Gestational weight gain and optimal wellness (GLOW): rationale and methods for a randomized controlled trial of a lifestyle intervention among pregnant women with overweight or obesity

Susan D Brown, Monique M Hedderson, Samantha F Ehrlich, Maren N Galarce, Ai-Lin Tsai, Charles P Quesenberry, Assiamira Ferrara, Susan D Brown, Monique M Hedderson, Samantha F Ehrlich, Maren N Galarce, Ai-Lin Tsai, Charles P Quesenberry, Assiamira Ferrara

Abstract

Background: Excess gestational weight gain (GWG) is common among women with overweight or obesity, increasing their risks for pregnancy complications, delivering a large infant, and postpartum weight retention. To date, only intensive interventions have had success and few interventions have been designed for implementation in healthcare settings.

Methods: We describe the development, rationale, and methods of GLOW (GestationaL Weight Gain and Optimal Wellness), a randomized controlled trial evaluating the efficacy of a lifestyle intervention to prevent excess GWG among racially/ethnically diverse women with overweight or obesity in an integrated healthcare delivery system. Participants in Kaiser Permanente Northern California will be randomized, within 2 weeks of completing a study baseline clinic visit at 10 weeks' gestation, to either usual medical care or a multi-component pregnancy lifestyle intervention adapted from the Diabetes Prevention Program (target N = 400). Informed by focus groups with patients and designed to be feasible in a clinical setting, the intervention will include 13 weekly individual sessions (11 delivered by telephone) focused on behavior change for weight management, healthy eating, physical activity, and stress management. Outcomes will be assessed in women and their infants from randomization to 12 months postpartum. The primary outcome is GWG. Secondary outcomes include changes in diet and physical activity during pregnancy and infant birthweight. Exploratory outcomes include cardiometabolic profile assessed via pregnancy blood samples and cord blood samples; and postpartum weight retention and infant anthropometrics up to 12 months of age. The trial includes systematic approaches to enhance intervention fidelity, intervention adherence, and participant retention in trial assessments.

Discussion: GLOW is among few trials targeting excess GWG among diverse women with overweight or obesity in a healthcare setting, with long-term maternal and infant outcomes assessed up to 12 months after delivery. This evaluation of a multi-component intervention is designed to produce generalizable results to inform potential adoption of the intervention in clinical settings.

Trial registration: ClinicalTrials.gov ( NCT02130232 ): submitted April 30, 2014; posted May 5, 2014.

Keywords: Clinical trial; Gestational weight gain; Lifestyle intervention; Obesity; Pregnancy; Protocol.

Conflict of interest statement

Ethics approval and consent to participate

This study is approved by the Kaiser Foundation Research Institute Human Subjects Committee. All participants provide written informed consent to participate.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Sequence of participant enrollment, intervention, and assessment activities: The GLOW trial

