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Prevalence of cardiovascular risk factors in middle-aged Lithuanian women in different body mass index and waist circumference groups

Published:December 16, 2022DOI:https://doi.org/10.1016/j.pcd.2022.12.003

      Highlights

      • Dyslipidaemia was the most common risk factor in middle-aged Lithuanian women.
      • Almost all risk factors are more prevalent in those with higher BMI and WC.
      • Smoking is more frequent in low weight BMI and normal WC groups.
      • There is a stronger association between WC and an adverse metabolic profile.

      Abstract

      Background and aims

      The aim of this study was to evaluate the prevalence of cardiovascular risk factors in middle-aged Lithuanian women in different body mass index and waist circumference groups.

      Methods and results

      Data selected from the Lithuanian High Cardiovascular Risk (LitHiR) primary prevention program between 2009 and 2016. This community-based cross-sectional study comprised 53,961 women aged 50–64 years old. We compared the prevalence of arterial hypertension, dyslipidaemia, diabetes mellitus, smoking, and metabolic syndrome in different body mass index (BMI) and waist circumference (WC) groups. The most prevalent cardiometabolic risk factor was dyslipidaemia (91.71%, n = 49,488). The prevalence of arterial hypertension, dyslipidaemia, diabetes mellitus, and metabolic syndrome was greater in those with higher-than-normal BMI and WC. Smoking was the most prevalent in women with low BMI and normal WC (24.00% and 13.17% respectively).

      Conclusion

      The analysis showed that all risk factors, except smoking, were significantly more prevalent in women with higher-than-normal BMI and with increased WC or abdominal obesity. The prevalence of dyslipidaemia was surprisingly high in all BMI and WC groups. Obesity measured by WC was more strongly associated with an adverse metabolic profile.

      Abbreviations:

      BMI (body mass index), WC (waist circumference), DM (diabetes mellitus), MetS (metabolic syndrome), CVD (cardiovascular disease), WHO (World Health Organisation), SBP (systolic blood pressure), DBP (diastolic blood pressure), HR (heart rate), TC (Total cholesterol), LDL-C (low density lipoprotein cholesterol), HDL-C (high density lipoprotein cholesterol), SCORE (systemic coronary risk evaluation index)

      Keywords

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      References

      1. World Health Organization. Obesity and overweight. 〈Https://WwwWhoInt/News-Room/Fact-Sheets/Detail/Obesity-and-Overweight〉 n.d.

        • Meldrum D.R.
        • Morris M.A.
        • Gambone J.C.
        Obesity pandemic: causes, consequences, and solutions—but do we have the will.
        Fertil. Steril. 2017; 107: 833-839https://doi.org/10.1016/j.fertnstert.2017.02.104
      2. WHO. Obesity and overweight. Fact sheet no. 311. 〈Http://WwwWhoInt/Mediacentre/Factsheets/Fs311/En/Stand〉 2015;13 2015.

        • Hruby A.
        • Hu F.B.
        The epidemiology of obesity: a big picture.
        Pharmacoeconomics. 2015; 33: 673-689https://doi.org/10.1007/s40273-014-0243-x
        • Manrique-Acevedo C.
        • Chinnakotla B.
        • Padilla J.
        • Martinez-Lemus L.A.
        • Gozal D.
        Obesity and cardiovascular disease in women.
        Int. J. Obes. 2020; 44: 1210-1226https://doi.org/10.1038/s41366-020-0548-0
        • Wilson P.W.F.
        • D’Agostino R.B.
        • Sullivan L.
        • Parise H.
        • Kannel W.B.
        Overweight and obesity as determinants of cardiovascular risk.
        Arch. Intern Med. 2002; 162: 1867https://doi.org/10.1001/archinte.162.16.1867
        • Garcia M.
        • Mulvagh S.L.
        • Bairey Merz C.N.
        • Buring J.E.
        • Manson J.E.
        Cardiovascular disease in women.
        Circ. Res. 2016; 118: 1273-1293https://doi.org/10.1161/CIRCRESAHA.116.307547
        • Mensah G.A.
        • Wei G.S.
        • Sorlie P.D.
        • Fine L.J.
        • Rosenberg Y.
        • Kaufmann P.G.
        • et al.
        Decline in cardiovascular mortality.
        Circ. Res. 2017; 120: 366-380https://doi.org/10.1161/CIRCRESAHA.116.309115
        • Schenck-Gustafsson K.
        Risk factors for cardiovascular disease in women.
        Maturitas. 2009; 63: 186-190https://doi.org/10.1016/j.maturitas.2009.02.014
        • Yumuk V.
        • Tsigos C.
        • Fried M.
        • Schindler K.
        • Busetto L.
        • Micic D.
        • et al.
        European guidelines for obesity management in adults.
        Obes. Facts. 2015; 8: 402-424https://doi.org/10.1159/000442721
        • Chen G.-C.
        • Arthur R.
        • Iyengar N.M.
        • Kamensky V.
        • Xue X.
        • Wassertheil-Smoller S.
        • et al.
        Association between regional body fat and cardiovascular disease risk among postmenopausal women with normal body mass index.
        Eur. Heart J. 2019; 40: 2849-2855https://doi.org/10.1093/eurheartj/ehz391
        • Hothorn T.
        • Hornik K.
        • Zeileis A.
        Unbiased recursive partitioning: a conditional inference framework.
        J. Comput. Graph. Stat. 2006; 15: 651-674https://doi.org/10.1198/106186006X133933
        • Hothorn T.
        • Zeileis A.
        partykit: a modular toolkit for recursive partytioning in R.
        J. Mach. Learn. Res. 2015; 16: 3905-3909
      3. Borkovec M., Madin N. ggparty: “ggplot” Visualizations for the “partykit” Package 2019.

