Abstract
OBJECTIVE
Gastrointestinal (GI) problems are common in eating disorders, but it is unclear whether these problems predate the onset of disordered eating. Recurrent abdominal pain (RAP) is the most prevalent GI problem of childhood, and this study aimed to explore longitudinal associations between persistent RAP (at ages 7 and 9) and fasting for weight control at 16.
METHODS
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a UK population cohort of children. Childhood RAP was reported by mothers and defined as RAP 5+ (5 pain episodes in the past year) in our primary analysis, and RAP 3+ (3 pain episodes) in our sensitivity analysis. Fasting for weight control was reported by adolescents at 16. We used logistic regression models to examine associations, with adjustments for potential confounders.
RESULTS
After adjustments, we found no association between childhood RAP 5+ and adolescent fasting for weight control at 16 (OR 1.30 (95% Confidence Intervals (CI) 0.87, 1.94) p= 0.197). However, we did find an association between RAP 3+ and later fasting, in the fully adjusted model (OR 1.50 (95% CI 1.16, 1.94) p= 0.002), and after excluding those with pre-existing anxiety (OR 1.52 (95% CI 1.17, 1.97) p= 0.002).
CONCLUSIONS
Our findings suggest a possible independent contribution of RAP to later risk of fasting for weight control, and RAP should be enquired about in the assessment of eating disorders. However, frequency of childhood abdominal pain (as captured by ALSPAC) may be less important to long term outcomes than functional impairment.
Keywords: ALSPAC, Abdominal Pain, Fasting, Longitudinal, Prospective, Child, Adolescent, Eating Disorders, Cohort Study, United Kingdom
Introduction
People with eating disorders (ED) are known to suffer from concurrent gastrointestinal (GI) complaints (e.g. abdominal pain, constipation and bloating) [1] and there is an expanding body of evidence that suggests, for a significant group of patients, that GI symptoms may precede their disordered eating [2] [3] [4]. By far the most common GI complaint in childhood is recurrent abdominal pain (RAP). This affects between 10–12% of 5- to 16-year-old schoolchildren, [5] [6] usually with no identifiable disease pathology [7]. The most widely accepted definition of recurrent abdominal pain, introduced by Apley, is when a child has had, ‘At least three bouts of pain, severe enough to affect his/her activities, over a period of at least 3 months, with attacks continuing in the year preceding examination’ [5]. However, the concept of childhood RAP has more recently (2016) been replaced by the term pediatric Functional Abdominal Pain Disorders (FAPDs) [8]. According to the Rome IV Criteria, FAPDs can be defined as when abdominal pain occurs 4 or more times a month, for at least 2 months, in either an episodic or continuous fashion, and cannot be ascribed to an inflammatory, anatomic, metabolic, or neoplastic process [9]. Pediatric FAPDs can be subclassified, utilizing the Rome IV criteria, to comprise irritable bowel syndrome, functional dyspepsia, abdominal migraine and functional abdominal pain not otherwise specified [10]. FAPDs are thought to share the same etiology and they more recently tend to be described as disorders of GI–brain interaction [8]. Whilst the Apley definition requires children to suffer from less frequent pain than those applied for childhood FAPDs, it includes pain severity and functional impairment, so it remains useful and relates to the operational definitions used in the Rome criteria, which became available in 2005 [11]. We believe that the RAP data used in this study, which were collected from 1991 onwards, will broadly capture all of the pediatric FAPDs, as the parents were asked a general question about their child’s stomach pain without any reference to its cause or other co-morbidities. Thus, for clarity and consistency in this study, we will refer to childhood RAP.
Children with RAP tend to have more concurrent anxiety and depressive disorders, [12] [13] and the presence of childhood RAP is a robust predictor of emotional disorders in adulthood [14–17]. The high association of childhood RAP with anxiety has meant that RAP has often been attributed to generalised anxiety [13]. However, more recent research has shown that visceral hypersensitivity (i.e. increased sensitivity to GI sensations) is especially important for developing increased pain sensitivity, hypervigilance, and poor coping responses[18] [19]. Such visceral hypersensitivity appears to be a key independent variable in long term health outcomes[20] [18]. The association between visceral hypersensitivity and GI symptom severity was elegantly demonstrated in a study that incorporated five large cohorts of patients with functional GI disorders. Associations between visceral hypersensitivity and GI symptom severity were still present after adjusting for anxiety, suggesting that visceral hypersensitivity makes an independent contribution to the severity of GI symptoms. [20].
It is plausible that early GI discomfort (as seen in RAP) may increase vulnerability to anorexia nervosa (AN) through processes of aversive visceral conditioning [3]. Early painful GI events may sensitize children’s pain pathways, leading to amplification, preoccupation, and generalization to innocuous sensations [18]. In other words, children with RAP become oversensitive to and hypervigilant about their essentially normal gut sensations. The fear-avoidance model of pain predicts that children who suffer from visceral hypersensitivity may start avoiding particular foods and other activities which they associate with the prediction of later pain [21]. Food and eating may be a particularly potent learning pathway in the context of GI pain. The act of eating requires that one penetrate a body boundary. As such, it is critical that a variety of protective responses help an organism to avoid ingestion of a potential toxin. One example is vivid visceral memories resulting from one-trial learning experiences such as food poisoning, memories that can strongly influence later avoidance behaviour [3]. Thus, GI sensations may be potent learning signals, causing individuals to become highly anxious and preoccupied with food choices, and this may contribute to the development of disordered eating patterns [18] [20].