References

    1. Institute of Medicine (IOM), National Research Council (NRC): Weight Gain During Pregnancy: Reexamining the Guidelines. Washington (DC): National Academies Press (US); 2009.
    1. Deputy NP, Sharma AJ, Kim SY, Hinkle SN. Prevalence and characteristics associated with gestational weight gain adequacy. Obstet Gynecol. 2015;125(4):773–781. doi: 10.1097/AOG.0000000000000739.
    1. QuickStats Gestational Weight Gain Among Women with Full-Term, Singleton Births, Compared with Recommendations - 48 States and the District of Columbia, 2015. MMWR Morb Mortal Wkly Rep. 2016;65(40):1121. doi: 10.15585/mmwr.mm6540a10.
    1. Goldstein RF, Abell SK, Ranasinha S, Misso M, Boyle JA, Black MH, Li N, Hu G, Corrado F, Rode L, et al. Association of gestational weight gain with maternal and infant outcomes: a systematic review and meta-analysis. J Amer Med Assoc. 2017;317(21):2207–2225. doi: 10.1001/jama.2017.3635.
    1. Margerison Zilko Claire E., Rehkopf David, Abrams Barbara. Association of maternal gestational weight gain with short- and long-term maternal and child health outcomes. American Journal of Obstetrics and Gynecology. 2010;202(6):574.e1-574.e8. doi: 10.1016/j.ajog.2009.12.007.
    1. Hedderson MM, Gunderson EP, Ferrara A. Gestational weight gain and risk of gestational diabetes mellitus. Obstet Gynecol. 2010;115(3):597–604. doi: 10.1097/AOG.0b013e3181cfce4f.
    1. Amorim AR, Rossner S, Neovius M, Lourenco PM, Linne Y. Does excess pregnancy weight gain constitute a major risk for increasing long-term BMI? Obesity (SilverSpring) 2007;15(5):1278–1286. doi: 10.1038/oby.2007.149.
    1. Savitz DA, Stein CR, Siega-Riz AM, Herring AH. Gestational weight gain and birth outcome in relation to prepregnancy body mass index and ethnicity. Ann Epidemiol. 2011;21(2):78–85. doi: 10.1016/j.annepidem.2010.06.009.
    1. Oken Emily, Taveras Elsie M., Kleinman Ken P., Rich-Edwards Janet W., Gillman Matthew W. Gestational weight gain and child adiposity at age 3 years. American Journal of Obstetrics and Gynecology. 2007;196(4):322.e1-322.e8. doi: 10.1016/j.ajog.2006.11.027.
    1. Muktabhant B, Lawrie TA, Lumbiganon P, Laopaiboon M. Diet or exercise, or both, for preventing excessive weight gain in pregnancy. Cochrane Database Syst Rev. 2015;6 Cd007145.
    1. Headen IE, Davis EM, Mujahid MS, Abrams B. Racial-ethnic differences in pregnancy-related weight. Adv Nutr. 2012;3(1):83–94. doi: 10.3945/an.111.000984.
    1. Peaceman AM, Clifton RG, Phelan S, Gallagher D, Evans M, Redman LM, Knowler WC, Joshipura K, Haire-Joshu D, Yanovski SZ, et al. Lifestyle interventions limit gestational weight gain in women with overweight or obesity: LIFE-moms prospective meta-analysis. Obesity. 2018;26(9):1396–1404. doi: 10.1002/oby.22250.
    1. Phillips JK, Higgins ST. Applying behavior change techniques to weight management during pregnancy: impact on perinatal outcomes. Prev Med. 2017;104:133–136. doi: 10.1016/j.ypmed.2017.07.023.
    1. Diabetes Prevention Program (DPP) Research Group The diabetes prevention program (DPP): description of lifestyle intervention. Diabetes Care. 2002;25(12):2165–2171. doi: 10.2337/diacare.25.12.2165.
    1. Chan AW, Tetzlaff JM, Gotzsche PC, Altman DG, Mann H, Berlin JA, Dickersin K, Hrobjartsson A, Schulz KF, Parulekar WR, et al. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013;346:e7586. doi: 10.1136/bmj.e7586.
    1. Similarity of the Adult Kaiser Permanente Membership in Northern California to the Insured and General Population in Northern California: Statistics from the 2011–12 California Health Interview Survey [].
    1. Saghaei M, Saghaei S. Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. J Biomed Sci Eng. 2011;4(11):734–739. doi: 10.4236/jbise.2011.411090.
    1. Ferrara A, Hedderson MM, Albright CL, Brown SD, Ehrlich SF, Caan BJ, Sternfeld B, Gordon NP, Schmittdiel JA, Gunderson EP, et al. A pragmatic cluster randomized clinical trial of diabetes prevention strategies for women with gestational diabetes: design and rationale of the gestational Diabetes' effects on moms (GEM) study. BMC Pregnancy Childbirth. 2014;14:21. doi: 10.1186/1471-2393-14-21.
