Jing Wang1, Susan M Sereika, Mindi A Styn, Lora E Burke. 1. Department of Nursing Systems, University of Texas Health Science Center at Houston School of Nursing, Houston, TX 77030, USA. Jing.Wang@uth.tmc.edu
Abstract
AIMS AND OBJECTIVES: To identify factors associated with health-related quality of life among overweight or obese adults. BACKGROUND: The obesity epidemic presents a global challenge. Obesity is associated with lower health-related quality of life; however, no study has comprehensively examined correlates of health-related quality of life in this population. DESIGN: A cross-sectional design. METHODS: The physical component score, mental component score and eight domain scores of the Short Form-36 v2 were used to assess health-related quality of life. We identified 23 possible correlates of health-related quality of life, including age, body mass index, health and weight histories, perceived stress, cholesterol-lowering diet self-efficacy, problem-solving, binge eating, dietary intake and physical activity. Correlational analyses were used to examine the bivariate associations between correlates and health-related quality of life variables. All possible subsets regression was used to develop predictive models of health-related quality of life. RESULTS: The sample (n = 210) was predominantly White (84·8%), female (78·1%) and middle-aged (average age = 46·80 years). Age, body mass index, education, having children at home, and being hypertensive were identified as the best predictors of physical component score, explaining about 9% of the variance. Age, marital status, having hyperlipidaemia, perceived stress, problem-solving, self-efficacy, binge eating and barriers to healthy eating predicted mental component score, explaining approximately 48% of the variance. Physical functioning and role physical domains of health-related quality of life had similar sets of predictors, with 15% and 13% of the variance explained, respectively, while similar predictors were identified for bodily pain (6%), general health (26%), vitality (40%), social functioning (32%), role emotional (42%) and mental health (46%) domains. CONCLUSIONS: Psychosocial factors were associated with the mental-related quality of life. Further exploration of factors related to physical-related quality of life is warranted in this population. RELEVANCE TO CLINICAL PRACTICE: When working with overweight/obese adults who are trying to lose weight, nurses need to consider socio-demographic and psychosocial factors in the development of a treatment plan that will improve health-related quality of life in this population.
AIMS AND OBJECTIVES: To identify factors associated with health-related quality of life among overweight or obese adults. BACKGROUND: The obesity epidemic presents a global challenge. Obesity is associated with lower health-related quality of life; however, no study has comprehensively examined correlates of health-related quality of life in this population. DESIGN: A cross-sectional design. METHODS: The physical component score, mental component score and eight domain scores of the Short Form-36 v2 were used to assess health-related quality of life. We identified 23 possible correlates of health-related quality of life, including age, body mass index, health and weight histories, perceived stress, cholesterol-lowering diet self-efficacy, problem-solving, binge eating, dietary intake and physical activity. Correlational analyses were used to examine the bivariate associations between correlates and health-related quality of life variables. All possible subsets regression was used to develop predictive models of health-related quality of life. RESULTS: The sample (n = 210) was predominantly White (84·8%), female (78·1%) and middle-aged (average age = 46·80 years). Age, body mass index, education, having children at home, and being hypertensive were identified as the best predictors of physical component score, explaining about 9% of the variance. Age, marital status, having hyperlipidaemia, perceived stress, problem-solving, self-efficacy, binge eating and barriers to healthy eating predicted mental component score, explaining approximately 48% of the variance. Physical functioning and role physical domains of health-related quality of life had similar sets of predictors, with 15% and 13% of the variance explained, respectively, while similar predictors were identified for bodily pain (6%), general health (26%), vitality (40%), social functioning (32%), role emotional (42%) and mental health (46%) domains. CONCLUSIONS:Psychosocial factors were associated with the mental-related quality of life. Further exploration of factors related to physical-related quality of life is warranted in this population. RELEVANCE TO CLINICAL PRACTICE: When working with overweight/obese adults who are trying to lose weight, nurses need to consider socio-demographic and psychosocial factors in the development of a treatment plan that will improve health-related quality of life in this population.
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