Excessive 5-year weight gain predicts metabolic syndrome development in healthy middle-aged adults

Associations of night shift work with weight gain among female nurses in The Netherlands: results of a prospective cohort study

OBJECTIVE

This study aimed to prospectively investigate associations of working night shifts with weight gain in the Nightingale Study, a large cohort of female nurses.

METHODS

This study included 36 273 registered nurses, who completed questionnaires in 2011 and 2017. Cumulative number of nights, mean number of nights/month and consecutive number of nights/month in 2007-2011 were assessed. We used Poisson regression to estimate multivariable-adjusted incidence rate ratios (IRR) of >5% weight gain from 2011 to 2017 among all participants and assess risk of development of overweight/obesity (BMI≥25 kg/m2) among women with healthy baseline body mass index. The reference group consisted of women who never worked nights.

RESULTS

Overall, working night shifts in 2007-2011 was associated with >5% weight gain [IRR 1.07, 95% confidence interval (CI) 1.01-1.13]. Associations differed by menopausal status in 2011, with an increased risk of gaining >5% weight limited to postmenopausal women who worked nights (IRR 1.23, 95% CI 1.10-1.38). Postmenopausal women had an increased risk of >5% weight gain when they worked on average ≥4 nights/month (4-5: IRR 1.29, 95% CI 1.09-1.52, ≥6: IRR 1.27, 95% CI 1.11-1.47) or ≥4 consecutive nights/month (IRR 1.37, 95% CI 1.19-1.58), compared to postmenopausal women who never worked nights. For postmenopausal women with healthy weight at baseline, night shift work was associated with an increased risk of overweight/obesity at follow-up (IRR 1.24, 95% CI 1.03-1.50).

CONCLUSIONS

Working night shifts was associated with a slightly increased risk of weight gain and overweight/obesity development among women who were postmenopausal at study inclusion. Our findings emphasize the importance of health promotion to maintain a healthy weight among (postmenopausal) night workers.

e-Cigarettes, Smoking Cessation, and Weight Change: Retrospective Secondary Analysis of the Evaluating the Efficacy of e-Cigarette Use for Smoking Cessation Trial

BACKGROUND

While smoking cessation has been linked to substantial weight gain, the potential influence of e-cigarettes on weight changes among individuals who use these devices to quit smoking is not fully understood.

OBJECTIVE

This study aims to reanalyze data from the Evaluating the Efficacy of e-Cigarette Use for Smoking Cessation (E3) trial to assess the causal effects of e-cigarette use on change in body weight.

METHODS

This is a secondary analysis of the E3 trial in which participants were randomized into 3 groups: nicotine e-cigarettes plus counseling, nonnicotine e-cigarettes plus counseling, and counseling alone. With adjustment for baseline variables and the follow-up smoking abstinence status, weight changes were compared between the groups from baseline to 12 weeks' follow-up. Intention-to-treat and as-treated analyses were conducted using doubly robust estimation. Further causal analysis used 2 different propensity scoring methods to estimate causal regression curves for 4 smoking-related continuous variables. We evaluated 5 different subsets of data for each method. Selection bias was addressed, and missing data were imputed by the machine learning method extreme gradient boosting (XGBoost).

RESULTS

A total of 257 individuals with measured weight at week 12 (mean age: 52, SD 12 y; women: n=122, 47.5%) were included. Across the 3 treatment groups, of the 257 participants, 204 (79.4%) who continued to smoke had, on average, largely unchanged weight at 12 weeks, with comparable mean weight gain ranging from -0.24 kg to 0.33 kg, while 53 (20.6%) smoking-abstinent participants gained weight, with a mean weight gain ranging from 2.05 kg to 2.70 kg. After adjustment, our analyses showed that the 2 e-cigarette arms exhibited a mean gain of 0.56 kg versus the counseling alone arm. The causal regression curves analysis also showed no strong evidence supporting a causal relationship between weight gain and the 3 e-cigarette-related variables. e-Cigarettes have small and variable causal effects on weight gain associated with smoking cessation.