    1. Ferrara A, Hedderson MM, Brown SD, Albright CL, Ehrlich SF, Tsai AL, Caan BJ, Sternfeld B, Gordon NP, Schmittdiel JA, et al. The comparative effectiveness of diabetes prevention strategies to reduce postpartum weight retention in women with gestational diabetes mellitus: the gestational Diabetes' effects on moms (GEM) cluster randomized controlled trial. Diabetes Care. 2016;39(1):65–74. doi: 10.2337/dc15-1254.
    1. Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall; 1986.
    1. Bandura A. Self-efficacy: the exercise of control. New York, NY, US: W H Freeman/Times Books/ Henry Holt & Co; 1997.
    1. Prochaska JO, CC DC. Common processes of self-change in smoking, weight control and psychological distress. In: Shiffman S, Wills T, editors. Coping and Substance Use: New York: Academic Press; 1985. p. 345–63.
    1. Miller WR, Rollnick S. Motivational interviewing: preparing people to change addictive behavior. New York: Guilford Press; 1991.
    1. Miller WR, Rollnick S. Motivational interviewing: preparing people for change. New York: Guilford Press; 2002.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81–95. doi: 10.1007/s12160-013-9486-6.
    1. Lytle LA, Svetkey LP, Patrick K, Belle SH, Fernandez ID, Jakicic JM, Johnson KC, Olson CM, Tate DF, Wing R, et al. The EARLY trials: a consortium of studies targeting weight control in young adults. Transl Behav Med. 2014;4(3):304–313. doi: 10.1007/s13142-014-0252-5.
    1. Kiernan M, Brown SD, Schoffman DE, Lee K, King AC, Taylor CB, Schleicher NC, Perri MG. Promoting healthy weight with "stability skills first": a randomized trial. J Consult Clin Psychol. 2013;81(2):336–346. doi: 10.1037/a0030544.
    1. Perri MG, Limacher MC, Durning PE, Janicke DM, Lutes LD, Bobroff LB, Dale MS, Daniels MJ, Radcliff TA, Martin AD. Extended-care programs for weight management in rural communities. Arch Intern Med. 2008;168:2347–2354. doi: 10.1001/archinte.168.21.2347.
    1. Perri MG, Nezu AM, Viegener BJ. Improving the long-term management of obesity: theory, research, and clinical guidelines. New York: John Wiley and Sons; 1992.
    1. Borrelli B, Sepinwall D, Ernst D, Bellg AJ, Czajkowski S, Breger R, DeFrancesco C, Levesque C, Sharp DL, Ogedegbe G, et al. A new tool to assess treatment fidelity and evaluation of treatment fidelity across 10 years of health behavior research. J Consult Clin Psychol. 2005;73(5):852–860. doi: 10.1037/0022-006X.73.5.852.
    1. Borrelli B. The assessment, monitoring, and enhancement of treatment fidelity in public health clinical trials. J Public Health Dent. 2011;71(Suppl 1):S52–S63. doi: 10.1111/j.1752-7325.2011.00233.x.
    1. Willett W. Nutritional epidemiology. Oxford: Oxford University Press; 1998.
    1. Bazzano LA, He J, Ogden LG, Loria CM, Vupputuri S, Myers L, Whelton PK. Agreement on nutrient intake between the databases of the first National Health and nutrition examination survey and the ESHA food processor. AmJEpidemiol. 2002;156(1):78–85.
    1. Sievert YA, Schakel SF, Buzzard IM. Maintenance of a nutrient database for clinical trials. ControlClinTrials. 1989;10(4):416–425.
    1. Calle EE, Rodriguez C, Jacobs EJ, Almon ML, Chao A, McCullough ML, Feigelson HS, Thun MJ. The American Cancer Society Cancer prevention study II nutrition cohort: rationale, study design, and baseline characteristics. Cancer. 2002;94(2):500–511. doi: 10.1002/cncr.10197.
    1. McDowell MA, Briefel RR. Nutrient database development and management: an NHANES perspective. Public Health Rev. 1998;26(1):49–53.
    1. Feskanich D, Sielaff BH, Chong K, Buzzard IM. Computerized collection and analysis of dietary intake information. ComputMethods Programs Biomed. 1989;30(1):47–57. doi: 10.1016/0169-2607(89)90122-3.
    1. Lalonde L, Graham M, Slovinee-D'Angelo M, Beaton L, Brown J, Block T. Validation of the Block Fat/Sugar/Fruit/Vegetable Screener in a Cardiac Rehabilitation Setting. In: Canadian Association of Cardiac Rehabilitation (CACR) Annual Meeting and Scientific Abstracts. Toronto, Ontario, Canada; 2008.
    1. Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43(2):357–364. doi: 10.1249/MSS.0b013e3181ed61a3.
