Capacity for Regulation of Energy Intake in Infancy.

Importance: The capacity for regulation of energy intake (REI) to match energy needs is thought to contribute to differences in weight gain, and preventing excess infant weight gain is a priority. Objective: To determine capacity for REI across infancy. Design, Setting, and Participants: For this cohort study, a convenience sample of mother-infant dyads was recruited from the community in Michigan between 2015 and 2019. Inclusion criteria were healthy, full-term infants with weight appropriate for gestational age; biological mothers who were 18 years or older, English speaking, and a legal and custodial guardian; and infant having had consumed 2 oz or more in 1 feeding from an artificial nipple at least once per week. Infants were followed in the home setting with staff support for up to 12 months. Interventions: Mother-infant dyads participated at infant age 1, 2.5, 5, 7, 10, and 12 months. In the intervention condition, mothers offered a feeding every hour for 6 hours. In the control condition, mothers fed infants as they typically would for 6 hours. Intake was recorded and kilocalories calculated. Main Outcomes and Measures: Capacity for REI was indexed as the difference in intake in kilocalories per kilogram of body weight (intervention minus control condition); a value of 0 indicated perfect REI. Maternal and infant characteristics were obtained by questionnaire, and anthropometry was measured. Using multiple imputation, the intercept and slope for difference in kilocalories per kilogram across the 6 age points were estimated using mixed models accounting for repeated measures within participants. Statistical analyses were conducted between September 2021 and February 2023. Results: The sample included 175 infants (87 [49.71%] female, 88 [50.29%] male; 494 pairs of intervention and control conditions and 4630 feedings). The mean (SD) 12-month weight-for-age z score was 0.1 (0.8). Mean (SD) gestational age as 39.55 (1.05) weeks, and mean (SD) birth weight was 3.43 (0.41) kg. Mean (SD) breastfeeding duration for those who reported stopping by 12 months was 17.83 (12.03) weeks. As designed, the intervention (compared with control) condition included more feedings at shorter intervals. After collapsing the data across age points in a mixed model accounting for repeated measures within participants, the REI estimate at 1 month differed from 0. On average, infants ate 5.21 kcal/kg (95% CI, 2.89-7.54 kcal/kg) more in the frequent feeding intervention condition than in the ad lib feeding control condition. This difference did not significantly change over 12 months of infancy (REI slope = -0.01 kcal/kg per month; 95% CI, -0.02 to 0.03 kcal/kg per month). Conclusions and Relevance: The study's findings suggested that, on average, when offered more frequent feedings, healthy, full-term infants may overeat. The results provide support for responsive feeding as a strategy for preventing excess infant weight gain.

Bayesian sensitivity analyses for longitudinal data with dropouts that are potentially missing not at random: A high dimensional pattern-mixture model.

Randomized clinical trials with outcome measured longitudinally are frequently analyzed using either random effect models or generalized estimating equations. Both approaches assume that the dropout mechanism is missing at random (MAR) or missing completely at random (MCAR). We propose a Bayesian pattern-mixture model to incorporate missingness mechanisms that might be missing not at random (MNAR), where the distribution of the outcome measure at the follow-up time tk , conditional on the prior history, differs across the patterns of missing data. We then perform sensitivity analysis on estimates of the parameters of interest. The sensitivity parameters relate the distribution of the outcome of interest between subjects from a missing-data pattern at time tk with that of the observed subjects at time tk . The large number of the sensitivity parameters is reduced by treating them as random with a prior distribution having some pre-specified mean and variance, which are varied to explore the sensitivity of inferences. The missing at random (MAR) mechanism is a special case of the proposed model, allowing a sensitivity analysis of deviations from MAR. The proposed approach is applied to data from the Trial of Preventing Hypertension.

A Bayesian Mixture Model for Predicting the COVID-19 Related Mortality in the United States.