CONCLUSIONS

In the E3 trial, e-cigarettes seemed to have minimal effects on mitigating the weight gain observed in individuals who smoke and subsequently quit at 3 months. However, given the modest sample size and the potential underuse of e-cigarettes among those randomized to the e-cigarette treatment arms, these results need to be replicated in large, adequately powered trials.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02417467; https://www.clinicaltrials.gov/study/NCT02417467.

Weight Gain After Antiretroviral Therapy Initiation and Subsequent Risk of Metabolic and Cardiovascular Disease

BACKGROUND

Weight gain following initiation of antiretroviral therapy (ART) is common. We assessed the impact of changes in weight in the year following ART initiation with subsequent cardiometabolic disease among AIDS Clinical Trials Group (ACTG) participants.

METHODS

Linear regression models were fit to examine the association between change in weight/waist circumference (WC) in weeks 0-48 and change in metabolic parameters in weeks 0-48 and 48-96. Cox proportional hazard models were fit to examine the association between changes in weight/WC in weeks 0-48 and diabetes mellitus (DM), metabolic syndrome, or cardiometabolic and cardiovascular events after week 48.

RESULTS

Participants (N = 2624) were primarily male (81%) and non-White (60%). Mean weight gain from 0-48 weeks was 3.6 kg (SD 7.3); 130 participants developed DM; 360 metabolic syndrome; 424 any cardiometabolic event; 28 any cardiovascular event, over 480 weeks of follow-up. In adjusted models, total cholesterol increased by 0.63 mg/dL (95% confidence interval [CI] [.38, .089]) and LDL by 0.39 mg/dL (0.19, 0.59) per 1 kg increase in weight from weeks 0 to48. Participants who experienced >10% weight gain (vs -5% to 5%) had an increased risk of DM (hazard ratio [HR] 2.01, 95% CI [1.30, 3.08]), metabolic syndrome (HR 2.24, 95% CI [1.55, 2.62]), and cardiometabolic outcomes (HR 1.54, 95% CI [1.22, 1.95]). Participants who lost more than 5% of their baseline weight had a lower risk of incident metabolic syndrome (HR 0.67, 95% CI [0.42, 1.07]). Trends for WC were similar.

CONCLUSIONS

Weight and body composition changes in the first year following ART initiation are associated with contemporaneous changes in metabolic parameters and subsequent cardiometabolic disease.

Body weight and blood pressure changes on dolutegravir-, efavirenz- or atazanavir-based antiretroviral therapy in Zimbabwe: a longitudinal study

INTRODUCTION

Dolutegravir (DTG) is widely used for antiretroviral therapy (ART). We compared weight and blood pressure trends and examined the association between high blood pressure and weight gain among people living with HIV (PLHIV) switching to or starting DTG-based, efavirenz (EFV)-based and ritonavir-boosted atazanavir (ATV/r)-based ART in Zimbabwe.

METHODS

PLHIV aged 18 years or older who started or switched to DTG, EFV or ATV/r-based ART between January 2004 and June 2022 at Newlands Clinic in Harare, Zimbabwe, were eligible. Weight was measured at all visits (Seca floor scales); blood pressure only at clinician-led visits (Omron M2 sphygmomanometer). We used Bayesian additive models to estimate trends in weight gain and the proportion with high blood pressure (systolic >140 mmHg or diastolic >90 mmHg) in the first 2 years after starting or switching the regimen. Finally, we examined whether trends in the proportion with high blood pressure were related to weight change.

RESULTS

We analysed 99,969 weight and 35,449 blood pressure records from 9487 adults (DTG: 4593; EFV: 3599; ATV/r: 1295). At 24 months after starting or switching to DTG, estimated median weight gains were 4.54 kg (90% credibility interval 3.88-5.28 kg) in women and 3.71 kg (3.07-4.45 kg) in men, around twice that observed for ATV/r and over four-times the gain observed for EFV. Prevalence of high blood pressure among PLHIV receiving DTG-based ART increased from around 5% at baseline to over 20% at 24 months, with no change in PLHIV receiving EFV- or ATV/r-based ART. High blood pressure in PLHIV switching to DTG was associated with weight gain, with stronger increases in the proportion with high blood pressure for larger weight gains.

