.67–2.95) Stroke 0.82 0.84(0.19–3.79) 0.69 0.66(0.08–5.19) smoking 0.13 0.77(0.54–1.08) 0.22 0.75(0.47–1.20) drinking 0.23 0.81 (0.58–1.14) 0.84 1.05 (0.67–1.65) Cereals 0.21 0.75(0.47–1.18) 0.34 0.74(0.40–1.37) Fishes 0.001 0.61 (0.46–0.82) 0.08 0.71(0.48–1.04) Milk and products 0.94 0.99(0.74–1.33) 0.16 1.32 (0.90–1.95) Bean products 0.33 1.16 (0.86–1.58) 0.86 1.04(0.69–1.55) Fried foods 0.86 1.04(0.70–1.53) 0.35 0.77 (0.45–1.33) Meat 0.09 1.36(0.95–1.95) 0.32 1.27(0.79–2.03) Fresh fruit and vegetables 0.85 1.04 (0.67–1.61) 0.87 0.95 (0.53–1.71) Eggs 0.58 0.91 (0.66–1.27) 0.88 1.04(0.66–1.62) Desserts 0.26 1.21(0.87–1.68) 0.12 1.40 (0.92–2.15) Salted and smoked foods 0.48 1.14(0.80–1.62) 0.74 1.09(0.67–1.75) Abbreviations: BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; OR, odds ratio; Food intake was divided into 2 categpries, seldom to 2 times a week, 3-7times a week, with seldom to 2 times a week as the reference category. Meat contains pork, beef, mutton, poultry. Continuous data are expressed as mean±SD or median (interquartile range) and categorical variables were expressed as percentages. OR and P value were obtained from a multivariate logistic regression analysis When the cutoff of hyperlipoproteinemia was set as Lp(a) ≥ 50 mg/dL, which was shown in 5.9% of all subjects, the elevated Lp(a) level shows an independent association with hypertension according to logistic regression analysis, while female remained an independent risk factor for the level of Lp(a) ≥ 50 mg/dL. However, eating more fish no longer correlates with Lp(a). Discussion Recent studies have indicated that the increase of plasma Lp(a) can lead to atherosclerosis, inflammation and thromboembolism[ 13 , 14 ]. Therefore, Lp(a) has attracted more and more attention and become a research hotspot. However, the influencing factors and cut-off points of Lp(a) are still controversial and the current research on Lp(a) is still insufficient. About LP (a) cut-off point value of CVD risk increase, recommendations in guidelines and consensus of different countries are also inconsistent. In 2016 Canadian Cardiovascular Society (CCS) guidelines for dyslipidemia management[ 15 ], LP (a) > 30 mg/dl is defined as a risk factor for increased CVD risk. 2016 prevention and treatment guidelines of dyslipidemia in Chinese adults suggest that[ 16 ], 30 mg/dl is taken as the cut-off point for increased ASCVD risk. European atherosclerotic chemistry Association and National Lipid Association (NLA) has been put forward[ 17 , 18 ], LP (a) ≥ 50 mg/dl as a cut-off point, as well as 2023 Italian Society for the Study of Atherosclerosis (SISA) consensus[ 19 ] and 2022 scientific statement from the National Lipid Association[ 20 ]. Because the recommendations of guideline and consensus on LP (a) cut-off point are not consistent, both cut-off value are considered in this study. Although multiple evidences have shown that the concentration of LP (a) in plasma is mainly affected by LPA gene polymorphism rather than diet and environmental factors, there are still several studies confirm the correlation between dietary components and LP (a) concentration. Lars Berglund[ 21 ] found that the diet supplemented with monounsaturated fatty acids can reduce the plasma Lp(a) concentration compared with carbohydrate diet. Ginsberg HN[ 22 ] gave 103 healthy people three different diets and found that Lp(a) concentration gradually increased with the decrease of saturated fatty acid content. Silaste ML[ 23 ] found that the Lp(a) concentration increased in people with a rich vegetable diet compared with a less vegetable diet. At present, there is a lack of research on the correlation between Lp(a) and its diverse diet in the Han population in China. In our study, if we take plasma lipoprotein (a) concentration greater than 30 mg/dl as the cutoff point, it is found the Lp(a) level was significantly reduced in people who eat more fish. The reason may be related to the high content of polyunsaturated fatty acids in fish, which is similar to Lars Berglund's study. In this study, the concentration of LP (a) increased with age between 20–60 years old. Compared with 51–60 years old, there were statistical differences between 31–40 and 41–50 years old. While in all age groups, females presented with higher LP (a) concentration than that in male, and there was a significant difference in women between the 21–50 age group. Even in a multivariate logistic regression analysis with 50 mg/dl as a cut-off point, gender is still an independent risk factor. There has been a lack of large-scale epidemiological investigation studies about LP (a), therefore, the relationship between sex and lipoprotein has not been confirmed. Existing research is also controversial. In a survey of four Australian populations, there was no significant difference in concentration between gender[ 24 ]. Another study suggested the association between LP (a) and gender varies among different races[ 25 ]. In another survey of LP (a) levels in 8442 healthy adults in Nanjing in china, it was found that the level of LP (a) in women was higher than that in men, the difference was statistically significant. There was a weak correlation between Lp (a) level and age in different gender groups. LP (a) level tended to increase with the increase of age. The results are similar to our study. The reason for high LP (a) level in women may be that the subjects include a considerable number of menopausal women and estrogen may affect the LP (a) level by regulating the gene transcription level. However, in our study, LP (a) level in women is higher than that in men not only in 41–60 age groups but also in 21–40 age groups. It seems that there are other factors independent of estrogen. There is still a lack of large-scale epidemiological research at present, and its mechanism needs further study. In addition, our study also found that whether the cutoff point of LP (a) is set at 30 mg/dl or 50 mg/dl, hypertension is an independent risk factor for increased LP (a) level. Currently, there still lacks evidence on the potential relationship between hypertension and Lp(a) levels. A previous study showed that there is a significant higher circulation LP (a) in hypertensive patients than in the healthy controls, with no differences between males and females[ 26 ]. Ghorbani A[ 27 ] explored a significant positive correlation between serum Lp(a) and age or duration of duration of hypertension period. So far, the