An outbreak of SARS-CoV-2 has led to a global pandemic affecting virtually every country. As of August 31, 2020, globally, there have been approximately 25,500,000 confirmed cases and 850,000 deaths; in the United States (50 states plus District of Columbia), there have been more than 6,000,000 confirmed cases and 183,000 deaths. We propose a Bayesian mixture model to predict and monitor COVID-19 mortality across the United States. The model captures skewed unimodal (prolonged recovery) or multimodal (multiple surges) curves. The results show that across all states, the first peak dates of mortality varied between April 4, 2020 for Alaska and June 18, 2020 for Arkansas. As of August 31, 2020, 31 states had a clear bimodal curve showing a strong second surge. The peak date for a second surge ranged from July 1, 2020 for Virginia to September 12, 2020 for Hawaii. The first peak for the United States occurred about April 16, 2020-dominated by New York and New Jersey-and a second peak on August 6, 2020-dominated by California, Texas, and Florida. Reliable models for predicting the COVID-19 pandemic are essential to informing resource allocation and intervention strategies. A Bayesian mixture model was able to more accurately predict the shape of the mortality curves across the United States than other models, including the timing of multiple peaks. However, given the dynamic nature of the pandemic, it is important that the results be updated regularly to identify and better monitor future waves, and characterize the epidemiology of the pandemic.

Sucking behavior in typical and challenging feedings in association with weight gain from birth to 4 Months in full-term infants.

Sucking behavior has been described as an obesity risk marker. Sucking behavior in response to challenge has not been examined as a prospective predictor of infant weight gain. Healthy, full term infants had sucking behavior assessed at ages 2 weeks and/or 2 months via a sucking pressure measurement device in two feeding conditions: during a standard feeding and during a feeding with a more challenging nipple. Weight and length were measured at 2 weeks, 2 months, and 4 months and weight-for-length z-score (WLZ) calculated. Among 45 full term infants, adjusted for age at measurement and time since last feeding, the challenging versus typical feedings differed with regard to amount consumed (54.1g vs. 65.6g, p < .05), maximum sucking pressure (121.3 mmHg vs. 99.2 mmHg, p < .05), mean burst duration (17.5s vs. 28.4s, p < .05), and feeding duration (18.51 min vs. 13.89 min, p < .01). Grams consumed in the challenging, but not typical, feeding, adjusted for age and time since last feeding, predicted rate of change in WLZ from time of measurement to age 4 months (r = 0.46, p = .013 for challenging, r = -0.07, p = .702 for typical). Nipples that are more challenging to suck from change the sucking behavior and intake among full term infants. Infants who consume more when the nipple is more challenging have greater prospective weight gain. This persistent sucking behavior in the face of challenge may reflect that a greater willingness to work for food, a known obesity risk factor, is detectable in early infancy.

Greater analgesic effects of sucrose in the neonate predict greater weight gain to age 18 months.

Intraoral sucrose has analgesic effects in the newborn period. The hedonic and analgesic effects of sucrose overlap and hedonic response to sweet food is associated with adiposity. The potential association between the analgesic effects of intraoral sucrose in the newborn period and subsequent weight gain has not been examined. Healthy, term newborns received 25% intraoral sucrose or water prior to metabolic screen heel stick. Negative affect, quiet alert behavior, and sleepiness were coded during heel stick. Weight and length were measured and z-score (WLZ) calculated at birth, 9, and 18 months. Mixed models tested associations of behavioral response to heel stick with WLZ trajectory among infants receiving sucrose (n = 154) versus water (n = 117). Among infants receiving sucrose prior to heel stick with birth WLZ ≥ the median, less negative affect and more sleepiness during heel stick were each associated with greater increases in WLZ. These associations were not present among infants receiving water only prior to heel stick. Greater analgesic effects of sucrose in the neonate were associated with greater future increases in WLZ, especially among infants with higher birth WLZ. Greater opioid-mediated newborn behavioral response to intraoral sucrose may be a marker for future obesity risk. CLINICAL TRIALS NUMBER: NCT02728141.