    1. Choi L, Ward SC, Schnelle JF, Buchowski MS. Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. Med Sci Sports Exerc. 2012;44(10):2009–2016. doi: 10.1249/MSS.0b013e318258cb36.
    1. Choi L, Beck C, Liu Z, Matthews CE, Buchowski MS. PhysicalActivity: Process Accelerometer Data for Physical Activity Measurement [software]. Version 0.2–2. 2018. Available from: .
    1. Keadle SK, Shiroma EJ, Freedson PS, Lee IM. Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health. 2014;14:1210. doi: 10.1186/1471-2458-14-1210.
    1. Hibbing PR, Lamunion SR, Kaplan AS, Crouter SE. Estimating energy expenditure with ActiGraph GT9X inertial measurement unit. Med Sci Sports Exerc. 2018;50(5):1093–1102. doi: 10.1249/MSS.0000000000001532.
    1. Hibbing PR, van Hees VT. TwoRegression: Process Data from Wearable Research Devices Using Two-Regression Algorithms [software]. Version 0.1.2. 2018. Available from: .
    1. Catellier DJ, Hannan PJ, Murray DM, Addy CL, Conway TL, Yang S, Rice JC. Imputation of missing data when measuring physical activity by accelerometry. Med Sci Sports Exerc. 2005;37(11 Suppl):S555–S562. doi: 10.1249/01.mss.0000185651.59486.4e.
    1. Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nystrom C, Mora-Gonzalez J, Lof M, Labayen I, Ruiz JR, Ortega FB. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Med. 2017;47(9):1821–1845. doi: 10.1007/s40279-017-0716-0.
    1. Chasan-Taber L, Schmidt MD, Roberts DE, Hosmer D, Markenson G, Freedson PS. Development and validation of a pregnancy physical activity questionnaire. Med Sci Sports Exerc. 2004;36:1750–1760. doi: 10.1249/01.MSS.0000142303.49306.0D.
    1. Chasan-Taber L, Freedson PS, Roberts DE, Schmidt MD, Fragala MS. Energy expenditure of selected household activities during pregnancy. Res Q Exerc Sport. 2007;78(2):133–137. doi: 10.1080/02701367.2007.10599410.
    1. Kiernan M, Schoffman DE, Lee K, Brown SD, Fair JM, Perri MG, Haskell WL. The Stanford leisure-time activity categorical item (L-cat): a single categorical item sensitive to physical activity changes in overweight/obese women. Int J Obes. 2013;37:1597–1602. doi: 10.1038/ijo.2013.36.
    1. Ross KM, Leahey TM, Kiernan M. Validation of the Stanford leisure-time activity categorical item (L-cat) using armband activity monitor data. Obesity science & practice. 2018;4(3):276–282. doi: 10.1002/osp4.155.
    1. Hytten FE, Chamberlain G: Clinical physiology in obstetrics. Oxford; Boston; St. Louis, Mo.: Blackwell Scientific Publications ; Blackwell Mosby Book Distributors; 1980.
    1. Van Loan MD, Kopp LE, King JC, Wong WW, Mayclin PL. Fluid changes during pregnancy: use of bioimpedance spectroscopy. J ApplPhysiol. 1995;78(3):1037–1042.
    1. Shaw JW, Johnson JA, Coons SJ. US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Med Care. 2005;43(3):203–220. doi: 10.1097/00005650-200503000-00003.
    1. Lobel M, Cannella DL, Graham JE, DeVincent C, Schneider J, Meyer BA. Pregnancy-specific stress, prenatal health behaviors, and birth outcomes. Health Psychol. 2008;27(5):604–615. doi: 10.1037/a0013242.
    1. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396. doi: 10.2307/2136404.
    1. Kroenke K, Strine TW, Spitzer RL, Williams JB, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. JAffectDisord. 2009;114(1–3):163–173.
    1. Taveras EM, Rifas-Shiman SL, Rich-Edwards JW, Mantzoros CS. Maternal short sleep duration is associated with increased levels of inflammatory markers at 3 years postpartum. Metabolism. 2011;60(7):982–986. doi: 10.1016/j.metabol.2010.09.008.
    1. Gunderson EP, Matias SL, Hurston SR, Dewey KG, Ferrara A, Quesenberry CP, Jr, Lo JC, Sternfeld B, Selby JV. Study of women, infant feeding, and type 2 diabetes mellitus after GDM pregnancy (SWIFT), a prospective cohort study: methodology and design. BMC Public Health. 2011;11:952. doi: 10.1186/1471-2458-11-952.
    1. Chang MW, Nitzke S, Brown RL, Baumann LC, Oakley L. Development and validation of a self-efficacy measure for fat intake behaviors of low-income women. JNutrEducBehav. 2003;35(6):302–307.
