Background:

NICE has called for greater support for frontline staff for the management of childhood obesity, who are often limited in dealing with these patients by lack of time and specialist training. However, whilst guidance statements and generic advice are available, few practical management tools for untrained staff currently exist. A detailed clinical tool based on a series of validated questions has been shown to be feasible in the secondary care setting in New Zealand. A similar tool for the management of adult obesity has been piloted in one PCT in England. The use of an electronic tool in the management of childhood obesity could assist practice nurses in the management and appropriate referral of childhood obesity, overcoming the issues of lack of time and training.

Aim:

To develop algorithms for use in the assessment, referral and management of childhood obesity in primary care.

The algorithms will: 1) help to identify those young people at greatest risk of obesity co-morbidities; and 2) identify characteristics of patients that will aid management decisions, e.g. child's current diet, level of physical activity, or psychological state.

The algorithms developed in this project will be incorporated into an electronic tool to assist practice nurses in the referral and management of obese children.

Methods:

- Potential data items for analysis will be identified through expert interviews and systematic reviews of the literature on childhood obesity management, co-morbidities, co-morbidity risk factors, and existing clinical algorithms for risk assessment and referral.

- Based on the preliminary list established through systematic reviews, data items from ALSPAC will be selected and analysed to identify variables that best predict obesity co-morbidities in this population. Data will also be analysed to identify characteristics of patients that will aid practice nurses in management decisions (including readiness to change, diet, activity, sedentary behaviours, sociodemographic characteristics).

- From these lists, eligible data items will be short-listed through a pre-defined selection process, which will include assessment of face validity, relevance, and sensitivity/specificity/predictive value in the UK population and feasibility of data collection in the primary care setting, to produce a list of approximately 20 items. Algorithms based on these items will be generated and incorporated into an electronic tool that identifies children at risk of co-morbidities, and generates personalised management plans.

Potential data items for the tool:

Assessment of co-morbidities

- Sex

- Age

- Ethnicity

- BMI

- Family history of disease/treatment/hospitalization/medical diagnoses

- Premature puberty

- Learning difficulties, syndromic obesity

- Skin - acanthosis nigricans

- Blood pressure

- Body fat distribution - wiast circumference, thigh circumference etc

Childhood obesity co-morbidities

- Nonalcoholic fatty liver disease (ALT)

- Impaired thyroid function (TF3, TF4)

- Components of metabolic syndrome:

- Hyperinsulinemia/insulin resistance

- Dyslipidemia

- Hypertension

- Proteinuria

- Prediabetes/type 2 diabetes

- Gastroesophageal reflux

- Musculoskeletal disorders, e.g. slipped capital femoral epiphysis and Blount disease

- Gallstones

- Asthma

- Polycystic ovarian syndrome

- Obstructive sleep apnoea

- Mood disorders/depression

Factors affecting treatment decisions

- Diet: level of consumption, consumption of fruit/veg, fizzy drinks, snacks between meals, portion size

- Activity: hours of organised activity, leisure activity, walking

- Sedentary behaviours: screen time, eating in front of TV

- Mood/depression

- Willingness to change

- Self-efficacy/confidence

- Family/environmental circumstances: free school meals, access to play area, who cooks at home

- Previous interventions

- Learning difficulties

- Behavioural problems

- Age, sex, ethnicity

- Degree of overweight.