Age- and sex-specific effects of a long-term lifestyle intervention on body weight and cardiometabolic health markers in adults with prediabetes: results from the diabetes prevention study PREVIEW

Ruixin Zhu, Ionut Craciun, Jan Bernhards-Werge, Elli Jalo, Sally D Poppitt, Marta P Silvestre, Maija Huttunen-Lenz, Melitta A McNarry, Gareth Stratton, Svetoslav Handjiev, Teodora Handjieva-Darlenska, Santiago Navas-Carretero, Jouko Sundvall, Tanja C Adam, Mathijs Drummen, Elizabeth J Simpson, Ian A Macdonald, Jennie Brand-Miller, Roslyn Muirhead, Tony Lam, Pia S Vestentoft, Kristine Færch, J Alfredo Martinez, Mikael Fogelholm, Anne Raben, Ruixin Zhu, Ionut Craciun, Jan Bernhards-Werge, Elli Jalo, Sally D Poppitt, Marta P Silvestre, Maija Huttunen-Lenz, Melitta A McNarry, Gareth Stratton, Svetoslav Handjiev, Teodora Handjieva-Darlenska, Santiago Navas-Carretero, Jouko Sundvall, Tanja C Adam, Mathijs Drummen, Elizabeth J Simpson, Ian A Macdonald, Jennie Brand-Miller, Roslyn Muirhead, Tony Lam, Pia S Vestentoft, Kristine Færch, J Alfredo Martinez, Mikael Fogelholm, Anne Raben

Abstract

Aims/hypothesis: Lifestyle interventions are the first-line treatment option for body weight and cardiometabolic health management. However, whether age groups or women and men respond differently to lifestyle interventions is under debate. We aimed to examine age- and sex-specific effects of a low-energy diet (LED) followed by a long-term lifestyle intervention on body weight, body composition and cardiometabolic health markers in adults with prediabetes (i.e. impaired fasting glucose and/or impaired glucose tolerance).

Methods: This observational study used longitudinal data from 2223 overweight participants with prediabetes in the multicentre diabetes prevention study PREVIEW. The participants underwent a LED-induced rapid weight loss (WL) period followed by a 3 year lifestyle-based weight maintenance (WM) intervention. Changes in outcomes of interest in prespecified age (younger: 25-45 years; middle-aged: 46-54 years; older: 55-70 years) or sex (women and men) groups were compared.

Results: In total, 783 younger, 319 middle-aged and 1121 older adults and 1503 women and 720 men were included in the analysis. In the available case and complete case analyses, multivariable-adjusted linear mixed models showed that younger and older adults had similar weight loss after the LED, whereas older adults had greater sustained weight loss after the WM intervention (adjusted difference for older vs younger adults -1.25% [95% CI -1.92, -0.58], p<0.001). After the WM intervention, older adults lost more fat-free mass and bone mass and had smaller improvements in 2 h plasma glucose (adjusted difference for older vs younger adults 0.65 mmol/l [95% CI 0.50, 0.80], p<0.001) and systolic blood pressure (adjusted difference for older vs younger adults 2.57 mmHg [95% CI 1.37, 3.77], p<0.001) than younger adults. Older adults had smaller decreases in fasting and 2 h glucose, HbA1c and systolic blood pressure after the WM intervention than middle-aged adults. In the complete case analysis, the above-mentioned differences between middle-aged and older adults disappeared, but the direction of the effect size did not change. After the WL period, compared with men, women had less weight loss (adjusted difference for women vs men 1.78% [95% CI 1.12, 2.43], p<0.001) with greater fat-free mass and bone mass loss and smaller improvements in HbA1c, LDL-cholesterol and diastolic blood pressure. After the WM intervention, women had greater fat-free mass and bone mass loss and smaller improvements in HbA1c and LDL-cholesterol, while they had greater improvements in fasting glucose, triacylglycerol (adjusted difference for women vs men -0.08 mmol/l [-0.11, -0.04], p<0.001) and HDL-cholesterol.

Conclusions/interpretation: Older adults benefited less from a lifestyle intervention in relation to body composition and cardiometabolic health markers than younger adults, despite greater sustained weight loss. Women benefited less from a LED followed by a lifestyle intervention in relation to body weight and body composition than men. Future interventions targeting older adults or women should take prevention of fat-free mass and bone mass loss into consideration.

Clinical trial registration number: ClinicalTrials.gov NCT01777893.