apoptotic mechanism is unknown. In a cross-sectional analysis, there is no significant differences in levels of Lp(a) and apo(a) isoforms of patients with hypertension compared with normotensive subjects[ 28 ]. Despite we found some relationship between Lp(a) and atherosclerosis, there still lacks adequent evidence on the association between elevated Lp(a) and hypertension. Currently, hypertension is thought to contribute to elevated Lp(a), which may be attributed to its effect direct via the vessel wall and its dependence effect on clearance by the kidneys[ 29 ]. The other limitation is that subjects enrolled to this study were mainly Chinese Han population. As Lp(a) concentrations differ from different populations, our results are possibly not applicable to other populations or ethnic groups. Besides, our research is a cross-sectional study rather than an intervention study. This kind of analysis may not establish a causal relationship between Lp(a) and other factors. Thus, a longitudinal study design could be used. Nevertheless, ours is a first step in identifying the relationship between Lp(a) and hypertension, gentle or dietary habits. For this reason, further longitudinal study is worth being performed in future researches of Chinese populations to investigate their exact causal relationship. In conclusion, our study demonstrated that in Chinese Han population, LP(a) increased gradually in 20–60 years, LP(a) level in female is higher than in male. This research indicates that Lp(a) concentration which is associated with hypertension, has a possible causal effect on dietary habit such as fish consumption. Further investigation of larger sizes of Chinese population are in great need, and the underlying pathophysiological mechanism between food consumption and hypertension remains to be unveiled. Declarations Author Contributions C. M. conceived and designed the study together with L. G., Y. Q. revised the manuscript, L.Z. prepared figures 1-4. T. L and G. X. contributed to data interpretation and revision of the manuscript. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of PLA General Hospital (S2021-095-02). Data availability The datasets generated during and/or analysed during the current study are not publicly available due to ensure individual privacymbut are available from the corresponding author on reasonable request. Informed Consent Statement All patients gave their informed consent for use of their data for research purposes Conflicts of Interest The authors declare no conflict of interest. References Contu, L, A new inherited serum beta-lipoprotein antigen in man and its relation to the Ag(xy) system, Vox Sang, 1968;15:367–373. 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Cobbaert, C, Mulder, P, Lindemans, J and Kesteloot, H, Serum LP(a) levels in African aboriginal Pygmies and Bantus, compared with Caucasian and Asian population samples, J Clin Epidemiol, 1997;50:1045–1053. Catalano, M, Perilli, E, Carzaniga, G, et al., Lp(a) in hypertensive patients, J Hum Hypertens, 1998;12:83–89. Ghorbani, A, Rafieian-Kopaei, M and Nasri, H, Lipoprotein (a): More than a bystander in the etiology of hypertension? A study on essential hypertensive patients not yet on treatment, J Nephropathol, 2013;2:67–70. Gazzaruso, C, Buscaglia, P, Garzaniti, A, et al., Lipoprotein(a) plasma concentrations, apolipoprotein (a) polymorphism and family history of coronary heart disease in patients with essential hypertension, J Cardiovasc Risk, 1996;3:191–197. Ward, NC, Nolde, JM, Chan, J, et al., Lipoprotein (a) and Hypertension, Curr Hypertens Rep, 2021;23:44. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4154807","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":288236300,"identity":"6f992947-7526-44c4-893d-045f12fc3579","order_by":0,"name":"Cong Ma","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Ma","suffix":""},{"id":288236301,"identity":"47ff23a9-53ee-4fac-a238-48174ba0bf88","order_by":1,"name":"Linggen Gao","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Linggen","middleName":"","lastName":"Gao","suffix":""},{"id":288236302,"identity":"0e2145a3-4233-4769-8af6-1474a3571a92","order_by":2,"name":"Yifan Que","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yifan","middleName":"","lastName":"Que","suffix":""},{"id":288236303,"identity":"64a6a54e-0c52-4b4f-a672-ed3220e74fa5","order_by":3,"name":"Libo Zhao","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Libo","middleName":"","lastName":"Zhao","suffix":""},{"id":288236304,"identity":"1b0f3470-0678-474f-ac29-fcdd61522b52","order_by":4,"name":"Tianzhi Li","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tianzhi","middleName":"","lastName":"Li","suffix":""},{"id":288236305,"identity":"9a92c43b-a298-4ac4-86cf-0ec7d048506c","order_by":5,"name":"Guogang Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYHACxocfDCQSQKwDDAwWRGlhNpaosIBoOcAgQZQWNgmeMxVgLQxEaZGPyDGrkGyTyOPnP3vw8IcaCQZ+6eMX8GoxPHPG7EZhm0Sx5Iy8hAMHjkkwSPblFODX0t5jdgNoS+KGGzwGBw6wSTAYnOFJwK+lmcesgBek5fwZoJZ/RGiRZ+8xY+A5A9RyIMfgwME2kBb2A3i1GPAcK5aWqJBInAnyy9k+CR7JHh68OhjkZyRv/PjBoC6xn//s4Q8V32zk+HnYH+C3BeEIHhjJY4DflgY0LUBAwJZRMApGwSgYcQAAg3lJeVOk1HQAAAAASUVORK5CYII=","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Guogang","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-03-23 14:29:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4154807/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4154807/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55264453,"identity":"745e4036-975a-4fc5-bd00-beac9125b2b1","added_by":"auto","created_at":"2024-04-25 01:43:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":638389,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4154807/v1/ad54dd2f-5533-4a92-88ad-f14d3e63d7bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Distribution characteristics of Lipoprotein (a) and non-genetic factors in Chinese Han population","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLipoprotein a (LP(a)) is an LDL-like lipoprotein that connected with large glycoproteins known as ApoA to exert biological activity and is first discovered in 1963 by Kare Berg[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In recent years, it has been reported that LP (a) is more associated with atherosclerosis than low-density lipoprotein cholesterol (LDL-C). LP (a) has been reported to be risk factors of cardiovascular events and some inflammatory progression[\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, more and more attention has been paid on the effect of LP (a).