Predictors of change in weight and waist circumference: 15-year longitudinal study in Australian adults

Modifiable determinants of central obesity among the rural black population in the DIMAMO HDSS, Limpopo, South Africa

Background

Central obesity is a leading risk factor for cardiometabolic diseases, in which body fat accumulates to a particular extent, and may negatively impact on health. The prevalence of abdominal obesity has increased over the last 10 years and currently surpasses that of overall obesity. There is a scarcity of data on the determinants of central obesity, especially among populations residing in rural Africa. The aim of the present study was thus to determine sociodemographic and lifestyle factors that are associated with central obesity.

Methods

This was a cross-sectional, retrospective study. The present study used secondary data from the AWI-Gen phase 1 study. The study comprised 791 participants, of which 242 were men and 549 were women aged 40 years and above. The participants were selected by convenient sampling. Data were analyzed using the Statistical Package for Social Sciences version 27. A comparison of proportions was performed using the chi-square test, while a comparison of means was performed using an unpaired Student t-test. The association between sociodemographic and lifestyle factors with central obesity was analyzed using bivariate correlation, partial correlation, and binary regression analysis, and the statistical significance was set at a p-value of <0.05.

Results

The proportion of central obesity in the total population was 59.9%, and significantly more women were centrally obese (79.6 vs. 15.3%, p = <0.001) as compared to men. Married status correlated positively and significantly with central obesity in both bivariate and partial correlations. Moreover, binary logistic regression further confirmed the positive association between married status and central obesity. Single status correlated negatively and significantly with central obesity. The correlation remained unchanged even after controlling for age and gender. Binary logistic regression showed that unemployment correlated significantly with central obesity. The proportion of smokers was also significantly higher in participants without central obesity than in those with central obesity (87.2 vs. 34.0%, p = <0.001). Smoking correlated negatively and significantly with central obesity in bivariate and partial correlations. In addition, binary logistic regression further confirmed the negative association between smoking and central obesity.

Conclusion

The present study shows that in this population, central obesity is determined by gender, unemployment, and marital status.

Analysis of Changes in Weight, Waist Circumference, or Both, and All-Cause Mortality in Chinese Adults

IMPORTANCE

Although numerous studies have separately investigated the associations of changes in weight or waist circumference with mortality risk, few studies have examined the associations of concurrent changes in these 2 anthropometric parameters with all-cause mortality.

OBJECTIVE

To assess the associations of changes in body weight, waist circumference, or both, combined with all-cause mortality.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from 2 longitudinal cohort studies in Dongfeng-Tongji and Kailuan, China. Participants included 58 132 adults (aged 40 years and older) with measures of weight and waist circumference at baseline and follow-up visit. Statistical analysis was performed from June 2020 to September 2021.

EXPOSURES

Changes in weight and waist circumference between 2 visits (2008-2010 to 2013 in the Dongfeng-Tongji cohort, and 2006-2007 to 2010-2011 in the Kailuan study). Stable weight was defined as change in weight within 2.5 kg between the 2 visits and stable waist circumference was defined as changes within 3.0 cm. Changes were categorized as loss, stable, or gain for weight and waist circumference separately, and created a 9-category variable to represent the joint changes.

MAIN OUTCOMES AND MEASURES

All-cause mortality from follow-up visit (2013 in Dongfeng-Tongji cohort and 2010-2011 in Kailuan study) until December 31, 2018. Cox proportional hazard regression models were used to estimate the associations with adjustment for potential confounders. Results were obtained in the 2 cohorts separately and pooled via fixed-effect meta-analysis.

RESULTS

A total of 10 951 participants in the Dongfeng-Tongji cohort (median [IQR] age, 62 [56-66] years; 4203 [38.4%] men) and 47 181 participants in the Kailuan study (median [IQR] age, 51 [46-58] years; 36 663 [77.7%] men) were included in the analysis. During 426 072 person-years of follow-up, 4028 deaths (523 in the Dongfeng-Tongji cohort and 3505 in the Kailuan study) were documented. When changes in weight and waist circumference were examined separately, U-shape associations were found: both gain and loss in weight (weight loss: pooled hazard ratio [HR], 1.33; 95% CI, 1.23-1.43; weight gain: HR, 1.10; 95% CI, 1.02-1.19) or waist circumference (waist circumference loss: HR, 1.14; 95% CI, 1.05-1.24; waist circumference gain: HR, 1.11; 95% CI, 1.03-1.21) were associated with higher mortality risk compared with stable weight or waist group. When changes in weight and waist circumference were jointly assessed, compared with participants with stable weight and waist circumference (16.9% of the total population [9828 of 58 132] with 508 deaths), participants with different combinations of weight and waist circumference change all had higher mortality risks except for those with stable weight but significant loss in waist. Notably, those who lost weight but gained waist circumference (6.4% of the total population [3698 of 58 132] with 308 deaths) had the highest risk of all-cause mortality (HR, 1.69; 95% CI, 1.46-1.96; absolute rate difference per 100 000 person-years in the Dongfeng-Tongji cohort: 414; 95% CI, 116-819; and in the Kailuan study: 333; 95% CI, 195-492) among the joint subgroups.