Maternal restrictive feeding and eating in the absence of hunger among toddlers: a cohort study.

BACKGROUND: Restrictive feeding by parents has been associated with greater eating in the absence of hunger (EAH) among children, a risk factor for obesity. However, few studies have examined the association between restrictive feeding and EAH longitudinally, raising questions regarding the direction of associations between restrictive feeding and child EAH. Our objective was to examine the bidirectional prospective associations between restrictive feeding and EAH among toddlers. METHODS: Low-income mother-child dyads (n = 229) participated when children were 21, 27, and 33 months old. Restriction with regard to food amount and food quality were measured with the Infant Feeding Styles Questionnaire. EAH was measured as kilocalories of food children consumed after a satiating meal. A cross-lagged analysis adjusting for child sex and weight-for-length z-score was used to simultaneously test cross-sectional and bidirectional prospective associations between each type of restriction and children's EAH. RESULTS: At 21 months, mothers of children with greater EAH reported higher restriction with regard to food amount (b = 0.17, p < .05). Restriction with regard to food amount at age 21 months was inversely associated with EAH at 27 months (b = -0.20, p < .05). Restriction with regard to food amount at 27 months was not associated with EAH at 33 months and restriction with regard to food quality was not associated with EAH. EAH did not prospectively predict maternal restriction. CONCLUSIONS: Neither restriction with regard to food amount nor food quality increased risk for EAH among toddlers. Current US clinical practice recommendations for parents to avoid restrictive feeding, and the potential utility of restrictive feeding with regard to food amount in early toddlerhood, deserve further consideration.

Observed infant food cue responsivity: Associations with maternal report of infant eating behavior, breastfeeding, and infant weight gain.

Infant obesity and the rate of weight gain during infancy are significant public health concerns, but few studies have examined eating behaviors in infancy. Food cue responsivity has been described as a key contributor to obesity risk in school age children and adults, but has been rarely examined during infancy. The purpose of the current study was to test among 30 infants aged 6-12 months the hypotheses that infants would show greater interest in food versus non-food stimuli, and that greater birth weight, greater rate of weight gain during infancy, greater mother-reported food responsiveness, being formula versus breastmilk fed, and higher maternal body mass index, would each be associated with greater interest in the food versus non-food stimulus. Results showed that overall infants showed a preference for the food versus non-food stimulus. Preference for the food versus non-food stimulus was predicted by greater infant rate of weight gain since birth, greater maternal-reported infant food responsiveness, and having been exclusively formula-fed, but not by any other factor tested. Results are discussed with regard to theoretical implications for the study of infant obesity and applied prevention implications.

Eating in the Absence of Hunger and Weight Gain in Low-income Toddlers.

OBJECTIVE: To identify predictors of eating in the absence of hunger (EAH) in low-income toddlers, describe affect during EAH, test EAH as a predictor of body mass index (BMI), and examine the type of food eaten as a predictor of BMI. METHODS: EAH, indexed as kilocalories (sweet, salty, and total) of palatable foods consumed after a satiating meal, was measured (n = 209) at ages 21, 27, and 33 months. Child gender, age, race/ethnicity, and previous exposure to the foods; maternal education and depressive symptoms; and family chaos, food insecurity, and structure were obtained via questionnaire. Child and mother BMI were measured. Child affect was coded from videotape. Linear regression was used to examine predictors of EAH and the association of kilocalories consumed and affect with 33 month BMI z-score (BMIz). RESULTS: Predictors of greater total kilocalories included the child being a boy (P < .01), being older (P < .001), and greater maternal education (P < .01). Being in the the top quartile of sweet kilocalories consumed at 27 months and showing negative affect at food removal had higher BMIz (ß = 0.29 [95% confidence interval 0.10 to 0.48] and ß = 0.34 [95% confidence interval, 0.12 to 0.56], respectively).There was no association of salty kilocalories consumed or positive affect with BMIz. CONCLUSIONS: There was little evidence that maternal or family characteristics contribute to EAH. EAH for sweet food predicts higher BMIz in toddlerhood. Studies investigating the etiology of EAH and interventions to reduce EAH in early childhood are needed.

