Maternal concern about her toddler undereating and becoming underweight and use of feeding practices - analysis of the NOURISH and SAIDI cohorts using structural equation modeling

The chubby baby who eats well is desirable in our culture. Perceived low weight gains and feeding concerns are common reasons mothers seek advice in the early years. In contrast, childhood obesity is a global public health concern. Use of coercive feeding practices, prompted by maternal concern about weight, may disrupt a child’s innate self regulation of energy intake, promoting overeating and overweight. This study describes predictors of maternal concern about her child undereating/becoming underweight and feeding practices. Mothers in the control group of the NOURISH and South Australian Infants Dietary Intake studies (n = 332) completed a self-administered questionnaire when the child was aged 12–16 months. Weight-for-age z-score (WAZ)was derived from weight measured by study staff. Mean age (SD) was 13.8 (1.3) months, mean WAZ (SD), 0.58 (0.86) and 49% were male. WAZ and two questions describing food refusal were combined in a structural equation model with four items from the Infant feeding Questionnaire (IFQ) to form the factor ‘Concern about undereating/weight’. Structural relationships were drawn between concern and IFQ factors ‘awareness of infant’s hunger and satiety cues’, ‘use of food to calm infant’s fussiness’ and ‘feeding infant on a schedule’, resulting in a model of acceptable fit. Lower WAZ and higher frequency of food refusal predicted higher maternal concern. Higher maternal concern was associated with lower awareness of infant cues (r = −.17, p = .01) and greater use of food to calm (r = .13, p = .03). In a cohort of healthy children, maternal concern about undereating and underweight was associated with practices that have the potential to disrupt self-regulation.

The ‘Good Eater’ : modelling maternal perception of food fussiness in Australian toddlers – the NOURISH and SAIDI cohorts

Purpose Food refusal is part of normal toddler development due to an innate ability to self-regulate energy intake and the onset of neophobia. For parents, this ‘fussy’ stage causes great concern, prompting use of coercive feeding practices which ignore a child’s own hunger and satiety cues, promoting overeating and overweight. This analysis defines characteristics of the ‘good eater’ using latent variable structural equation modelling and the relationship with maternal perception of her child as a fussy eater. Methods Mothers in the control group of the NOURISH and South Australian Infants Dietary Intake studies (n=332) completed a self-administered questionnaire - when child was age 12-16 months - describing refusal of familiar and unfamiliar foods and maternal perception as fussy/not fussy. Weight-for-age z-score (WAZ) was derived from weight measured by study staff. Questionnaire items and WAZ were combined in AMOS to represent the latent variable the ‘good eater’. Results/findings Mean age(sd) of children was 13.8(1.3) months, mean WAZ(sd), .58(.86) and 49% were male. The ‘good eater’ was represented by higher WAZ, a child that hardly ever refuses food, hardly ever refuses familiar food, and willing to eat unfamiliar foods (x2/df=2.80, GFI=.98, RMSEA=.07(.03-.12), CFI=.96). The ‘good eater’ was inversely associated with maternal perception of her child as a fussy eater (β=-.64, p<.05). Conclusions Toddlers displaying characteristics of a ‘good eater’ are not perceived as fussy, but these characteristics, especially higher WAZ, may be undesirable in the context of obesity prevention. Clinicians can promote food refusal as normal and even desirable in healthy young children.

Can mothers accurately describe their toddler’s weight? Results from the NOURISH cohort

A mother’s perception of her child’s weight may be more important in determining how she feeds her child, than the child’s actual weight status. Use of controlling feeding practices, prompted by perceptions and concerns about weight, may disrupt the child’s innate self-regulation of energy intake. This can promote overeating and overweight (Costanzo & Woody, 1985). This study describes mother’s perception of her child’s weight relative to the child’s actual weight. Mothers in the control group of NOURISH (n=276) were asked to describe their child as underweight, normal weight, or somewhat/very overweight via self-administered questionnaire when children were aged 12-16 months (Daniels et al, 2009). Child’s weight and length were measured by study staff. At assessment, mean age (sd) was 13.7(1.3) months, mean weight-for-age z-score (sd) was 0.6(0.8) (WHO standards, 2008), and 51% were male. Twenty-seven children were perceived as underweight (10%) and twelve children were perceived as overweight (4%). ANOVA revealed significant differences in weight-for-age z-scores across each category of weight perception, mean (sd) -0.2(0.5), 0.6(0.8) and 1.8(0.7) for underweight, normal weight and overweight respectively F(4, 288)= 15.6, (p<0.00). Based on WHO criteria only one of the 27 children was correctly perceived as underweight (WHO 2008). Similarly while 12 children were perceived as overweight, 88 were actually overweight/at risk. At group level, children of mothers who perceived their child as underweight were indeed leaner. However at the individual level mothers could not accurately describe their child’s weight, tending to over-identify underweight and perceive overweight children as normal weight.

