Reversal for metabolic syndrome criteria following the CHANGE program: What are the driving forces? Results from an intervention community-based study

Hanan E. Badr; Travis Saunders; Omar Bayoumy; Angelie Carter; Laura Reyes Castillo; Marilyn Barrett; Hanan E. Badr; Travis Saunders; Omar Bayoumy; Angelie Carter; Laura Reyes Castillo; Marilyn Barrett

doi:10.3934/publichealth.2025011

AIMS Public Health

2025, Volume 12, Issue 1: 162-184. doi: 10.3934/publichealth.2025011

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Research article

Reversal for metabolic syndrome criteria following the CHANGE program: What are the driving forces? Results from an intervention community-based study

1.
Department of Applied Human Sciences, Faculty of Science, University of Prince Edward Island, Charlottetown, Canada
2.
Health and Wellness Centre, University of Prince Edward Island, Charlottetown, Canada

Received: 18 June 2024 Revised: 21 August 2024 Accepted: 02 January 2025 Published: 21 January 2025

Objective
To examine the impact of the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) program on the reversal of one or more metabolic syndrome (MetS) criteria among community members with MetS and define the significant predictors of upholding individual MetS criterion from 2020 to 2023.
Methods
The program enrolled 278 community members with/or at risk of MetS. Participants followed regular physical activity and a Mediterranean diet for 12 months with the assistance of a registered dietitian and a kinesiologist. A licensed practical nurse and/or registered nurse measured participants' weight, height, waist circumference, and blood pressure and withdrew blood samples for laboratory investigations. Physical activity, physical fitness, Mediterranean diet score (MDS), anthropometric measurements, and laboratory investigations were assessed at the baseline and every three months. Descriptive statistics were calculated, and binary logistic regression analysis was performed to define the significant predictors of upholding each criterion of the MetS.
Results
Participants' mean age was 60.5 ± 11.7 years, and 74.8% were females. Participants with MetS decreased by 5.04% by the end of the program. The percentage of participants with each MetS criterion showed a significant decrease at the end of the study, except for low HDL, which remained with no change. Moreover, the mean of physical activity, physical fitness tests, and MDS scores showed a significant increase after the 12 months of study. Compared to baseline, daily sedentary and screen times showed a significant decrease at the end of the program (8.6 vs. 7.2 and 3.2 vs. 2.6 hours, respectively). Logistic regression analysis revealed that age, female gender, low educational attainment, physical activity, physical fitness, and screen time were significant predictors for upholding one or more MetS criteria.
Conclusion
MetS criteria can be reversed following the CHANGE program. Sociodemographic and lifestyle features are significant predictors for upholding MetS criteria. The program is cost-effective considering its low cost and could lead to significant savings on healthcare costs. Further studies among different communities are recommended to confirm the generalizability of the results.
- metabolic syndrome,
- hypertension,
- HbA1c,
- triglycerides,
- HDL,
- waist circumference,
- abdominal obesity,
- diabetes mellitus
Citation: Hanan E. Badr, Travis Saunders, Omar Bayoumy, Angelie Carter, Laura Reyes Castillo, Marilyn Barrett. Reversal for metabolic syndrome criteria following the CHANGE program: What are the driving forces? Results from an intervention community-based study[J]. AIMS Public Health, 2025, 12(1): 162-184. doi: 10.3934/publichealth.2025011

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Abstract

Objective

To examine the impact of the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) program on the reversal of one or more metabolic syndrome (MetS) criteria among community members with MetS and define the significant predictors of upholding individual MetS criterion from 2020 to 2023.

Methods

The program enrolled 278 community members with/or at risk of MetS. Participants followed regular physical activity and a Mediterranean diet for 12 months with the assistance of a registered dietitian and a kinesiologist. A licensed practical nurse and/or registered nurse measured participants' weight, height, waist circumference, and blood pressure and withdrew blood samples for laboratory investigations. Physical activity, physical fitness, Mediterranean diet score (MDS), anthropometric measurements, and laboratory investigations were assessed at the baseline and every three months. Descriptive statistics were calculated, and binary logistic regression analysis was performed to define the significant predictors of upholding each criterion of the MetS.

