Are Babies More Likely to Be Fat if They Their Parents Were Fat
Obesity (Silver Jump). Author manuscript; available in PMC 2013 October 1.
Published in final edited grade as:
PMCID: PMC3671382
NIHMSID: NIHMS417068
Parental obesity moderates the human relationship between childhood appetitive traits and weight
Bernard F. Fuemmeler
1Knuckles Academy Medical Center, Durham NC
Cheryl A. Lovelady
2Academy of Due north Carolina at Greensboro, Greensboro NC
Nancy L. Zucker
1Duke University Medical Center, Durham NC
Truls Østbye
iDuke University Medical Center, Durham NC
Abstract
This study examined the independent and combined associations between childhood appetitive traits and parental obesity on weight gain from 0 to 24 months and body mass index (BMI) z score at 24 months in a diverse community-based sample of dual parent families (n = 213). Participants were mothers who had recently completed a randomized trial of weight loss for overweight/obese post-partum women. Every bit measures of childhood appetitive traits, mothers completed subscales of the Kid Eating Beliefs Questionnaire, including Desire to Potable (DD), Enjoyment of Food (EF), and Satiety Responsiveness (SR), and a 24-hour dietary recall for their child. Heights and weights were measured for all children and mothers and self-reported for mothers' partners. The human relationship between children's appetitive traits and parental obesity on toddler weight proceeds and BMI z score were evaluated using multivariate linear regression models, controlling for a number of potential confounders. Having 2 obese parents was related to greater weight proceeds from birth to 24 months independent of babyhood appetitive traits, and while significant associations were found between appetitive traits (DD and SR) and child BMI z score at 24 months, these associations were observed only amidst children who had two obese parents. When both parents were obese, increasing DD and decreasing SR was associated with a higher BMI z-score. The results highlight the importance of considering familial risk factors when examining the relationship between babyhood appetitive traits on babyhood obesity.
Keywords: Childhood eating behaviors, parental obesity, babyhood obesity, prevention
INTRODUCTION
Obesity is a multifactorial condition reflecting a circuitous interaction between private predisposition, social, and ecology factors.(1) The rise in obesity prevalence among children is particularly alarming given that early childhood obesity not only results in a number of adverse health consequences during babyhood, but also tracks into adolescence and adulthood.(2) Recent data suggests that for many children who are overweight, the onset occurs early in development before the historic period of ii years; however, the reasons for this are not well understood.(3) A better agreement of the factors associated with excess weight gain during early on development is primal to developing effective babyhood prevention and treatment strategies.
Socio-economical factors along with gestational historic period, birth weight, and length of chest feeding are factors related to early babyhood weight gain.(4) Even so, other factors such as individual differences in disposition related to eating and nutrient are likewise relevant. For instance, early theoretical models of obesity (e.g. Stunkard and Schachter'south externality model) posited that obese individuals may be less sensitive to internal physiological cues of satiety and more responsive to the presence of food, as well equally environmental stimuli associated with nutrient consumption (e.m. food commercials, images of food, etc.).(5, 6) A number of contempo studies have examined the tenets of these models by investigating childhood appetite regulation as a potential behavioral marker of obesity susceptibility.(7–9) Lab-based studies have found that observations of "eating in the absence of hunger" (EAH) and "bite frequency" predict weight status and weight proceeds.(10, 11) Such observations may correspond a kid'south dispositional responsiveness to satiety or heightened enjoyment of nutrient. Studies of customs samples have also provided evidence that these dispositional differences or appetitive traits measured using psychometric approaches may exist relevant to childhood BMI and risk for obesity. Specifically, psychometric constructs such as parent-reported kid "Satiety Responsiveness" is associated with lower BMI, and both greater "Enjoyment of Food" and "Nutrient Responsiveness" are associated with higher BMI and weight gain.(9, 12, thirteen) These psychometric constructs have besides been shown to be convergent with behavioral measures, such as EAH and eating rate and college caloric intake. Notably, definitively establishing the direction of influence is non possible in cross-sectional studies such as these. Even so, recent longitudinal studies provide further back up that appetitive traits contribute, in office, to weight proceeds rather than the other way around. (xiv) These studies advise that children differ in their appetitive traits and that these differences could explain why some children may be more sensitive to external nutrient cues or less sensitive to internal satiety cues. These factors could contribute to an increased nutrient intake and ultimately higher risk for obesity.
Another important risk factor for babyhood obesity is having parents who are obese. Children with 2 obese parents are ten to 12 times more than likely to exist obese.(15, 16) Weight gain in early childhood (3 to 5 years of age) is also significantly greater amidst children with overweight or obese parents or amongst those born of overweight or obese mothers.(17) children of heavier parents have been found to showroom lower levels of physical activity and take greater preference for high fatty foods and lower preference for healthier foods.(18, 19) This familial influence may exist through genetic mechanisms or through the environment.