CONCLUSIONS

Among PLHIV starting ART or switching to a new regimen, DTG-based ART was associated with larger weight gains and a substantial increase in the prevalence of high blood pressure. Routine weight and blood pressure measurement and interventions to lower blood pressure could benefit PLHIV on DTG-based ART. Further studies are needed to elucidate the mechanisms and reversibility of these changes after discontinuation of DTG.

Weight Gain and Increased Body Mass Index in Patients with Hepatitis C after Eradication Using Direct-Acting Antiviral Therapy in Taiwan

Few studies have reported weight gain in patients with hepatitis C virus (HCV) infection treated with direct-acting antiviral agents (DAAs). This retrospective cohort study identified factors associated with substantial weight gain after DAA treatment in Taiwan. This study involved patients treated using DAAs at the Chiayi and Yunlin branches of Chang Gung Memorial Hospital from 1 January 2017 to 31 October 2020. Body weight data were collected at the start of DAA therapy and 2 years after the confirmation of a sustained virologic response. We performed multiple logistic regression to evaluate the clinical and laboratory parameters associated with a large body mass index (BMI) increase (≥5%). The mean BMI was 25.56 ± 4.07 kg/m2 at baseline and 25.77 ± 4.29 kg/m2 at the endpoint (p = 0.005). A considerable reduction in fibrosis-4 (FIB-4) score was a significant predictor of a large BMI increase (OR: 1.168; 95% CI: 1.047-1.304, p = 0.006). By contrast, older age (OR: 0.979; 95% CI: 0.963-0.996, p = 0.013) and a higher baseline BMI (OR: 0.907; 95% CI: 0.863-0.954, p < 0.001) were associated with a reduced risk of a large increase in BMI at the endpoint. In summary, a larger BMI increase was closely associated with a younger age, lower baseline BMI, and higher FIB-4 score reduction. Notably, differences in DAA regimens did not affect outcomes. Future studies are needed to elucidate the long-term effects and metabolic outcomes associated with this body weight change and investigate the exact underlying mechanisms.

Association between weight change and risk of metabolic abnormalities in non-overweight/obese and overweight/obese population: A retrospective cohort study among Chinese adults

OBJECTIVES

To explore the effects of weight change on the risk of metabolic abnormalities in the Chinese population.

METHODS

A total of 1895 metabolically healthy adults aged 21-78 years completed anthropometric and biological measurements at baseline (2012) and at an eight year follow-up (2020). Based on absolute weight change and relative weight change, the participants were split into five classes. A Cox proportional hazards regression model was used to estimate the relative risk (RR) and 95% confidence intervals (95% CI) for the risk of metabolic abnormalities using stable weight as the reference group. Stratified analysis was used to explore this relationship in participants with different baseline body mass index (BMI) levels.

RESULTS

During the follow-up period, 35.41% of the participants retained a stable weight, and 10.71% had metabolic abnormalities. After covariate adjustment, for every kilogram gained over eight years, the risk of developing metabolic abnormalities increased by 22% (RR: 1.094; 95% CI: 1.063-1.127). Compared with stable weight participants, weight gain of 2-4 Kg and weight gain ≥ 4 Kg exhibited significantly higher risks of metabolic abnormalities, with RR of 1.700 (95% CI 1.150-2.513) and 1.981 (95% CI 1.372-2.859), respectively. A weight gain of ≥ 4 Kg had an opposite effect on the overweight/obesity and non-overweight/obesity groups, with an increased risk of metabolic abnormalities only in the non-overweight/obesity group (RR, 2.291; 95% CI, 1.331-3.942). Moreover, weight loss ≥ 4 Kg significantly reduced the risk of metabolic abnormalities only among overweight/obese adults (RR 0.373; 95% CI 0.154-0.906). Similar results were observed in relative body weight change analyses.

CONCLUSIONS

Long-term excessive body weight gain is positively associated with an increased risk of metabolic abnormalities among adults with non-overweight/obesity, whereas long-term body weight loss is a protective factor for metabolic health among adults with overweight/obesity.

Smoking Cessation, Weight Gain, and the Trajectory of Estimated Risk of Coronary Heart Disease: 8-Year Follow-up From a Prospective Cohort Study

Introduction

The effect of weight gain following smoking cessation on cardiovascular risks is unclear. We aimed to prospectively investigate the association of weight gain following smoking cessation with the trajectory of estimated risks of coronary heart disease (CHD).