\u003c/p\u003e \u003cp\u003eAt present, most studies believe that the level of circulating LP (a) is mainly determined by the LPA gene encoding ApoA, and is less affected by age, gender, exercise, diet and nutrition[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, some studies still showed that low-fat diet can increase the concentration of plasma Lp (a)[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and the concentration of plasma Lp (a) varies with the content of cellulose in the diet. Besides, the concentration of plasma LP (a) varies greatly in the population, especially in different races[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. At present, there is a lack of investigation on the distribution characteristics and influencing factors of LP (a) in the Han population in China.\u003c/p\u003e \u003cp\u003eThus, this research investigates the level and influencing factors of Chinese Han population in order to better understand LP (a) and provide theoretical basis for the prevention and management of cardiovascular events.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePopulation\u003c/h2\u003e \u003cp\u003e All participants enrolled to this study were recruited between June 2019 and January 2020 in Health Management Institute, Chinese PLA General Hospital. All the subjects were Han Chinese aged from 30 to 60 years old. Patient with the following conditions were excluded, including myocardial infarction within half a year, cerebrovascular accident, severe trauma, severe diseases of liver, kidney and hematopoietic system, psychosis, pregnant and lactating women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinical assessment\u003c/h2\u003e \u003cp\u003eBaseline clinical characteristics about disease history, LP(a) results and health-associated behaviors were collected for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory examinations\u003c/h2\u003e \u003cp\u003eVenous blood samples were collected after an overnight fast of at least 12 h. Serum Lp(a) levels were measured by latex immune turbidimetry (LP (a) Assay Kit, Liderman Biochemical Co., Ltd., Beijing).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSelf-administrated questionnaire\u003c/h2\u003e \u003cp\u003eAll selected subjects were required to complete self-administrated questionnaires at the first physical examination to collect information including demographic characteristics, family medical records and history, height, weight, smoking and drinking history. Food frequency questionnaires were performed to collect dietary habits, including 10 single food items as cereals, fishes, milk and products, bean products, fried foods, meat product, fresh vegetables and fruits, eggs, sweetmeats and smoked foods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (interquartile range), while categorical variables were presented as percentages. The students t-test or one-way ANOVA and the chi-square test or fisher exact test were applied to compare differences of continuous variables and categorical variables between groups, respectively. Logistic regression analysis was applied to investigate the independent association of Lp(a) with other relevant factors. SPSS software version 24.0 was used for all analysis. P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significantly different.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong 2135 participants, 68.3% were men and 31.7% were women, with a mean age of 48.09\u0026thinsp;\u0026plusmn;\u0026thinsp;7.98 years. Take Serum Lp(a) levels 30mg/dl as the cutoff point, there were significant differences in male, smoking and drinking proportion (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant difference was observed based on age, BMI, combined diseases such as hypertension, coronary heart disease, stroke, diabetes.\u003c/p\u003e\n\u003cp\u003eIf take Serum Lp(a) levels 50mg/dl as the cutoff point, there were no significant differences based on age, BMI, drinking proportion,combined diseases such as coronary heart disease, stroke, diabetes. Furthermore, there were significant differences in male, smoking and hypertension proportion (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of the participants based on serum Lp(a).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline characteristics of study participants based on serum Lp(a)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eItem\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eApoa 30mg/dl\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eApoa 50mg/dl\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;300\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;300\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47.99\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48. 94\u0026thinsp;\u0026plusmn;\u0026thinsp;7.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.015(0.10-1.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02 (1.00-1.045)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex(male)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1336(69.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133(55.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.84(1.40\u0026ndash;2.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1391(69.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68(53.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.96(1.36\u0026ndash;2.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.97(0.93\u0026ndash;1.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.44\u0026thinsp;\u0026plusmn;\u0026thinsp;3.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.98(0.73\u0026ndash;1.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e789(41.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72(30.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.61(0.46\u0026ndash;0.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e825(41.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36(28.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.57(0.38\u0026ndash;0.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDrinking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1270(67%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132(55.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.61(0.47\u0026ndash;0.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1329(66.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74(58.