Frequency of Breakfast and Meals in Relation to Weight Change in a Cohort of Mexican Women (P18-031-19)

Abstract Objectives To evaluate weight change between 2008 and 2011 in relation to the frequency of breakfast and meals. Methods Data were obtained from 60,946 women from the Mexican Teacher's cohort. Lifestyle, diet, and anthropometric data were obtained by self-report. Frequency of breakfast and meals were categorized (0, 1–3, 4–6, or 7 day/week; 1–2, 3–4, or >5 times/day). We used linear and logistic regression to analyze weight change continuous or dichotomized as significant weight change (>5 kg). Models were adjusted for sociodemographic, dietary and lifestyle factors. Results Women who ate breakfast daily obtained an odds ratio (OR) of 0.95; (95% confidence interval (CI) 0.88, 1.03) versus women who did not have breakfast any day of the week (reference category). As the frequency of breakfast increased, the tendency to gain weight increased (P-trend = 0.07). Daily breakfast decreased the chance of gaining 5 kg in women with BMI 18–24.9 m/kg2, (OR 0.86; CI 0.75, 0.99). In this group of women, the odds of gaining 5 kg in 3 years decreased as the weekly breakfast frequency increased (P-trend < 0.02). Women who consumed 5 meals a day gained 300 g more than women who consumed 3–4 meals a day (CI = .170 g, .480 g). Weight gain was greater as the number of meals per day increased (P-trend < .0001). Women who had 5 or more meals a day were 22% more likely gain 5 kg than women who had 3–4 meals a day (OR 1.22; CI 1.14, 1.31). This trend increased as the frequency of meals increased (P-trend < .0001). Conclusions The effect of breakfast is not clear, however it seems to have a protective role. The number of meals showed an important relationship with weight gain among Mexican women. Funding Sources This work was supported by the American Institute for Cancer Research, National Council of Science and Technology and Ministry of Health Mexico.

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The Influence of Food Reinforcement and Eating Disorder Pathology on Weight Change in Adolescents (P21-057-19)

Current Developments in Nutrition ◽

10.1093/cdn/nzz041.p21-057-19 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

Author(s):

Katherine Balantekin ◽

Amanda Crandall ◽

Amanda Ziegler ◽

Jennifer Temple

Keyword(s):

Eating Disorder ◽

Weight Gain ◽

Weight Change ◽

Weight Status ◽

Food Reinforcement ◽

Self Report ◽

Schedules Of Reinforcement ◽

Eating Disorder Examination ◽

Funding Sources ◽

Median Split

Abstract Objectives Both the relative reinforcing value (RRV) of food, or the motivation to obtain food, and eating disorder (ED) pathology have been shown to independently predict weight gain. However, less is known about how the interaction between the RRV of food and ED pathology predicts weight gain over time. Therefore, the purpose of this study was to examine the combined effects of the RRV of food and ED pathology on weight change over 6 months in a sample of adolescents. Methods Participants included 77 12–14 year old adolescents participating in a longitudinal study examining factors that predict changes in weight status. Data presented are from baseline and 6 months. The RRV of food was assessed using a computer task. Participants earned points for energy dense food by pressing a mouse button on a computer across escalating schedules of reinforcement. Participants were classified as “low” or “high” in RRV based on a median split of their total responses. Global ED pathology was assessed at baseline using adolescent self-report on the Eating Disorder Examination Questionnaire. Participants were classified as “low” or “high” in ED pathology based on a median split of their global ED pathology. Four groups were created: low ED pathology/low RRV (n = 20), high ED pathology/low RRV (n = 23), low ED pathology/high RRV (n = 15), and high ED pathology/high RRV (n = 19). Height and weight were measured at both baseline and 6 months and used to calculate zBMI. ANOVA was used to examine differences in zBMI change over 6 months by RRV/ED pathology group. Results zBMI change from baseline to 6 months differed by RRV/ED pathology group (P < .05). Changes in zBMI over 6 months were as follows: - 0.025 ± 0.298 for low ED pathology/low RRV; 0.010 ± 0.322 for high ED pathology/low RRV; - 0.095 ± 0.181 for low ED pathology/high RRV; and 0.186 ± 0.268 for high ED pathology/high RRV. Follow-up contrasts revealed that the high ED pathology/high RRV group experienced greater zBMI changes than the other groups (ps < 0.05). Conclusions While the RRV of food and ED pathology are both independently associated with weight gain, the current study indicates that there may be something unique about the combination of high RRV of food and high ED pathology related to risk of weight gain. Future work is needed to identify strategies to limit weight gain in this vulnerable population. Funding Sources National Institutes of Health.