Keywords: Cardiovascular disease; Men; Middle-aged people; Obesity; Older people; Weight loss; Weight loss maintenance; Women; Young people.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Study flow diagram. A total of 2224 participants started the weight loss phase, but one withdrew consent and requested data deletion. Younger adults: 25–45 years; middle-aged adults: 46–54 years; older adults: 55–70 years. To enable the data collection to be as complete as possible, we allowed the following visit windows for data collection: at 8 weeks: −3 to 5 days; at 26 weeks: ±1 week; at 52 weeks: ±2 weeks; remaining time points: ±4 weeks
Fig. 2
Fig. 2
Changes in anthropometry and body composition from baseline by age group (n=2223). Values are estimated marginal mean (95% CI) changes from baseline in body weight (a), waist circumference (b), fat mass (c), FFM (d), BMC (e) and BMD (f). Younger adults: 25–45 years; middle-aged adults: 46–54 years; older adults: 55–70 years. Analyses were performed using a linear mixed model including sex, age, ethnicity, baseline BMI, baseline smoking status, baseline alcohol consumption, baseline values of the outcome being considered, baseline energy intake and PA, time-varying changes in energy intake and PA from baseline, intervention arm, time and interaction of time and age group or sex as fixed covariates and participant identifier and intervention centre as random effects. Post hoc multiple comparisons with Bonferroni adjustment were performed to compare age groups at each time point, where appropriate. Older vs younger adults *p<0.05, **p<0.01 and ***p<0.001; middle-aged vs younger adults †p<0.05, ††p<0.01 and †††p<0.001; older vs middle-aged adults ‡p<0.05 and ‡‡p<0.01. BMC data were based on 614 younger, 227 middle-aged and 639 older participants from Denmark, Spain, Bulgaria, Australia and New Zealand. BMD data were based on 419 younger, 221 middle-aged and 476 older participants from Denmark, Spain, Australia and New Zealand
Fig. 3
Fig. 3
Weight loss-adjusted changes in cardiometabolic health markers from baseline by age group (n=2223). Values are estimated marginal mean (95% CI) changes from baseline in FPG (a), 2 h plasma glucose (b), HbA1c (c), triacylglycerol (d), HDL-cholesterol (e), LDL-cholesterol (f), SBP (g) and DBP (h). Younger adults: 25–45 years; middle-aged adults: 46–54 years; older adults: 55–70 years. Analyses were performed using a linear mixed model including sex, age, ethnicity, baseline BMI, baseline smoking status, baseline alcohol consumption, baseline values of the outcome being considered, time-varying percentage weight loss from baseline, baseline energy intake and PA, time-varying changes in energy intake and PA from baseline, intervention arm, time and interaction of time and age group as covariates and participant identifier and intervention centre as random effects. Post hoc multiple comparisons with Bonferroni adjustment were performed to compare age groups at each time point. Older vs younger adults *p<0.05, **p<0.01 and ***p<0.001; middle-aged vs younger adults †p<0.05, ††p<0.01 and †††p<0.001; older vs middle-aged adults ‡p<0.05, ‡‡p<0.01 and ‡‡‡p<0.001
Fig. 4
Fig. 4
Changes in anthropometry and body composition from baseline in women and men (n=2223). Values are estimated marginal mean (95% CI) changes from baseline in body weight (a), waist circumference (b), fat mass (c), FFM (d), BMC (e) and BMD (f). Analyses were performed using a linear mixed model including sex, age, ethnicity, baseline BMI, baseline smoking status, baseline alcohol consumption, baseline values of the outcome being considered, baseline energy intake and PA, time-varying changes in energy intake and PA from baseline, intervention arm, time and interaction of time and age group or sex as fixed covariates and participant identifier and intervention centre as random effects. Post hoc pairwise comparisons (independent samples t tests) were performed to compare women and men at each time point, where appropriate. Women vs men **p<0.01 and ***p<0.001. BMC data were based on 1037 women and 443 men from Denmark, Spain, Bulgaria, Australia and New Zealand. BMD data were based on 759 women and 357 men from Denmark, Spain, Australia and New Zealand
Fig. 5
Fig. 5
Weight-adjusted changes in cardiometabolic health markers from baseline in women and men (n=2223). Values are estimated marginal mean (95% CI) changes from baseline in FPG (a), 2 h plasma glucose (b), HbA1c (c), triacylglycerol (d), HDL-cholesterol (e), LDL-cholesterol (f), SBP (g) and DBP (h). Analyses were performed using a linear mixed model including sex, age, ethnicity, baseline BMI, baseline smoking status, baseline alcohol consumption, baseline values of the outcome being considered, time-varying percentage weight loss from baseline, baseline energy intake and PA, time-varying changes in energy intake and PA from baseline, intervention arm, time and interaction of time and sex as fixed covariates and participant identifier and intervention centre as random effects. Post hoc pairwise comparisons (independent samples t tests) were performed to compare women and men at each time point, where appropriate. Women vs men *p<0.05, **p<0.01 and ***p<0.001
Fig. 6
Fig. 6
Cumulative incidence of type 2 diabetes by age and sex (n=2223). Values are cumulative incidence of diabetes by age (a) and sex (b) at each time point. Diabetes was diagnosed by an OGTT with 75 g glucose or by a medical doctor. Cumulative incidence was calculated using the Kaplan–Meier method, without adjustment. The incidence of diabetes was compared among age groups or between women and men using a time-dependent Cox hazards regression model adjusted for loge(time) × age or sex, ethnicity, baseline smoking status, baseline alcohol consumption, baseline BMI, baseline FPG, baseline 2 h plasma glucose, baseline PA and baseline energy intake, changes in PA and energy intake from baseline, intervention arm and intervention site as covariates