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.71(0.48\u0026ndash;1.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e536(28.31%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76(31.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.19(0.89\u0026ndash;1.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e564(28.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48(37.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.56(1.07\u0026ndash;2.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93(4.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16(6.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.40(0.81\u0026ndash;2.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100(5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(7.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.46(0.72\u0026ndash;2.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStroke\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16(0.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(0.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0(0.23\u0026ndash;4.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17(0.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(0.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93(0.12\u0026ndash;7.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e251(13.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24(10.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.74(0.47\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e262(13%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13(10.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.76(0.42\u0026ndash;1.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"9\"\u003eAbbreviations: BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; OR, odds ratio; Continuous data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (interquartile range) and categorical variables were expressed as percentages. OR and P value were obtained from a univariate logistic regression analysis\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eDistribution of LP (a) in different age groups\u003c/h2\u003e\n\u003cp\u003eThe 2135 participants ranged in age from 21 to 79 years old. All the participants were divided into five groups by every 10 years as a group (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). According to our study, serum Lp(a) increases with age from 21 to 60 years old. One-way ANOVA analysis showed that serum Lp(a) levels varied among the age groups. Individuals in 51\u0026ndash;60 age group presented with significantly higher serum Lp(a) levels than those in 31\u0026ndash;40 age group and 41\u0026ndash;50 age group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDistribution of LP (a) in different age groups\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eN\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMedian\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e5th percentile\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95th percentile\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMaximum\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eminimum\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u0026ndash;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e9.62\u0026thinsp;\u0026plusmn;\u0026thinsp;13.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u0026ndash;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e254\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e10.91\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u0026thinsp;+\u0026thinsp;.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e43.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e99.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u0026ndash;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;17.27+\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e54.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e124.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51\u0026ndash;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e694\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e14.02\u0026thinsp;\u0026plusmn;\u0026thinsp;18.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e58.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e104.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61\u0026ndash;79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e119\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e13.06\u0026thinsp;\u0026plusmn;\u0026thinsp;17.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e57.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e12.46\u0026thinsp;\u0026plusmn;\u0026thinsp;17.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e94.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e124.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003eThe unit of lipoprotein a is Milligrams per deciliter\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eDistribution of LP (a) in different gender groups\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the sex distribution of LP (a) for each age group. In both men and women aged 21 to 60, serum Lp(a) increases with age. Within each age group, the effect of gender was assessed. We observed a significant difference in LP (a) between sexes, showing a higher LP (a) value of females in the 21\u0026ndash;50 age group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No sex distribution differences were found for the 51\u0026ndash;79 age group, which implies that age effects of LP (a) are different for males and females.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDistribution of LP (a) in different ages and sexes groups\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003esex\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eN\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMedian\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e5th percentile\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95th percentile\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMaximum\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eminimum\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u0026ndash;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e6.87\u0026thinsp;\u0026plusmn;\u0026thinsp;8.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e12.36\u0026thinsp;\u0026plusmn;\u0026thinsp;16.