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Breakfast Frequency Is Inversely Associated with Weight Gain in a Cohort of Mexican Women

Journal of Nutrition ◽

10.1093/jn/nxaa367 ◽

2020 ◽

Author(s):

Claudia F Martínez ◽

Eduardo Ortiz-Panozo ◽

Josiemer Mattei ◽

Hannia Campos ◽

Mario Flores-Aldana ◽

...

Keyword(s):

Body Weight ◽

Weight Gain ◽

Weight Change ◽

Weight Control ◽

Prevalence Ratio ◽

Continuous Variable ◽

Normal Weight ◽

Mexican Women ◽

Body Weight Change ◽

Regular Consumption

ABSTRACT Background Food timing affects circadian rhythms involved in weight control. Regular consumption of breakfast may affect body weight. Objective We examined the relation between breakfast frequency with weight change in middle-age women over a 3-y period. Methods We used data from 65,099 nonpregnant women aged >20 y participating in the Mexican Teachers’ Cohort (MTC) who at baseline (2006–2008) were cancer free and for whom self-reported breakfast frequency at baseline was available. We analyzed body weight change between baseline and the first follow-up (2011) according to breakfast frequency. Participants were classified according to baseline breakfast frequency 0, 1–3, 4–6, or 7 d/wk and meal frequency 1–2, 3–4, or ≥5 meals/d. We used linear and modified Poisson regression to analyze body weight change as a continuous variable and for weight gain ≥5 kg (yes/no), respectively. Models were adjusted for sociodemographic and lifestyle confounders. Results At baseline, 25% of participants were daily breakfast consumers and 18.4% of women increased ≥5 kg between 2008 and 2011. The prevalence of weight gain ≥5 kg among daily breakfast consumers was 7% lower than among those who skipped breakfast (prevalence ratio: 0.93; 95% CI: 0.89, 0.97; P-trend = 0.02). The association was stronger among normal-weight women at baseline with a corresponding estimate of 0.87 (95% CI: 0.79, 0.97; P-trend = 0.02). Conclusion Daily breakfast consumption was inversely associated with weight gain ≥5 kg over 3 y in middle-aged Mexican women. Regular breakfast may be an important dietary factor for body weight change.

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The Relationship between Change of Weight and Chronic Low Back Pain in Population over 50 Years of Age: A Nationwide Cross-Sectional Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083969 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3969

Author(s):

Choung Ah Lee ◽

Hae-Dong Jang ◽

Ji Eun Moon ◽

Sangsoo Han

Keyword(s):

Low Back Pain ◽

Back Pain ◽

Weight Gain ◽

General Population ◽

Weight Change ◽

Self Report ◽

Low Back ◽

Sampling Weights ◽

Increased Risk ◽

The Relationship

Introduction: There is increasing evidence supporting an association between obesity and low back pain (LBP). However, the association between weight change and LBP in the general population is poorly understood. We investigated the relationship between weight change and LBP in a representative sample of the Korean general population from a nationwide survey. Methods: We analyzed data collected from the Korea National Health and Nutrition Examination Survey VI (2013–2015). Chronic LBP was defined as LBP lasting over 30 days in the last 3 months in the self-report health survey. Weight change was defined as the difference in weight from one year prior, and the amount of change was divided into no change, 3–6 kg, and ≥6 kg. Sampling weights were used to generate representative estimates for the general Korean population. Results: Overall, 6629 (12.0%) and 1848 (11.5%) participants were in the non-LBP and LBP groups, respectively. On multiple regression analysis, weight gain was significantly associated with LBP (adjusted odds ratio (OR) 1.29, p = 0.011), compared with no weight change. Weight gain of ≥6 kg was particularly closely associated with LBP (adjusted OR 1.42, p = 0.037), compared with no weight change. No association was found between LBP and weight loss. Conclusion: Weight gain is significantly associated with chronic LBP and, in particular, the greater the amount of weight gain, the stronger the association with an increased risk of chronic LBP. Clinicians should carefully monitor weight gain in LBP patients.