Results

Participants' mean age was 60.5 ± 11.7 years, and 74.8% were females. Participants with MetS decreased by 5.04% by the end of the program. The percentage of participants with each MetS criterion showed a significant decrease at the end of the study, except for low HDL, which remained with no change. Moreover, the mean of physical activity, physical fitness tests, and MDS scores showed a significant increase after the 12 months of study. Compared to baseline, daily sedentary and screen times showed a significant decrease at the end of the program (8.6 vs. 7.2 and 3.2 vs. 2.6 hours, respectively). Logistic regression analysis revealed that age, female gender, low educational attainment, physical activity, physical fitness, and screen time were significant predictors for upholding one or more MetS criteria.

Conclusion

MetS criteria can be reversed following the CHANGE program. Sociodemographic and lifestyle features are significant predictors for upholding MetS criteria. The program is cost-effective considering its low cost and could lead to significant savings on healthcare costs. Further studies among different communities are recommended to confirm the generalizability of the results.

Acknowledgments

The study fund depended on donations in the first cohort, then on PEI Governmental support in the second and third cohorts.

Authors' contribution

Hanan E. Badr designed the study, analyzed and interpreted the data, and drafted the study discussion. Travis Saunders drafted the introduction, helped in the discussion and revised the whole manuscript. Omar Bayoumy tabulated the data, conducted literature review, prepared the reference list, and revised the manuscript. Angelie Carter and Laura Reyes Castillo interviewed the participants, conducted the study assessments for participants, and delivered the data. Marilyn Barrett managed the ethics approval of the study and revised the manuscript.

Conflict of interest

All authors declare no conflicts of interest in this paper.