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u0026ndash;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e168\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e8.91\u0026thinsp;\u0026plusmn;\u0026thinsp;12.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e99.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e14.81\u0026thinsp;\u0026plusmn;\u0026thinsp;19.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e64.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e86.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u0026ndash;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e721\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e10.19\u0026thinsp;\u0026plusmn;\u0026thinsp;15.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e103.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e293\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e15.94\u0026thinsp;\u0026plusmn;\u0026thinsp;20.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e68.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e124.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51\u0026ndash;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e479\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e12.94\u0026thinsp;\u0026plusmn;\u0026thinsp;17.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e56.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e90.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.069\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e215\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e16.43\u0026thinsp;\u0026plusmn;\u0026thinsp;20.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e72.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e104.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61\u0026ndash;79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e12.56\u0026thinsp;\u0026plusmn;\u0026thinsp;17.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e66.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.812\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e13.64\u0026thinsp;\u0026plusmn;\u0026thinsp;18.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"10\"\u003eThe unit of lipoprotein a is Milligrams per deciliter\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNon genetic factors at different cutoff points of LP (a): A Multivariate Logistic Regression Analysis for relevant factors of LP (a)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, 11.1% of all subjects presented with Lp(a) level of \u0026ge;\u0026thinsp;30 mg/dL, which refers to hyperlipoproteinemia(a). According to logistic regression analysis, patient complicated hypertension shows an independent association with elevated Lp(a) level(Lp(a)\u0026thinsp;\u0026ge;\u0026thinsp;30 mg/dl); whereas eating more fish was negatively correlated with the elevated Lp(a) level.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCorrelation regression analysis of non-genetic factors at different cutoff points of LP (a)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eItem\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eApoa 30mg/dL\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eApoa 50mg/dl\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01 (0.99\u0026ndash;1.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.02(0.99\u0026ndash;1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.42(0.96\u0026ndash;2.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.78 (1.06\u0026ndash;2.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.98(0.93\u0026ndash;1.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.98 (0.92\u0026ndash;1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertenison\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.44(1.03\u0026ndash;1.99)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.90 (1.25\u0026ndash;2.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.72(0.45\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.71(0.38\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.49(0.84\u0026ndash;2.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.40 (0.67\u0026ndash;2.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStroke\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.84(0.19\u0026ndash;3.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.66(0.08\u0026ndash;5.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003esmoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.77(0.54\u0026ndash;1.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.75(0.47\u0026ndash;1.20)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edrinking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.81 (0.58\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05 (0.67\u0026ndash;1.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCereals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.75(0.47\u0026ndash;1.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.74(0.40\u0026ndash;1.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFishes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.61 (0.46\u0026ndash;0.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.71(0.48\u0026ndash;1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMilk and products\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99(0.74\u0026ndash;1.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.32 (0.90\u0026ndash;1.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBean products\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.16 (0.86\u0026ndash;1.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04(0.69\u0026ndash;1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFried foods\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04(0.70\u0026ndash;1.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.77 (0.45\u0026ndash;1.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMeat\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.36(0.95\u0026ndash;1.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.27(0.79\u0026ndash;2.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFresh fruit and vegetables\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04 (0.67\u0026ndash;1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.95 (0.53\u0026ndash;1.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEggs\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.91 (0.66\u0026ndash;1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04(0.66\u0026ndash;1.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDesserts\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.21(0.87\u0026ndash;1.