Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2016

Open Access 01-12-2016 | Research article

Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China

Authors: Li Xu, Dejian Lai, Ya Fang

Published in: BMC Public Health | Issue 1/2016

Login to get access

Abstract

Background

Previous studies have shown that there may be gender disparities in the prevalence of hypertension; however, these studies do not address the spatial information contained in the sample which may limit the analytical results. Our study extends the existing Shared Component Model (SCM) and compares its utility with a logistic regression model to evaluate the significance of spatial information for identifying risk factors for hypertension and other non-rare diseases.

Methods

A total of 1267 residents aged 45 years of age and over were included in our study, of which 48.1 % were males. The overall prevalence of hypertension was 33.2 %, with females experiencing a higher prevalence than males (35.5 % vs. 30.6 %). The research variables included body mass index (BMI), Waist -to-Height Ratio (WHtR), smoking status, alcohol consumption etc. The extended SCM is employed to investigate regional gender variations in the risk of hypertension and assess the gender variation in the middle-aged and elderly populations of Zhejiang Province in eastern China and then its performance is compared with that of a traditional multiple logistic regression model.

Results

Our SCM analysis determined that the spatial pattern of hypertension risk for the middle-aged and elderly populations of Zhejiang Province in eastern China is quite different for males and females. Furthermore, Waist -to-Height Ratio (WHtR) continues to be a simple and effective predictor of hypertension risk for males at the regional level.

Conclusions

We believe that the extended SCM spatial model is a useful tool for identifying risk factors at the regional level.
Appendix
Available only for authorised users
Footnotes
1
City is larger than county in China.
 
