Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-26T05:16:10.143Z Has data issue: false hasContentIssue false

Determinants of hypertension in Nepal using odds ratios and prevalence ratios: an analysis of the Demographic and Health Survey 2016

Published online by Cambridge University Press:  02 July 2020

Rajat Das Gupta*
Affiliation:
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, USA Center for Non-Communicable Diseases and Nutrition, BRAC James P. Grant School of Public Health, BRAC University, Dhaka, Bangladesh Center for Science of Implementation & Scale Up, BRAC James P. Grant School of Public Health, BRAC University, Dhaka, Bangladesh
Animesh Talukder
Affiliation:
Center for Non-Communicable Diseases and Nutrition, BRAC James P. Grant School of Public Health, BRAC University, Dhaka, Bangladesh
Shams Shabab Haider
Affiliation:
Center for Science of Implementation & Scale Up, BRAC James P. Grant School of Public Health, BRAC University, Dhaka, Bangladesh
Gulam Muhammed Al Kibria
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
*
*Corresponding author. Email: [email protected]

Abstract

This cross-sectional study investigated the factors associated with hypertension among Nepalese adults aged 18 years or above using data from the Nepal Demographic and Health Survey 2016. Prevalence ratios (PRs) and odds ratios (ORs) were obtained using log-binomial regression and logistic regression, respectively. Initially, unadjusted PRs and ORs were obtained. The variables that yielded a significance level below 0.2 in unadjusted analyses were included in the multivariable analysis. The overall prevalence of hypertension among the 13,393 participants (58% male and 61.2% urban) was 21.1% (n = 2827). In the adjusted analysis, those aged 30–49 years (adjusted PR [APR]: 3.1, 95% Confidence Interval (CI): 2.6, 3.7; adjusted OR [AOR]: 3.6, 95% CI: 2.9, 4.5), 50–69 years (APR: 5.3, 95% CI: 4.4, 6.6; AOR: 8.2, 95% CI: 6.4, 10.4) and ≥70 years (APR: 7.3, 95% CI: 5.8, 9.2; AOR: 13.6, 95% CI: 10.1, 18.3) were more likely to be hypertensive than younger participants aged 18–29 years. Males (APR: 1.3, 95% CI: 1.2, 1.4; AOR: 1.5, 95% CI: 1.3, 1.7), overweight/obese participants (APR: 1.8, 95% CI: 1.7, 2.0; AOR: 2.4, 95% CI: 2.2, 2.8) and those in the richest wealth quintile (APR: 1.3, 95% CI: 1.1, 1.5; AOR: 1.5, 95% CI: 1.1, 1.9) had higher prevalences and odds of hypertension than their female, normal weight/underweight and poorest wealth quintile counterparts, respectively. Those residing in Province 4 (APR: 1.2, 95% CI: 1.0, 1.5; AOR: 1.4, 95% CI: 1.1, 1.8) and Province 5 (APR: 1.2, 95% CI: 1.0, 1.4; AOR: 1.3, 95% CI: 1.1, 1.7) were more likely to be hypertensive than those residing in Province 1. The point estimate was inflated more in magnitude by ORs than by PRs, but the direction of association remained the same. Public health programmes in Nepal aimed at preventing hypertension should raise awareness among the elderly, males, individuals in the richest wealth quintile and the residents of Provinces 4 and 5.

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

#

These authors contributed equally to this work.

