Keyword search (4,164 papers available)

"cardiometabolic" Keyword-tagged Publications:

Title Authors PubMed ID
1 Comparing the impact of in-person vs. virtual 10-week family-based childhood obesity management program on anthropometric, cardiometabolic, and mental health outcomes Heidl AJ; Sun D; Faustini C; Gierc M; Bains A; Cohen TR; 41332896
MATHSTATS
2 Development and Application of Children s Sex- and Age-Specific Fat-Mass and Muscle-Mass Reference Curves From Dual-Energy X-Ray Absorptiometry Data for Predicting Cardiometabolic Risk Saputra ST; Van Hulst A; Henderson M; Brugiapaglia S; Faustini C; Kakinami L; 40878792
SOH
3 Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer s disease Tremblay SA; Nathan Spreng R; Wearn A; Alasmar Z; Pirhadi A; Tardif CL; Chakravarty MM; Villeneuve S; Leppert IR; Carbonell F; Medina YI; Steele CJ; Gauthier CJ; 40086421
PSYCHOLOGY
4 Health behavior profiles in young survivors of childhood cancer: Findings from the St. Jude Lifetime Cohort Study Webster RT; Dhaduk R; Gordon ML; Partin RE; Kunin-Batson AS; Brinkman TM; Willard VW; Allen JM; Alberts NM; Lanctot JQ; Ehrhardt MJ; Li Z; Hudson MM; Robison LL; Ness KK; 36943740
PSYCHOLOGY
5 Body-composition phenotypes and their associations with cardiometabolic risks and health behaviours in a representative general US sample Kakinami L; Plummer S; Cohen TR; Santosa S; Murphy J; 36183799
PERFORM
6 Associations of the BDNF Val66Met Polymorphism With Body Composition, Cardiometabolic Risk Factors, and Energy Intake in Youth With Obesity: Findings From the HEARTY Study Goldfield GS; Walsh J; Sigal RJ; Kenny GP; Hadjiyannakis S; De Lisio M; Ngu M; Prud' homme D; Alberga AS; Doucette S; Goldfield DB; Cameron JD; 34867148
IMAGING
7 Body Mass Index Z Score vs Weight-for-Length Z Score in Infancy and Cardiometabolic Outcomes at Age 8-10 Years Roberge JB; Harnois-Leblanc S; McNealis V; van Hulst A; Barnett TA; Kakinami L; Paradis G; Henderson M; 34302856
PERFORM
8 Weight cycling is associated with adverse cardiometabolic markers in a cross-sectional representative US sample Kakinami L; Knäuper B; Brunet J; 32366587
PERFORM

 

Title:Weight cycling is associated with adverse cardiometabolic markers in a cross-sectional representative US sample
Authors:Kakinami LKnäuper BBrunet J
Link:https://pubmed.ncbi.nlm.nih.gov/32366587/
DOI:10.1136/jech-2019-213419
Publication:Journal of epidemiology and community health
Keywords:EpidemiologyObesitycardiometabolicweight cycling
PMID:32366587 Category:J Epidemiol Community Health Date Added:2020-05-06
Dept Affiliation: PERFORM
1 Mathematics and Statistics, Concordia University, Montreal, Quebec, Canada lisa.kakinami@concordia.ca.
2 PERFORM Centre, Montreal, Canada.
3 McGill University, Montreal, Quebec, Canada.
4 University of Ottawa, Ottawa, Ontario, Canada.

Description:

Background: Whether weight cycling (repeated weight loss and regain) is associated with cardiometabolic health is unclear. Study objective was to examine whether weight cycling since young adulthood (ie, 25 years of age) was associated with cardiometabolic markers.

Methods: Data from a nationally representative cross-sectional US sample (National Health and Nutrition Examination Survey, 1999-2014) were used. Weight history was based on self-reported weight at age 25, 10 years prior and 1 year prior to the survey (n=4190, 51% male). Using current self-reported weight as the anchor, participants were classified as (1) stable weight, (2) weight losers, (3) weight gainers and (4) weight cyclers. Cardiometabolic markers included fasting lipids, insulin sensitivity and blood pressure. Multiple linear regressions were used to analyse weight history (reference: stable weight) and adjusted for covariates. Analyses incorporated the sampling design and survey weights and were stratified by sex or weight status.

Results: Compared with females with stable weight, female weight cyclers had worse lipids and homeostasis model assessment for insulin resistance (HOMA-IR) (all ps<0.05). Compared with males with stable weight, male weight cyclers had worse high-density lipoprotein cholesterol (HDL) and HOMA-IR (ps<0.05). Weight cyclers with normal weight had worse HDL and low-density lipoprotein cholesterol (ps<0.05), and weight cyclers with overweight or obesity had worse HOMA-IR (p=0.05). Blood pressure was not associated.

Conclusion: Weight cycling is adversely associated with cardiometabolic markers but associations differ by sex and weight status. While weight cycling is consistently associated with worse cardiometabolic markers among females, results are mixed among males. Weight cycling is associated with worse lipid measures for normal weight persons, and marginally worse insulin sensitivity for those with overweight/obesity.





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