Figure 1 illustrates how a child with RAP can develop fearful reactions to normal GI sensations, and start to avoid foods which they associate with the pain. Based on the fear-avoidance model of pain [21], the model predicts that those suffering from childhood RAP will be more likely to avoid food by fasting to control their weight. Within the model, we propose that RAP and anxiety are intrinsically linked, and co-exist on the potential causal pathway to disordered eating.
Figure 1.

Fear avoidance model of abdominal pain and food restriction
A clinical study from Sweden showed that childhood GI complaints (defined as severe abdominal pain, early feeding problems, or in-patient treatment for GI problems) were more common in their sample of 51 adolescent females with anorexia nervosa than in healthy controls [22]. Also, in adult women with bulimia nervosa, those who recalled early childhood GI issues were found to have an earlier age of onset of their eating disorder and of the symptom of self-induced vomiting compared with women with no childhood GI complaints [23]. A case-control study (Quick, McWilliams, & Byrd-Bredbenner, 2012) matching individuals with a medical condition typically treated with a dietary manipulation (e.g., diabetes, irritable bowel syndrome) to healthy control subjects, found that those with a medical condition were twice as likely to be diagnosed with an eating disorder [24]. In a systematic review, Conviser, Fisher, and McColley (2018) found that reported age of onset of a medical condition requiring dietary manipulation often preceded that of an eating disorder, but no prospective data about this relationship were reported in regard to GI disorders generally or RAP specifically [25]. To our knowledge, no study has assessed the prospective association between childhood RAP and subsequent fasting behaviours. Research using longitudinal data that have been collected prospectively is needed to avoid the challenges of bias in retrospective designs. Furthermore, population-based studies can help us to study more people with these difficulties, as many people with harmful fasting behaviours do not seek medical help [26]. Moreover, population studies consistently find that many people meeting diagnostic criteria for eating disorders do not receive any kind of treatment [27].
We therefore examined the prospective relationship between childhood RAP and fasting behaviour in adolescence using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK population-based cohort [28]. We hypothesised that persistent childhood RAP (present at both ages 7 and 9) would be associated with an increased risk of fasting to control weight at age 16. In order to explore the complex relationship between RAP and anxiety, we subsequently excluded children with a pre-existing anxiety diagnosis at age 7, to see if any potential relationship between RAP and fasting to control weight remained.
Methods
Sample
Pregnant women resident in Avon, UK with expected dates of delivery from 1st April 1991 to 31st December 1992 were invited to take part in ALSPAC. The initial number of pregnancies enrolled was 14,541 (for these at least one questionnaire has been returned or a “Children in Focus” clinic had been attended by 19th July 1999). Of these initial pregnancies, there was a total of 14,676 fetuses, resulting in 14,062 live births and 13,988 children who were alive at 1 year of age [28, 29].
When the oldest children were approximately 7 years of age, an attempt was made to bolster the initial sample with eligible cases who had failed to join the study originally. As a result, when considering variables collected from the age of seven onwards (and potentially abstracted from obstetric notes) there are data available for more than the 14,541 pregnancies mentioned above. The number of new pregnancies not in the initial sample (known as Phase I enrolment) that are currently represented on the built files and reflecting enrolment status at the age of 24 is 913 (456, 262 and 195 recruited during Phases II, III and IV respectively), resulting in an additional 913 children being enrolled. The phases of enrolment are described in more detail in the cohort profile paper and its update [28]. The total sample size for analyses using any data collected after the age of seven is therefore 15,454 pregnancies, resulting in 15,589 fetuses. Of these 14,901 were alive at 1 year of age.
A 10% sample of the ALSPAC cohort, known as the Children in Focus (CiF) group, attended clinics at the University of Bristol at various time intervals between 4 to 61 months of age. The CiF group was chosen at random from the last 6 months of ALSPAC births (1432 families attended at least one clinic). Excluded were those mothers who had moved out of the area or were lost to follow-up, and those partaking in another study of infant development in Avon.
The study website contains details of all the data that are available through a fully searchable data dictionary and variable search tool: http://www.bristol.ac.uk/alspac/researchers/our-data.
Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees: http://www.bristol.ac.uk/alspac/researchers/research-ethics/. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time [28] [29].
We first excluded multiple births from the dataset, to remove any possible familial clustering effects. In this study, we present results on individuals with complete case data (n=3001) on exposures, outcome and potential confounders, as well as individuals with imputed data (n=8041). Please see our Figure 2 Flowchart of Attrition.
Figure 2.

Flowchart of Participant Attrition
Measures
Exposure: Recurrent Abdominal Pain (RAP) in childhood
ALSPAC collected childhood abdominal pain data by asking the parents the following questions:
1. Have there been times when your child seems to have had a pain in their stomach in the past 12 months?
(yes/no)
2. How many separate times has this happened in the past 12 months?
(Answer: Once, Twice, 3 or 4 times, 5 or more times, or Don’t know)
ALSPAC sent questionnaires to mothers when their children were 3, 4, 7 and 9 years old. We focused on RAP at age 7 years and 9 years, as RAP in childhood peaks at age 7–9 years [30]. In line with previous research [7, 15] the RAP exposure measure for our primary analysis included all children reported as having 5 or more episodes of abdominal pain (RAP 5+) in the past year, because this most closely matched Apley’s definition of 3 episodes of abdominal pain in 3 months [5]. The ALSPAC dataset, however, differs from Apley’s definition, because it only asks about pain frequency, and it does not ask parents about the intensity of their child’s pain or their functional impairment. Since previous research highlights the association between avoidant behaviour, impairment, and parameters of pain beyond frequency [31] we did not want to miss relevant data by only capturing those children with the most frequent pain. We therefore conducted a sensitivity analysis including data from children who experienced 3 or more episodes of pain (RAP 3+) per year.