Childhood appetitive traits and familial risk factors, like parental obesity, may be independently associated with child obesity, and if these factors are contained, it would be informative to know which (appetitive traits or parental obesity) is more than important in relation to children's food intake or risk for obesity. However, coexisting evidence suggests children's appetitive traits may vary depending on whether or not they have other familial take a chance factors, such as obese parents.(nineteen) For instance, college levels of EAH take been observed among children born to mothers who were obese prior to pregnancy compared to their counterparts built-in to mothers who were lean. (8) The link between appetitive traits and obesity may therefore depend on other factors similar parental obesity. Understanding the conditions under which appetitive traits relate to children's nutrient intake and risk for obesity would allow for more precise conclusions about these associations.
The purpose of this study was therefore to examine the extent to which children's appetitive traits (food responsiveness, enjoyment of food, desire for drinks, and satiety responsiveness), and parental obesity condition are associated with food intake, weight gain from birth, and BMI z score at 24 months. This written report extends previous research by i) examining these associations among very immature children during a critical time when eating patterns and preferences for certain foods are established and 2) evaluating whether these associations between appetitive traits and risk for obesity were chastened by parental obesity.
METHODS
Participants
Participants in the current written report were recruited from three large obstetrics clinics in Southeastern, US for a larger behavioral randomized controlled trial, Active Female parent's Postpartum (AMP).(20, 21) Eligibility for AMP was based upon BMI ≥ 25 measured by study staff at the 6 week postpartum obstetrics appointment. Women who did not speak English, were aged < xviii years, or had health conditions that prevented them from walking a mile unassisted were excluded from participation. The AMP intervention was designed to enhance weight loss in postpartum women who were overweight or obese prior to pregnancy. Participants were randomized at 6–viii weeks postpartum to either the AMP intervention (n=225) or the attention command grouping (due north=225). The AMP intervention, which lasted ix months with postal service-intervention and follow-upwardly assessments, focused primarily on improving lifestyle behaviors in the female parent. The intervention did not encourage the adoption of certain parenting styles or efforts to amend the health of their newborn infant. The mean weight loss was 0.90 kg (±five.1 kg) in the intervention grouping and 0.36 kg (±4.9 kg) in the control group, which was not a statistically meaning difference. There were too no significant group differences in improvement of diet or increased physical activity.(20, 21) At their concluding follow-up (24 months postpartum) mothers and their 2 twelvemonth old children were recruited for the current observational report, AMP As well for Twos!
Of the 450 participants who were enrolled in the main AMP trial, 309 agreed to participate in the electric current written report. Subsequently excluding 43 unmarried parent families, 266 mothers of dual-parent families were asked if they would be willing to evangelize a survey bundle to their partner, which included a letter describing the report, a consent form, a brief survey, and a pre-paid return envelope. From these 266 dual-parent families, 213 partners returned surveys (80% of the eligible 266). In nearly all cases, parents in this sample were biological (93%) or the partner was living in the home with the mother and target kid (97%). Compared to the participants who originally enrolled in the AMP trial (n=450), participants in the sample for this study (n=213) were more than likely to be White (Cramer's 5 = −.xviii), have a college degree (Cramer's V = .xix), have a family income greater than $sixty,000 (Cramer'south V = .twenty), and were slightly older (Cohen'southward d = .27). However, there were no significant differences between the two groups as related to percent calories from fat calculated from dietary recalls (Cohen's d = .01), number of boob tube viewing hours per day (Cohen's d = .03), number of reported minutes per calendar week of walking for physical activity (Cohen's d = .18), and BMI (Cohen'due south d = .fourteen). Thus, although there were some socio-demographic differences between the 2 groups, the differences were modest (i.e., effect sizes < .three;(22)) and there were no differences between the groups with respect to central health behaviors. All procedures were approved by the collaborating Academy'due south Institutional Review Boards.