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.40 (0.92\u0026ndash;2.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSalted and smoked foods\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.14(0.80\u0026ndash;1.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.09(0.67\u0026ndash;1.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; OR, odds ratio; Food intake was divided into 2 categpries, seldom to 2 times a week, 3-7times a week, with seldom to 2 times a week as the reference category. Meat contains pork, beef, mutton, poultry. Continuous data are expressed as mean\u0026plusmn;SD or median (interquartile range) and categorical variables were expressed as percentages. OR and P value were obtained from a multivariate logistic regression analysis\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eWhen the cutoff of hyperlipoproteinemia was set as Lp(a)\u0026thinsp;\u0026ge;\u0026thinsp;50 mg/dL, which was shown in 5.9% of all subjects, the elevated Lp(a) level shows an independent association with hypertension according to logistic regression analysis, while female remained an independent risk factor for the level of Lp(a)\u0026thinsp;\u0026ge;\u0026thinsp;50 mg/dL. However, eating more fish no longer correlates with Lp(a).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eRecent studies have indicated that the increase of plasma Lp(a) can lead to atherosclerosis, inflammation and thromboembolism[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, Lp(a) has attracted more and more attention and become a research hotspot. However, the influencing factors and cut-off points of Lp(a) are still controversial and the current research on Lp(a) is still insufficient.\u003c/p\u003e \u003cp\u003e About LP (a) cut-off point value of CVD risk increase, recommendations in guidelines and consensus of different countries are also inconsistent. In 2016 Canadian Cardiovascular Society (CCS) guidelines for dyslipidemia management[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], LP (a)\u0026thinsp;\u0026gt;\u0026thinsp;30 mg/dl is defined as a risk factor for increased CVD risk. 2016 prevention and treatment guidelines of dyslipidemia in Chinese adults suggest that[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], 30 mg/dl is taken as the cut-off point for increased ASCVD risk. European atherosclerotic chemistry Association and National Lipid Association (NLA) has been put forward[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], LP (a)\u0026thinsp;\u0026ge;\u0026thinsp;50 mg/dl as a cut-off point, as well as 2023 Italian Society for the Study of Atherosclerosis (SISA) consensus[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and 2022 scientific statement from the National Lipid Association[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Because the recommendations of guideline and consensus on LP (a) cut-off point are not consistent, both cut-off value are considered in this study.\u003c/p\u003e \u003cp\u003eAlthough multiple evidences have shown that the concentration of LP (a) in plasma is mainly affected by LPA gene polymorphism rather than diet and environmental factors, there are still several studies confirm the correlation between dietary components and LP (a) concentration. Lars Berglund[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] found that the diet supplemented with monounsaturated fatty acids can reduce the plasma Lp(a) concentration compared with carbohydrate diet. Ginsberg HN[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] gave 103 healthy people three different diets and found that Lp(a) concentration gradually increased with the decrease of saturated fatty acid content. Silaste ML[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] found that the Lp(a) concentration increased in people with a rich vegetable diet compared with a less vegetable diet. At present, there is a lack of research on the correlation between Lp(a) and its diverse diet in the Han population in China. In our study, if we take plasma lipoprotein (a) concentration greater than 30 mg/dl as the cutoff point, it is found the Lp(a) level was significantly reduced in people who eat more fish. The reason may be related to the high content of polyunsaturated fatty acids in fish, which is similar to Lars Berglund's study.\u003c/p\u003e \u003cp\u003eIn this study, the concentration of LP (a) increased with age between 20\u0026ndash;60 years old. Compared with 51\u0026ndash;60 years old, there were statistical differences between 31\u0026ndash;40 and 41\u0026ndash;50 years old. While in all age groups, females presented with higher LP (a) concentration than that in male, and there was a significant difference in women between the 21\u0026ndash;50 age group. Even in a multivariate logistic regression analysis with 50 mg/dl as a cut-off point, gender is still an independent risk factor.\u003c/p\u003e \u003cp\u003eThere has been a lack of large-scale epidemiological investigation studies about LP (a), therefore, the relationship between sex and lipoprotein has not been confirmed. Existing research is also controversial. In a survey of four Australian populations, there was no significant difference in concentration between gender[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Another study suggested the association between LP (a) and gender varies among different races[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In another survey of LP (a) levels in 8442 healthy adults in Nanjing in china, it was found that the level of LP (a) in women was higher than that in men, the difference was statistically significant. There was a weak correlation between Lp (a) level and age in different gender groups. LP (a) level tended to increase with the increase of age. The results are similar to our study. The reason for high LP (a) level in women may be that the subjects include a considerable number of menopausal women and estrogen may affect the LP (a) level by regulating the gene transcription level. However, in our study, LP (a) level in women is higher than that in men not only in 41\u0026ndash;60 age groups but also in 21\u0026ndash;40 age groups. It seems that there are other factors independent of estrogen. There is still a lack of large-scale epidemiological research at present, and its mechanism needs further study.