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Early weight gain after stopping smoking: a predictor of overall large weight gain? A single-site retrospective cohort study.

ABSTRACT: OBJECTIVES:Most people gain weight on stopping smoking but the extent of weight gain varies greatly. Interventions aimed at all quitters to prevent weight gain on cessation have proven unpopular but targeting people who have gained excess weight immediately after quitting may improve uptake and cost-effectiveness. We examined whether early large postcessation weight gain predicts overall large weight gain. DESIGN:Retrospective cohort study. SETTING:Primary care setting-smoking cessation centre in Prague, Czech Republic. PARTICIPANTS:Out of 3537 patients treated between 2005 and 2013, 1050 were continuous abstainers (verified by carbon monoxide measurement) at 1-year follow-up and formed the cohort of the current report. 48.7% were women (n=511) with the mean age of 46 (±14.4) years. METHODS:In this retrospective cohort study, all patients underwent usual tobacco dependence treatment using evidence-based methods. Weight was measured prior to smoking cessation and at each visit after quitting. RESULTS:The mean weight gain in the first month (n=763) was 0.79% (±2.03%), in the second month (n=646) was 1.49% (±2.58%), for the third month (n=566) 2.33% (±3.44%) and 4.1% (±5.31%) after 1-year follow-up (n=1050). The regression coefficient per 1% rise in the first 3?months was +0.13% (95% CI -0.04% to 0.30%). A receiver operating curve analysis showed that patients gaining more than 0.98% of their baseline weight during first 3?months had a sensitivity of 66% and specificity of 44% for gaining 7% or more weight by 12 months. In addition, lower body mass index and an increase in appetite at 3?months after quitting were associated with greater weight gain, while using nicotine replacement therapy was associated with less weight gain at 1-year follow-up. CONCLUSIONS:People who stop smoking and gain a larger amount of weight early after quitting are not more likely to gain excessively at 1?year.

SUBMITTER: Pankova A

PROVIDER: S-EPMC6303564 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Early weight gain after stopping smoking: a predictor of overall large weight gain? A single-site retrospective cohort study.

Pankova Alexandra A Kralikova Eva E Zvolska Kamila K Stepankova Lenka L Blaha Milan M Ovesna Petra P Aveyard Paul P

BMJ open 20181216 12

<h4>Objectives</h4>Most people gain weight on stopping smoking but the extent of weight gain varies greatly. Interventions aimed at all quitters to prevent weight gain on cessation have proven unpopular but targeting people who have gained excess weight immediately after quitting may improve uptake and cost-effectiveness. We examined whether early large postcessation weight gain predicts overall large weight gain.<h4>Design</h4>Retrospective cohort study.<h4>Setting</h4>Primary care setting-smok ...[more]

PMID: 30559159

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Project description:BackgroundThe generalizability of the gestational weight gain (GWG) ranges recommended by the Institute of Medicine (IOM) to Chinese women is disputed.MethodsIn 2016, 16,780 pregnant women who gave birth to live singletons in Changsha, China, were enrolled. First, subjects with optimal pregnancy outcomes were identified for the GWG percentile distribution description and for comparison to the IOM recommendations. Second, all subjects with optimal GWG according to the IOM body mass index (BMI) cutoffs and those with optimal GWG according to the Asian BMI cutoffs were selected. Pregnancy outcomes were compared between those two groups.ResultsA total of 13,717 births with optimal pregnancy outcomes were selected to describe the GWG distribution. The height and central position of the GWG distributions determined by the Asian BMI cutoffs differed from those determined by the IOM BMI cutoffs among the overweight and obese groups. The recommended IOM GWG ranges were narrower than and shifted to the left of the observed distributions. In both BMI classification schemes, however, the IOM-recommended ranges were within the middle 70% (Pc 15th-85th) and 50% (Pc 25th-75th) of the observed distribution. A total of 6438 (38.37%) and 6110 (36.41%) women gained optimal GWG, according to the IOM and Asian BMI classifications, respectively. Compared with those with optimal GWG according to IOM BMI cutoffs, women with optimal GWG according to the Asian BMI cutoffs had lower risks of both macrosomia (adjusted OR = 0.79, 95%CI: 0.67-0.94) and large-for-gestational age (adjusted OR = 0.86, 95%CI: 0.76, 0.98). However, no significantly different risks of preterm, low birthweight, small-for-gestational age, pregnancy-induced hypertension, or gestational diabetes were found between them.ConclusionsThe IOM-recommended GWG ranges are within the middle 70% of the distributions in Chinese women, and pre-pregnancy weight status should be determined by the Asian BMI cut-off points for monitoring and making GWG recommendations to Chinese women.