CONCLUSIONS AND RELEVANCE

In this cohort study, weight loss with concurrent waist circumference gain was associated with a higher mortality risk in middle-aged and older Chinese adults. This study's findings suggest the importance of evaluating the changes in both body weight and waist circumference when assessing their associations with mortality.

Change in waist circumference and lifestyle habit factors as a predictor of metabolic risk among middle-aged and elderly Japanese people: population-based retrospective 10-year follow-up study from 2008 to 2017

Background

Waist circumference (WC) increases more than body mass index (BMI) over time. This study investigated the change in WC among middle-aged and elderly Japanese people for 10 years, and its relationship with lifestyle and lipid metabolism factor.

Methods

Health checkup data and lifestyle habits of a retrospective cohort of 745 people aged 40–65 years who underwent health checkups at least three times between 2008 and 2017 were analyzed. Information of Lifestyle habits about smoking history, regular exercise, alcohol intake skipping breakfast was collected using a self-administered questionnaire. Participants who were taking medications for diabetes, hyperlipidemia, or hypertension were excluded from analyses. Longitudinal associations between the change in WC and lifestyle habit factors with adjustments for sex, age, and WC at the start of health checkups were assessed using generalized linear models.

Results

Regardless of lifestyle, body weight (BW) decreased 0.8 kg (p < 0.001) for women, 0.9 kg (p = 0.003) for men, WC increased 0.8 cm (p = 0.007) for women, 0.2 cm (p = 0.657) for men. In addition, serum triglycerides and high- and low-density lipoprotein levels estimated 10 years later revealed that increased WC ratios also exacerbated the respective blood sample data.

Conclusion

Both men and women showed an increase in WC regardless of BW changes, and the increase in WC worsened lipid metabolism. For the middle-aged and elderly, whose WC increases over time, it will be more important to take notice of their WC than BW or BMI for effective health checkups.

10-Year Weight Gain in 13,802 US Adults: The Role of Age, Sex, and Race

PURPOSE

The primary objective of the present investigation was to identify 10-year weight gain patterns in 13,802 US adults and also to determine the extent that differences in 10-year weight gains were associated with the key demographic variables: age, sex, and race.

METHODS

The study design was cross-sectional and included the years 2011-2018. Data for 2019-2020 were not available because of COVID. A multistage random sampling strategy was employed. Specifically, individual sample weights and randomly selected clusters and strata were used with each statistical model, allowing the results to be generalized to the US adult population.

RESULTS

Mean (±SE) 10-year weight gain was 4.2 ± 0.2 kg or 6.6 ± 0.2% of initial body weight. A total of 51% of the participants gained 5% or more body weight, 36% gained 10% or more, and 16% gained 20% or more across the 10-years. Age was linearly and inversely associated with 10-year weight gain, expressed in kg (F = 166.4, P < 0.0001) or percent weight gain (F = 246.9, P < 0.0001), after adjusting for sex and race. For each 1-year increase in age, 10-year weight gain decreased by 0.20 ± 0.02 kg and 0.28 ± 0.02 percent. After adjusting for age and race, 10-year weight gain (kg) was significantly greater (F = 73.6, P < 0.0001) in women (5.4 ± 0.3) than in men (2.6 ± 0.2). Weight gain also differed across races, kg (F = 27.7, P < 0.0001) and % (F = 28.5, P < 0.0001). Non-Hispanic Blacks gained more weight and NH Asians gained less weight than the other races.

CONCLUSION

Without question, 10-year weight gain is a serious problem within the US adult population. Younger adults, women, and Non-Hispanic Blacks, particularly Black women, seem to experience the highest levels of 10-year weight gain. Consequently, obesity and weight gain prevention programs focusing on these at-risk individuals should be a public health priority.

Prevalence of general and abdominal obesity and its relationship with opium, total opiate drugs, and chronic smoking: Fasa cohort study

BACKGROUND AND AIMS

Obesity and drug use are two major global issues today. This study aimed to evaluate the relationship between alcohol and tobacco use with general and central obesity.

METHODS

The data of the longitudinal population-based study were collected from the basis of the Fasa Cohort Study (FACS). Participants were 10141 people with 35-70 years old. Data were analyzed by SPSS 20 software. Binary logistic regression (BLR) was used for modelling. A significance level (α) less than 0.05% was considered for hypothesis testing.