Outcome: Fasting
Data on “fasting to control weight” behaviours were gathered at age 16, using questions adapted from the Youth Risk Behaviour Surveillance System questionnaire [32]. The adolescents were asked the following question:
“During the past year, how often did you fast (not eat for at least a day) to lose weight or avoid gaining weight?”
(Answer: Never; Less than once a month; Monthly; Weekly)
We converted this to a binary (yes/no) variable of whether the adolescents had ever engaged in fasting behaviour over the past year. The question has been validated in comparison with the Eating Behaviours Interview in a population-based sample of adolescents [33].
Confounders
We adjusted for gender and various maternal factors (socioeconomic status (SES), maternal educational level, maternal anxiety and depression). Gender was included as a confounder because girls experience considerably higher rates of both RAP [7] and fasting to control weight [34].
We included maternal SES because high SES has been found to be associated with EDs in offspring [34]. RAP is also more common in children of mothers with higher educational attainment and social class [7]. Maternal SES was defined as an ordinal variable [I (professional), II (managerial/technical), IIIN (skilled non-manual), IIIM (skilled manual), IV (partly skilled), V (unskilled)]. Maternal educational level has been associated with EDs in offspring [35] and was included from maternal report at 32 weeks’ gestation. Mother’s highest educational qualification was coded as either advanced level qualifications obtained at age 18 or degree (1), or lower (ordinary level qualifications or certificate of secondary school education obtained at age 16, vocational qualification or none) (0).
Since RAP was determined via maternal reports, we controlled for maternal anxiety (a binary variable of mothers in the top 20% (≥8) on the Crown Crisp Experimental Index anxiety subscale [36] (during pregnancy, at 32 weeks’ gestation) and maternal depression (a binary variable of those scoring ≥12 on the Edinburgh Postnatal Depression Scale [37] (measured 8 weeks after birth) as previous research has shown both of these measures to be correlated with both RAP [38] and EDs in offspring [39].
Given the complex relationship between RAP and anxiety, we also repeated the analyses, excluding individuals with a Development and Wellbeing Assessment (DAWBA) anxiety diagnosis at age 7. We excluded these individuals to ensure that anxiety was not a pre-cursor to the RAP. However, Childhood RAP and anxiety are highly co-morbid and intrinsically linked on the potential causal pathway to disordered eating. Mothers reported child anxiety on a questionnaire version of the Development and Wellbeing Assessment (DAWBA)[40] when the child was 7. Responses were coded in line with DSM-IV anxiety diagnoses (separation anxiety disorder, specific phobia, social phobia, posttraumatic stress disorder, obsessive compulsive disorder, generalised anxiety disorder and anxiety disorder not otherwise specified). We used a derived binary (yes/no) variable for any anxiety disorder.
Statistical Analysis
All analyses were conducted using Stata version 16 [41]. First, we describe sample characteristics in complete cases, those with all available data, and the imputed dataset (see Table 1). We used logistic regression models to examine associations between persistent RAP 5 + (5 or more episodes per year) at ages 7 and 9 years and subsequent fasting at age 16. Initially, we examined unadjusted associations, before sequentially adjusting for gender (Model A), maternal social class and education (Model B), and maternal anxiety and depression (Model C). We conducted a sensitivity analysis using persistent RAP 3+ at 7 and 9 years and fasting at 16. Given the complex relationship between RAP and anxiety, we repeated these analyses in individuals without a DAWBA anxiety diagnosis at age 7.
Table 1.
Sample characteristics for participants with complete case and all available data
| Available data (N varies by variable) |
Complete case (N=3001) |
Imputed data (n=8041) |
|
|---|---|---|---|
| Persistent RAP at 7 and 9 years (N, %) | 359/6607 (5.43%) | 186 (6.20%) | 5.51% |
| Fasting to control weight at 16 (N, %) | 624/4726 (13.20%) | 380 (12.66%) | 11.57% |
| Anxiety diagnosis at 7 years (N, %) | 250/8041 (3.11%) | 73 (2.43%) | 5.14% |
| Gender, female (N, %) | 6589/13604 (48.43%) | 1693 (56.41%) | 48.68% |
| Maternal social class, I (N, %) | 578/9794 (5.90%) | 286 (9.53%) | † |
| Maternal education, A level or higher (N, %) | 4276/12090 (35.37%) | 1592 (53.05%) | 41.40% |
| Maternal anxiety (N, %) | 2601/11407 (22.80%) | 494 (16.46%) | 20.68% |
| Maternal depression (N, %) | 1486/11416 (13.02%) | 296 (9.86%) | 11.85% |
Complete case = data for all RAP exposures, fasting to control weight, and all covariates;
RAP = Recurrent Abdominal Pain defined as 5+ instances of stomach pain in the last 6 months
Social class could not be computed in the imputational model
Missing data
Due to missing data on RAP, fasting, and confounding variables, the complete case analysis sample was smaller than the original starting sample. Thus, to avoid biased or underestimated results, we examined the potential impact of missing data by imputing data using the multivariate imputation by chained equations (MICE) approach [42] to boost the sample to those responding to the age 7 questionnaire with anxiety diagnosis. This was done using the “mi impute chained” command in Stata which assumes data is missing at random (MAR), that is, differences between respondents and non-respondents can be explained by other observed data. Imputation models included variables required for analysis in addition to auxiliary variables related to missingness. Auxiliary variables included in the models were RAP at 3 and 4 years, BMI at ages 7 and 15, parent-reported child fear of weight gain and fat avoidance at ages 13 and 16, child-reported body dissatisfaction at age 14, and parent-reported child depressive symptoms at age 11. Fifty imputed datasets were created for each of two different imputation models – one for all participants responding to the age 7 anxiety diagnosis questionnaire (n=8041), and another for all participants without an anxiety diagnosis at age 7 (n=7791).