References

    1. Global Burden of Disease Obesity Collaborators Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377(1):13–27. doi: 10.1056/NEJMoa1614362.
    1. Heymsfield SB, Wadden TA. Mechanisms, pathophysiology, and Management of Obesity. N Engl J Med. 2017;376(15):1492. doi: 10.1056/NEJMc1701944.
    1. Eckel RH, Jakicic JM, Ard JD, et al. 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a report of the American College of Cardiology/American Heart Association task force on practice guidelines. Circulation. 2014;129(25 Suppl 2):S76–S99. doi: 10.1161/01.cir.0000437740.48606.d1.
    1. American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Obesity Expert Panel, 2013 (2014) Executive summary: guidelines (2013) for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the obesity society published by the obesity society and American college of cardiology/American heart association task force on practice guidelines. Based on a systematic review from the the obesity expert panel, 2013. Obesity (Silver Spring) 22(Suppl 2):S5–S39. 10.1002/oby.20821
    1. Jensen MD, Ryan DH, Apovian CM, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the obesity society. J Am Coll Cardiol. 2014;63(25 Pt B):2985–3023. doi: 10.1016/j.jacc.2013.11.004.
    1. American Diabetes Association 3. Foundations of care and comprehensive medical evaluation. Diabetes Care. 2016;39(Suppl 1):S23–S35. doi: 10.2337/dc16-S006.
    1. Diabetes Prevention Program Outcomes Study Research G. Orchard TJ, Temprosa M, et al. Long-term effects of the diabetes prevention program interventions on cardiovascular risk factors: a report from the DPP outcomes study. Diabet Med. 2013;30(1):46–55. doi: 10.1111/j.1464-5491.2012.03750.x.
    1. Salas-Salvado J, Diaz-Lopez A, Ruiz-Canela M, et al. Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on weight loss and cardiovascular risk factors: one-year results of the PREDIMED-plus trial. Diabetes Care. 2019;42(5):777–788. doi: 10.2337/dc18-0836.
    1. Höchsmann C, Dorling JL, Martin CK, et al. Effects of a 2-year primary care lifestyle intervention on cardiometabolic risk factors: a cluster-randomized trial. Circulation. 2021;143(12):1202–1214. doi: 10.1161/CIRCULATIONAHA.120.051328.
    1. Wing RR, Bolin P, Brancati FL, et al. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013;369(2):145–154. doi: 10.1056/NEJMoa1212914.
    1. Waters DL, Ward AL, Villareal DT. Weight loss in obese adults 65 years and older: a review of the controversy. Exp Gerontol. 2013;48(10):1054–1061. doi: 10.1016/j.exger.2013.02.005.
    1. Haywood C, Sumithran P. Treatment of obesity in older persons-a systematic review. Obes Rev. 2019;20(4):588–598. doi: 10.1111/obr.12815.
    1. Espeland MA, Rejeski WJ, West DS, et al. Intensive weight loss intervention in older individuals: results from the action for health in diabetes type 2 diabetes mellitus trial. J Am Geriatr Soc. 2013;61(6):912–922. doi: 10.1111/jgs.12271.
    1. Williams RL, Wood LG, Collins CE, Callister R. Effectiveness of weight loss interventions--is there a difference between men and women: a systematic review. Obes Rev. 2015;16(2):171–186. doi: 10.1111/obr.12241.
    1. Christensen P, Meinert Larsen T, Westerterp-Plantenga M, et al. Men and women respond differently to rapid weight loss: metabolic outcomes of a multi-Centre intervention study after a low-energy diet in 2500 overweight, individuals with pre-diabetes (PREVIEW) Diabetes Obes Metab. 2018;20(12):2840–2851. doi: 10.1111/dom.13466.
    1. Jesuthasan A, Zhyzhneuskaya S, Peters C et al (2021) Sex differences in intraorgan fat levels and hepatic lipid metabolism: implications for cardiovascular health and remission of type 2 diabetes after dietary weight loss. Diabetologia. 10.1007/s00125-021-05583-4
