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Biomedical subjects

R Reading

Publications and source records attributed to R Reading.

17 recordsLinked to original sources
PubMed2000

Cluster randomised trials in maternal and child health: implications for power and sample size.

BACKGROUND: Interventions based in the community can be evaluated by randomising clusters, such as general practices, rather than individuals, as in conventional randomised trials. This increases the sample size needed because of intracluster correlation. AIMS: To estimate sample size requirements for cluster randomised trials of interventions based in general practice directed at common health problems affecting mothers and infants. METHODS: Data were collected from a pilot trial of the effect of Citizen's Advice Bureau services involving six general practices. Outcome measures included the Edinburgh postnatal depression score, the Warwick child health and morbidity profile, number of visits to the general practitioner, and two questionnaires delivered at the beginning and end of the study. Intracluster correlation coefficients and inflation factors (the ratio of the sample size required for a cluster randomised trial to that required for an individually randomised trial) were calculated. RESULTS: Intracluster correlation coefficients ranged from 0 (sleeping problems, accidental injury, hospitalisation) to 0.09 (maternal smoking), with most being < 0.04 (for example, maternal depression, breast feeding, general health, minor illness, behavioural problems, and visits to the general practitioner). Assuming 50 cases/practice, cluster randomised trials require sample sizes up to 3 times greater than individually randomised trials for most health outcomes measured. CONCLUSIONS: These data enable sample sizes to be estimated for cluster randomised trials into a range of maternal and child health outcomes. Using such a design, approximately 40 practices would be sufficient to evaluate the effect of an intervention on maternal depression, sleeping, and behavioural problems, and non-routine visits to the general practitioner.

Analysis of Variance↗
PubMed1999

Accidents to preschool children: comparing family and neighbourhood risk factors.

Accidental injury in young children is more common among poorer families and in deprived areas but little is known about how these factors interact. This paper describes a study to measure the contribution of individual family factors and area characteristics in determining risk of accidental injury among preschool children. We conducted a population based study of preschool accident and emergency attendances over two years in and around the city of Norwich, UK. Information on individual families was extracted from the district child health information system while "social areas" were constructed from adjacent census enumeration districts with homogeneous social and demographic characteristics. Statistical analysis was by multilevel modelling. Accidental injury rates were much higher in deprived urban neighbourhoods than in affluent areas but the multilevel analysis showed that, for all accidents, much of the variation in rates was accounted for by factors at the individual level i.e. male sex, young maternal age, number of elder siblings and distance from hospital, with a smaller, but independent, influence of living in a deprived neighbourhood. The model for more severe injuries was similar except single parenthood was now significant at the level of individuals and the effect of area deprivation was stronger. We conclude that preschool accidental injuries are influenced by factors operating at both the level of individual families and between areas. This evidence suggests that both social policy changes to improve child care among unsupported young families and targeting accident prevention measures at a local level towards deprived neighbourhoods would reduce accidents.

Accidents↗
PubMed1997

The impact of social inequalities in child health on health visitors' work.

BACKGROUND: Preventive and health promotion work by health visitors ought to reduce social inequalities in child health. However, the increased health and developmental problems among disadvantaged children may constrain health visitors' ability to carry out effective preventive work. This paper measures the impact of socioeconomic inequalities in children's health on the work of health visitors and the amount of preventive work they can provide, with emphasis on 'parenting' programmes. METHODS: Data collected for health visitors' profiles were analysed in an ecological cross-sectional study. Individual caseloads were classified according to the proportions of families in social class IV or V and families headed by an unemployed person. A range of measures of young children's health and development indicated the demands on health visitors' time. Preventive work was divided into post-natal support, parenting programmes, special clinics and other preventive work. RESULTS: All the outcome measures were poorer in the most disadvantaged caseloads. Odds ratios between the most and least disadvantaged 20 per cent of caseloads were 0.6 for breast feeding at birth, and at seven months, 1.9 for post-natal depression, 3.2 for mothers under 18, 10 for lone parent families, 2.6 for families needing high intervention, 4.5 for families with a smoker, 11 for domestic violence, 4.4 for parents with a chronic health problem, 2.7 for children on the child protection register and 2.8 for children with developmental problems. There was 30 per cent greater health visitor time provided in the most disadvantaged caseloads than in the most advantaged. There was no consistent difference in the amount of preventive work carried out; in particular, parenting programmes were delivered at a similar rate in all caseloads. CONCLUSIONS: Large differences in demands on health visitors' time exist between affluent and disadvantaged caseloads which are barely reflected in the provision of extra time to poorer caseloads. There is no consistent pattern to the delivery of preventive programmes designed to ameliorate the effects of disadvantage on children's health and development.

Child↗
PubMed1994

Equity in the NHS. Monitoring and promoting equity in primary and secondary care.