Results
Table 1 provides descriptive information about the participants with complete case and partial data for the exposure and outcome variables, including the numbers in the imputed data.
In complete case analyses, 186 of 3001 children (6.2%) were reported by their parents as having persistent abdominal pain at both ages 7 and 9 years. When we defined RAP as 3+ instead of 5+ episodes in the past year, the number of children with persistent pain increased to 571 of 3001 (19.0%). 380 of the 3001 adolescents (12.7%) reported fasting for more than one day, to lose weight. In the complete case sample of 3001, 494 (16.5%) of mothers suffered from an anxiety disorder, and 73 (2.73%) children suffered from an anxiety disorder at age 7.
In the complete case sample, 18.82% (35/186) of children with RAP5+ reported fasting at age 16, compared to 12.26% (345/2815) of individuals without RAP5+. Similarly, 18.74% (107/571) of children with RAP3+ reported fasting at age 16 compared to 11.23% (273/2430) without RAP3+.
Persistent childhood RAP (5+) and fasting at 16
In our primary analysis, defining RAP as 5 or more episodes of abdominal pain in the past year, we found an initial association between RAP 5+ and fasting to control weight at age 16 in the unadjusted model (OR 1.66 (95% CI.1.13, 2.44), p= 0.011) (Table 2). However, this association decreased after adjusting for gender, and included the possibility of no association (OR 1.28 (95% CI.0.86, 1.91), p= 0.216) (Table 2). In the fully adjusted model (controlling for gender, maternal education and SES, and maternal anxiety and depression) we found no evidence for an association between RAP 5+ and fasting to control weight (OR 1.30 (95% CI.0.87, 1.94), p= 0.197) (Table 2).
Table 2.
Associations between persistent RAP (defined as 5+ episodes of abdominal pain in the past year) and fasting to control weight at age 16
| Unadjusted | Adjusted Model A | Adjusted Model B | Fully adjusted Model C | |||||
|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | |
| Persistent RAP (5+) at 7 and 9 years (complete cases, n=3001) |
1.66 (1.13, 2.44) | .011 | 1.28 (0.86, 1.91) | .216 | 1.31 (0.88, 1.95) | .186 | 1.30 (0.87, 1.94) | .197 |
| Persistent RAP (5+) at 7 and 9 years (imputed dataset, n=8041) |
1.37 (0.99, 1.91) | .060 | 1.04 (0.73, 1.46) | .841 | 1.06 (0.75, 1.49) | .761 | 1.04 (0.74, 1.48) | .822 |
| Analyses restricted to individuals without DAWBA anxiety diagnosis at age 7 | ||||||||
| Persistent RAP (5+) at 7 and 9 years (complete cases, n=2928) |
1.61 (1.08, 2.38) | .018 | 1.25 (0.83, 1.88) | .276 | 1.27 (0.85, 1.92) | .244 | 1.27 (0.84, 1.91) | .254 |
| Persistent RAP (5+) at 7 and 9 years (imputed dataset, n=7791) |
1.35 (0.92, 1.98) | .130 | 1.01 (0.67, 1.51) | .972 | 1.03 (0.69, 1.54) | .891 | 1.02 (0.68, 1.53) | .931 |
Model A = adjusted for gender;
Model B = adjusted for gender, maternal social class and maternal education;
Fully adjusted Model C = adjusted for gender, maternal social class, maternal education, maternal anxiety and maternal depression
RAP = Recurrent Abdominal Pain defined as 5+ episodes of stomach pain in the last 12 months
We did not find an association after we excluded those with a DAWBA-diagnosed anxiety disorder at age 7 (OR 1.27 (95% CI.0.84, 1.91), p= 0.254) (Table 2). Findings from imputed data were consistent with complete case results.
Persistent childhood RAP (3+) and fasting at 16
In our sensitivity analysis, defining RAP as 3 or more episodes of abdominal pain in the past year, we found an association between RAP 3+ and fasting to control weight at 16, and this association remained after adjusting for confounding variables (OR 1.50 (95% CI.1.16, 1.94), p=0.002) (Table 3).
Table 3.
