Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Obesityarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Obesity
Article
Data sources: UnpayWall
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Obesity
Article . 2008 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
Obesity
Article . 2008
versions View all 2 versions
addClaim

Gender Differences in Predictors of Body Weight and Body Weight Change in Healthy Adults

Authors: Chiriboga, David E.; Ma, Yunsheng; Li, Wenjun; Olendzki, Barbara C.; Pagoto, Sherry L.; Merriam, Philip A.; Matthews, Charles E.; +2 Authors

Gender Differences in Predictors of Body Weight and Body Weight Change in Healthy Adults

Abstract

Background: Overweight and obesity are important predictors of a wide variety of health problems. Analysis of naturally occurring changes in body weight can provide valuable insights in improving our understanding of the influence of demographic, lifestyle, and psychosocial factors on weight gain in middle‐age adults.Objective: To identify gender‐specific predictors of body weight using cross‐sectional and longitudinal analyses.Methods and Procedures: Anthropometric, lifestyle and psychosocial factors were measured at baseline and then quarterly for 1 year in 572 healthy adult volunteers from Central Massachusetts who were recruited between 1994 and 1998. Linear mixed models were used to analyze the relationship between body weight and potential predictors, including demographic (e.g., age, educational level), lifestyle (e.g., diet, physical activity, smoking), and psychosocial (e.g., anxiety, depression) factors.Results: Over the 1‐year study period, on average, men gained 0.3 kg and women lost 0.2 kg. Predictors of lower body weight at baseline in both men and women included current cigarette smoking, greater leisure‐time physical activity, and lower depression and anxiety scores. Lower body weights were associated with a lower percentage of caloric intake from protein and greater occupational physical activity levels only among men; and with higher education level only among women. Longitudinal predictors of 1‐year weight gain among women included increased total caloric intake and decreased leisure‐time physical activity, and among men, greater anxiety scores.Discussion: Demographic, lifestyle and psychosocial factors are independently related to naturally occurring changes in body weight and have marked differential gender effects. These effects should be taken into consideration when designing interventions for weight‐loss and maintenance at the individual and population levels.

Country
United States
Keywords

Adult, Male, Weight Gain, Behavior and Behavior Mechanisms, Predictive Value of Tests, Humans, Psychology, Obesity, Longitudinal Studies, Life Style, Demography, Sex Characteristics, *Sex Characteristics, Behavioral Disciplines and Activities, Body Weight, Community Health and Preventive Medicine, Middle Aged, Cross-Sectional Studies, Health, Body Change, *Weight Gain, Linear Models, *Body Weight, Female, Preventive Medicine, Public Health

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    52
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
bronze