Reply by authors to J.C. Wilcox

This is a reply to "Comment on 'Online Estimation of Allan Variance Parameters' " by James C.Wilcox published in JOURNAL OF GUIDANCE, CONTROL, AND DYNAMICS Vol. 24, No. 3, May–June 2001. OUR statement “Modern gyros provide angular rate measurements directly, and hence, angular quantization is meaningless” made in the original paper should first be read with the accompanying sentences in the paragraph. The meaning of the sentence would perhaps have been clearer if written". . .

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

Adaptive estimation of HMM transition probabilities

This paper presents new schemes for recursive estimation of the state transition probabilities for hidden Markov models (HMM's) via extended least squares (ELS) and recursive state prediction error (RSPE) methods. Local convergence analysis for the proposed RSPE algorithm is shown using the ordinary differential equation (ODE) approach developed for the more familiar recursive output prediction error (RPE) methods. The presented scheme converges and is relatively well conditioned compared with the ...

On adaptive HMM state estimation

In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.

Adaptive estimation of hidden semi-Markov chains with parameterised transition probabilities and exponential decaying states

This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

Optimal HMM processing of differentially phase modulated communication systems

This paper investigates demodulation of differentially phase modulated signals DPMS using optimal HMM filters. The optimal HMM filter presented in the paper is computationally of order N3 per time instant, where N is the number of message symbols. Previously, optimal HMM filters have been of computational order N4 per time instant. Also, suboptimal HMM filters have be proposed of computation order N2 per time instant. The approach presented in this paper uses two coupled HMM filters and exploits knowledge of ...

Reduced complexity on-line estimation of hidden Markov model parameters

In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

Faster parameter estimation using risk-sensitive filters

In this paper, we propose a risk-sensitive approach to parameter estimation for hidden Markov models (HMMs). The parameter estimation approach considered exploits estimation of various functions of the state, based on model estimates. We propose certain practical suboptimal risk-sensitive filters to estimate the various functions of the state during transients, rather than optimal risk-neutral filters as in earlier studies. The estimates are asymptotically optimal, if asymptotically risk neutral, and can give significantly improved transient performance, which is a very desirable objective for certain engineering applications. To demonstrate the improvement in estimation simulation studies are presented that compare parameter estimation based on risk-sensitive filters with estimation based on risk-neutral filters.

On-line estimation of Allan variance parameters

A new online method is presented for estimation of the angular random walk and rate random walk coefficients of IMU (inertial measurement unit) gyros and accelerometers. The online method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph. Allan variance graphs have large off-line computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of O(100) calculations per data sample.

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Association study of MTHFD1 coding polymorphisms R134K and R653Q with migraine susceptibility

Objective There is evidence that folate metabolism has a role in migraine pathophysiology, particularly in the migraine with aura subtype. In this study we investigate whether two non-synonymous single nucleotide polymorphisms (SNPs), rs1950902 (C401T; R134K) and rs2236225 (G1958A; R653Q), in MTHDF1 are associated with migraine in an Australian case-control population. Background Increased plasma levels of homocysteine (HCy), one of the metabolites produced in the folate pathway, has been found to be a risk factor for migraine. There is also a genetic link, as a common polymorphism (C667T) that reduces the catalytic activity of MTHFR, the enzyme that catalyses the formation of HCy, is associated with an increase in risk of the migraine with aura (MA) subtype. MTHFD1 is a crucial multifunctional enzyme that catalyses three separate reactions of the folate pathway and therefore variants in MTHFD1 may also influence migraine susceptibility. Methods The R134K and R653Q variants in MTHFD1 were genotyped in an Australian cohort of 520 unrelated migraineurs (162 were diagnosed with migraine without aura [MO] and 358 with MA) and 520 matched controls. Data were analysed for association with migraine and for interaction with the MTHFR C667T polymorphism. Results We find no significant differences in genotype or allele frequencies for either SNP between migraineurs and controls, or when either MO or MA cases were compared to controls. In addition these MTHFD1 polymorphisms did not appear to influence the risk of MA conferred by the MTHFR 667T allele. Conclusions We find no evidence for association of the MTHFD1 R134K and R653Q polymorphisms with migraine in our Australian case-control population. However, as folate metabolism appears to be important in migraine, particularly with respect to the aura component, future studies using high throughput methods to expand the number of SNPs in folate-related genes genotyped and investigation of interactions between SNPs may be justified.