        • Sangrós F.J.
        • Torrecilla J.
        • Giráldez-García C.
        • Carrillo L.
        • Mancera J.
        • Mur T.
        • et al.
        Association of general and abdominal obesity with hypertension, dyslipidemia and prediabetes in the PREDAPS study.
        Rev. Esp. De. Cardiol. (Engl. Ed.). 2018; 71: 170-177https://doi.org/10.1016/j.rec.2017.04.035
        • Obsa M.S.
        • Ataro G.
        • Awoke N.
        • Jemal B.
        • Tilahun T.
        • Ayalew N.
        • et al.
        Determinants of dyslipidemia in Africa: a systematic review and meta-analysis.
        Front Cardiovasc Med. 2022; : 8https://doi.org/10.3389/fcvm.2021.778891
        • Nahar N.
        • Dubey S.S.
        • Joshi A.
        • Phadnis S.
        • Sharma V.K.
        Association of anthropometric indices of obesity with diabetes, hypertension and dyslipidemia: a study from Central India.
        Indian J. Med. Spec. 2012; : 3
        • Paccaud F.
        • Schlüter-Fasmeyer V.
        • Wietlisbach V.
        • Bovet P.
        Dyslipidemia and abdominal obesity.
        J. Clin. Epidemiol. 2000; 53: 393-400https://doi.org/10.1016/S0895-4356(99)00184-5
        • Nguyen N.T.
        • Magno C.P.
        • Lane K.T.
        • Hinojosa M.W.
        • Lane J.S.
        Association of hypertension, diabetes, dyslipidemia, and metabolic syndrome with obesity: findings from the national health and nutrition examination survey, 1999 to 2004.
        J. Am. Coll. Surg. 2008; 207: 928-934https://doi.org/10.1016/j.jamcollsurg.2008.08.022
      4. Ala Alwan T., Bettcher D., Branca F., et al. Global status report on noncommunicable diseases 2010. World Health Organization 2011.