References

Anchala, R, Kannuri, NK, Pant, H, Khan, H, Franco, OH, Di Angelantonio, E and Prabhakaran, D (2014) Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. Journal of Hypertension 32(6), 11701177.CrossRefGoogle ScholarPubMed
Ashraf, MS and Vongpatanasin, W (2006) Estrogen and hypertension. Current Hypertension Reports 8(5), 368376.CrossRefGoogle ScholarPubMed
Busingye, D, Arabshahi, S, Subasinghe, AK, Evans, RG, Riddell, MA and Thrift, AG (2014) Do the socioeconomic and hypertension gradients in rural populations of low- and middle-income countries differ by geographical region? A systematic review and meta-analysis. International Journal of Epidemiology 43(5), 15631577.CrossRefGoogle ScholarPubMed
Chobanian, AV, Bakris, GL, Black, HR, Cushman, WC, Green, LA, Izzo, JL et al. (2003) The seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 Report. JAMA 289(19), 25602572.CrossRefGoogle ScholarPubMed
Chow, CK, Teo, KK, Rangarajan, S, Islam, S, Gupta, R, Avezum, A et al. (2013) Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA 310(9), 959968.CrossRefGoogle Scholar
Danaei, G, Finucane, MM, Lin, JK, Singh, GM, Paciorek, CJ, Cowan, MJ et al. (2011) National, regional, and global trends in systolic blood pressure since 1980: systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5.4 million participants. The Lancet 377(9765), 568577.CrossRefGoogle ScholarPubMed
Das Gupta, R, Bin Zaman, S, Wagle, K, Crispen, R, Hashan, MR and Al Kibria, GM (2019a) Factors associated with hypertension among adults in Nepal as per the Joint National Committee 7 and 2017 American College of Cardiology/American Heart Association hypertension guidelines: a cross-sectional analysis of the Demographic and Health Survey 2016. BMJ Open 9(8), e030206.CrossRefGoogle Scholar
Das Gupta, R, Haider, SS, Hashan, MR, Rahman, MA and Sarker, M (2019b) Association between height and hypertension in the adult Nepalese population: findings from a nationally representative survey. Health Science Reports 2(12), e141.CrossRefGoogle ScholarPubMed
Devi, P, Rao, M, Sigamani, A, Faruqui, A, Jose, M, Gupta, R et al. (2013) Prevalence, risk factors and awareness of hypertension in India: a systematic review. Journal of Human Hypertension 27(5), 281287.CrossRefGoogle ScholarPubMed
Feeney, G, Thapa, S and Sharma, KR (2001) One and a half centuries of demographic transition in Nepal. Journal of Health, Population, and Nutrition 19(3), 160166.Google Scholar
Fleg, JL and Strait, J (2012) Age-associated changes in cardiovascular structure and function: a fertile milieu for future disease. Heart Failure Reviews, 17(4–5), 545554.CrossRefGoogle ScholarPubMed
GBD 2017 Causes of Death Collaborators (2018) Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet 392(10159), 17361788.CrossRefGoogle Scholar
Gheorghe, A, Griffiths, U, Murphy, A, Legido-Quigley, H, Lamptey, P and Perel, P (2018) The economic burden of cardiovascular disease and hypertension in low-and middle-income countries: a systematic review. BMC Public Health 18(1), 975.CrossRefGoogle ScholarPubMed
Ghosh, S, Mukhopadhyay, S and Barik, A (2016) Sex differences in the risk profile of hypertension: a cross-sectional study. BMJ Open 6(7), e010085.CrossRefGoogle ScholarPubMed
Gillis, EE and Sullivan, JC (2016) Sex differences in hypertension: recent advances. Hypertension 68(6), 13221327.CrossRefGoogle ScholarPubMed
Harshfield, E, Chowdhury, R, Harhay, MN, Bergquist, H and Harhay, MO (2015) Association of hypertension and hyperglycaemia with socioeconomic contexts in resource-poor settings: the Bangladesh Demographic and Health Survey. International Journal of Epidemiology 44(5), 16251636.CrossRefGoogle ScholarPubMed
Hasan, M, Sutradhar, I, Akter, T, Das Gupta, R, Joshi, H, Haider, MR and Sarker, M (2018) Prevalence and determinants of hypertension among adult population in Nepal: data from Nepal Demographic and Health Survey 2016. PloS One 13(5), e0198028.CrossRefGoogle ScholarPubMed
Huang, Y, Guo, P, Karmacharya, BM, Seeruttun, SR, Xu, DR and Hao, Y (2019) Prevalence of hypertension and prehypertension in Nepal: a systematic review and meta-analysis. Global Health Research and Policy, 4(11), doi: 10.1186/s41256-019-0102-6 CrossRefGoogle ScholarPubMed
Kibria, GMA, Swasey, K, Sharmeen, A, Sakib, MN and Burrowes, V (2018) Prevalence and associated factors of pre-hypertension and hypertension in Nepal: analysis of the Nepal Demographic and Health Survey 2016. Health Science Reports 1(10), e83.CrossRefGoogle ScholarPubMed