Project description:BackgroundThe primary aim of this study was to examine weight gain during pregnancy and associated adverse outcomes across different types of antenatal health care providers. Our research question examined whether type of antenatal health care provider (family physician, obstetrician, midwife, or family physician plus obstetrician) was associated with differing rates of excess or inadequate weight gain and associated adverse outcomes including being large for gestational age, being small for gestational age, cesarean delivery and preterm birth.MethodsThis retrospective cohort study used data from the Better Outcomes Registry & Network Information System, 2014-2016, for singleton hospital births at 20-42 weeks' gestation in Ontario. We calculated descriptive statistics to summarize patient characteristics and outcomes by antenatal health care provider. We calculated crude and adjusted relative risks with 95% confidence intervals (CIs) for the exposure (weight gain during pregnancy) relative to each secondary outcome by health care provider. We calculated population attributable fractions with 95% CIs to assess the proportion of secondary outcomes that could be prevented if inadequate or excess weight gain (according to the 2009 Institute of Medicine guidelines) were removed by health care provider.ResultsThe final cohort consisted of 231 697 pregnancies, of which 26 043 (11.2%), 136 994 (59.1%), 32 262 (13.9%) and 36 298 (15.7%) were managed by a family physician, obstetrician, midwife, and family physician plus obstetrician, respectively. Rates of weight gain below, within or above recommended levels were 31 742 (13.7%), 71 826 (31.0%) and 128 128 (55.3%), respectively, and did not differ across health care provider groups. No difference was observed in rates of secondary outcomes according to weight gain across health care providers. Excess weight gain was associated with a significant risk of being large for gestational age and cesarean delivery, and inadequate weight gain was associated with an increased risk of being small for gestational age and preterm birth. The population attributable fractions indicated a pronounced contribution of excess weight gain to being large for gestational age across all health care provider groups.InterpretationWeight gain during pregnancy and rates of associated secondary outcomes did not differ according to antenatal health care provider. This suggests a need for further research exploring counselling techniques and strategies for all types of antenatal health care providers to use in order to promote optimal weight gain during pregnancy.

Project description:BackgroundPrevious research has demonstrated that early weight gain in family-based treatment (FBT) is predictive of remission for adolescents with anorexia nervosa (AN). However, no published data has addressed if early weight gain is also predictive of reaching weight restoration (i.e., 95% EBW) in patients with avoidant/restrictive food intake disorder (ARFID). Furthermore, no studies have evaluated the performance of the statistical models used to predict weight restoration at the end of treatment. This study sought to examine whether early weight gain in ARFID is predictive of weight restoration at 20 weeks using ROC analysis. Additionally, this study assessed how accurately the model classified patients and what types of misclassifications occurred.MethodsParticipants (n = 130, 57.7% cisgender female 70.0% white) received virtual outpatient FBT. Receiver operating characteristics (ROC) were used to predict successful weight restoration at end of treatment, using early weight gain as the predictor. Twenty weeks was considered as the end of treatment, to align with the definition of end of treatment in FBT clinical trials. ROC analyses demonstrated that gaining at least 6.2 pounds by week 5 of treatment was the strongest predictor of achieving 95% EBW at 20 weeks (AUC = 0.72 [0.63, 0.81]). ROC analyses misclassified 35% of patients; the most common misclassification was predicting that a patient would not achieve 95% EBW when they actually did (61.6%). A logistical regression model, which included the patients' %EBW at admission in addition to early weight gain as a predictor, outperformed the ROC analyses (AUC = 0.90 [0.85, 0.95]) and provided additional context by showing the probability that a patient would succeed.ConclusionTaken together, research demonstrates that early weight gain is a useful predictor of 95% EBW at 20 weeks of treatment for patients with ARFID who require weight restoration. Furthermore, results suggest that statistical models need to take into account additional information, such as %EBW at admission, along with early weight gain in order to more accurately predict which patients will reach weight restoration at week 20.

Project description:BackgroundApproximately 17% of children in the U.S. are obese. Children that are overweight or obese are also more likely to be obese as adults and suffer from various chronic diseases and premature death. Maternal obesity can affect the weight status of her offspring through intrauterine mechanisms like excessive gestational weight gain (GWG). Current literature shows a positive association between maternal weight status and GWG on child obesity, yet the direct and indirect effects have not been decomposed or quantified. The purpose of this study was to estimate the effect of maternal obesity on child obesity, mediated by GWG, which is a modifiable risk factor.MethodsThe study participants were a birth cohort of offspring from women who received prenatal care in the Duke/Durham Regional health care system in Durham, NC between 2005 and 2009. Anthropomorphic data was collected via electronic medical records (EMRs) during each voluntary visit to a health care facility. The exposure of interest was maternal obesity, measured by pre-pregnancy body mass index, the mediator was GWG, dichotomized into excessive and not excessive based on maternal prenatal BMI, and the outcome was child obesity at age 4, measured as BMI z-scores from the last recorded height and weight. A counterfactual theory-based product method analysis estimated the mediated effects of GWG, adjusted for maternal race, socioeconomic status, and smoking status.ResultsOf the 766 children, 25% were overweight or obese, and among all mothers, 25 and 31% were overweight and obese, respectively. Maternal BMI was associated with an overall increase of 0.04 in offspring z-score. The proportion of the effect of maternal obesity on child age 4 obesity mediated by GWG was 8.1%.ConclusionGWG, in part, mediated the relationship between maternal BMI and childhood adiposity. Even when the mediator is fixed, children are at an increased risk of a higher BMI if the mother is obese. These findings highlight an important public health education opportunity to stress the impact of a pre-pregnancy weight and excessive GWG on the risk of child obesity for all mothers.

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Early weight gain after stopping smoking: a predictor of overall large weight gain? A single-site retrospective cohort study.

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Early weight gain after stopping smoking: a predictor of overall large weight gain? A single-site retrospective cohort study.

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