    1. Raben A, Vestentoft PS, Brand-Miller J, et al. PREVIEW-results from a 3-year randomised 2 x 2 factorial multinational trial investigating the role of protein, glycemic index and physical activity for prevention of type-2 diabetes. Diabetes Obes Metab. 2020;23:324–337. doi: 10.1111/dom.14219.
    1. Cai X, Zhang Y, Li M, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ. 2020;370:m2297. doi: 10.1136/bmj.m2297.
    1. Almourani R, Chinnakotla B, Patel R, Kurukulasuriya LR, Sowers J. Diabetes and cardiovascular disease: an update. Curr Diab Rep. 2019;19(12):161. doi: 10.1007/s11892-019-1239-x.
    1. Welsh C, Welsh P, Celis-Morales CA, et al. Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: data from UK biobank. Diabetes Care. 2020;43(2):440–445. doi: 10.2337/dc19-1683.
    1. Fogelholm M, Larsen TM, Westerterp-Plantenga M, et al. PREVIEW: prevention of diabetes through lifestyle intervention and population studies in Europe and around the world. Design, methods, and baseline participant description of an adult cohort enrolled into a three-year randomised clinical trial. Nutrients. 2017;9(6):632. doi: 10.3390/nu9060632.
    1. American Diabetes Association Professional Practice Committee 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2022. Diabetes Care. 2022;45(Suppl 1):S17–S38. doi: 10.2337/dc22-S002.
    1. Dyussenbayev A. Age periods of human life. Adv Soc Sci Res J. 2017;4(6):258–263. doi: 10.14738/assrj.46.2924.
    1. Zhu D, Chung H-F, Dobson AJ, et al. Age at natural menopause and risk of incident cardiovascular disease: a pooled analysis of individual patient data. Lancet Public Health. 2019;4(11):e553–e564. doi: 10.1016/S2468-2667(19)30155-0.
    1. Kahlert D, Unyi-Reicherz A, Stratton G, et al. PREVIEW behavior modification intervention toolbox (PREMIT): a study protocol for a psychological element of a multicenter project. Front Psychol. 2016;7:1136. doi: 10.3389/fpsyg.2016.01136.
    1. World Health Organization (2006) Definition and Diagnosis of Diabetes Mellitus and Intermediate Hyperglycaemia. Available from . Accessed July 19 2017.
    1. Duncan MS, Freiberg MS, Greevy RA, Jr, Kundu S, Vasan RS, Tindle HA. Association of smoking cessation with subsequent risk of cardiovascular disease. JAMA. 2019;322(7):642–650. doi: 10.1001/jama.2019.10298.
    1. Chiva-Blanch G, Badimon L. Benefits and risks of moderate alcohol consumption on cardiovascular disease: current findings and controversies. Nutrients. 2020;12(1):108. doi: 10.3390/nu12010108.
    1. Malik MO, Govan L, Petrie JR, et al. Ethnicity and risk of cardiovascular disease (CVD): 4.8 year follow-up of patients with type 2 diabetes living in Scotland. Diabetologia. 2015;58(4):716–725. doi: 10.1007/s00125-015-3492-0.
    1. Barbaresko J, Rienks J, Nothlings U. Lifestyle indices and cardiovascular disease risk: a Meta-analysis. Am J Prev Med. 2018;55(4):555–564. doi: 10.1016/j.amepre.2018.04.046.
    1. Mau T, Yung R. Adipose tissue inflammation in aging. Exp Gerontol. 2018;105:27–31. doi: 10.1016/j.exger.2017.10.014.
    1. Lovejoy JC, Sainsbury A, Stock Conference Working G Sex differences in obesity and the regulation of energy homeostasis. Obes Rev. 2009;10(2):154–167. doi: 10.1111/j.1467-789X.2008.00529.x.
    1. Kologrivova IV, Vinnitskaya IV, Koshelskaya OA, Suslova TE. Visceral obesity and cardiometabolic risk: features of hormonal and immune regulation. Obes Metab. 2017;14(3):3–10. doi: 10.14341/omet201733-10.
    1. Arpón A, Milagro FI, Santos JL, García-Granero M, Riezu-Boj J-I, Martínez JA. Interaction among sex, aging, and epigenetic processes concerning visceral fat, insulin resistance, and dyslipidaemia. Front Endocrinol. 2019;10:496. doi: 10.3389/fendo.2019.00496.