References

[1]	Riediger ND, Clara I (2011) Prevalence of metabolic syndrome in the Canadian adult population. CMAJ 183: E1127-E1134. https://doi.org/10.1503/cmaj.110070
[2]	Galassi A, Reynolds K, He J (2006) Metabolic syndrome and risk of cardiovascular disease: A meta-analysis. Am J Med 119: 812-819. https://doi.org/10.1016/j.amjmed.2006.02.031
[3]	Aschner P (2010) Metabolic syndrome as a risk factor for diabetes. Expert Rev Cardiovasc Ther 8: 407-412. https://doi.org/10.1586/erc.10.13
[4]	Janiszewski PM, Saunders TJ, Ross R (2008) Themed review: Lifestyle treatment of the metabolic syndrome. Am J Lifestyle Med 2: 99-108. https://doi.org/10.1177/1559827607311426
[5]	Metabolic Syndrome CanadaMetabolic Syndrome (2022). Available from: https://www.metabolicsyndromecanada.ca/
[6]	Yamaoka K, Tango T (2012) Effects of lifestyle modification on metabolic syndrome: A systematic review and meta-analysis. BMC Med 10: 1-10. https://doi.org/10.1186/1741-7015-10-138
[7]	Bassi N, Karagodin I, Wang S, et al. (2014) Lifestyle modification for metabolic syndrome: A systematic review. Am J Med 127: 1242.e1-e10. https://doi.org/10.1016/j.amjmed.2014.06.035
[8]	Sy RG, Llanes EJB, Reganit PFM, et al. (2014) Socio-demographic factors and the prevalence of metabolic syndrome among Filipinos from the LIFECARE cohort. J Atheroscler Thromb 21: S9-S17. https://doi.org/10.5551/jat.21_Sup.1-S9
[9]	Bener A, Mohammad A, Ismail AN, et al. (2010) Gender and agerelated differences in patients with the metabolic syndrome in a highly endogamous population. Bosn J Basic Med Sci 10: 210-217. https://doi.org/10.17305/bjbms.2010.2687
[10]	Badr HE, Saunders T, Carter A, et al. (2022) Impact of lifestyle modification on quality of life in patients with metabolic syndrome: Findings from the CHANGE program intervention study in Prince Edward Island, Canada. Metab Syndr Relat Disord 20: 532-542. https://doi.org/10.1089/met.2022.0056
[11]	PEI Population Report QuarterlyPopulation report, fourth quarter 2023 (2023). Available from: https://www.princeedwardisland.ca/en/information/finance/pei-population-report-quarterlywebsite
[12]	Brun S It's statistically official: Access to health care worse in P.E.I. than in any other province (2024). Available from: https://www.cbc.ca/news/canada/prince-edward-island/pei-health-care-access-lowest-in-canada-1.7089196#:~:text=worse%20in%20P.E.I.-,than%20in%20any%20other%20province,points%20from%20three%20years%20before
[13]	Rikli RE, Jones CJ (2013) Senior fitness test manual. Human kinetics. USA: Science and Education Publishing, Library of Congress Cataloging-in- publication Data.
[14]	Canadian Society for Exercise Physiology (CSEP)CSEP Physical Activity Training for Health (CSEP-PATH) Resource Manual, 3rd ed. eBook (2021). Available from: https://store.csep.ca/collections/csep-path/products/csep-path_resource_manual_third_edition_english
[15]	Rosenberg DE, Norman GJ, Wagner N, et al. (2010) Reliability and validity of the Sedentary Behavior Questionnaire (SBQ) for adults. J Phys Act Health 7: 697-705. https://doi.org/10.1123/jpah.7.6.697
[16]	Estruch R, Ros E, Salas-Salvadó J, et al. (2018) Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts. N Engl J Med 378: e34. https://doi.org/10.1056/NEJMoa1800389
[17]	Godin G (2011) The Godin-Shephard leisure-time physical activity questionnaire. Health Fit J Canada 4: 18-22.
[18]	Morvaridzadeh M, Zoubdane N, Heshmati J, et al. (2024) High-density lipoprotein metabolism and function in cardiovascular diseases: What about aging and diet effects?. Nutrients 16: 653. https://doi.org/10.3390/nu16050653
[19]	Wilkins K, Campbell NR, Joffres MR, et al. (2010) Blood pressure in Canadian adults. Health Rep 21: 37-46.
[20]	Robitaille C, Dai S, Waters C, et al. (2012) Diagnosed hypertension in Canada: Incidence, prevalence and associated mortality. CMAJ 184: E49-E56. https://doi.org/10.1503/cmaj.101863
[21]	Weaver CG, Clement FM, Campbell NR, et al. (2015) Healthcare costs attributable to hypertension: Canadian population-based cohort study. Hypertension 66: 502-508. https://doi.org/10.1161/HYPERTENSIONAHA.115.05702
[22]	Government of Canada, Health CanadaUniversal Access to Diabetes Medications, and Diabetes Device Fund for Devices and Supplies (2024). Available from: https://www.canada.ca/en/health-canada/news/2024/02/universal-access-to-diabetes-medications-and-diabetes-device-fund-for-devices-and-supplies.html
[23]	Ottawa: Diabetes CanadaDiabetes and diabetes-related out-of-pocket costs: 2022 update (2023). Available from: https://www.diabetes.ca/DiabetesCanadaWebsite/media/Advocacy-and-Policy/Advocacy%20Reports/Diabetes-Canada-2022-Out-Of-Pocket-Report-EN-FINAL.pdf