Measures
Child eating behaviors
Eating behaviors were assessed using the Children'southward Eating Behavior Questionnaire (CEBQ).(23) Items for the CEBQ were adult from focus groups and interviews with parents of children 2–half-dozen years of historic period and the hateful age of the sample for testing psychometrics of the items was 4.ii (± 1.4) years.(23) The calibration is being used in studies with samples of children ranging in historic period from two to 11 years of historic period.(13, 24, 25) Items have Likert scale response options ranging from 1 (never) to five (e'er). For this study, we restricted our assay to the following CEBQ subscales: Enjoyment of Food (EF), Food Responsiveness (FR), Desire to Drink (DD), and Satiety Responsiveness + Slowness in Eating (SR). Satiety Responsiveness and Slowness in Eating were combined every bit they have been shown to load onto the same factor.(23) Domains of EF, FR and DD reflect a general ardor toward eating and food (e.chiliad., "my child loves nutrient (EF);" "if allowed, my kid would consume too much (FR);" and "if given the chance, my kid would ever exist having a drink (DD)." SR reflects how easily a kid reaches satiety (e.g., my child cannot eat a meal if he/she has had a snack just before"). The CEBQ has been shown to have high internal consistency, good test-retest reliability, stability over time (23, 26), and these particular subscales have been correlated with weight.(9) Cronbach's alphas for subscales in this sample were acceptable (SR = .70; EF = .86; FR = .71; DD = .84).
Child anthropometrics
At ii years of age children's weights (to the nearest 10th of a pound) and standing heights (to the nearest quarter inch) were measured by study staff during a visit to the laboratory using a Seca portable stadiometer and Tanita BWB-800 scale. Measurements were completed with children wearing coincidental attire with belts and shoes removed. BMI z score was calculated using the Centers for Affliction Control and Prevention SAS macro which computes age and gender adjusted standardized scores.(27)
Parental weight status
At the same report visit in which children's weights and heights were measured, mother'southward weights and heights were also measured. The mothers' partners self-reported height and weight every bit function of their surveys. Since the purpose of this study was to examine how parental obesity related to children's BMI, we quantified parental weight status into three groups: 0 = neither parent was obese (BMI < xxx); 1 = i parent was obese (BMI ≥ thirty), simply the other was non (BMI < xxx); and two = both parents were obese (BMI of mother ≥ 30 and BMI of partner ≥ xxx).
Dietary Intake
Dietary intake of children was assessed similarly to the Feeding Infants and Toddlers Study.(28) The primary caregiver (in most all cases the mother) reported on their child'southward nutrition. Dietary recalls were collected on two randomly selected days over a 2 week flow. Mothers had been given a packet with 2-dimensional visuals to assist in determining food portion sizes. The visuals included various examples of toddler food portions and eating implements (due east.g., "sippy-cups" and minor bowls). If children attended daycare, mothers were given a form for the daycare provider to record the kid's dietary intake (type of food eaten and corporeality). Mothers used this list to complete the 24-hour call back. The dietary intake of the children was assessed past telephone, using the Nutrition Data System for Research (NDS-R, Academy of MN), a valid and established method for assessing energy intake.(28, 29) These data included estimated free energy [kilocalorie (kcal)] intake available from 183 of the 208 (88%) children. There were no differences in main demographic characteristics (maternal teaching and child's race) between mothers who provided dietary information vs. those who did not.
Other measures
Parents reported on level of educational attainment, historic period, and their child's race/ethnicity. Kid's birth weight and gestational weeks were reported by mothers when they first enrolled in AMP written report, which was shortly after the birth of their child (vi–viii weeks). Breast feeding corporeality was summarized by a lactation score, a mensurate of breastfeeding "intensity" combining the duration and exclusivity of breastfeeding.(30) This score was derived from the detailed monthly feeding data collected at the 12-calendar month follow-up. A value was assigned for each month—0 if formula fed, 1 if mixed, and 2 if fully breastfed. The resulting score has a possible range of 0–24, and more explanatory ability than a uncomplicated measure of duration.(31)
Assay
The outcomes for these analyses included weight proceeds from birth (measured by the change in kilograms from nativity to 24 months of historic period), BMI z score at 24 months, and energy intake at 24 months. The initial analyses involved one) bivariate Pearson r correlations between children'due south eating behaviors (EF, FR, DD, SR), BMI z-score, weight gain from nascency, energy intake at 24 months, and parental BMI; and 2) mean comparisons (general linear model) for BMI z score and weight gain from birth for parental obesity categorical variable (0,1,2) controlling for intervention arm and birth weight. We also calculated the odds of existence overweight (BMI z score ≥ 85thursday percentile and < 95thursday percentile) and obesity (BMI z score ≥ 95thursday percentile) using a multinomial logistic regression for children with one or both parents obese relative to neither obese controlling for intervention arm and birth weight. Split multivariate linear regression models were performed to examine associations between children's eating behaviors (EF, FR, DD, or SR), the parental obesity variable, and their interaction on each of the anthropometric outcomes (BMI z score and weight gain from birth) and energy intake. All multivariate models included treatment arm, children's age, gender, race, gestational age at birth, birth weight, lactation score, and historic period and educational level of mothers and their partners. Merely chief effects models (i.due east., models not including interaction terms) are reported when interaction terms were non meaning. Post-hoc probes were conducted for all meaning interaction effects.(32)
RESULTS
In the overall sample (Table i), the prevalence of children with BMI z scores exceeding the 85thursday percentile was 25% (n = 54) which is slightly higher than the national average of 21% for children ages ii to v years.(33) On average children were born full-term (mean gestational age = 39 weeks).