Although need is often assumed to be the most important factor in determining the use of health services, there are many inequities in the provision and use of NHS services in both primary and secondary care. For example, existing data from district child health information services have been combined with census data for small areas to show wide variations in immunisation rates between affluent and deprived areas. Purchasers of health care are already responsible for assessing health needs and evaluating services, and the process of monitoring equity is a logical extension of these activities. Routine data sources used to collect activity data in both primary and secondary care can be used to assess needs for care and monitor how well these needs are met. Purchasers and providers should collaborate to improve the usefulness of these routine data and to develop a framework for monitoring and promoting equity more systematically.

Age Factors↗
PubMed1994

Do interventions that improve immunisation uptake also reduce social inequalities in uptake?

OBJECTIVE: To investigate whether an intervention designed to improve overall immunisation uptake affected social inequalities in uptake. DESIGN: Cross-sectional small area analyses measuring immunisation uptake in cohorts of children before and after intervention. Small areas classified into five groups, from most deprived to most affluent, with Townsend deprivation score of census enumeration districts. SETTING: County of Northumberland. SUBJECTS: All children born in country in four birth cohorts (1981-2, 1985-6, 1987-8, and 1990-1) and still resident at time of analysis. MAIN OUTCOME MEASURES: Overall uptake in each cohort of pertussis, diphtheria, and measles immunisation, difference in uptake between most deprived and most affluent areas, and odds ratio of uptake between deprived and affluent areas. RESULTS: Coverage for pertussis immunisation rose from 53.4% in first cohort to 91.1% in final cohort. Coverage in the most deprived areas was lower than in the most affluent areas by 4.7%, 8.7%, 10.2%, and 7.0% respectively in successive cohorts, corresponding to an increase in odds ratio of uptake between deprived and affluent areas from 1.2 to 1.6 to 1.9 to 2.3. Coverage for diphtheria immunisation rose from 70.0% to 93.8%; differences between deprived and affluent areas changed from 8.6% to 8.3% to 9.0% to 5.5%, corresponding to odds ratios of 1.5, 2.0, 2.5, and 2.6. Coverage for measles immunisation rose from 52.5% to 91.4%; differences between deprived and affluent areas changed from 9.1% to 5.7% to 8.2% to 3.6%, corresponding to odds ratios of 1.4, 1.4, 1.7, and 1.5. CONCLUSION: Despite substantial increase in immunisation uptake, inequalities between deprived and affluent areas persisted or became wider. Any reduction in inequality occurred only after uptake in affluent areas approached 95%. Interventions that improve overall uptake of preventive measures are unlikely to reduce social inequalities in uptake.

Cohort Studies↗
PubMed1994

Are multidimensional social classifications of areas useful in UK health service research?

OBJECTIVES: To show the advantages and disadvantages of a multi-dimensional small area classification in the analysis of child health data in order to measure social inequalities in health and to identify the types of area that have greater health needs. DESIGN: Health data on children from the district child health information system and a survey of primary school children's height were classified by the census enumeration district of residence using the Super profiles neighbourhood classification. SETTING: County of Northumberland, United Kingdom. SUBJECTS: One cohort comprised 21,702 preschool children age 0-5 years resident in Northumberland, and another cohort 9930 school children aged 5-8.5 years. MAIN OUTCOME MEASURES: Variations between types of area in the proportions of babies with birthweight less than 2.8 kg; births to mothers aged less than 20 years; pertussis immunisation uptake; child health screening uptake; and mean height of school children. RESULTS: Areas with the poorest child health measures were those which were most socially disadvantaged. The most affluent areas tended to have the best measures of health, although rural areas also had good measures. Problems in analysis included examples of the "ecological fallacy", misleading area descriptions, and the identification of the specific factors associated with poor health measures. Advantages included a wider view of social circumstances than simply "deprivation" and the ability to identify characteristic types of areas with increased child health needs. CONCLUSIONS: There is a limited place for multidimensional small area classifications in the analysis of health data for both research and health needs assessment provided the inherent drawbacks of these data are understood in interpreting the results.

Child↗
PubMed1993

Deprivation, low birth weight, and children's height: a comparison between rural and urban areas.

OBJECTIVE: To compare proportions of low birthweight babies and mean heights of schoolchildren between rural and urban areas at different levels of social deprivation. DESIGN: Cross sectional population based study classifying cases by Townsend material deprivation index of enumeration district of residence and by rural areas, small towns, and large towns. SETTING: Northumberland Health District. SUBJECTS: 18,930 singleton infants delivered alive during January 1985 to September 1990 and resident in Northumberland in October 1990; 9055 children aged 5 to 8 1/2 years attending Northumberland schools in the winter of 1989-90. MAIN OUTCOME MEASURES: Odds ratios for birth weight less than 2800 g; difference in mean height measured by standard deviation (SD) score. RESULTS: Between the most deprived and most affluent 20% of enumeration districts the odds ratio for low birth weight adjusted for rural or urban setting was 1.71 (95% confidence interval 1.51 to 1.93) and the difference in mean height -0.232 SD score (-0.290 to -0.174). Between large towns and rural areas the odds ratio for low birth weight adjusted for deprivation was 1.37 (1.23 to 1.53) and the difference in mean height -0.162 SD score (-0.214 to -0.110). Results for small towns were intermediate between large towns and rural areas. CONCLUSIONS: Inequalities in birth weight and height exist in all rural and urban settings between deprived and affluent areas. In addition, there is substantial disadvantage to living in urban areas compared with rural areas which results from social or environmental factors unrelated to current levels of deprivation.