Literature
1.
Liu L, Wu Z, Zhu D. Guidelines for Prevention and Treatment of Hypertension in China (revised edition, 2010). Beijing: People’s Medical Publishing House Co., LTD; 2010.
2.
Lloyd-Sherlock P, Beard J, Minicuci N, et al. Hypertension among older adults in low-and middle-income countries: Prevalence, awareness and control. Int J Epidemiol. 2014;43(1):116–28.CrossRefPubMedPubMedCentral
3.
Non-Communicable Chronic Disease Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention. Report on chronic diseases and risk factor surveillance in China (2010). Beijing: Military Medical Science Press; 2012.
4.
Liao H, Mei JI, Zhang K, et al. A study on risk factors of essential hypertension (EHT) among the rural middle-aged and elderly people. Chin J Prev Contr Chron Non-commun Dis. 1999;7(06):256–58.
5.
Wang J-s, Yu J-m, Hu D-y, et al. Prevalence of hypertension and risk factors among young adults aged 20 to 44 years in Beijing Community. Chin J Hypertens. 2009;17(9):811–16.
6.
Wang L-n, Li CAO, Jing-yi Z, et al. The investigation of risk factor s of hyper tension among adult residents in Hebei Province. Chin J Prev Contr Chron Non-commun Dis. 2008;16(2):125–29.
7.
Xin-jian L, Xu J-y, Hai-hong Y. Case-control study on risk factors for hypertension among Shanghai residents. Chin J Prev Contr Chron Dis. 2010;18(4):375–76.
8.
Luo L, Rong-sheng L, Ping Y. Meta-analysis of risk factor on hypertension in China. Chin J Epidemiol. 2003;24(01):50–3.
9.
Xiao J*, Yang M, Zong L, et al. Application of logistic regression and log-linear model on the study of risk factors of hypertension. Chin J Prev Contr Chron Dis. 2012;20(04):372–74.
10.
Hong-yan L, Hui P, Ao-bo L, et al. Risk factors of essential hypertension in China: A meta-analysis. Chin J Cardiovasc Med. 2009;14(3):205–09.
11.
Niskanen L, Laaksonen DE, Nyyssönen K, et al. Inflammation, abdominal obesity, and smoking as predictors of hypertension. Hypertension. 2004;44(6):859–65.CrossRefPubMed
12.
Ishikawa K, Ohta T, Zhang J, et al. Influence of age and gender on exercise training-induced blood pressure reduction in systemic hypertension. Am J Cardiol. 1999;84(2):192–96.CrossRefPubMed
13.
Helmers KF, Baker B, O’Kelly B, et al. Anger expression, gender, and ambulatory blood pressure in mild, unmedicated adults with hypertension. Ann Behav Med. 2000;22(1):60–4.CrossRefPubMed
14.
Momtaz YA, Hamid TA, Yusoff S, et al. Loneliness as a risk factor for hypertension in later life. J Aging Health. 2012;24(4):696–710.CrossRefPubMed
15.
Lopez Garcia E, Faubel R, GuallarCastillon P, et al. Self-reported sleep duration and hypertension in older Spanish adults. J Am Geriatr Soc. 2009;57(4):663–68.CrossRefPubMed
16.
Kagan A, Faibel H, Ben-Arie G, et al. Gender differences in ambulatory blood pressure monitoring profile in obese, overweight and normal subjects. J Hum Hypertens. 2007;21(2):128–34.CrossRefPubMed
17.
Pechère-Bertschi A, Burnier M. Females sex hormones, salt, and blood pressure regulation*. Am J Hypertens. 2004;17(10):994–1001.CrossRefPubMed
18.
Shunichi K, Kazuo M, Genjiro K, et al. A gender difference in the association between salt sensitivity and family history of hypertension. Am J Hypertens. 1992;5(1):1–7.CrossRef
19.
Sesso HD, Cook NR, Buring JE, et al. Alcohol consumption and the risk of hypertension in women and men. Hypertension. 2008;51(4):1080–87.CrossRefPubMed
20.
Witteman J, Willett WC, Stampfer MJ, et al. Relation of moderate alcohol consumption and risk of systemic hypertension in women. Am J Cardiol. 1990;65(9):633–37.CrossRefPubMed
21.
Cappuccio FP, Stranges S, Kandala N, et al. Gender-specific associations of short sleep duration with prevalent and incident hypertension the Whitehall II study. Hypertension. 2007;50(4):693–700.CrossRefPubMedPubMedCentral
22.
Hagberg JM, Park J, Brown MD. The role of exercise training in the treatment of hypertension. Sports Med. 2000;30(3):193–206.CrossRefPubMed
23.
Hui L. Gender Differences of Prevalence and Control of Hypertension in Rural Shandong, China. China: Shandong University; 2009.
24.
Kaplan MS, Huguet N, Feeny DH, et al. Self-reported prevalence of hypertension and income among older adults in Canada and the United States. Soc Sci Med. 2010;70(6):844–49.CrossRefPubMed
25.
de Gaudemaris R, Lang T, Chatellier G, et al. Socioeconomic inequalities in prevalence of hypertension and care the IHPAF study. Hypertension. 2002;39(6):1119–25.CrossRefPubMed
26.
Gangwisch JE, Heymsfield SB, Boden-Albala B, et al. Short sleep duration as a risk factor for hypertension analyses of the first national health and nutrition examination survey. Hypertension. 2006;47(5):833–39.CrossRefPubMed
27.
Ma Y-x, Bing Z, Wang H-j, et al. The Effect of Alcohol Consumption on Prevalence of Hypertension among Adults Residents from 9 Provinces of China. Chin J Prev Contr Chron Dis. 2011;19(01):9–12.
28.
Wu X-g, Xiu-fang D, Guang-yong H, et al. Prevalence and relevant influence factors of isolated systolic hypertension in the elderly in China. Chin J Cardiol. 2003;31(06):456–59.
29.