        • Guh D.P.
        • Zhang W.
        • Bansback N.
        • Amarsi Z.
        • Birmingham C.L.
        • Anis A.H.
        The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis.
        BMC Public Health. 2009; 9: 88https://doi.org/10.1186/1471-2458-9-88
        • Abdullah A.
        • Peeters A.
        • de Courten M.
        • Stoelwinder J.
        The magnitude of association between overweight and obesity and the risk of diabetes: A meta-analysis of prospective cohort studies.
        Diabetes Res Clin. Pr. 2010; 89: 309-319https://doi.org/10.1016/j.diabres.2010.04.012
        • Kotsis V.
        • Jordan J.
        • Micic D.
        • Finer N.
        • Leitner D.R.
        • Toplak H.
        • et al.
        Obesity and cardiovascular risk.
        J. Hypertens. 2018; 36: 1427-1440https://doi.org/10.1097/HJH.0000000000001730
        • Bell J.A.
        • Kivimaki M.
        • Hamer M.
        Metabolically healthy obesity and risk of incident type 2 diabetes: a meta‐analysis of prospective cohort studies.
        Obes. Rev. 2014; 15: 504-515https://doi.org/10.1111/obr.12157
        • Reilly J.J.
        • Kelly J.
        Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review.
        Int J. Obes. (Lond.). 2011; 35: 891-898https://doi.org/10.1038/ijo.2010.222
        • Carreras-Torres R.
        • Johansson M.
        • Haycock P.C.
        • Relton C.L.
        • Davey Smith G.
        • Brennan P.
        • et al.
        Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank.
        BMJ. 2018; : k1767https://doi.org/10.1136/bmj.k1767
        • Chatkin R.
        • Mottin C.C.
        • Chatkin J.M.
        Smoking among morbidly obese patients.
        BMC Pulm. Med. 2010; 10: 61https://doi.org/10.1186/1471-2466-10-61
        • Tuovinen E.-L.
        • Saarni S.E.
        • Männistö S.
        • Borodulin K.
        • Patja K.
        • Kinnunen T.H.
        • et al.
        Smoking status and abdominal obesity among normal- and overweight/obese adults: population-based FINRISK study.
        Prev. Med Rep. 2016; 4: 324-330https://doi.org/10.1016/j.pmedr.2016.07.003
        • Park K.
        • Lim S.
        • Park Y.
        • Ju W.
        • Shin Y.
        • Yeom H.
        Cardiovascular disease risk factors and obesity levels in Korean adults: results from the Korea national health and nutrition examination survey, 2007–2015.
        Osong Public Health Res Perspect. 2018; 9: 150-159https://doi.org/10.24171/j.phrp.2018.9.4.03
        • Li Y.
        • Zhang T.
        • Han T.
        • Li S.
        • Bazzano L.
        • He J.
        • et al.
        Impact of cigarette smoking on the relationship between body mass index and insulin: Longitudinal observation from the bogalusa heart study.
        Diabetes Obes. Metab. 2018; 20: 1578-1584https://doi.org/10.1111/dom.13259
        • Lv J.
        • Chen W.
        • Sun D.
        • Li S.
        • Millwood I.Y.
        • Smith M.
        • et al.
        Gender-specific association between tobacco smoking and central obesity among 0.5 million Chinese people: the china kadoorie biobank study.
        PLoS One. 2015; 10e0124586https://doi.org/10.1371/journal.pone.0124586
        • Jee S.H.
        • Lee S.Y.
        • Nam C.M.
        • Kim S.Y.
        • Kim M.T.
        Effect of smoking on the paradox of high waist-to-hip ratio and low body mass index.
        Obes. Res. 2002; 10: 891-895https://doi.org/10.1038/oby.2002.122
        • Hu T.
        • Yang Z.
        • Li M.D.
        Pharmacological effects and regulatory mechanisms of tobacco smoking effects on food intake and weight control.
        J. Neuroimmune Pharmacol. 2018; 13: 453-466https://doi.org/10.1007/s11481-018-9800-y
        • Folsom A.R.
        • Kushi L.H.
        • Anderson K.E.
        • Mink P.J.
        • Olson J.E.
        • Hong C.-P.
        • et al.
        Associations of general and abdominal obesity with multiple health outcomes in older women.
        Arch. Intern Med. 2000; 160: 2117https://doi.org/10.1001/archinte.160.14.2117
        • Lovejoy J.C.
        • de la Bretonne J.A.
        • Klemperer M.
        • Tulley R.
        Abdominal fat distribution and metabolic risk factors: effects of race.
        Metabolism. 1996; 45: 1119-1124https://doi.org/10.1016/S0026-0495(96)90011-6
        • Vazquez G.
        • Duval S.
        • Jacobs D.R.
        • Silventoinen K.
        Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis.
        Epidemiol. Rev. 2007; 29: 115-128https://doi.org/10.1093/epirev/mxm008
        • Ford E.S.
        • Mokdad A.H.
        • Giles W.H.
        Trends in waist circumference among U.S. adults.
        Obes. Res. 2003; 11: 1223-1231https://doi.org/10.1038/oby.2003.168
        • Ostchega Y.
        • Hughes J.P.
        • Terry A.
        • Fakhouri T.H.I.
        • Miller I.
        Abdominal obesity, body mass index, and hypertension in US adults: NHANES 2007–2010.
        Am. J. Hypertens. 2012; https://doi.org/10.1038/ajh.2012.120