Table i
Sample characteristics (percentages or ways and standard deviations)
| Overall sample (northward = 213) | ||
|---|---|---|
| PARENT CHARACTERISTICS | ||
| Mother's age, hateful (s.d.) | 33.6 | five.i |
| Partner's age, mean (due south.d.) | 35.1 | 5.7 |
| Mother's Educational activity Level | ||
| < HS, HS/GED, Voc Degree, Some Higher | thirty% | |
| Associates Degree, College Graduate or Higher | 70% | |
| Partner'due south Educational activity Level | ||
| < HS, HS/GED, Voc Degree, Some College | 36% | |
| Associates Degree, College Graduate or College | 64% | |
| Mother'southward Measured BMI, hateful (s.d.) | 32.3 | vii.iii |
| Mother'due south Measured BMI (category) | ||
| Normal weight | 11% | |
| Overweight | 33% | |
| Obese | 56% | |
| Partner's Reported BMI, hateful (due south.d.) | 28.3 | 5.0 |
| Partner'due south Reported BMI (category) | ||
| Normal weight | 27% | |
| Overweight | 42% | |
| Obese | 31% | |
| Child CHARACTERISTICS | ||
| Gender % female | 44% | |
| Race | ||
| White | 64% | |
| Black | 36% | |
| Age, mean (s.d.) | 24.ii | 1.3 |
| Gestational age (weeks), mean (due south.d.) | 38.v | two.0 |
| Lactation score, hateful (s.d.) | 9.vii | 8.8 |
| Birthweight (kg), mean (s.d.) | three.4 | 1.3 |
| 24 month weight (kg), mean (s.d.) | 5.9 | 0.vii |
| weight proceeds from nascency (kg), mean (south.d.) | nine.v | 1.5 |
| 24 month BMI z score, mean (s.d.) | ||
| BMI Categories | ||
| < 85th %ile | 75% | |
| 85th – 95th %ile | 16% | |
| >95th %ile | 9% | |
| Average kcal, mean (southward.d.) | 1221 | 296 |
| Boilerplate percent calories from fatty, mean (s.d.) | 31.0 | 6.4 |
Children's appetitive traits and anthropometrics
Table 2 displays the bivariate correlations between CEBQ subscales, BMI z-score, and weight gain from birth. Significant correlation coefficients were in the expected management with subscales assessing Enjoyment of Food (EF), Food Responsiveness (FR), and Want to Potable (DD) being positively correlated with BMI z score and weight gain from birth and Satiety Responsiveness (SR) being negatively correlated. All correlations were statistically pregnant except for the association between EF and weight proceeds from birth. Mother's BMI and partner's BMI were non related to babyhood appetitive traits. Energy intake was significantly associated with FR (r = .18, p < .05) and SR (r = −.17, p < .05), but was not related to kid's BMI z score.
Tabular array 2
Correlations between children's appetitive traits, BMI z score, parent's BMI, and child energy intake
| EF | FR | DD | SR | BMI z | Weight gain | Female parent'south BMI | Partner'south BMI | |
|---|---|---|---|---|---|---|---|---|
| 1 Enjoyment of Food (EF) | -- | |||||||
| 2 Food Responsiveness (FR) | 0.52** | -- | ||||||
| 3 Desire to Drinkable (DD) | −0.02 | 0.21** | -- | |||||
| iv Satiety Responsiveness (SR) | −0.58** | −0.49** | 0.08 | -- | ||||
| v BMI z score | 0.17** | 0.xx** | 0.fourteen* | −0.xx** | -- | |||
| 6 Weight gain from nativity (kg) | 0.x | 0.16 | 0.14* | −0.17* | 0.74* | -- | ||
| seven Mother'south BMI | −0.11 | −0.05 | 0.06 | 0.04 | 0.07 | 0.12 | -- | |
| 8 Partner'southward BMI | −0.01 | 0.01 | 0.thirteen | 0.00 | 0.14* | 0.17* | 0.19** | -- |
| 9 Average energy intake | 0.14 | 0.xviii* | 0.thirteen | −0.17 | 0.10 | 0.thirteen | 0.02 | 0.08 |
Parental obesity and childhood anthropometrics
Table 3 displays the mean weight gain from nascence and BMI z score for children with neither parent obese, one parent obese, and both parents obese. Statistical comparison of ways controlled for intervention arm and birth weight. Mean weight gain from birth and BMI z score both increased with increasing parental obesity. The greatest mean difference was observed amidst children who take 2 obese parents relative to children with neither parent obese (mean weight gain nine.9 kg vs 9.2 kg and BMI z score 0.7 vs. 0.3). The ways for each CEBQ subscale were also evaluated in relation to parental obesity condition (neither, one or both obese) controlling for intervention status, child's age in months, gender and race. There were no statistically significant mean differences for EF, FR, DD, or SR by category of obesity condition in these models (all p values > .05; data non shown).