Jie C, Xiu-li Z, Wu F, et al. Epidemiology of obesity and overweight and relation thereof to the prevalence of hypertension in 14 provinces/municipality in China. Natl Med J China. 2005;85(40):2830–33.
30.
Bowman TS, Gaziano JM, Buring JE, et al. A prospective study of cigarette smoking and risk of incident hypertension in women. J Am Coll Cardiol. 2007;50(21):2085–92.CrossRefPubMed
31.
Knorr Held L, Best NG. A shared component model for detecting joint and selective clustering of two diseases. J R Stat Soc Ser A (Stat Soc). 2001;164(1):73–85.CrossRef
32.
33.
Schur N, Gosoniu L, Raso G, et al. Modelling the geographical distribution of co-infection risk from single-disease surveys. Stat Med. 2011;30(14):1761–76.CrossRefPubMed
34.
Held L, Graziano G, Frank C, et al. Joint spatial analysis of gastrointestinal infectious diseases. Stat Methods Med Res. 2006;15(5):465–80.CrossRefPubMed
35.
36.
Kazembe LN, Muula AS, Simoonga C. Joint spatial modelling of common morbidities of childhood fever and diarrhoea in Malawi. Health Place. 2009;15(1):165–72.CrossRefPubMed
37.
Earnest A, Beard JR, Morgan G, et al. Small area estimation of sparse disease counts using shared component models-application to birth defect registry data in New South Wales. Australia Health Place. 2010;16(4):684–93.CrossRefPubMed
38.
Ibáñez-Beroiz B, Librero-López J, Peiró-Moreno S, et al. Shared component modelling as an alternative to assess geographical variations in medical practice: Gender inequalities in hospital admissions for chronic diseases. BMC Med Res Methodol. 2011;11(1):172–81.CrossRefPubMedPubMedCentral
39.
Strong M, Pearson T, Macnab YC, et al. Mapping gender variation in the spatial pattern of alcohol-related mortality: A Bayesian analysis using data from South Yorkshire, United Kingdom. Spat Spatiotemporal Epidemiol. 2012;3(2):141–49.CrossRefPubMed
40.
41.
Committee on Aging. Zhejiang Elderly Population and an Aging Career Statistical Bulletin (2014); 2015.
42.
Truelsen T, Begg S, Mathers C. The global burden of cerebrovascular Disease (Global Burden of Disease 2000). 2000.
43.
44.
Coorperative Meta-analysis Group of China Obesity Task Force. Predictive values of body mass index and waist circumference to risk factors of related disease in Chinese adult population. Chin J Epidemiol. 2002;23(1):5–10.
45.
Ware LJ, Rennie KL, Kruger HS, et al. Evaluation of waist-to-height ratio to predict 5 year cardiometabolic risk in sub-Saharan African adults. Nutr Metab Cardiovasc Dis. 2014;24(08):900–07.CrossRefPubMed
46.
Li W, Chen I, Chang Y, et al. Waist-to-height ratio, waist circumference, and body mass index as indices of cardiometabolic risk among 36,642 Taiwanese adults. Eur J Nutr. 2013;52(1):57–65.CrossRefPubMed
47.
Besag J, York J, Mollié A. Bayesian image restoration, with two applications in spatial statistics. Ann Inst Stat Math. 1991;43(1):1–20.CrossRef
48.
Mollié A. Bayesian mapping of disease. Markov chain Monte Carlo in practice. Berlin: Springer; 1996. p. 359–79.
49.
Brooks SP, Gelman A. General methods for monitoring convergence of iterative simulations. J Comput Graph Stat. 1998;7(4):434–55.
50.
Spiegelhalter DJ, Best NG, Carlin BP, et al. Bayesian measures of model complexity and fit. J R Stat Soc Series B (Stat Methodol). 2002;64(4):583–639.CrossRef
51.
Onicescu G, Hill EG, Lawson AB, et al. Joint disease mapping of cervical and maleoropharyngeal cancer incidence in blacks and whites in South Carolina. Spat Spatiotemporal Epidemiol. 2010;1:133–41.CrossRefPubMedPubMedCentral
52.
Xiao -zhen L, Huang Y-b, Zhan S-y. The predictive value of waist -height ratio to discriminate adult hypertension: A Meta-analysis. Chin J Prev Contr Chron Dis. 2009;17(3):254–57.
53.
Luoto R, Sharrett AR, Schreiner P, et al. Blood pressure and menopausal transition: the Atherosclerosis Risk in Communities study (1987-95). J Hypertens. 2000;18(1):27–33.CrossRefPubMed
Metadata
Title
Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China
Authors
Li Xu
Dejian Lai
Ya Fang
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2016
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-016-3121-y

Other articles of this Issue 1/2016

BMC Public Health 1/2016 Go to the issue

Research article

Prevalence, correlates and patterns of waterpipe smoking among secondary school students in southeast London: a cross-sectional study

Research article

Can socio-economic differences explain low expectation of health services among HIV patients compared to non-HIV counterparts?

Research article

An analysis of three levels of scaled-up coverage for 28 interventions to avert stillbirths and maternal, newborn and child mortality in 27 countries in Latin America and the Caribbean with the Lives Saved Tool (LiST)

Research article

Psychosocial determinants of parental human papillomavirus (HPV) vaccine decision-making for sons: Methodological challenges and initial results of a pan-Canadian longitudinal study

Research article

Thai district Leaders’ perceptions of managing the direct observation treatment program in Trang Province, Thailand

Research article

Poor awareness of syphilis prevention and treatment knowledge among six different populations in south China