Methods

In a cohort of 18 562 Japanese male employees aged 30–64 years and initially free of cardiovascular diseases, participants were exclusively grouped into sustained smokers, quitters with weight gain (body weight increase ≥5%), quitters without weight gain (body weight increase <5% or weight loss), and never smokers. Global 10-year CHD risk was annually estimated by using a well-validated prediction model for the Japanese population. Linear mixed models and piecewise linear mixed models were used to compare changes in the estimated 10-year CHD risk by smoking status and weight change following smoking cessation.

Results

During a maximum of 8-year follow-up, both quitters with and without weight gain had a substantially decreased level of estimated 10-year CHD risk after quitting smoking, compared with sustained smokers (all ps for mean differences < .001). The estimated 10-year CHD risk within the first year after cessation decreased more rapidly in quitters without weight gain than in quitters with weight gain (change rate [95% confidence interval, CI] −0.90 [−1.04 to −0.75] vs. −0.40 [−0.60 to −0.19] % per year, p < .0001). Thereafter, the estimated 10-year CHD risk in both groups increased at similar rates (change rate [95% CI] −0.07 [−0.21 to 0.07] vs. 0.11 [−0.09 to 0.30] % per year, p = .16, from year 1 to year 2; and 0.10 [0.05 to 0.15] vs. 0.11 [0.04 to 0.18] % per year, p = .80, from year 2 to year 8).

Conclusions

In this population of middle-aged, Japanese male workers, smoking cessation greatly reduces the estimated 10-year risk of CHD. However, weight gain weakens the beneficial effect of quitting smoking in a temporary and limited fashion.

Implications

To the best of our knowledge, this study is the first to examine the effect of weight gain following smoking cessation on the trajectory of the absolute risk of CHD. Our data imply that the benefits of cessation for reducing the absolute risk of CHD outweigh the potential risk increase due to weight gain, and suggest that in order to maximize the beneficial effects of quitting smoking, interventions to control post-cessation weight gain might be warranted.

Early weight gain predicts later metabolic syndrome in depressed patients treated with antidepressants: Findings from the METADAP cohort

BACKGROUND

Metabolic syndrome (MetS) is a major public health issue. We assessed whether early weight gain predicts later MetS in depressed patients treated with antidepressants.

METHODS

In the 6-month prospective METADAP cohort, 260 non-overweight patients with a Major Depressive Disorder (MDD) and a current Major Depressive Episode (MDE) were assessed for early weight gain (>5%) after one month of treatment, and for the later incidence of MetS after three and six months of treatment. Outcome variables were MetS, the number of MetS criteria, and each MetS criterion (high Waist Circumference (WC), high Blood Pressure (BP), high triglyceridemia (TG), low HDL-Cholesterolemia, and high Fasting Plasma Glucose (FPG). Multivariate models were adjusted for age, sex, previous MDD duration, severity of current MDE, and antidepressants.

RESULTS

24.6% of patients had early weight gain. Compared to those without weight gain, patients with early weight gain had higher MetS incidence: 16.7% vs. 6.9% after 3 months (p = 0.07), and 23.8% vs. 7.1% after 6 months (p = 0.02). Among completers (n = 120), early weight gain was significantly associated with later MetS incidence (OR: 5.5) and a higher number of MetS criteria (IRR: 1.7). This effect was driven by the WC, TG, and HDL-C criteria.

CONCLUSION

Compared to Non-early weight gainers, patients with early weight gain in the first month of antidepressant treatment have a significant higher risk of developing MetS during the 6 months of treatment. Early weight monitoring is recommended in order to set preventive measures to avoid new metabolic syndromes in depressed patients treated with antidepressants.

Longitudinal Changes in Body Fat and Its Distribution in Relation to Cardiometabolic Risk in Black South African Women

BACKGROUND

Ethnic differences in body composition and cardiometabolic risk have been reported in cross-sectional studies. This study aimed to investigate changes in body composition over 5.5 years, and its association with cardiometabolic risk in premenopausal black South African (SA) women.