Table 3
Association between parental obesity and anthropometrics
| Weight gain from nascency (kg) | BMI z score | ≥ 85th %ile vs < 85th %ile | ≥ 95th %ile vs < 85th %ile | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Parent obesity status (n = 204)1 | Mean2 (south.e.) | 95% CI | Meaniii (due south.due east.) | 95% CI | AORb | 95% CI | AORb | 95% CI | |
| | | ||||||||
| Neither Obese (n=79) | nine.ii (0.16) | 8.86 – 9.49 | 0.iii (0.eleven) | 0.10 – 0.51 | |||||
| Ane Parent Obese (n=73) | nine.six (0.xv) | 9.29 – 9.90 | 0.5 (0.09) | 0.29 – 0.64 | 1.78 | .69 – iv.56 | 1.10 | .30 – 4.01 | |
| Both Parents Obese (n=53) | 9.9 (0.23) | ix.46 – 10.34* | 0.seven (0.fifteen) | 0.39 – 0.97* | 2.55 | .97 – half-dozen.74 | ii.40 | .70 – 8.17 | |
Multivariate linear regression analyses and interaction effects
Main effects models without interaction
Appetitive traits were not statistically significantly related to weight proceeds from 0 to 24 months in models that included the parental obesity variable (ane or two parents who were obese) equally well as the other covariates (child's age, gender, race, gestational age, birth weight, lactation score, mother's and partner's educational level, mother's and partner's age, and intervention status). Having two obese parents was significantly associated with kid weight gain, controlling for appetitive traits and the other covariates (kid'southward age, gender, race, gestational age, birth weight, lactation score, mother'south and partner'southward educational level, mother's and partner'southward historic period, and intervention status). In a reduced model, which retained the covariates just removed the appetitive traits, having one parent who was obese was not statistically associated with greater weight gain from nascence (β = 0.26, s.e. = 0.23, p = 0.25), but having two parents who were obese was associated greater weight proceeds from birth (β = 0.60, due south.e = 0.26, p < .05) (data not shown in table).
Controlling for parental obesity status and the other covariates (kid'due south age, gender, race, gestational age, birth weight, lactation score, mother'due south and partner's educational level, female parent'southward and partner's historic period, and intervention status), there were no significant associations observed betwixt appetitive traits and BMI z score, with one exception: FR was significantly associated with BMI z score. Specifically, a one unit increment in FR was associated with about a .25 unit increase above the BMI z score intercept (run across Table 4).
Tabular array 4
Multivariate linear regression analyses for CEBQ subscales, parental obesity, and interaction predicting weight gain (kg) from birth, BMI z score, and energy intake
| Weight Proceeds from Birth (kg) | BMI z score | Energy Intake | ||||
|---|---|---|---|---|---|---|
| CEBQ subscale | Beta | (s.e.) | Beta | (s.e.) | Beta | (s.eastward.) |
| | | |||||
| Intercept | ix.00 | (3.99) | −0.77 | (2.22) | 1601.34 | (737.45) |
| Enjoyment of Food (EF) | 0.13 | (0.sixteen) | 0.20 | (0.11) | 33.66 | (29.73) |
| One Parent Obese | 0.29 | (0.23) | 0.12 | (0.sixteen) | −25.55 | (52.33) |
| Both Parents Obese | 0.61 | (0.26)* | 0.32 | (0.18) | 70.07 | (56.95) |
| One Parent Obese × EF | … | … | … | |||
| Both Parents Obese × EF | … | … | … | |||
| Intercept | 8.33 | (iii.92) | −ane.31 | (2.xiii) | 1399.15 | (689.67) |
| Food Responsiveness (FR) | 0.23 | (0.19) | 0.25 | (0.10)* | lxx.92 | (37.thirty) |
| One Parent Obese | 0.26 | (0.23) | 0.10 | (0.15) | −46.04 | (49.68) |
| Both Parents Obese | 0.60 | (0.27)* | 0.29 | (0.18) | 70.02 | (56.74) |
| Ane Parent Obese × FR | … | … | … | |||
| Both Parents Obese × FR | … | … | … | |||
| Intercept | 8.34 | (4.12) | −0.60 | (2.39) | 1479.96 | (737.55) |
| Desire to Drink (DD) | 0.12 | (0.xi) | −0.15 | (0.06) | 23.79 | (25.27) |
| Ane Parent Obese | 0.25 | (0.23) | −0.74 | (0.53) | −fifty.11 | (49.53) |
| Both Parents Obese | 0.57 | (0.27)* | −1.25 | (0.67) | 59.84 | (56.56) |
| I Parent Obese × DD | … | 0.26 | (0.15) | … | ||
| Both Parnes Obese × DD | … | 0.46 | (0.18)** | … | ||
| Intercept | 9.50 | (three.78) | −0.66 | (2.27) | 1855.46 | (734.94) |
| Satiety Responsiveness (SR) | −0.10 | (0.29) | 0.12 | (0.19) | −83.fourscore | (43.61) |
| I Parent Obese | −0.04 | (1.53) | 0.88 | (1.00) | −30.84 | (49.94) |
| Both Parents Obese | 3.67 | (1.50)* | iii.xvi | (one.02) | 79.21 | (56.29) |
| One Parent Obese × SR | 0.eleven | (0.49) | −0.24 | (0.32)** | … | |
| Both Parents Obese × SR | −1.04 | (0.50)* | −0.96 | (0.33)** | … | |