Maternal representations of their children in relation to feeding beliefs and practices among low-income mothers of young children.

Identifying maternal characteristics in relation to child feeding is important for addressing the current childhood obesity epidemic. The present study examines whether maternal representations of their children are associated with feeding beliefs and practices. Maternal representations refer to mothers' affective and cognitive perspectives regarding their children and their subjective experiences of their relationships with their children. This key maternal characteristic has not been examined in association with maternal feeding. Thus the purpose of the current study was to examine whether maternal representations of their children, reflected by Working Model of the Child Interview typologies (Balanced, Disengaged, or Distorted), were associated with maternal feeding beliefs (Authority, Confidence, and Investment) and practices (Pressure to Eat, Restriction, and Monitoring) among low-income mothers of young children, with maternal education examined as a covariate. Results showed that Balanced mothers were most likely to demonstrate high authority, Distorted mothers were least likely to demonstrate confidence, and Disengaged mothers were least likely to demonstrate investment in child feeding. Moreover, Balanced mothers were least likely to pressure their children to eat. Findings are discussed with regard to implications for the study of childhood obesity and for applied preventions.

Bayesian sensitivity analysis of incomplete data: bridging pattern-mixture and selection models.

Pattern-mixture models (PMM) and selection models (SM) are alternative approaches for statistical analysis when faced with incomplete data and a nonignorable missing-data mechanism. Both models make empirically unverifiable assumptions and need additional constraints to identify the parameters. Here, we first introduce intuitive parameterizations to identify PMM for different types of outcome with distribution in the exponential family; then we translate these to their equivalent SM approach. This provides a unified framework for performing sensitivity analysis under either setting. These new parameterizations are transparent, easy-to-use, and provide dual interpretation from both the PMM and SM perspectives. A Bayesian approach is used to perform sensitivity analysis, deriving inferences using informative prior distributions on the sensitivity parameters. These models can be fitted using software that implements Gibbs sampling.

Surgency and negative affectivity, but not effortful control, are uniquely associated with obesogenic eating behaviors among low-income preschoolers.

Despite increased attention to the role of temperament in children's obesogenic eating behaviors, there is a paucity of research examining whether different dimensions of temperament may be differentially associated with specific eating behaviors among preschool-age children. The purpose of the current study was to examine whether three temperament dimensions (surgency, negative affectivity, and effortful control) were uniquely associated with six obesogenic eating behaviors (caregiver-reported food responsiveness, enjoyment of food, emotional overeating, satiety responsiveness, and tantrums over food; and observed eating in the absence of hunger) among low-income preschool-age children, covarying home environment quality. Results showed that temperament dimensions were differentially associated with different eating behaviors. Specifically, preschoolers with higher surgency were more likely to overeat in response to external cues, have frequent desire to eat, derive pleasure from food, and eat in the absence of hunger. In contrast, preschoolers with higher negative affectivity were more likely to have tantrums over being denied food and less likely to eat in the absence of hunger. Effortful control was not uniquely associated with obesogenic eating behavior. Findings remained significant even when home chaos was accounted for, suggesting that child surgency and negative affectivity are important to consider, independent of home environment. Results are discussed with regard to theoretical implications for the study of childhood obesity and for applied prevention implications.

In prehypertension leukocytosis is associated with body mass index but not with blood pressure or incident hypertension.