Sensitivity analysis: Associations between RAP (defined as 3+ episodes of abdominal pain in the last year) and fasting to control weight at age 16
| Unadjusted | Adjusted Model A | Adjusted Model B | Fully adjusted Model C | |||||
|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | |
| Persistent RAP (3+) at 7 and 9 years (complete cases, n=3001) |
1.82 (1.43, 2.33) | <.001 | 1.49 (1.15, 1.92) | .002 | 1.50 (1.16, 1.94) | .002 | 1.50 (1.16, 1.94) | .002 |
| Persistent RAP (3+) at 7 and 9 years (imputed dataset, n=8041) |
1.53 (1.23, 1.92) | <.001 | 1.27 (1.00, 1.62) | .051 | 1.29 (1.02, 1.64) | .040 | 1.28 (1.01, 1.63) | .041 |
| Analyses restricted to individuals without DAWBA anxiety diagnosis at age 7 | ||||||||
| Persistent RAP (3+) at 7 and 9 years (complete cases, n=2928) |
1.85 (1.44, 2.37) | <.001 | 1.50 (1.16, 1.95) | <.001 | 1.52 (1.17, 1.97) | .001 | 1.52 (1.17, 1.97) | .002 |
| Persistent RAP (3+) at 7 and 9 years (imputed dataset, n=7791) |
1.58 (1.27, 1.97) | <.001 | 1.31 (1.05, 1.65) | <.001 | 1.34 (1.07, 1.67) | .011 | 1.33 (1.05, 1.67) | .021 |
Model A = adjusted for gender;
Model B = adjusted for gender, maternal social class and maternal education;
Fully adjusted Model C = adjusted for gender, maternal social class, maternal education, maternal anxiety and maternal depression
RAP = Recurrent Abdominal Pain defined as 3+ episodes of stomach pain in the last 12 months
The association also remained after we excluded those with a DAWBA-diagnosed anxiety disorder at age 7 (OR 1.52 (95% CI.1.17, 1.97), p=0.002). The findings were also unchanged when we conducted the analyses using the imputed datasets (Table 3).
Discussion
In our primary analysis, we did not find evidence of a relationship between persistent childhood RAP (defined as 5+ episodes in the past year at age 7 and 9) and fasting to control weight at 16, once we adjusted for gender. This suggests that the apparent relationship seen in the unadjusted model was explained by the strong associations between female gender and both childhood RAP and adolescent fasting to control weight. However a different picture emerged in our sensitivity analysis. When we defined RAP as 3+ episodes of pain in the past year at age 7 and 9, we found that RAP 3+ was associated with fasting to control weight at 16, and this association persisted following adjustment for confounding variables, and in an analysis excluding those with a DAWBA anxiety diagnosis at age 7.
There are a number of possible reasons why we found an association between “fasting to control weight” with RAP 3+ but not RAP 5+. One explanation could be that pain frequency (as captured by ALSPAC) may be less important to long term outcomes than pain severity, pain distress and/or the child’s functional impairment resulting from their pain. For example, previous research has demonstrated an association between a child’s avoidant coping style when experiencing pain and their functional disability, and this link may be especially relevant to the association between RAP and fasting to control weight, [31] in that either there is an important mediator between RAP and fasting (e.g., pain distress, fear of weight-gain/intolerance of bloating) that would be a crucial target for intervention or that another feature of pain (e.g., pain intensity) was related to more functional impairment. Thus, having a cut off of RAP 3+ could have captured children with more emotional or functional impairment (e.g. school avoidance, social withdrawal) despite having fewer episodes of pain.
Another explanation for an association with RAP 3+ but not RAP 5+ could be the contribution of the Non-Extreme Response bias, whereby participants tend to avoid selecting the extreme endpoints on a scale, preferring to select the middle values [43]. Thus, by asking the parents to report their child’s RAP as 5+ episodes in the past year, we may have inadvertently missed out on important and relevant data.
Alternatively, it could be that the children with the more frequent abdominal pain (RAP 5+) have some other underlying cause that might get treated prior to adolescence. This seems unlikely, however, as there is robust evidence that childhood RAP is rarely due to a disease process [7] [44]. RAP may arise from a variety of causes and this is highlighted by the conceptualization of RAP as a disorder of GI-brain interaction. The complex interaction between GI physiology and top-down influences, such as threat interpretations of somatic sensations, must be taken into account when creating a formulation of childhood RAP. From this standpoint, bottom-up influences (e.g. delayed gastric emptying, constipation, aberrant immune responses) would enrich our understanding of an individual’s unique pain/eating pathway and potentially help us to develop more personalized intervention strategies. Also, because of this complexity, the number of episodes of abdominal pain (e.g., 3 versus 5 episodes) is but one facet to take into consideration in understanding an individual’s pain experience and how they choose to manage that experience (e.g., as with restricting eating).
The other possibility is that our results may be due to chance. We think this is unlikely because the association between childhood RAP 3+ and fasting to control weight at 16 held after adjusting for a variety of confounders known to be associated with both our exposure and outcome.
Various mechanisms might explain the possible association between less frequent, but nonetheless persistent, childhood RAP and adolescent fasting to control weight. First, unpleasant GI experiences could lead children to become oversensitive to and hypervigilant about essentially normal GI sensations [20]. Consuming food is inevitably associated with GI sensations, so a desire to avoid uncomfortable GI feelings could contribute to beliefs about the avoidance of certain foods, food amounts, or periods of food abstinence as contributing to improvement in GI sensations [2]. Second, such behaviours could have physiological and metabolic consequences such as alterations in the composition of the intestinal microbiome. In a cohort of children with functional GI problems, their microbiome composition correlated with abdominal pain severity and frequency [45]. Also, there is evidence that in patients with AN, levels of depression, anxiety, and eating disorder psychopathology were associated with composition and diversity of their gut bacteria [46].