Body Height↗
PubMed1993

Measurement of social inequalities in health and use of health services among children in Northumberland.

Social inequalities in a variety of indicators of child health were measured using a 'small area' geographical method of social classification. Cross sectional analyses of routine child health information and of a population survey of the height of primary school children were used. Social classification was by census enumeration district of residence using the Townsend deprivation score. Over 21,000 children resident in Northumberland born between January 1985 and September 1990, and 9930 children aged 5-8.6 years in Northumberland schools were studied. The following differences between the most deprived 10% of areas and the most affluent 10% of areas were used as outcome measures: the proportion of birth weights less than 2800 g; the proportion of births to teenage mothers; the proportion of 15 month old children not immunised against pertussis; the proportion of infants not screened at 6 weeks of age; the proportion of children not screened at 18 months of age; and the mean height of children in SD scores. Between the most deprived and most affluent areas birth weights less than 2800 g varied from 18 to 11%, the percentage of teenage mothers from 18 to 3%, non-immunised children from 30 to 19%, children not screened at 18 months from 21 to 14%, and mean height from -0.2 SD scores to +0.1 SD scores. The area variation in screening at 6 weeks of age was less, but still poorer in deprived areas. It is concluded that small area methods are effective in showing inequalities in child health, even in a rural area where such methods might be expected to perform less well. Social inequalities in all the aspects of child health measured remain evident.

Adolescent↗
PubMed1993

Do inaccuracies in small area deprivation analyses matter?

OBJECTIVE: To assess the accuracy of computerised matching of postcode to enumeration district (ED) and to determine whether any mismatching reduces the validity of methods to distinguish socioeconomic differences in "small area" deprivation studies. DESIGN: Computerised and manual matching of postcodes to EDs were compared and the census based Townsend deprivation score was compared with socioeconomic data on individual families. SETTING: County of Northumberland, England, 1989. SUBJECTS: Random sample of 301 families with a child aged less than 15 months. MAIN RESULTS: With computerised matching only 47% of postcodes were matched to the correct ED. Eighty per cent of the deprivation scores of the computer matched EDs, however, approximated (+/- 2) to the deprivation score of the actual ED. When EDs were divided into quintiles according to the deprivation score, accurate manual matching showed that 75% of families in the most deprived EDs were classed as deprived compared with 4% in the most affluent EDs. With the inaccuracies introduced by computer matching of postcodes, the corresponding figures were 56% and 12% respectively. CONCLUSIONS: Computerised matching of postcodes to EDs is highly inaccurate, but this has little effect on the allocation of deprivation scores. The socioeconomic inequalities shown by the deprivation score are blunted, but not eradicated, by this mismatching.

Computers↗
PubMed1992

A rural advantage? Urban-rural health differences in northern England.

Rural health inequalities have been relatively neglected in recent years. The data assembled for a large study of health and deprivation in the Northern Region of England have been reanalysed to examine three questions. How wide are rural health inequalities compared with those in urban areas? Is health intrinsically better in rural areas, given comparable deprivation or affluence? Is the association between health and wealth weaker in rural than in urban areas? It is shown that, although health inequalities are wider in urban areas, this corresponds to wider socio-economic divisions: at equivalent levels of wealth, health measures are similar. This relationship breaks down, however, when the most remote rural areas are compared with matching localities in conurbations, for in this case rural areas have a clear advantage. We go on to show that the apparent weakness of the association between health and wealth in rural areas is largely an artefact; the association becomes stronger when the units of population (electoral wards) are enlarged to resemble more closely those in urban contexts. The comparability of rural and urban forms of deprivation is discussed in the light of these results.

Catchment Area, Health↗
PubMed1987

Pulmonary haemosiderosis and gluten.

A child with idiopathic pulmonary haemosiderosis for three years required three monthly transfusions. Circulating avian, gliadin, and reticulin antibodies suggested the diagnosis of gluten enteropathy, and jejunal biopsy showed subtotal villous atrophy. During 15 months on a gluten free diet his growth and behaviour improved and he required no transfusions.

Celiac Disease↗
PubMed1976

Laser meridional refractometry.

Laser meridonal refractions were undertaken on 30 subjects. The results were compared to classical subjective techniques utilizing both correlative statistics and clinical criteria. The laser meridional techniques were highly correlated with the subjective procedures and were accurate when judged by clinical criteria.

Adolescent↗