BACKGROUND: Previous studies reported increased white blood cell counts (WBCCs), an inflammatory marker, in hypertension, prehypertension and metabolic syndrome. Evidence suggests that inflammation precedes blood pressure (BP) elevation and may contribute to incident hypertension. Angiotensin receptor blockers (ARBs) may reduce inflammation. We analyzed WBCC trends in TRial Of Preventing HYpertension (TROPHY) to determine if this inflammatory marker predicted incident hypertension in prehypertensive individuals and whether randomized assignment to the ARB candesartan (391 individuals) for 2 years, lowered WBCC compared with placebo-treated controls (381 individuals). METHODS: A new analysis of TROPHY trial data. RESULTS: In the total population, baseline BMI correlated with WBCC (r = 0.185, P < 0.0001), neutrophils (r = 0.135, P < 0.001) and lymphocytes (r = 0.204, P < 0.0001). Baseline triglycerides also correlated significantly with inflammatory markers. Despite a wide range of home BP (HBP) values, HBP did not correlate with baseline WBCC counts. After 2 years, candesartan decreased placebo corrected HBP by -5.5/-2.5 mmHg, (P < 0.0001), but WBCC, neutrophil and lymphocyte counts were not different in placebo and in candesartan groups. Baseline WBCC, neutrophils and lymphocyte counts did not predict incident hypertension in the placebo group. CONCLUSION: In TROPHY, candesartan lowered BP but did not alter WBCC. Baseline WBCC did not predict incident hypertension. Our findings do not support the hypothesis that inflammation contributes to incident hypertension or that ARB treatment suppresses inflammation. The significant independent association of WBCC with baseline BMI and triglycerides is consistent with the evidence that obesity and insulin resistance are associated with inflammation. The findings highlight the importance of effective lifestyle modification in prehypertension to reduce inflammatory cardio-metabolic risk and suppress transition to hypertension.

A Bayesian model for time-to-event data with informative censoring.

Randomized trials with dropouts or censored data and discrete time-to-event type outcomes are frequently analyzed using the Kaplan-Meier or product limit (PL) estimation method. However, the PL method assumes that the censoring mechanism is noninformative and when this assumption is violated, the inferences may not be valid. We propose an expanded PL method using a Bayesian framework to incorporate informative censoring mechanism and perform sensitivity analysis on estimates of the cumulative incidence curves. The expanded method uses a model, which can be viewed as a pattern mixture model, where odds for having an event during the follow-up interval $$({t}_{k-1},{t}_{k}]$$, conditional on being at risk at $${t}_{k-1}$$, differ across the patterns of missing data. The sensitivity parameters relate the odds of an event, between subjects from a missing-data pattern with the observed subjects for each interval. The large number of the sensitivity parameters is reduced by considering them as random and assumed to follow a log-normal distribution with prespecified mean and variance. Then we vary the mean and variance to explore sensitivity of inferences. The missing at random (MAR) mechanism is a special case of the expanded model, thus allowing exploration of the sensitivity to inferences as departures from the inferences under the MAR assumption. The proposed approach is applied to data from the TRial Of Preventing HYpertension.

Controlling maternal feeding practices associated with decreased dieting behavior in sixth-grade children.

Controlling maternal feeding practices have been linked to increased caloric intake, disinhibited eating, and obesity in children. Its relationship to child dieting behavior, however, is unknown. Using the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development, this study examined whether controlling feeding practices are associated with increased or decreased dieting behavior in children. Controlling maternal feeding practices were assessed in third grade with the question, "Do you let your child eat what he/she feels like eating?" Answers ranged from 1 to 4; higher scores were reverse-coded to indicate greater control. Child dieting behavior was assessed in sixth grade and dichotomized into "any dieting behaviors" vs "none." Multiple logistic regression was used to investigate the relationship between controlling maternal feeding practices and dieting behavior and included the covariates of sex, race, maternal education, maternal weight status, child weight status in third grade, and change in body mass index z score between third and sixth grade. In sixth grade (n=776), 41.5% of children engaged in dieting behavior. In the multivariate analysis, greater maternal control over child eating predicted lower odds of child dieting in sixth grade (odds ratio=0.79; 95% confidence interval: 0.64 to 0.97). There was no interaction between controlling maternal feeding practices and child's sex or baseline obesity status. Exerting more control over what a child eats in third grade may protect against future dieting behavior in children, independent of child's weight status or rate of weight gain. Further work is needed to better define which controlling feeding practices are beneficial for the child.