Strengths and Limitations
The major strengths of our study are the large sample size, prospective collection of data on RAP and confounders, and the long duration of follow up. Using this study design, we have also been able to include more participants. Many of these will have experienced RAP and unhealthy fasting behaviours, but may never have come to the attention of doctors [26].
These results need to be interpreted in the light of some limitations. The diagnostic criteria for RAP have been subject to some debate [8]. Apley’s original definition of childhood RAP [5], which corresponds best to the ALSPAC data collected in 1991, requires children to suffer from less frequent pain than the Rome IV criteria, and it does not include a detailed assessment of their functional impairment. Thus, it is possible that the group we describe here was affected less severely than those in other studies [8, 9]. However, we think this is unlikely because a previous ALSPAC study showed that nearly one quarter (23.5%) of the children with RAP had been taken to the doctor because of their abdominal pain [7].
The most widely used measure of eating disorder psychopathology is the Eating Disorder Examination Questionnaire (EDE-Q), which defines “food avoidance” as, “Going without food for a period of 8 or more waking hours in order to influence weight or shape”. Previously, the DSM-IV criterion of “fasting” defined it as “not eating anything at all for 24 hours” [47] but this is now considered to be overly restrictive [48]. In our study, 12.66% of 16-year-olds stated that over the past year, they fasted (did not eat for at least a day) to lose weight. Whilst this is quite a stringent measure in terms of duration of fasting, it corresponds to other non-selected population samples [49], suggesting that we were broadly capturing the same people. However, we may have missed adolescents with milder, but still impairing fasting behaviours. On the other hand, fasting for a day does not in itself indicate a clinically diagnosable eating disorder.
As with any population based prospective cohort, sample attrition is a problem (see Figure 2). We used multiple imputation to account for missing data, but this technique is limited by our pre-existing knowledge of which factors to explore. Another potential limitation is that RAP was determined by maternal report. Nevertheless, adjusting for relevant maternal factors that may have influenced their reporting did not substantially alter the results. In addition the ALSPAC sample is a predominantly white British cohort [28], so results may not be applicable to other ethnic groups.
Clinical Implications
Our findings have a number of clinical implications and directions for future research. For example, we might want to consider routinely enquiring about childhood RAP in eating disorder assessments, not just those concerning Avoidant and Restrictive Food Intake Disorder (ARFID) [3] and routinely assessing disordered eating in patients with GI disorders [3]. Also, our findings suggest that our cognitive-behavioural interventions for patients with eating disorders might be enriched by incorporating an exposure component that targets patients’ anxiety and fear associated with their visceral sensations, and helps them to accept and better tolerate their physiology [50] [51].
Conclusions
To our knowledge, this is the first study to provide prospective evidence suggesting that there may be an association between childhood recurrent abdominal pain and later fasting behaviours in adolescence. By analysing a large cohort, our findings tentatively support previous clinical studies that have found that, for a group of eating disorder patients, RAP may precede and contribute to disordered eating [3] [22]. Our study extends previous work by suggesting that childhood RAP, may be an independent and specific risk factor for later fasting, above and beyond pre-existing anxiety.
Whilst the independent contribution of RAP to the overall risk of developing an eating disorder appears to be quite modest, coupled with anxiety and other important psychological factors it may be clinically significant and should be enquired about in the assessment and management of eating disorders.
Acknowledgements:
We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses.
Funding:
The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and Dr Kate Stein and Dr Helen Bould will serve as guarantors for the contents of this paper.
A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf); This research was specifically funded by the NIH (Grant ref: MH087786-01).
Dr Kate Stein is an NIHR funded Academic Clinical Fellow. We are grateful to Oxford University Clinical Academic Graduate Scheme (OUCAGS) for their financial support in allowing us to access the ALSPAC dataset. Dr Naomi Warne is supported by funding from the Medical Research Council/Medical Research Foundation (MRC/MRF grant number MR/S020292/1). Dr Zucker received funding from the National Science Foundation/National Institute of Mental Health (NIMH), Grant R01MH122370.
Footnotes
Data Availability Statement
The informed consent obtained from ALSPAC participants does not allow the data to be made freely available through any third party maintained public repository. However, data used for this submission can be made available on request to the ALSPAC Executive. The ALSPAC data management plan describes in detail the policy regarding data sharing, which is through a system of managed open access. Full instructions for applying for data access can be found here: http://www.bristol.ac.uk/alspac/researchers/access/. The ALSPAC study website contains details of all the data that are available (http://www.bristol.ac.uk/alspac/researchers/our-data/)
Conflicts of Interest: The authors have no conflicts to declare.
Contributor Information
K. Stein, Academic Clinical Fellow in Child and Adolescent Psychiatry, University of Oxford; Warneford Hospital, Oxford OX3 7JX.