\u003c/p\u003e \u003cp\u003eIn addition, our study also found that whether the cutoff point of LP (a) is set at 30 mg/dl or 50 mg/dl, hypertension is an independent risk factor for increased LP (a) level. Currently, there still lacks evidence on the potential relationship between hypertension and Lp(a) levels. A previous study showed that there is a significant higher circulation LP (a) in hypertensive patients than in the healthy controls, with no differences between males and females[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Ghorbani A[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] explored a significant positive correlation between serum Lp(a) and age or duration of duration of hypertension period. So far, the apoptotic mechanism is unknown. In a cross-sectional analysis, there is no significant differences in levels of Lp(a) and apo(a) isoforms of patients with hypertension compared with normotensive subjects[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite we found some relationship between Lp(a) and atherosclerosis, there still lacks adequent evidence on the association between elevated Lp(a) and hypertension. Currently, hypertension is thought to contribute to elevated Lp(a), which may be attributed to its effect direct via the vessel wall and its dependence effect on clearance by the kidneys[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The other limitation is that subjects enrolled to this study were mainly Chinese Han population. As Lp(a) concentrations differ from different populations, our results are possibly not applicable to other populations or ethnic groups. Besides, our research is a cross-sectional study rather than an intervention study. This kind of analysis may not establish a causal relationship between Lp(a) and other factors. Thus, a longitudinal study design could be used. Nevertheless, ours is a first step in identifying the relationship between Lp(a) and hypertension, gentle or dietary habits. For this reason, further longitudinal study is worth being performed in future researches of Chinese populations to investigate their exact causal relationship.\u003c/p\u003e \u003cp\u003eIn conclusion, our study demonstrated that in Chinese Han population, LP(a) increased gradually in 20\u0026ndash;60 years, LP(a) level in female is higher than in male. This research indicates that Lp(a) concentration which is associated with hypertension, has a possible causal effect on dietary habit such as fish consumption. Further investigation of larger sizes of Chinese population are in great need, and the underlying pathophysiological mechanism between food consumption and hypertension remains to be unveiled.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC. M. conceived and designed the study together with L. G., Y. Q. revised the manuscript, L.Z.\u0026nbsp;prepared figures 1-4. \u0026nbsp;T. L and G. X. contributed to data interpretation and revision of the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of PLA General Hospital (S2021-095-02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are not publicly available due to ensure individual privacymbut are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients gave their\u0026nbsp;informed consent\u0026nbsp;for use of their data for research purposes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eContu, L, A new inherited serum beta-lipoprotein antigen in man and its relation to the Ag(xy) system, Vox Sang, 1968;15:367\u0026ndash;373.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNordestgaard, BG, Chapman, MJ, Ray, K, et al., Lipoprotein(a) as a cardiovascular risk factor: current status, Eur Heart J, 2010;31:2844\u0026ndash;2853.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNordestgaard, BG and Langsted, A, Lipoprotein (a) as a cause of cardiovascular disease: insights from epidemiology, genetics, and biology, J Lipid Res, 2016;57:1953\u0026ndash;1975.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGurdasani, D, Sjouke, B, Tsimikas, S, et al., Lipoprotein(a) and risk of coronary, cerebrovascular, and peripheral artery disease: the EPIC-Norfolk prospective population study, Arterioscler Thromb Vasc Biol, 2012;32:3058\u0026ndash;3065.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssini, JM, Clark, JR, Youssef, A, et al., High levels of lipoprotein(a) in transgenic mice exacerbate atherosclerosis and promote vulnerable plaque features in a sex-specific manner, Atherosclerosis, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuarte Lau, F and Giugliano, RP, Lipoprotein(a) and its Significance in Cardiovascular Disease: A Review, JAMA Cardiol, 2022;7:760\u0026ndash;769.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLampsas, S, Xenou, M, Oikonomou, E, et al., Lipoprotein(a) in Atherosclerotic Diseases: From Pathophysiology to Diagnosis and Treatment, Molecules, 2023;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKronenberg, F and Utermann, G, Lipoprotein(a): resurrected by genetics, J Intern Med, 2013;273:6\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKronenberg, F, Lipoprotein(a), In: von Eckardstein, A. and Binder, C. J. (eds), Prevention and Treatment of Atherosclerosis: Improving State-of-the-Art Management and Search for Novel Targets, Cham (CH), 2022:201\u0026ndash;232.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaw, HG, Khan, MA, Zhang, W, et al., Reducing saturated fat intake lowers LDL-C but increases Lp(a) levels in African Americans: the GET-READI feeding trial, J Lipid Res, 2023;64:100420.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirani, SS, Brautbar, A, Davis, BC, et al., Associations between lipoprotein(a) levels and cardiovascular outcomes in black and white subjects: the Atherosclerosis Risk in Communities (ARIC) Study, Circulation, 2012;125:241\u0026ndash;249.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao, J, Steffen, BT, Budoff, M, et al., Lipoprotein(a) Levels Are Associated With Subclinical Calcific Aortic Valve Disease in White and Black Individuals: The Multi-Ethnic Study of Atherosclerosis, Arterioscler Thromb Vasc Biol, 2016;36:1003\u0026ndash;1009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsimikas, S, A Test in Context: Lipoprotein(a): Diagnosis, Prognosis, Controversies, and Emerging Therapies, J Am Coll Cardiol, 2017;69:692\u0026ndash;711.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoffa, MB and Koschinsky, ML, Oxidized phospholipids as a unifying theory for lipoprotein(a) and cardiovascular disease, Nat Rev Cardiol, 2019;16:305\u0026ndash;318.