Kibria, GMA (2019) Prevalence and factors affecting underweight, overweight and obesity using Asian and World Health Organization cutoffs among adults in Nepal: analysis of the Demographic and Health Survey 2016. Obesity Research & Clinical Practice 13(2), 129136.CrossRefGoogle ScholarPubMed
Kovesdy, CP, Furth, SL and Zoccali, C (2017) Obesity and kidney disease: hidden consequences of the epidemic. Pediatric Nephrology 32(4), 537545.CrossRefGoogle ScholarPubMed
Lawes, CM, Vander Hoorn, S and Rodgers, A (2008) Global burden of blood-pressure-related disease, 2001. Lancet 371(9623), 15131518.CrossRefGoogle ScholarPubMed
Lee, SH, Kim, YS, Sunwoo, S and Huh, BY (2005) A retrospective cohort study on obesity and hypertension risk among Korean adults. Journal of Korean Medical Science 20(2), 188195.CrossRefGoogle ScholarPubMed
Lim, SS, Vos, T, Flaxman, AD, Danaei, G, Shibuya, K and Adair-Rohani, H et al. (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380(9859), 22242260.CrossRefGoogle ScholarPubMed
Maldonado, G and Greenland, S (1993) Simulation study of confounder-selection strategies. American Journal of Epidemiology 138(11), 923936.CrossRefGoogle ScholarPubMed
Meshram, II, Vishnu Vardhana Rao, M, Sudershan Rao, V, Laxmaiah, A and Polasa, K (2016) Regional variation in the prevalence of overweight/obesity, hypertension and diabetes and their correlates among the adult rural population in India. British Journal of Nutrition 115(7), 12651272.CrossRefGoogle ScholarPubMed
Ministry of Health Nepal, New ERA Nepal, Nepal Health Sector Support Program (NHSSP) and ICF (2017) Nepal Health Facility Survey 2015. Ministry of Health, Kathmandu, Nepal. URL: https://dhsprogram.com/pubs/pdf/SPA24/SPA24.pdf (accessed 2nd February 2020).Google Scholar
Mishra, SR, Neupane, D, Bhandari, PM, Khanal, V and Kallestrup, P (2015) Burgeoning burden of non-communicable diseases in Nepal: a scoping review. Globalization and Health 11(32), doi: 10.1186/s12992-015-0119-7 CrossRefGoogle ScholarPubMed
Nawal, D and Goli, S (2013a) Birth preparedness and its effect on place of delivery and post-natal check-ups in Nepal. PloS One 8(5), e60957.CrossRefGoogle ScholarPubMed
Nawal, D and Goli, S (2013b) Inequalities in utilization of maternal health care services in Nepal. Ethnicity and Inequalities in Health and Social Care 6(1), 315.CrossRefGoogle Scholar
Neupane, D, Shrestha, A, Mishra, SR, Bloch, J, Christensen, B, McLachlan, CS et al. (2017) Awareness, prevalence, treatment, and control of hypertension in Western Nepal. American Journal of Hypertension 30(9), 907913.CrossRefGoogle ScholarPubMed
Poulter, NR, Prabhakaran, D and Caulfield, M (2015) Hypertension. Lancet 386(9995), 801812.CrossRefGoogle ScholarPubMed
Ralston, SH, Penman, ID, Strachan, MW and Hobson, R (2018) Davidson’s Principles and Practice of Medicine. 23rd Edition. Elsevier Health Sciences.Google Scholar
Reddy, KS, Naik, N and Prabhakaran, D (2006) Hypertension in the developing world: a consequence of progress. Current Cardiology Reports 8(6), 399404.CrossRefGoogle ScholarPubMed
Sandberg, K and Ji, H (2012) Sex differences in primary hypertension. Biology of Sex Differences 3(1), 7.CrossRefGoogle ScholarPubMed
Sarki, AM, Nduka, CU, Stranges, S, Kandala, NB and Uthman, OA (2015) Prevalence of hypertension in low- and middle-income countries: a systematic review and meta-analysis. Medicine 94(50), e1959.CrossRefGoogle ScholarPubMed
Subedi, YP, Marais, D and Newlands, D (2017) Where is Nepal in the nutrition transition? Asia Pacific Journal of Clinical Nutrition 26(2), 358367.Google ScholarPubMed
Swasey, KK, Gupta, RD, Nayeem, J & Kibria, GMA (2019) Determinants of diabetes in Bangladesh using two approaches: an analysis of the Demographic and Health Survey 2011. Journal of Biosocial Science, doi: 10.1017/S002193201900066X Google ScholarPubMed
Tamhane, AR, Westfall, AO, Burkholder, GA and Cutter, GR (2017) Prevalence odds ratio versus prevalence ratio: choice comes with consequences. Statistics in Medicine 36(23), 3760.CrossRefGoogle ScholarPubMed
WHO Expert Consultation (2004) Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. The Lancet 363(9403), 157163.CrossRefGoogle Scholar
Zhou, D, Xi, B, Zhao, M, Wang, L and Veeranki, SP (2018) Uncontrolled hypertension increases risk of all-cause and cardiovascular disease mortality in US adults: the NHANES III Linked Mortality Study. Scientific Reports 8(1), 9418.CrossRefGoogle ScholarPubMed
Zocchetti, C, Consonni, D and Bertazzi, PA (1997) Relationship between prevalence rate ratios and odds ratios in cross-sectional studies. International Journal of Epidemiology 26(1), 220223.CrossRefGoogle ScholarPubMed