Neither the appetitive traits nor the parental obesity variable was associated with energy intake in multivariate models. In a reduced model, excluding parental obesity but retaining the covariates, both FR and SR were significantly associated to boilerplate energy intake in aforementioned direction as the bivariate correlations (above). Specifically, decision-making for covariates (kid's age, gender, race, gestational age, birth weight, lactation score, mother'due south and partner's educational level, female parent's and partner'south historic period, and intervention status), a one unit of measurement increase in FR was associated with an increase of 82.2 kilocalories in a higher place the intercept (β = 82.two, s.due east.=38.7, p <.05). A i unit increase in SR was associated with a subtract of 95.two kilocalories below the intercept (β = −95.2, south.e.=44.2, p <.05) (data not shown in table).
Models with main effects and interaction effect
In the models examining weight gain from 0 to 24 months and BMI z-score with parental obesity condition and child appetitive traits, there were significant interactions betwixt parental obesity status and SR (Table iv and Figures 1a, 1b). A post-hoc probe of the significant interaction for weight proceeds indicated that SR was statistically significantly associated with weight proceeds for children who had two obese parents (β = −ane.25, p <.01), but not associated when i parent was obese (β = −.21 p = .64), or when neither parent was obese (β = −.twenty, p = .48). Besides, the post-hoc probe of the interaction examining BMI z score indicated that SR was statistically significantly associated with BMI z score for children with two obese parents (β = −.81, p < .01), merely was not associated when i (β = −.16, p = .55), or when neither parent was obese (β = −.12, p = .49). A meaning interaction between parental obesity status and DD on BMI z score was also establish (Table 4 and Figures 1c). DD was significantly associated with BMI z score for children who had ii obese parents (β = .28, p <.05), but non associated when one parent was obese (β = .15, p = .12), or when neither parent was obese (β = .07, p = .37).
(a, b, c). Weight gain from birth and BMI z score for children high and low on select appetitive traits with neither parent obese, one parent obese, or ii parents obese
Give-and-take
We institute pregnant associations between parental obesity, children's appetitive traits and BMI z score among a sample of 24 month old children, controlling for a number of variables. Specifically, a positive relationship between Food Responsiveness (FR) and BMI z score was significant and independent of parental obesity status. Lower Satiety Responsiveness (SR) and greater Desire to Beverage (DD) were besides establish to be associated with a higher BMI z score at 24 months, but this association was observed but amidst children with ii obese parents. Appetitive traits were associated with energy intake at 24 months (greater FR and lower SR was associated with greater energy intake), simply controlling for parental obesity status reduced these associations to not-significance, indicating potential confounding of parental obesity status in these associations.
The present findings are consistent with previous reports from the U.K. linking EF, FR, DD, and SR with standardized BMI score in older children (8 – nine years) (9) and SR and EF with BMI standardized score in younger children (three–5 years).(13) In these studies, the associations were maintained even after controlling for kid's historic period, sex, and socio-economic factors. Even so, previous studies did non account for parental weight status or examine how parental weight status might change these associations. Our findings back up and extend these previous reports by taking into business relationship parental weight status in the human relationship betwixt appetitive traits and childhood BMI. Information technology is reasonable to suspect that parent'southward weight status is a relevant modifying variable in these associations. Using the same measure of childhood appetitive traits, at to the lowest degree one study has found higher scores on the FR and DD constructs among children who have overweight parents (19). Likewise, behavioral measures of satiety are greater among children born of mothers who were overweight.(7, 8) The findings presented here extend previous literature to back up the notion that the association between children's appetitive traits and their risk for obesity may be modified past other relevant familial risk factors, like having parents who are obese. The study is too unique in that the associations between appetitive traits and weight and diet outcomes were evaluated in young children. Continued studies are needed that address these associations in young children as this age may represent a sensitive period of development in the pathway to weight regulation throughout childhood.