[24]	Anis AH, Zhang W, Bansback N, et al. (2010) Obesity and overweight in Canada: an updated cost-of-illness study. Obes Rev 11: 31-40. https://doi.org/10.1111/j.1467-789X.2009.00579.x
[25]	Holzer M, Trieb M, Konya V, et al. (2013) Aging affects high-density lipoprotein composition and function. Biochim Biophys Acta 1831: 1442-1448. https://doi.org/10.1016/j.bbalip.2013.06.004
[26]	Wilson PW, Abbott RD, Castelli WP (1988) High density lipoprotein cholesterol and mortality. The Framingham Heart Study. Arteriosclerosis 8: 737-741. https://doi.org/10.1161/01.ATV.8.6.737
[27]	Kunnen S, Van Eck M (2012) Lecithin: Cholesterol acyltransferase: Old friend or foe in atherosclerosis?. J Lipid Res 53: 1783-1799. https://doi.org/10.1194/jlr.R024513
[28]	Steenman M, Lande G (2017) Cardiac aging and heart disease in humans. Biophys Rev 9: 131-137. https://doi.org/10.1007/s12551-017-0255-9
[29]	Rodgers JL, Jones J, Bolleddu SI, et al. (2019) Cardiovascular risks associated with gender and aging. J Cardiovasc Dev Dis 6: 19. https://doi.org/10.3390/jcdd6020019
[30]	North BJ, Sinclair DA (2012) The intersection between aging and cardiovascular disease. Circ Res 110: 1097-1108. https://doi.org/10.1161/CIRCRESAHA.111.246876
[31]	Berrougui H, Isabelle M, Cloutier M, et al. (2007) Age-related impairment of HDL-mediated cholesterol efflux. J Lipid Res 48: 328-336. https://doi.org/10.1194/jlr.M600167-JLR200
[32]	Huxley RR, Barzi F, Lam TH, et al. (2011) Isolated low levels of high-density lipoprotein cholesterol are associated with an increased risk of coronary heart disease: An individual participant data meta-analysis of 23 studies in the Asia-Pacific region. Circulation 124: 2056-2064. https://doi.org/10.1161/CIRCULATIONAHA.111.028373
[33]	Song R, Hu M, Qin X, et al. (2023) The roles of lipid metabolism in the pathogenesis of chronic diseases in the elderly. Nutrients 15: 3433. https://doi.org/10.3390/nu15153433
[34]	Alibhai SM, Greenwood C, Payette H (2005) An approach to the management of unintentional weight loss in elderly people. CMAJ 172: 773-780. https://doi.org/10.1503/cmaj.1031527
[35]	Miller SL, Wolfe RR (2008) The danger of weight loss in the elderly. J Nutr Health Aging 12: 487-491. https://doi.org/10.1007/BF02982710
[36]	Parasuaraman G, Ayyasamy L, Aune D, et al. (2023) The association between body mass index, abdominal fatness, and weight change and the risk of adult asthma: A systematic review and meta-analysis of cohort studies. Sci Rep 13: 7745. https://doi.org/10.1038/s41598-023-31373-6
[37]	Darbandi M (2020) Discriminatory capacity of anthropometric indices for cardiovascular disease in adults: A systematic review and meta-analysis. Prev Chronic Dis 17: E131. https://doi.org/10.5888/pcd17.200112
[38]	Langley-Evans SC, Pearce J, Ellis S (2022) Overweight, obesity and excessive weight gain in pregnancy as risk factors for adverse pregnancy outcomes: A narrative review. J Hum Nutr Diet 35: 250-264. https://doi.org/10.1111/jhn.12999
[39]	Eapen DJ, Kalra GL, Rifai L, et al. (2010) Raising HDL cholesterol in women. Int J Women's Health 1: 181-191. https://doi.org/10.2147/IJWH.S5110
[40]	Stevenson JC, Crook D, Godsland IF (1993) Influence of age and menopause on serum lipids and lipoproteins in healthy women. Atherosclerosis 98: 83-90. https://doi.org/10.1016/0021-9150(93)90225-J
[41]	Granfone A, Campos H, McNamara JR, et al. (1992) Effects of estrogen replacement on plasma lipoproteins and apolipoproteins in postmenopausal, dyslipidemic women. Metab Clin Exp 41: 1193-1198. https://doi.org/10.1016/0026-0495(92)90008-X
[42]	Marhoum TA, Abdrabo AA, Lutfi MF (2013) Effects of age and gender on serum lipid profile in over 55 years-old apparently healthy Sudanese individuals. Asian J Biomed Pharm Sci 3: 10.
[43]	Gu T, Zhou W, Sun J, et al. (2018) Gender and age differences in lipid profile among Chinese adults in Nanjing: A retrospective study of over 230,000 individuals from 2009 to 2015. Exp Clin Endocrinol Diabetes 126: 429-436. https://doi.org/10.1055/s-0043-117417
[44]	Brancati FL, Whelton PK, Kuller LH, et al. (1996) Diabetes mellitus, race, and socioeconomic status a population-based study. Ann Epidemiol 6: 67-73. https://doi.org/10.1016/1047-2797(95)00095-X
[45]	Borrell LN, Dallo FJ, White K (2006) Education and diabetes in a racially and ethnically diverse population. Am J Public Health 96: 1637-1642. https://doi.org/10.2105/AJPH.2005.072884
[46]	Link BG, Phelan J (1995) Social conditions as fundamental causes of disease. J Health Soc Behav 1995: 80-94. https://doi.org/10.2307/2626958