RESULTS

Of the total participants (N = 10104), 54.8% (n = 5539) were women. The prevalence of central obesity in terms of waist circumference (WC), waist to hip ratio (WHR), and waist to height ratio (WHtR) were calculated 48.20% (N = 4871), 79.50% (N = 8032), and 83.30% (N = 8314). The Odds Ratio (OR) adjusted of Abnormal body mass index (BMI) for Opium and chronic smoking were 0.54 (CI: 0.47-0.63) and 0.47 (CI:0.40-0.56). OR adjusted Abnormal WC for opium and chronic smoking were calculated 0.65 (CI: 0.53-0.80) and 0.57 (CI:0.46-0.72), respectively. Three variables of opium (OR = 0.54, CI: 0.46-0.64), total opiate drugs (OR = 1.46, CI:1.16-1.83) and chronic smoking (OR = 0.58, CI: 0.48-0.70) remained in the modeling for Abnormal WHR. Which were statistically significant.

CONCLUSION

Significant and inverse relationships were found between obesity and opium, total opiate drugs, and chronic smoking.

Analyzing the Influence of Wine and Beer Drinking, Smoking, and Leisure Time Screen Viewing Activity on Body Weight: A Cross-Sectional Study in Germany

The increasing global prevalence of overweight and obesity highlights an urgent need to explore modifiable obesogenic factors. This study investigated the impact of lifestyle factors, such as beer and wine drinking, cigarette smoking, and leisure time screen viewing activities, on body weight and the development of obesity. Individual level data were selected from a random sample of 3471 German adults using a two-stage disproportionate random sampling procedure. The empirical analysis employed a two-stage equations system and combined the endogenous treatment effects model with the quantile regression technique. Our estimations showed that the decisions to smoke and consume wine and beer were positively interrelated, especially in women. Frequent beer/wine drinkers of normal weight were found to have a lower BMI in the male subsample. Quantile regression estimates indicated a significant influence of smoking on BMI in both genders, with smokers’ BMI following an upward trend, especially in the upper quantiles of the distribution. Leisure time screen activity was found to have a major impact on females’ BMI. Prolonged television viewing and regular computer gaming had a strong relationship with weight increase in overweight women, whereas internet surfing was inversely correlated with the BMI of normal weight and slightly overweight female participants. Nutrition and health policies should direct individuals toward alternative recreational activities in order to substitute screen usage and reduce sedentary time. This study also raised doubts about the general belief that smokers have a lower body weight. As unhealthy behaviors usually co-occur or cluster together, obesity prevention interventions might also contribute to a decrease in smoking.

Contribution of vitamin D status as a determinant of cardiometabolic risk factors: a structural equation model, National Food and Nutrition Surveillance

Background

Structural equation modeling (SEM) is a method used to evaluate linear causal relationships among variables. This study aimed to investigate the direct and indirect effects of serum 25(OH) D on certain cardiovascular risk factors using SEM.

Methods

An analytical cross-sectional study was conducted in six provinces of Iran. Subjects (n = 922), aged 19–65 years, were selected from National Food and Nutrition Surveillance. The assessments were sun-exposure behavior, anthropometric and biochemical measurements. A series of SEM models were tested and the model with the best fit indices was considered for use in the structural part of the model. Based on the literature review of previous theoretical models and supporting bivariate analyses, an overall SEM examined direct or indirect associations among observed and latent variables. We put the demographic, duration of sun exposure, anthropometric and metabolic variables in our model.

Results

The paths between serum 25(OH) D and BMI were inverse and statistically significant, whereas age showed a positive association with BMI (B = 0.06, p < 0.001), both direct (st. effect = 0.11, p = 0.01) and indirect via vitamin D (st. effect = − 0.02, p = 0.01). The results confirmed that serum 25(OH) D concentration is a predictor for latent variable of lipid profile (B = − 0.13, p = 0.01) both through direct (p = 0.02) and indirect effects via BMI (p = 0.01).

Conclusion

Serum 25(OH) D concentration is a predictor of BMI and also a latent variable of lipid profile via direct and indirect effects. It can also attenuate the harmful effect of age on BMI and lipid profile particularly in women.

Successful weight maintainers among young adults-A ten-year prospective population study

OBJECTIVES

To assess factors associated with successful weight maintenance over ten years in a prospective general population sample of young adults.

MATERIAL AND METHODS

Our study comprised 2452 women and 2227 men born in 1975-1979 (mean age at baseline 24 years, attrition 27.1%). Weight maintenance was defined as weight maintained within ±5% of baseline body mass index (BMI). We examined the role of various sociodemographic and lifestyle factors in successful weight maintenance.