The observation of a significant interaction between SR and parental obesity in association with weight gain mirrors the associations observed with BMI z score in that SR was related to weight gain only amidst children who had two obese parents. Overall, the boilerplate weight gain from 0 to 24 months (9.51 kg) was fairly high for this cohort of children of primarily overweight mothers and fathers. Weight proceeds between 8.15kg and 9.76kg during this developmental period has been considered "risky" growth.(34, 35) Among children with two parents who were obese, a ane unit of measurement decrease in SR was associated with a i.3 kg increment in weight gain from 0 to 24 months and an increase in BMI z score of 0.81 relative to the average case. Thus, children lower in satiety responsiveness appear to accept a higher BMI z score at 24 months and greater early on weight proceeds particularly in familial contexts where there are two obese parents. A moderating effect of parental obesity on the relationship between DD and BMI z score was also observed. Information technology is notable that meaning associations were nowadays for DD and SR in relation to BMI z score among children with two obese parents, but FR or EF were not. One possibility is that sure types of appetitive traits are more easily discernible when children are younger. DD and SR may exist more noticeable during before development when caregivers are providing well-nigh of the feeding opportunities as opposed to later circumstance when children first to independently admission the types of food they savor eating.
Children with certain appetitive traits who accept obese parents may have a higher BMI z score at 24 moths for a number of reasons. In general, parental obesity may represent parenting and environmental qualities as well every bit genetic risk factors. The early work of Stunkard and Schachter'southward externality model suggested that obese adults take difficulty recognizing internal satiety signals and are over responsive to external food cues.(5, 6, 36) Obese parents may be inadvertently modeling these eating behaviors during sensitive developmental periods when children are forming their full general orientation toward nutrient and eating. Parents may be modeling maladaptive behaviors all along the food consumption sequence: from attentiveness to food cues, capacities to inhibit food responsiveness when making food selections, to demonstrating sensitivity to somatic signals in terminating a meal. The feeding practices (due east.m., offering nutrient in response to distress) of obese parents might also differ from those of not-obese parents and parent feeding practices could shape or encourage the expression of specific eating tendencies. Notably, it is not clear whether these appetitive traits are completely learned behaviors and influenced by nurturing or if they are influenced by biologically mediated mechanisms, such as genetic differences. SR and EF have been associated with specific cistron variants suggesting a biologically mediated component.(37) Appetitive traits observed in children could share mutual underlying neurological substrates that are modulated in role past genotype differences, which are inherited via positive assortative mating.(38) While it is unclear why the associations nosotros observed were significant when both parents were obese rather than when only one parent was obese, it is possible that two obese parents constitute a more unambiguous model. Perhaps, having ane non-obese parent attenuates or fifty-fifty reverses the negative modeling by the obese parent. Having two obese parents might too increment the propensity for biologically mediated eating beliefs traits, or influence the expression of these traits through nurturing patterns that may be more prevalent when both parents are obese. Yet some other possibility is that obese parents are more vigilant to external food cues or recognize their ain insensitivity to satiety and more than likely to notice and written report these similar traits in their children. It will be important in future studies to begin to deconstruct what exactly is existence measured by bookkeeping for parental obesity, since this is such a strong risk factor for childhood obesity and may change other childhood factors and traits that are related to take a chance for obesity.
Mechanistic explanations that underlie the associations between parental obesity, children's appetitive traits and babyhood BMI are hard to discern in the context of this report. In this study, parental BMI was not strongly correlated with children's appetitive traits, so it is unlikely that the effect of parental obesity on babyhood obesity is mediated by childhood appetitive traits. Besides, in our data, strong associations between energy intake and BMI z score were non present, which would demand to exist established to support a mediation hypothesis that appetitive traits influence BMI via increased free energy intake. We did explore whether this association between free energy intake and BMI z score varied when parents were obese, but there were no significant effects of parental obesity on these associations (data non shown), suggesting that this pathway is not supported even in contexts where both parents are obese. To our cognition, extant studies take non established different types of mediating pathway with statistical certainty. Equally for the influence of childhood appetitive traits on BMI z score via increased caloric intake, information technology may be difficult to elucidate this pathway using a cross-sectional design. In this study, dietary recalls were conducted over the phone and shortly after the participants visited the lab when their heights and weights were measured. Longitudinal studies would permit a meliorate examination of these associations. Information technology would be helpful to know whether early babyhood appetitive traits increase caloric intake (or dietary patterns) and ultimately obesity as children grow and develop, and whether the trajectories of increased caloric intake are steeper amid those with obese parents.