N. Warne, Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN
J. Heron, Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN
N. Zucker, Associate Professor of Clinical Psychology, Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
H. Bould, Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN & Gloucestershire Health and Care NHS Foundation Trust, Gloucester, UK
References
- 1.Sato Y and Fukudo S, Gastrointestinal symptoms and disorders in patients with eating disorders. Clin J Gastroenterol, 2015. 8(5): p. 255–63. [DOI] [PubMed] [Google Scholar]
- 2.Wiklund CA, et al. , Prolonged constipation and diarrhea in childhood and disordered eating in adolescence. J Psychosom Res, 2019. 126: p. 109797. [DOI] [PubMed] [Google Scholar]
- 3.Zucker NL and Bulik CM, On bells, saliva, and abdominal pain or discomfort: Early aversive visceral conditioning and vulnerability for anorexia nervosa. Int J Eat Disord, 2020. 53(4): p. 508–512. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Jacobi C, et al. , Coming to terms with risk factors for eating disorders: application of risk terminology and suggestions for a general taxonomy. Psychol Bull, 2004. 130(1): p. 19–65. [DOI] [PubMed] [Google Scholar]
- 5.Apley J and Naish N, Recurrent abdominal pains: a field survey of 1,000 school children. Arch Dis Child, 1958. 33(168): p. 165–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Boey C, Yap S, and Goh KL, The prevalence of recurrent abdominal pain in 11- to 16-year-old Malaysian schoolchildren. J Paediatr Child Health, 2000. 36(2): p. 114–6. [DOI] [PubMed] [Google Scholar]
- 7.Ramchandani P, Hotopf M, Sandhu B, Stein A, The epidemiology of recurrent abdominal pain from 2 to 6 years of age: results of a large, population-based study. . Pediatrics, 2005. 116(1): p. 46–50. [DOI] [PubMed] [Google Scholar]
- 8.Thapar N, et al. , Paediatric functional abdominal pain disorders. Nat Rev Dis Primers, 2020. 6(1): p. 89. [DOI] [PubMed] [Google Scholar]
- 9.Hyams JS, et al. , Abdominal pain and irritable bowel syndrome in adolescents: a community-based study. J Pediatr, 1996. 129(2): p. 220–6. [DOI] [PubMed] [Google Scholar]
- 10.Hyams JS, et al. , Functional Disorders: Children and Adolescents. Gastroenterology, 2016. [DOI] [PubMed] [Google Scholar]
- 11.Rasquin-Weber A, et al. , Childhood functional gastrointestinal disorders. Gut, 1999. 45 Suppl 2(Suppl 2): p. Ii60–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ramchandani PG, et al. , Early parental and child predictors of recurrent abdominal pain at school age: results of a large population-based study. J Am Acad Child Adolesc Psychiatry, 2006. 45(6): p. 729–736. [DOI] [PubMed] [Google Scholar]
- 13.Campo JV, Annual Research Review: Functional somatic symptoms and associated anxiety and depression – developmental psychopathology in pediatric practice. Journal of Child Psychology and Psychiatry, 2012. 53(5): p. 575–592. [DOI] [PubMed] [Google Scholar]
- 14.Hotopf M, et al. , Why do children have chronic abdominal pain, and what happens to them when they grow up? Population based cohort study. BMJ, 1998. 316(7139): p. 1196–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Stein K, et al. , The predictive value of childhood recurrent abdominal pain for adult emotional disorders, and the influence of negative cognitive style. Findings from a cohort study. PLoS One, 2017. 12(9): p. e0185643. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Shelby GD, et al. , Functional abdominal pain in childhood and long-term vulnerability to anxiety disorders. Pediatrics, 2013. 132(3): p. 475–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.von Gontard A, et al. , Abdominal pain symptoms are associated with anxiety and depression in young children. Acta Paediatrica, 2015. 104(11): p. 1156–1163. [DOI] [PubMed] [Google Scholar]
- 18.Labus JS, et al. , The central role of gastrointestinal-specific anxiety in irritable bowel syndrome: further validation of the visceral sensitivity index. Psychosom Med, 2007. 69(1): p. 89–98. [DOI] [PubMed] [Google Scholar]
- 19.Hazlett-Stevens H, et al. , Prevalence of irritable bowel syndrome among university students: the roles of worry, neuroticism, anxiety sensitivity and visceral anxiety. J Psychosom Res, 2003. 55(6): p. 501–5. [DOI] [PubMed] [Google Scholar]
- 20.Simrén M, et al. , Visceral hypersensitivity is associated with GI symptom severity in functional GI disorders: consistent findings from five different patient cohorts. Gut, 2018. 67(2): p. 255–262. [DOI] [PubMed] [Google Scholar]
- 21.Leeuw M, et al. , The fear-avoidance model of musculoskeletal pain: current state of scientific evidence. J Behav Med, 2007. 30(1): p. 77–94. [DOI] [PubMed] [Google Scholar]
- 22.Råstam M, Anorexia nervosa in 51 Swedish adolescents: premorbid problems and comorbidity. J Am Acad Child Adolesc Psychiatry, 1992. 31(5): p. 819–29. [DOI] [PubMed] [Google Scholar]
- 23.Gendall KA, et al. , Childhood gastrointestinal complaints in women with bulimia nervosa. Int J Eat Disord, 2005. 37(3): p. 256–60. [DOI] [PubMed] [Google Scholar]
- 24.Quick VM, McWilliams R, and Byrd-Bredbenner C, Case-control study of disturbed eating behaviors and related psychographic characteristics in young adults with and without diet-related chronic health conditions. Eat Behav, 2012. 13(3): p. 207–13. [DOI] [PubMed] [Google Scholar]
