BackgroundHealth-related data at local level could be provided by supplementing national health surveys with local boosts. Self-completion surveys are less costly than interviews, enabling larger samples to be achieved for a given cost. However, even when the same questions are asked with the same wording, responses to survey questions may vary by mode of data collection. These measurement differences need to be investigated further.MethodsThe Health Survey for England in London ('Core') and a London Boost survey ('Boost') used identical sampling strategies but different modes of data collection. Some data were collected by face-to-face interview in the Core and by self-completion in the Boost; other data were collected by self-completion questionnaire in both, but the context differed. Results were compared by mode of data collection using two approaches. The first examined differences in results that remained after adjusting the samples for differences in response. The second compared results after using propensity score matching to reduce any differences in sample composition.ResultsThere were no significant differences between the two samples for prevalence of some variables including long-term illness, limiting long-term illness, current rates of smoking, whether participants drank alcohol, and how often they usually drank. However, there were a number of differences, some quite large, between some key measures including: general health, GHQ12 score, portions of fruit and vegetables consumed, levels of physical activity, and, to a lesser extent, smoking consumption, the number of alcohol units reported consumed on the heaviest day of drinking in the last week and perceived social support (among women only).ConclusionSurvey mode and context can both affect the responses given. The effect is largest for complex question modules but was also seen for identical self-completion questions. Some data collected by interview and self-completion can be safely combined.

BackgroundThere is a need for local level health data for local government and health bodies, for health surveillance and planning and monitoring of policies and interventions. The Health Survey for England (HSE) is a nationally-representative survey of the English population living in private households, but sub-national analyses can be performed only at a regional level because of sample size. A boost of the HSE was commissioned to address the need for local level data in London but a different mode of data collection was used to maximise participant numbers for a given cost. This study examines the effects on survey and item response of the different survey modes.MethodsHousehold and individual level data are collected in HSE primarily through interviews plus individual measures through a nurse visit. For the London Boost, brief household level data were collected through interviews and individual level data through a longer self-completion questionnaire left by the interviewer and collected later. Sampling and recruitment methods were identical, and both surveys were conducted by the same organisation. There was no nurse visit in the London Boost. Data were analysed to assess the effects of differential response rates, item non-response, and characteristics of respondents.ResultsHousehold response rates were higher in the 'Boost' (61%) than 'Core' (HSE participants in London) sample (58%), but the individual response rate was considerably higher in the Core (85%) than Boost (65%). There were few differences in participant characteristics between the Core and Boost samples, with the exception of ethnicity and educational qualifications. Item non-response was similar for both samples, except for educational level. Differences in ethnicity were corrected with non-response weights, but differences in educational qualifications persisted after non-response weights were applied. When item non-response was added to those reporting no qualification, participants' educational levels were similar in the two samples.ConclusionAlthough household response rates were similar, individual response rates were lower using the London Boost method. This may be due to features of London that are particularly associated with lower response rates for the self-completion element of the Boost method, such as the multi-lingual population. Nevertheless, statistical adjustments can overcome most of the demographic differences for analysis. Care must be taken when designing self-completion questionnaires to minimise item non-response.

BackgroundThere is a strong case for early identification of factors predicting life-course-persistent conduct disorder. The authors aimed to identify factors associated with repeated parental reports of preschool conduct problems.MethodNested case–control study of Scottish children who had behavioural data reported by parents at 3, 4 and 5 years.Results79 children had abnormal conduct scores at all three time points (‘persistent conduct problems’) and 434 at one or two points (‘inconsistent conduct problems’). 1557 children never had abnormal scores. Compared with children with no conduct problems, children with reported problems were significantly more likely to have mothers who smoked during pregnancy. They were less likely to be living with both parents and more likely to be in poor general health, to have difficulty being understood, to have a parent who agrees that smacking is sometimes necessary and to be taken to visit other people with children rarely. The results for children with persistent and inconsistent conduct problems were similar, but associations with poverty and maternal smoking were significantly less strong in the inconsistent group.ConclusionThese factors may be valuable in early identification of risk of major social difficulties.

This study describes the distribution of glycosylated haemoglobin (HbA1c) and glucose concentrations in the combined year 1 (2008–2009), year 2 (2009–2010) and year 3 (2010–2011) of the National Diet and Nutrition Survey (NDNS) rolling programme. The NDNS rolling programme is a nationally representative survey of food consumption, nutrient intakes and nutritional status of people aged 1.5 years and over living in England, Wales, Scotland and Northern Ireland. The study population comprised survey members who completed three or four days of dietary recording and who provided a blood sample. After excluding survey members with self-reported diabetes (n=25), there were 1016 results for HbA1c and 942 for glucose (not the same individuals in each case). Around 5.4% of men and 1.7% of women aged 19–64 years, and 5.1% of men and 5.9% of women aged ≥65 years had impaired fasting glucose (glucose concentrations 6.1–6.9 mmol/L). Over 20% of men aged ≥65 years had fasting glucose concentrations above the clinical cut-off for diabetes (≥7 mmol/L) compared to 2.1% of women of similar age (p=0.007). Similarly, 16.4% of men had HbA1c concentrations ≥6.5%, compared to 1.5% of women (p=0.003). Children and teenagers had fasting glucose and HbA1c values largely within the normal range. To conclude, this is the first study to provide data on the distribution of HbA1c and glucose concentrations in a nationally representative sample of the British population. The high prevalence of men aged ≥65 years with HbA1c and glucose concentrations above the clinical cut-off of diabetes warrants further attention.

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