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Global Impact of COVID-19 on Weight and Weight-Related Behaviors in the Adult Population: A Scoping Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041876 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1876

Author(s):

Han Shi Jocelyn Chew ◽

Violeta Lopez

Keyword(s):

Weight Gain ◽

Scoping Review ◽

Screen Time ◽

Weight Status ◽

Adult Population ◽

Self Report ◽

Future Research ◽

Sedentary Behaviors ◽

Management Interventions ◽

The Impact

Objective: To provide an overview of what is known about the impact of COVID-19 on weight and weight-related behaviors. Methods: Systematic scoping review using the Arksey and O’Malley methodology. Results: A total of 19 out of 396 articles were included. All studies were conducted using online self-report surveys. The average age of respondents ranged from 19 to 47 years old, comprised of more females. Almost one-half and one-fifth of the respondents gained and lost weight during the COVID-19 pandemic, respectively. Among articles that examined weight, diet and physical activity changes concurrently, weight gain was reported alongside a 36.3% to 59.6% increase in total food consumption and a 67.4% to 61.4% decrease in physical activities. Weight gain predictors included female sex, middle-age, increased appetite, snacking after dinner, less physical exercise, sedentary behaviors of ≥6 h/day, low water consumption and less sleep at night. Included articles did not illustrate significant associations between alcohol consumption, screen time, education, place of living and employment status, although sedentary behaviors, including screen time, did increase significantly. Conclusions: Examining behavioral differences alone is insufficient in predicting weight status. Future research could examine differences in personality and coping mechanisms to design more personalized and effective weight management interventions.

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Overcoming limitations of self-report: an assessment of fear of weight gain in anorexia nervosa and healthy controls using implicit association tests

Journal of Eating Disorders ◽

10.1186/s40337-021-00379-8 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Tiana Borgers ◽

Nathalie Krüger ◽

Silja Vocks ◽

Jennifer J. Thomas ◽

Franziska Plessow ◽

...

Keyword(s):

Anorexia Nervosa ◽

Weight Gain ◽

Normal Weight ◽

Self Report ◽

Healthy Controls ◽

Drive For Thinness ◽

Implicit Association ◽

Association Tests ◽

Implicit Assessment ◽

Fear Of Weight Gain

Abstract Background Fear of weight gain is a characteristic feature of anorexia nervosa (AN), and reducing this fear is often a main target of treatment. However, research shows that 20% of individuals with AN do not report fear of weight gain. Studies are needed that evaluate the centrality of fear of weight gain for AN with a method less susceptible to deception than self-report. Methods We approximated implicit fear of weight gain by measuring implicit drive for thinness using implicit association tests (IATs). We asked 64 participants (35 AN, 29 healthy controls [HCs]) to categorize statements as pro-dieting vs. non-dieting and true vs. false in a questionnaire-based IAT, and pictures of underweight vs. normal-weight models and positive vs. negative words in a picture-based IAT using two response keys. We tested for associations between implicit drive for thinness and explicitly reported psychopathology within AN as well as group differences between AN and HC groups. Results Correlation analyses within the AN group showed that higher implicit drive for thinness was associated with more pronounced eating disorder-specific psychopathology. Furthermore, the AN group showed a stronger implicit drive for thinness than HCs in both IATs. Conclusion The results highlight the relevance of considering fear of weight gain as a continuous construct. Our implicit assessment captures various degrees of fear of weight gain in AN, which might allow for more individually tailored interventions in the future.

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Depression-related weight change and incident diabetes in a community sample

Scientific Reports ◽

10.1038/s41598-021-92963-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Eva Graham ◽

Tristan Watson ◽

Sonya S. Deschênes ◽

Kristian B. Filion ◽

Mélanie Henderson ◽

...

Keyword(s):

Type 2 Diabetes ◽

Weight Loss ◽

Weight Gain ◽

Weight Change ◽

Short Form ◽

Community Sample ◽

Overweight And Obesity ◽

Community Dwelling ◽

Increased Risk

AbstractThis cohort study aimed to compare the incidence of type 2 diabetes in adults with depression-related weight gain, depression-related weight loss, depression with no weight change, and no depression. The study sample included 59,315 community-dwelling adults in Ontario, Canada. Depression-related weight change in the past 12 months was measured using the Composite International Diagnostic Interview—Short Form. Participants were followed for up to 20 years using administrative health data. Cox proportional hazards models compared the incidence of type 2 diabetes in adults with depression-related weight change and in adults with no depression. Adults with depression-related weight gain had an increased risk of type 2 diabetes compared to adults no depression (HR 1.70, 95% CI 1.32–2.20), adults with depression-related weight loss (HR 1.62, 95% CI 1.09–2.42), and adults with depression with no weight change (HR 1.39, 95% CI 1.03–1.86). Adults with depression with no weight change also had an increased risk of type 2 diabetes compared to those with no depression (HR 1.23, 95% CI 1.04–1.45). Associations were stronger among women and persisted after adjusting for attained overweight and obesity. Identifying symptoms of weight change in depression may aid in identifying adults at higher risk of type 2 diabetes and in developing tailored prevention strategies.