METHODS

Changes in body composition and body fat distribution (dual-energy x-ray absorptiometry and computerized tomography), fasting glucose, insulin, and lipid concentrations, were measured in 63 black SA women at baseline (age: 27 ± 8 years), and 5.5 years later.

RESULTS

Body weight and fat mass (FM) increased by 6.9 ± 9.9 kg and 4.3 ± 6.9 kg, respectively, over the 5.5 years with a relative (%FM) increase in central and decrease in peripheral FM (all P < 0.05). Fasting glucose and lipid concentrations (except HDL-cholesterol) increased over the follow-up period (all P < 0.05). Both baseline and changes in body fat distribution were associated with cardiometabolic risk. Independent of baseline age, FM and insulin sensitivity, baseline trunk:leg was associated with reduced insulin sensitivity at follow-up (Matsuda index; β = -0.41, P = 0.002). Increasing trunk:gynoid ratio was associated with higher plasma insulin levels (β = 0.31, P = 0.023) and reduced insulin sensitivity (Matsuda index; β = -0.52, P < 0.001) at follow-up.

CONCLUSIONS

Weight gain in free-living black SA women over 5.5 years was associated with a centralization of fat mass, which predicted an increase in cardiometabolic risk.

Supplementary use of HbA1c as hyperglycemic criterion to detect metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS) refers to a cluster of cardiovascular risk factors including hyperglycemia, dyslipidemia, abdominal obesity and hypertension. An effective detection of MetS not only reflects the prediction risk of diabetes mellitus and cardiovascular diseases but also helps to plan for management strategy which could reduce the healthcare burden of the society. This study aimed to compare the use of hemoglobin A1c (HbA1c) to fasting plasma glucose (FPG) as the hyperglycemic component in MetS diagnosis.

METHODS

Waist circumference, blood pressure, blood triglyceride, high-density lipoprotein (HDL)-cholesterol, FPG, and HbA1c were examined in 120 Hong Kong Chinese adults with MetS and 120 without MetS. After reviewing the subject basal characteristics, 11 of them were found with undiagnosed diabetes (FPG ≧7.0 mmol/L) and were excluded for further analysis.

RESULTS

The most prevalent MetS components among the included subjects were elevated systolic blood pressure and central obesity. Significant correlation relationships existed between FPG and HbA1c in both subject pools diagnosed with and without MetS (p < 0.001). The diagnostic rate of MetS using HbA1c was compared to FPG by the receiver operating characteristics (ROC) analysis which suggested an area under curve of 0.807 (95% CI: 0.727 to 0.887). The agreement was 90.7% in MetS-positive group with increased FPG as one of the criterion co-existed with elevated HbA1c. If including HbA1c as an additional criterion to FPG in the MetS diagnosis, 30 more participants in MetS-negative group would be MetS-positive leading to an increase in detection rate. Furthermore, 47 subjects (38 from MetS-positive group and 9 from MetS-negative group) were found having HbA1c ≧6.5%, who would have been diagnosed with diabetes based on the diagnostic criteria implemented by the Expert Group in 2009.

CONCLUSION

These findings suggest that HbA1c enhances the detection of hyperglycemia for the diagnosis of MetS.

Clinical biomarkers in metabolic syndrome

A biomarker can be defined as a measurable variable that may be used as an indicator of a given biological state or condition. Biomarkers have been used in health and disease for diagnostic purposes, as tools to assess effectiveness of nutritional or drug intervention, or as risk markers to predict the development of certain diseases. In nutrition studies, selecting appropriate biomarkers is important to assess compliance, or incidence of a particular dietary component in the biochemistry of the organism, and in the diagnosis and prognosis of nutrition-related diseases. Metabolic syndrome is a cluster of cardiovascular risk factors that occur simultaneously in the same individual, and it is associated with systemic alterations that may involve several organs and tissues. Given its close association with obesity and the increasing prevalence of obesity worldwide, identifying obese individuals at risk for metabolic syndrome is a major clinical priority. Biomarkers for metabolic syndrome are therefore potential important tools to maximize the effectiveness of treatment in subjects who would likely benefit the most. Choice of biomarkers may be challenging due to the complexity of the syndrome, and this article will mainly focus on nutrition biomarkers related to the diagnosis and prognosis of the metabolic syndrome.