    1. Svetkey LP, Clark JM, Funk K, et al. Greater weight loss with increasing age in the weight loss maintenance trial. Obesity (Silver Spring) 2014;22(1):39–44. doi: 10.1002/oby.20506.
    1. Brokaw SM, Carpenedo D, Campbell P, et al. Effectiveness of an adapted diabetes prevention program lifestyle intervention in older and younger adults. J Am Geriatr Soc. 2015;63(6):1067–1074. doi: 10.1111/jgs.13428.
    1. Armamento-Villareal R, Aguirre L, Waters DL, Napoli N, Qualls C, Villareal DT. Effect of aerobic or resistance exercise, or both, on bone mineral density and bone metabolism in obese older adults while dieting: a randomized controlled trial. J Bone Miner Res. 2020;35(3):430–439. doi: 10.1002/jbmr.3905.
    1. Pinheiro MB, Oliveira J, Bauman A, Fairhall N, Kwok W, Sherrington C. Evidence on physical activity and osteoporosis prevention for people aged 65+ years: a systematic review to inform the WHO guidelines on physical activity and sedentary behaviour. Int J Behav Nutr Phys Act. 2020;17(1):150. doi: 10.1186/s12966-020-01040-4.
    1. Weinheimer EM, Sands LP, Campbell WW. A systematic review of the separate and combined effects of energy restriction and exercise on fat-free mass in middle-aged and older adults: implications for sarcopenic obesity. Nutr Rev. 2010;68(7):375–388. doi: 10.1111/j.1753-4887.2010.00298.x.
    1. Wing RR, Espeland MA, Clark JM, et al. Association of weight loss maintenance and weight regain on 4-year changes in CVD risk factors: the action for health in diabetes (look AHEAD) clinical trial. Diabetes Care. 2016;39(8):1345–1355. doi: 10.2337/dc16-0509.
    1. Berger SE, Huggins GS, McCaffery JM, Jacques PF, Lichtenstein AH. Change in cardiometabolic risk factors associated with magnitude of weight regain 3 years after a 1-year intensive lifestyle intervention in type 2 diabetes mellitus: the look AHEAD trial. J Am Heart Assoc. 2019;8(20):e010951. doi: 10.1161/JAHA.118.010951.
    1. Wing RR, Lang W, Wadden TA, et al. Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes. Diabetes Care. 2011;34(7):1481–1486. doi: 10.2337/dc10-2415.
    1. Slopien R, Wender-Ozegowska E, Rogowicz-Frontczak A, et al. Menopause and diabetes: EMAS clinical guide. Maturitas. 2018;117:6–10. doi: 10.1016/j.maturitas.2018.08.009.
    1. Robertson C, Avenell A, Boachie C, et al. Should weight loss and maintenance programmes be designed differently for men? A systematic review of long-term randomised controlled trials presenting data for men and women: the ROMEO project. Obes Res Clin Pract. 2016;10(1):70–84. doi: 10.1016/j.orcp.2015.04.005.
    1. Evans EM, Mojtahedi MC, Thorpe MP, Valentine RJ, Kris-Etherton PM, Layman DK. Effects of protein intake and gender on body composition changes: a randomized clinical weight loss trial. Nutr Metab (Lond) 2012;9(1):55. doi: 10.1186/1743-7075-9-55.
    1. Tirosh A, de Souza RJ, Sacks F, Bray GA, Smith SR, LeBoff MS. Sex differences in the effects of weight loss diets on bone mineral density and body composition: POUNDS LOST trial. J Clin Endocrinol Metab. 2015;100(6):2463–2471. doi: 10.1210/jc.2015-1050.
    1. Stiegler P, Cunliffe A. The role of diet and exercise for the maintenance of fat-free mass and resting metabolic rate during weight loss. Sports Med. 2006;36(3):239–262. doi: 10.2165/00007256-200636030-00005.
    1. Goossens GH, Jocken JWE, Blaak EE. Sexual dimorphism in cardiometabolic health: the role of adipose tissue, muscle and liver. Nat Rev Endocrinol. 2021;17(1):47–66. doi: 10.1038/s41574-020-00431-8.
    1. Perreault L, Ma Y, Dagogo-Jack S, et al. Sex differences in diabetes risk and the effect of intensive lifestyle modification in the diabetes prevention program. Diabetes Care. 2008;31(7):1416–1421. doi: 10.2337/dc07-2390.

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