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1043. The impact of integrase strand transfer inhibitors (InSTIs) on weight gain among adults with HIV in clinical care

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1229 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S551-S551

Author(s):

Sneha Thatipelli ◽

Chad Achenbach ◽

Shannon Galvin

Keyword(s):

Weight Gain ◽

Weight Change ◽

Metabolic Diseases ◽

Clinical Care ◽

First Year ◽

Strand Transfer ◽

Art Initiation ◽

Integrase Strand Transfer Inhibitors ◽

Clinically Significant ◽

The Impact

Abstract Background Integrase strand transfer inhibitors (InSTIs) as ART for HIV has been associated with clinically significant weight gain, in addition to the “return to health phenomenon”. Methods We conducted a cohort study on adults over 18 with HIV, who had baseline weights and an additional weight at least 6 months later. Individuals with malignancies, thyroid disorders, and disseminated tuberculosis or mycobacterium avium complex were excluded. To understand the impact of InSTIs on chronic vs. recently infected persons, we divided the cohort into four groups: (1) well-controlled on non-InSTI ART [WN] (2) well-controlled on InSTI ART [WI] (3) uncontrolled on non-InSTI ART [UN], and (4) uncontrolled on InSTI ART [UI]. Well-controlled persons (viral load < 2000) were proxies for chronic infection on long-term ART and uncontrolled for recently infected and initiated on ART. New diagnoses of diabetes, hyperlipidemia, and hypertension were determined by ICD10 codes. Participants with a weight change more than 10 kg in 6 months were excluded. Results 612 of the initial 910 participants in the cohort met the inclusion criteria. Comparing those who remained on the designated regimen throughout the study led to 86 WN, 153 WI, 166 UN, and 145 UI. Mean weight change at 6 months for WN was +0.22 kg (95% CI [-0.86, 1.3]), at 1 year was -0.86 kg (95% CI [-2.94, 1.22]), and at 2 years was +0.026 kg (95% CI [-2.347, 2.399]). For WI, mean weight change at 6 months was +0.21 kg (95% CI [-0.79, 1.21]), at 1 year was -0.50 kg (95% CI [-2.02, 1.04]), and at 2 years was +0.43 kg (95% CI [-1.35, 2.21]). UN gained weight until the first year (+1.74 kg at 6 mo (95% CI [0.24, 3.24]) and +3.84 kg at 1 year (95% CI [1.57, 6.11])), but plateaued at 2 years (+2.42 kg (95% CI [-0.44, 5.28])). At 6 months mean weight gain for UI was +0.78 kg (95% CI [-0.15, 1.71]), at 1 year was +2.33 kg (95% CI [1.02, 3.64]), and at 2 years was +3.04 kg (95% CI [1.2, 4.85]). WI had a higher incidence of diabetes (37% vs. 32%, p=0.40), hyperlipidemia (32% vs. 29%, p=0.66), and hypertension (34% vs. 26%, p=0.19) compared to WN. Conclusion InSTIs may confer a larger and more sustained weight gain among individuals in the first two years after ART initiation. Well controlled individuals did not have statistically significant weight change, but those on Insti-based ART had more metabolic diseases. Disclosures All Authors: No reported disclosures

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Abstract 13946: Sleep Problems on Simvastatin Differentially Predict Weight Change in Men

Circulation ◽

10.1161/circ.130.suppl_2.13946 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Beatrice A Golomb ◽

Hayley J Koslik ◽

Alexis K Bui

Keyword(s):