- 25.Conviser JH, Fisher SD, and McColley SA, Are children with chronic illnesses requiring dietary therapy at risk for disordered eating or eating disorders? A systematic review. Int J Eat Disord, 2018. 51(3): p. 187–213. [DOI] [PubMed] [Google Scholar]
- 26.Solmi F, et al. , Eating disorders in a multi-ethnic inner-city UK sample: prevalence, comorbidity and service use. Soc Psychiatry Psychiatr Epidemiol, 2016. 51(3): p. 369–81. [DOI] [PubMed] [Google Scholar]
- 27.Swanson SA, et al. , Prevalence and correlates of eating disorders in adolescents. Results from the national comorbidity survey replication adolescent supplement. Arch Gen Psychiatry, 2011. 68(7): p. 714–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Boyd A, et al. , Cohort Profile: the ‘children of the 90s’--the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol, 2013. 42(1): p. 111–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Fraser A, et al. , Cohort Profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int J Epidemiol, 2013. 42(1): p. 97–110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ramchandani PG, et al. , The epidemiology of recurrent abdominal pain from 2 to 6 years of age: results of a large, population-based study. Pediatrics, 2005. 116(1): p. 46–50. [DOI] [PubMed] [Google Scholar]
- 31.Walker LS, et al. , A typology of pain coping strategies in pediatric patients with chronic abdominal pain. Pain, 2008. 137(2): p. 266–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Kann L, et al. , Youth Risk Behavior Surveillance - United States, 2017. MMWR Surveill Summ, 2018. 67(8): p. 1–114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Field AE, et al. , Comparison of self-report to interview assessment of bulimic behaviors among preadolescent and adolescent girls and boys. Int J Eat Disord, 2004. 35(1): p. 86–92. [DOI] [PubMed] [Google Scholar]
- 34.Lindberg L and Hjern A, Risk factors for anorexia nervosa: a national cohort study. Int J Eat Disord, 2003. 34(4): p. 397–408. [DOI] [PubMed] [Google Scholar]
- 35.Ahrén JC, et al. , We are family--parents, siblings, and eating disorders in a prospective total-population study of 250,000 Swedish males and females. Int J Eat Disord, 2013. 46(7): p. 693–700. [DOI] [PubMed] [Google Scholar]
- 36.Birtchnell J, Evans C, and Kennard J, The total score of the Crown-Crisp Experiential Index: a useful and valid measure of psychoneurotic pathology. Br J Med Psychol, 1988. 61 (Pt 3): p. 255–66. [DOI] [PubMed] [Google Scholar]
- 37.Cox JL, Holden JM, and Sagovsky R, Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry, 1987. 150: p. 782–6. [DOI] [PubMed] [Google Scholar]
- 38.Ramchandani PG, et al. , The impact of recurrent abdominal pain: predictors of outcome in a large population cohort. Acta Paediatr, 2007. 96(5): p. 697–701. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Bould H, et al. , Parental mental illness and eating disorders in offspring. Int J Eat Disord, 2015. 48(4): p. 383–91. [DOI] [PubMed] [Google Scholar]
- 40.Goodman R, et al. , The Development and Well-Being Assessment: description and initial validation of an integrated assessment of child and adolescent psychopathology. J Child Psychol Psychiatry, 2000. 41(5): p. 645–55. [PubMed] [Google Scholar]
- 41.StataCorp. 2019. Stata Statistical Software: Release 16. College Station, T.S.L., Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC. 2019. [Google Scholar]
- 42.White IR and Royston P, Imputing missing covariate values for the Cox model. Stat Med, 2009. 28(15): p. 1982–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Liu M, et al. , The Effect of Extreme Response and Non-extreme Response Styles on Testing Measurement Invariance. Frontiers in psychology, 2017. 8: p. 726–726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Thornton GC, et al. , Diagnostic outcomes following childhood non-specific abdominal pain: a record-linkage study. Arch Dis Child, 2016. 101(4): p. 305–9. [DOI] [PubMed] [Google Scholar]
- 45.Saulnier DM, et al. , Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome. Gastroenterology, 2011. 141(5): p. 1782–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Kleiman SC, et al. , The Intestinal Microbiota in Acute Anorexia Nervosa and During Renourishment: Relationship to Depression, Anxiety, and Eating Disorder Psychopathology. Psychosom Med, 2015. 77(9): p. 969–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.DSM-4, American Psychiatric Association. Diagnostic & statistical manual of mental disorders. 1994: Washington DC: America Psychiatric Associations. [Google Scholar]
- 48.Cooper Z and Fairburn CG, Refining the definition of binge eating disorder and nonpurging bulimia nervosa. Int J Eat Disord, 2003. 34 Suppl: p. S89–95. [DOI] [PubMed] [Google Scholar]
- 49.Carter JC, Stewart DA, and Fairburn CG, Eating disorder examination questionnaire: norms for young adolescent girls. Behav Res Ther, 2001. 39(5): p. 625–32. [DOI] [PubMed] [Google Scholar]
- 50.Plasencia M, et al. , Applying the disgust conditioning model of food avoidance: A case study of acceptance-based interoceptive exposure. Int J Eat Disord, 2019. 52(4): p. 473–477. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Zucker NL, et al. , Feeling and body investigators (FBI): ARFID division-An acceptance-based interoceptive exposure treatment for children with ARFID. Int J Eat Disord, 2019. 52(4): p. 466–472. [DOI] [PMC free article] [PubMed] [Google Scholar]