Maternal feeding practices become more controlling after and not before excessive rates of weight gain.

It is unclear whether controlling maternal feeding practices (CMFPs) lead to or are a response to increases in a child's BMI. Our goal was to determine the direction of this relationship. Data were obtained from National Institute of Child Health and Human Development's Study of Early Child Care and Youth Development. Child BMI z-score (zBMI) was calculated from measured weight and height. CMFP was defined by, "Do you let your child eat what he/she feels like eating?". Change in child zBMI was calculated between 4-7 years and 7-9 years, and dichotomized into "increasing" vs. "no change or decreasing". Change in CMFP was calculated over the same time periods, and dichotomized into "more controlling" vs. "no change or less controlling." Multiple logistic regression, stratified by gender and controlling for race, maternal education, maternal weight status, and baseline child weight status, was used for analysis. A total of 789 children were included. From 4 to 9 years, mean zBMI increased (P = 0.02) and mothers became more controlling (P < 0.001). Increasing CMFP between 4 and 7 years was associated with decreased odds of increasing zBMI between 7 and 9 years in boys (odds ratio = 0.52, 95% confidence interval = 0.27-1.00). There was no relationship in girls. Increasing zBMI between 4 and 7 years was associated with increasing CMFPs between 7 and 9 years in girls (odds ratio = 1.72, 95% confidence interval = 1.08-2.74), but not boys. Early increases in CMFP were not associated with later increases in zBMI for boys or girls. However, early increases in zBMI among girls were associated with later increases in CMFP. Clarifying the relationship between maternal feeding practices and child weight will inform future recommendations.

A Bayesian sensitivity model for intention-to-treat analysis on binary outcomes with dropouts.

Intention-to-treat (ITT) analysis is commonly used in randomized clinical trials. However, the use of ITT analysis presents a challenge: how to deal with subjects who drop out. Here we focus on randomized trials where the primary outcome is a binary endpoint. Several approaches are available for including the dropout subject in the ITT analysis, mainly chosen prior to unblinding the study. These approaches reduce the potential bias due to breaking the randomization code. However, the validity of the results will highly depend on untestable assumptions about the dropout mechanism. Thus, it is important to evaluate the sensitivity of the results across different missing-data mechanisms. We propose here a Bayesian pattern-mixture model for ITT analysis of binary outcomes with dropouts that applies over different types of missing-data mechanisms. We introduce a new parameterization to identify the model, which is then used for sensitivity analysis. The parameterization is defined as the odds ratio of having an endpoint between the subjects who dropped out and those who completed the study. Such parameterization is intuitive and easy to use in sensitivity analysis; it also incorporates most of the available methods as special cases. The model is applied to TRial Of Preventing HYpertension.

A Bayesian model for longitudinal count data with non-ignorable dropout.

Asthma is an important chronic disease of childhood. An intervention programme for managing asthma was designed on principles of self-regulation and was evaluated by a randomized longitudinal study.The study focused on several outcomes, and, typically, missing data remained a pervasive problem. We develop a pattern-mixture model to evaluate the outcome of intervention on the number of hospitalizations with non-ignorable dropouts. Pattern-mixture models are not generally identifiable as no data may be available to estimate a number of model parameters. Sensitivity analyses are performed by imposing structures on the unidentified parameters.We propose a parameterization which permits sensitivity analyses on clustered longitudinal count data that have missing values due to non-ignorable missing data mechanisms. This parameterization is expressed as ratios between event rates across missing data patterns and the observed data pattern and thus measures departures from an ignorable missing data mechanism. Sensitivity analyses are performed within a Bayesian framework by averaging over different prior distributions on the event ratios. This model has the advantage of providing an intuitive and flexible framework for incorporating the uncertainty of the missing data mechanism in the final analysis.