    1. Albright CL, Steffen AD, Novotny R, Nigg CR, Wilkens LR, Saiki K, Yamada P, Hedemark B, Maddock JE, Dunn AL, et al. Baseline results from Hawaii's Na Mikimiki project: a physical activity intervention tailored to multiethnic postpartum women. Women Health. 2012;52(3):265–291. doi: 10.1080/03630242.2012.662935.
    1. Ball K, Crawford D. An investigation of psychological, social and environmental correlates of obesity and weight gain in young women. Int J Obes. 2006;30(8):1240–1249. doi: 10.1038/sj.ijo.0803267.
    1. Kiernan M, Moore SD, Schoffman DE, Lee K, King AC, Taylor CB, Kiernan NE, Perri MG. Social support for healthy behaviors: scale psychometrics and prediction of weight loss among women in a behavioral program. Obesity (Silver Spring) 2012;20(4):756–764. doi: 10.1038/oby.2011.293.
    1. Catalano PM, Thomas AJ, Avallone DA, Amini SB. Anthropometric estimation of neonatal body composition. AmJObstetGynecol. 1995;173(4):1176–1181.
    1. Group WHOMGRS . WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: methods and development in. Geneva: World Health Orgainzation; 2006.
    1. Group WHOMGRS . WHO child growth standards: head circumference-for-age, arm circumference-for-age, triceps skinfold-for-age and subscapular skinfold-for-age: methods and development. Geneva: World Health Organization; 2007.
    1. Robinson KA, Dinglas VD, Sukrithan V, Yalamanchilli R, Mendez-Tellez PA, Dennison-Himmelfarb C, Needham DM. Updated systematic review identifies substantial number of retention strategies: using more strategies retains more study participants. J Clin Epidemiol. 2015;68(12):1481–1487. doi: 10.1016/j.jclinepi.2015.04.013.
    1. Kost RG, Lee LM, Yessis J, Coller BS, Henderson DK. Research participant perception survey focus group S: assessing research participants' perceptions of their clinical research experiences. Clin Transl Sci. 2011;4(6):403–413. doi: 10.1111/j.1752-8062.2011.00349.x.
    1. Kost RG, Lee LM, Yessis J, Wesley RA, Henderson DK, Coller BS. Assessing participant-centered outcomes to improve clinical research. N Engl J Med. 2013;369(23):2179–2181. doi: 10.1056/NEJMp1311461.
    1. Goldberg JH, Kiernan M. Innovative techniques to address retention in a behavioral weight-loss trial. Health Educ Res. 2005;20(4):439–447. doi: 10.1093/her/cyg139.
    1. Brueton VC, Tierney JF, Stenning S, Meredith S, Harding S, Nazareth I, Rait G. Strategies to improve retention in randomised trials: a Cochrane systematic review and meta-analysis. BMJ Open. 2014;4(2):e003821. doi: 10.1136/bmjopen-2013-003821.
    1. Kost RG, Lee LM, Yessis J, Coller BS, Henderson DK. Research participant perception survey focus group subcommittee: assessing research participants' perceptions of their clinical research experiences. Clin Transl Sci. 2011;4(6):403–413. doi: 10.1111/j.1752-8062.2011.00349.x.
    1. Raab GM, Day S, Sales J. How to select covariates to include in the analysis of a clinical trial. Control Clin Trials. 2000;21(4):330–342. doi: 10.1016/S0197-2456(00)00061-1.
    1. U.S. Preventive Services Task Force. Final Research Plan: Healthy Weight and Weight Gain During Pregnancy: Counseling. 2018. Available from: [].
    1. Ferrara A, Hedderson MM, Ching J, Kim C, Peng T, Crites YM. Referral to telephonic nurse management improves outcomes in women with gestational diabetes. Am J Obstet Gynecol. 2012;206(6):491.e491–491.e495. doi: 10.1016/j.ajog.2012.04.019.
    1. Hedderson MM, Brown SD, Ehrlich SF, Tsai AL, Zhu Y, Quesenberry CP, Crites Y, Ferrara A. A tailored letter based on electronic health record data improves gestational weight gain among women with gestational diabetes mellitus: the gestational Diabetes' effects on moms (GEM) cluster-randomized controlled trial. Diabetes Care. 2018;41(7):1370–1377. doi: 10.2337/dc17-1133.
    1. Wilcox S, Liu J, Addy CL, Turner-McGrievy G, Burgis JT, Wingard E, Dahl AA, Whitaker KM, Schneider L, Boutte AK. A randomized controlled trial to prevent excessive gestational weight gain and promote postpartum weight loss in overweight and obese women: health in pregnancy and postpartum (HIPP) Contemp Clin Trials. 2018;66:51–63. doi: 10.1016/j.cct.2018.01.008.

Source: PubMed

Sponzoři a spolupracovníci

Zdravotní podmínky

Drogové intervence

3
Předplatit