RESULTS

Relatively few young adults were able to maintain their weight over ten years (28.6% of women vs. 23.0% of men); net weight loss was uncommon (7.5% and 3.8%). Most participants gained weight (mean annual weight gain was 0.9 kg in women and 1.0 kg in men). Among women, exercise was associated with successful weight maintenance, but having two or more children, frequent use of sweet drinks, irregular eating, history of dieting (intentional weight loss) and low life satisfaction were associated with weight gain. Among men, higher baseline BMI and higher education were associated with successful weight maintenance, whereas irregular eating, history of dieting and smoking were associated with weight gain.

CONCLUSIONS

Only about a quarter of young adults were able to resist weight gain. Regular eating and having no history of dieting were associated with successful weight maintenance in young women and men.

Will I get fat? 22-year weight trajectories of individuals with eating disorders

OBJECTIVE

For some, fat phobia or fear of uncontrollable weight gain is diagnostic of eating disorders, often inhibiting treatment engagement and predicting symptom relapse. Prior research has reported weight changes at infrequent or long intervals, but rate, shape, and magnitude of long-term changes remain unknown. Our study examined 22-year longitudinal trajectories of body mass index (BMI) in women with anorexia nervosa (AN) and bulimia nervosa (BN).

METHOD

Participants were followed over 10 years (N = 225) and at 22-year follow-up (N = 175). Using latent growth curves, we examined: (1) shape and rate of intra-individual BMI change over 10 years; (2) predictors of BMI change over 10 years, (3) 22-year BMI outcomes; and (4) BMI changes over 10 years as predictors of 22-year BMI.

RESULTS

The best-fitting model captured overall intra-individual rates of BMI change in three intervals, showing moderate rate of BMI increase from intake to year 2, modest increase from year 2 to 5, and plateau from year 5 to 10. At 22 years, 14% were underweight, 69% were normal weight, and only 17% were overweight or obese. Greater increases from intake to year 2 predicted higher BMI at 22 years (β = 0.43, p < 0.01) and were predicted by intake diagnosis of AN-restricting (β = 0.31, p < 0.01) or AN-binge eating/purging (β = 0.29, p < 0.01).

DISCUSSION

BMI increased most rapidly during earlier years of the study for those with lower weight at study intake (i. e., AN) and plateaued over time, settling in the normal range for most. Psychoeducation about expected BMI trajectory may challenge patients' long-term fat phobic predictions.

Predictors of BMI Vary along the BMI Range of German Adults - Results of the German National Nutrition Survey II

OBJECTIVE

The objective of the study was to identify predictors of BMI in German adults by considering the BMI distribution and to determine whether the association between BMI and its predictors varies along the BMI distribution.

METHODS

The sample included 9,214 adults aged 18-80 years from the German National Nutrition Survey II (NVS II). Quantile regression analyses were conducted to examine the association between BMI and the following predictors: age, sports activities, socio-economic status (SES), healthy eating index-NVS II (HEI-NVS II), dietary knowledge, sleeping duration and energy intake as well as status of smoking, partner relationship and self-reported health.

RESULTS

Age, SES, self-reported health status, sports activities and energy intake were the strongest predictors of BMI. The important outcome of this study is that the association between BMI and its predictors varies along the BMI distribution. Especially, energy intake, health status and SES were marginally associated with BMI in normal-weight subjects; this relationships became stronger in the range of overweight, and were strongest in the range of obesity.

CONCLUSIONS

Predictors of BMI and the strength of these associations vary across the BMI distribution in German adults. Consequently, to identify predictors of BMI, the entire BMI distribution should be considered.

Alcohol Consumption and Obesity: An Update

Recreational alcohol intake is a widespread activity globally and alcohol energy (7 kcal/g) can be a contributing factor to weight gain if not compensated for. Given that both excessive alcohol intake and obesity are of public health interest, the present paper provides an update on the association between alcohol consumption and body weight. In general, recent prospective studies show that light-to-moderate alcohol intake is not associated with adiposity gain while heavy drinking is more consistently related to weight gain. Experimental evidence is also mixed and suggests that moderate intake of alcohol does not lead to weight gain over short follow-up periods. However, many factors can explain the conflicting findings and a better characterization of individuals more likely to gain weight as a result of alcohol consumption is needed. In particular, individuals who frequently drink moderate amounts of alcohol may enjoy a healthier lifestyle in general that may protect them from weight gain. In conclusion, despite the important limitations of current studies, it is reasonable to say that alcohol intake may be a risk factor for obesity in some individuals, likely based on a multitude of factors, some of which are discussed herein.