Young Adults ◽

Weight Gain ◽

Weight Change ◽

Sleep Problems ◽

Metabolic Effects ◽

Muscle Loss ◽

Relative Contribution ◽

Age Related ◽

Baseline Weight ◽

Interaction Term

Background and Goal: Sleep problems were significantly increased on simvastatin ( simva ) (but not pravastatin) vs placebo in the UCSD Statin Study. Sleep problems on simva predicted glucose rise. Weight gain has also been reported as a statin side effect. We sought to capitalize on existing data to assess whether sleep problems on simva related to weight gain in men. Method: 442 men without known diabetes or CVD were randomized to simva 20mg or placebo for 6 mon. One hundred eighty and 186 completed single-item self-rating of change in sleep problems vs baseline ( Δslpprob ). Weight (lb) was measured at baseline and 6 mon. Missing 6 mon values were imputed. Analyses: A. Regressions stratified by treatment assessed prediction of weight change by Δslpprob, adjusted for baseline weight. B. Regressions assessed prediction of weight change by the interaction term of simva (vs placebo) x Δslpprob, adjusted for the components of the interaction and baseline weight. Since age-related muscle loss may complicate weight change in elderly; and young adults have low vulnerability to metabolic problems, analyses were repeated excluding these groups. Results: A. Increased sleep problems on simva predicted weight gain (significant), but on placebo predicted weight loss (nonsignificant). B. The Δslpprob x simva interaction term significantly predicted weight gain. When that was parceled out, simva, outside of the sleep relationship, negatively predicted weight change. Exclusion of young adults and elderly strengthened significance of findings (Table). Discussion: Sleep problems, which differentially arise on simva, differentially predict weight gain on simva. This expands the metabolic effects to which sleep problems on simva may contribute and might possibly favor mediation by sleep apnea (a reported complication of simva). Once the sleep problem effect is considered, simva use predicted weight loss . The relative contribution of fat vs muscle loss (vs other) requires exploration.

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Patterns of weight change in a weight gain prevention study for young adults

Obesity ◽

10.1002/oby.23268 ◽

2021 ◽

Author(s):

Jacqueline F. Hayes ◽

Deborah F. Tate ◽

Mark A. Espeland ◽

Jessica Gokee LaRose ◽

Amy A. Gorin ◽

...

Keyword(s):

Young Adults ◽

Weight Gain ◽

Weight Change ◽

Weight Gain Prevention ◽

Prevention Study

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Abstract MP88: Neighborhood-Level Socioeconomic Deprivation Predicts Weight Gain in a Multi-Ethnic Population: Longitudinal Data from the Dallas Heart Study

Circulation ◽

10.1161/circ.127.suppl_12.amp88 ◽

2013 ◽

Vol 127 (suppl_12) ◽

Author(s):

Priscilla Agyemang ◽

Colby Ayers ◽

Min Lian ◽

Sandeep Das ◽

Christine Hoehner ◽

...

Keyword(s):

Physical Activity ◽

Weight Gain ◽

Weight Change ◽

Socioeconomic Deprivation ◽

Neighborhood Environment ◽

Dallas County ◽

Heart Study ◽

Deprived Neighborhoods ◽

Dallas Heart Study ◽

Neighborhood Level

Background: Although neighborhood-level socioeconomic deprivation associates with prevalent obesity, its relationship to individual-level weight change over time is poorly elucidated. Few studies have evaluated the impact of behavioral and psychosocial factors on this relationship. Methods: We examined the relationship between neighborhood-level socioeconomic deprivation and weight change among those who did not move in the 7-year study period (N=955) of the Dallas Heart Study (DHS), a multi-ethnic, population-based sample of Dallas County residents aged 18-65. Baseline weight measurements were performed in 2000-02 and weight was re-measured at 7-year follow-up. Home addresses obtained at baseline and follow-up were geocoded and linked to residential census tracts in Dallas County. A neighborhood deprivation index (NDI) for DHS participants was created using factor analysis of 21 census-tract neighborhood characteristics, with higher scores indicating more socioeconomic deprivation. Repeated-measures linear mixed modeling with random effects was used to determine weight change (kg) relative to tertiles of NDI. Reported physical activity (yes/no: exercised <150 mets/min-wk) and perceptions of neighborhood environment (questionnaire-derived score with higher score = more unfavorable perceptions of neighborhood violence, aesthetics, and social cohesion) were examined as mediators. Results: DHS participants living in more socioeconomically deprived neighborhoods had lower income and education (p-trend <0.001 for both). Blacks were more likely to live in more socioeconomically deprived neighborhoods than whites and Hispanics (p<0.001). Adjusting for age, sex, race, smoking, education, and income as fixed effects, DHS participants living in the most socioeconomically deprived neighborhoods (highest NDI tertile) gained 5.8±2.5 more kilograms (p=0.02) over the 7-year period compared to those in the least deprived neighborhoods. Living in the most socioeconomically deprived neighborhoods remained associated with a 6.4±2.5 kg greater increase in weight (p=0.01) compared to living in the least deprived neighborhoods after adjustment for physical activity levels and a 6.6±2.6 kg greater increase in weight (p=0.01) after adjustment for perceptions of neighborhood environment. Conclusions: Living in more socioeconomically deprived neighborhoods is associated with greater weight gain among DHS participants over a 7-year period. This relationship does not appear to be fully explained by lower levels of physical activity or unfavorable perceptions of the neighborhood environment. In Dallas County, the high risk for greater weight gain among people living in socioeconomically deprived neighborhoods supports the need to develop targeted community-based interventions to address obesity and reduce disparities in cardiovascular risk.

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