[47]	Nowicki GJ, Ślusarska B, Naylor K, et al. (2021) The relationship between the metabolic syndrome and the place of residence in the local community on the example of the janów lubelski district in eastern Poland: A population-based study. Diabetes Metab Syndr Obes 14: 2041-2056. https://doi.org/10.2147/DMSO.S301639
[48]	Bakhetia P, Bains K, Cheema S (2023) Comparison of prevalence of metabolic disorders of urban and rural adults of Punjab, India. Indian J Public Health 67: 520-522. https://doi.org/10.4103/ijph.ijph_1747_22
[49]	Jacobs KA, Krauss RM, Fattor JA, et al. (2006) Endurance training has little effect on active muscle free fatty acid, lipoprotein cholesterol, or triglyceride net balances. Am J Physiol Endocrinol Metab 291: E656-E665. https://doi.org/10.1152/ajpendo.00020.2006
[50]	Gonzales AM, Orlando RA (2007) Role of adipocyte-derived lipoprotein lipase in adipocyte hypertrophy. Nutr Metab 4: 22. https://doi.org/10.1186/1743-7075-4-22
[51]	Crichton GE, Alkerwi A (2015) Physical activity, sedentary behavior time and lipid levels in the observation of cardiovascular risk factors in Luxembourg study. Lipids Health Dis 14: 87. https://doi.org/10.1186/s12944-015-0085-3
[52]	Voss ML, Pope JP, Copeland JL (2020) Reducing sedentary time among older adults in assisted living: Perceptions, barriers, and motivators. Int J Environ Res Public Health 17: 717. https://doi.org/10.3390/ijerph17030717
[53]	Churilla JR, Summerlin M, Richardson MR, et al. (2020) Mean combined relative grip strength and metabolic syndrome: 2011–2014 national health and nutrition examination survey. J Strength Cond Res 34: 995-1000. https://doi.org/10.1519/JSC.0000000000003515
[54]	Shen C, Lu J, Xu Z, et al. (2020) Association between handgrip strength and the risk of new-onset metabolic syndrome: A population-based cohort study. BMJ Open 10: e041384. https://doi.org/10.1136/bmjopen-2020-041384
[55]	Alkahtani SA, Alshammari GM, Alzuwaydi A, et al. (2024) Association between handgrip strength and metabolic syndrome in relation to gender and adiposity among middle aged and older Saudi populations. Aging Male 27: 2325146. https://doi.org/10.1080/13685538.2024.2325146
[56]	Mancia G, Fagard R (2013) New blood pressure control goals, more rational but facilitating therapeutic inertia?. J Hypertens 31: 2463. https://doi.org/10.1097/HJH.0000000000000005
[57]	Yano Y, Inokuchi T, Hoshide S, et al. (2011) Association of poor physical function and cognitive dysfunction with high nocturnal blood pressure level in treated elderly hypertensive patients. Am J Hypertens 24: 285-291. https://doi.org/10.1038/ajh.2010.224
[58]	Ozaldemir I, Iyigun G, Malkoc M (2020) Comparison of processing speed, balance, mobility and fear of falling between hypertensive and normotensive individuals. Braz J Phys Ther 24: 503-511. https://doi.org/10.1016/j.bjpt.2019.09.002
[59]	Xing L, Bao Y, Wang B, et al. (2023) Falls caused by balance disorders in the elderly with multiple systems involved: Pathogenic mechanisms and treatment strategies. Front Neurol 14: 1128092. https://doi.org/10.3389/fneur.2023.1128092
[60]	Government of CanadaFalls among older adults in Canada (2023). Available from: https://health-infobase.canada.ca/falls-in-older-adults/
[61]	Shah KM, Clark BR, McGill JB, et al. (2015) Shoulder limited joint mobility in people with diabetes mellitus. Clin Biomech 30: 308-313. https://doi.org/10.1016/j.clinbiomech.2014.12.013
[62]	Shah KM, Clark BR, McGill JB, et al. (2015) Upper extremity impairments, pain and disability in patients with diabetes mellitus. Physiotherapy 101: 147-154. https://doi.org/10.1016/j.physio.2014.07.003
[63]	Brownlee M (1992) Glycation products and the pathogenesis of diabetic complications. Diabetes Care 15: 1835-1843. https://doi.org/10.2337/diacare.15.12.1835
[64]	Shinabarger NI (1987) Limited joint mobility in adults with diabetes mellitus. Phys Ther 67: 215-218. https://doi.org/10.1093/ptj/67.2.215
[65]	Silverstein JH, Gordon G, Pollock BH, et al. (1998) Long-term glycemic control influences the onset of limited joint mobility in type 1 diabetes. J Pediatr 132: 944-947. https://doi.org/10.1016/S0022-3476(98)70388-9
[66]	Wang Y, Xie W, Tian T, et al. (2022) The relationship between dietary patterns and high blood glucose among adults based on structural equation modelling. Nutrients 14: 4111. https://doi.org/10.3390/nu14194111
[67]	Luna-Castillo KP, Olivares-Ochoa XC, Hernández-Ruiz RG, et al. (2022) The effect of dietary interventions on hypertriglyceridemia: From public health to molecular nutrition evidence. Nutrients 14: 1104. https://doi.org/10.3390/nu14051104

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