This study has certain limitations. This was a sample of women who were participating in a postpartum obesity prevention study. Thus, the parents in this report are more likely to be overweight. Information technology is worthwhile to replicate these findings in samples that also include normal weight parents. The overall effects may be underestimated, since the reference group is heavier than one including normal weight parents. While this sample option may limit generalizability, the oversampling of overweight mothers allowed us to examine childhood appetitive traits in a high-risk sample – a notable add-on to the literature. Related to this is that, by design, but ii-parent families who were living with the child were included in these analyses. Thus, the findings here may not generalize to situations where merely 1 parent is in the home. Notable in this study as well was the use of dietary recalls, which may take precluded our ability to detect associations between appetitive traits and energy intake. Other methods such as the use of doubly labeled h2o or daily nutrient diaries could be used in futurity validations studies that aim to decide the association betwixt appetitive traits and energy intake. Such approaches would take been quite crushing for participants in this written report and are typically not feasible in epidemiologic studies. Some other limitation is that although trained study staff measured heights and weights for mothers and their children at 2 years of age, nativity weight and the partner'due south measurements were not. Measurement of birth weight and length on calibrated scales and measured heights and weights of partners is preferable for future studies. Parents were too the source of reporting for their children's appetitive traits in this study. Ratings from parents are often used to collect data on childhood behavior and temperament, and thus, information technology is standard practice to ask primary caregivers to charge per unit their children's traits.(23) Future studies could include other methods of measurement, such every bit straight observation. However, it is important to keep in mind that observations, although correlated, may not necessarily be the same as appetitive traits that are reported by caregivers (39). Circumspection is too warranted in drawing conclusions near causal associations from the findings in this written report. Although we did examine changes from birth, this is essentially a cross-exclusive design since eating behavior and 24 month heights and weights were measured at the same time. We did include a number of covariates that might influence weight gain from birth, such as gestational age and a measure out of the length of lactation, yet, unmeasured potential confounders cannot exist ruled out. Also, it could be that heavier toddlers are viewed by their mothers as existence more responsive to nutrient or being insatiable. Nosotros are currently following this accomplice of children and parents equally the children turn six years of age. Time to come studies will examine whether these associations between childhood traits at 24 months predict subsequent weight gain and if this is modified by other familial take chances factors. Studies extending these analyses could also exist informed past assessing how parent behaviors or feeding practices contribute to these associations. In general, since randomization to appetitive traits is not possible, longitudinal studies with multiple follow-upwardly assessments will let for a clearer understanding of the extent to which such traits influence childhood weight gain and the potential mediating and moderating factors that contribute to this association.
CONCLUSIONS
Our findings point that certain factors, like parental obesity, can collaborate with childhood appetitive traits to heighten the risk of childhood obesity. The extent to which these traits are modifiable is largely unknown. These characteristics or temperamental dispositional behaviors toward nutrient reverberate a range of responding, which potentially increases children's vulnerability to factors in the family unit environment (e.m., accessibility/availability of energy dense foods) that place children at chance for obesity.(37) However, it may exist that, with targeted interventions, select deficits may be strengthened. The standard approach for childhood obesity treatments and interventions has been to address dietary quality and concrete activity with attending to modifying the parent'due south lifestyle behavior or their feeding practices. In pre-school age children, these multi-component, family-based programs have shown modest effectiveness in reducing weight in children who are already obese. (40) Less research has focused on methodologies for directly modifying children's appetitive traits. Strategies for increasing satiety awareness or reducing food responsiveness (e.g., teaching children to more accurately recognize hunger and fullness or reducing their reactivity to food cues) are warranted. Such strategies could complement traditional interventions focused on improving dietary quality and may exist particularly useful for children whose parents are themselves obese. In short, assessing family risk factors in add-on to the individual childhood characteristics may be a particularly useful for further clarifying the associations that appetitive traits have with childhood gamble for obesity, and continued research in this area could be useful in informing prevention strategies.
Acknowledgments
Sources of Back up: R01 DK064986 (TO), R01 DK064986S (TO and BFF), and K07CA124905 (BFF).
Footnotes
DISCLOSURE
The following are the potential conflicts of interest: Drs. Fuemmeler, Lovelady, Zucker, and Østbye have received funding from the National Institutes of Health. Additionally, Dr. Østbye has received consulting fees from Eli Lilly and Astra/Zeneca.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3671382/
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