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson, TJ, Gregoire, J, Pearson, GJ, et al., 2016 Canadian Cardiovascular Society Guidelines for the Management of Dyslipidemia for the Prevention of Cardiovascular Disease in the Adult, Can J Cardiol, 2016;32:1263\u0026ndash;1282.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoint committee issued Chinese guideline for the management of dyslipidemia in, a, [2016 Chinese guideline for the management of dyslipidemia in adults], Zhonghua Xin Xue Guan Bing Za Zhi, 2016;44:833\u0026ndash;853.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson, DP, Jacobson, TA, Jones, PH, et al., Use of Lipoprotein(a) in clinical practice: A biomarker whose time has come. A scientific statement from the National Lipid Association, J Clin Lipidol, 2019;13:374\u0026ndash;392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMach, F, Baigent, C, Catapano, AL, et al., 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk, Eur Heart J, 2020;41:111\u0026ndash;188.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiesa, G, Zenti, MG, Baragetti, A, et al., Consensus document on Lipoprotein(a) from the Italian Society for the Study of Atherosclerosis (SISA), Nutr Metab Cardiovasc Dis, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson, DP, Jacobson, TA, Jones, PH, et al., Use of Lipoprotein(a) in clinical practice: A biomarker whose time has come. A scientific statement from the National Lipid Association, J Clin Lipidol, 2022;16:e77-e95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerglund, L, Lefevre, M, Ginsberg, HN, et al., Comparison of monounsaturated fat with carbohydrates as a replacement for saturated fat in subjects with a high metabolic risk profile: studies in the fasting and postprandial states, Am J Clin Nutr, 2007;86:1611\u0026ndash;1620.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGinsberg, HN, Kris-Etherton, P, Dennis, B, et al., Effects of reducing dietary saturated fatty acids on plasma lipids and lipoproteins in healthy subjects: the DELTA Study, protocol 1, Arterioscler Thromb Vasc Biol, 1998;18:441\u0026ndash;449.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilaste, ML, Rantala, M, Alfthan, G, et al., Changes in dietary fat intake alter plasma levels of oxidized low-density lipoprotein and lipoprotein(a), Arterioscler Thromb Vasc Biol, 2004;24:498\u0026ndash;503.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong, ZW, Wahlqvist, ML, Biegler, B, et al., Cross-cultural comparison of Lp(a) profiles, Asia Pac J Clin Nutr, 1998;7:182\u0026ndash;191.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCobbaert, C, Mulder, P, Lindemans, J and Kesteloot, H, Serum LP(a) levels in African aboriginal Pygmies and Bantus, compared with Caucasian and Asian population samples, J Clin Epidemiol, 1997;50:1045\u0026ndash;1053.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCatalano, M, Perilli, E, Carzaniga, G, et al., Lp(a) in hypertensive patients, J Hum Hypertens, 1998;12:83\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhorbani, A, Rafieian-Kopaei, M and Nasri, H, Lipoprotein (a): More than a bystander in the etiology of hypertension? A study on essential hypertensive patients not yet on treatment, J Nephropathol, 2013;2:67\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGazzaruso, C, Buscaglia, P, Garzaniti, A, et al., Lipoprotein(a) plasma concentrations, apolipoprotein (a) polymorphism and family history of coronary heart disease in patients with essential hypertension, J Cardiovasc Risk, 1996;3:191\u0026ndash;197.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWard, NC, Nolde, JM, Chan, J, et al., Lipoprotein (a) and Hypertension, Curr Hypertens Rep, 2021;23:44.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"lipoprotein (a), Chinese Han population, diet","lastPublishedDoi":"10.21203/rs.3.rs-4154807/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4154807/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To explore the distribution characteristics and influencing factors of Lipoprotein (a) [Lp(a)] in Chinese Han population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn total, 2135 Chinese Han individuals who received physical examinations and lab tests from June 2019 to January 2020 in Health Management Institute, Chinese PLA General Hospital were enrolled in the current study. Basic clinical characteristics including disease history, family history, diet habit, blood lipid were collected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 1459 males and 676 females were finally enrolled to this research, with an average age of 48.09±7.98 years old and an overall level of LP (a) of 12.46±17.58 mg/dl. LP(a) increased gradually in 20-60 years. Women presented with a higher LP(a) than that of men in all age groups. The multivariate logistic regression revealed that the influencing factors of LP(a) varied with different cut-off points. Hypertension acted as the risk factor (P \u0026lt; 0.05), while fish consumption acted as the protective factor for the increase of LP (a) (P = 0.001) when the cut-off point was 30mg/dl. However, women and hypertension acted as the risk factors for the increase of LP (a) (P\u0026lt; 0.05) when the cut-off point was 50mg/dl.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This research analyzed the clinical characteristics of Chinese Han population and investigated the potential influencing factors. Fish consumption is conducive to the decrease of LP(a). However, women and patients with hypertension should put more emphasis on the monitor of LP(a) and be wary of cardiovascular disease. This study may provide some evidence on the lifestyle management of Chinese Han population.\u003c/p\u003e","manuscriptTitle":"Distribution characteristics of Lipoprotein (a) and non-genetic factors in Chinese Han population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 16:44:44","doi":"10.21203/rs.3.rs-4154807/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b98a8667-ca61-4a9f-a7bb-a867e23e3f18","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30348004,"name":"Health sciences/Cardiology"},{"id":30348005,"name":"Health sciences/Health care"},{"id":30348006,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-04-22T07:48:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 16:44:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4154807","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4154807","identity":"rs-4154807","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}