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The aim of this work is to explore the feasibility and comparative advantages of the use of regression methods (net-benefit approach) versus standard aggregate measures (incremental cost effectiveness ratio) for presenting and interpreting results of effectiveness and cost-effectiveness of maternal health strategies. Methods: Databases were existing datasets from a Demographic Surveillance Site and a prospective survey on costs borne by women and households for institutional delivery (to evaluate the community based health insurance scheme in Nouna, Burkina Faso), and from a real life evaluation (to asses the Skilled Care Initiative in Ouargaye, Burkina Faso). Results: Regression frameworks are feasible and more practical than traditional aggregate measures of maternal mortality ratio and incremental cost effectiveness ratio.  The approach has shown promise by overcoming the shortcomings of the use of aggregate measures by identifying differentials in outcomes by subgroups of populations and by providing useful information on the marginal cost-effectiveness of important covariates. Whilst regression frameworks provide straightforward interpretation and better clues for course of action, the application of the net-benefit approach also provides opportunities for enhancing data collection at Demographic Surveillance Site and national surveys.  Indeed, the application of this framework to maternal and child health requires a transformation of current surveys to allow for patient-level data on cost and on effectiveness measures and the use of various stated preference methods for eliciting the maximum contribution communities are willing to pay for extra gain of health outcome or for preventing an extra adverse outcome.

A two stage survey was carried out in order, a) to investigate trends and differentials in infant mortality in Abu Dhabi Emirate from 1980 to 1996 and b) to investigate the influence of risk factors on the problem of mortality under five years. The first stage reviewed infant mortality by sex, ethnicity, locality and cause of death. Data about the births and deaths of children were obtained from the Departments of Preventive Medicine in the three Health Regions of Abu Dhabi, Al Ain and the Western Region; 4523 infant deaths were coded according to the 9<SUP>th</SUP> revision of the International Classification of Diseases. The underlying causes of death were grouped into six main categories, namely: infections; congenital anomalies; conditions originating in the perinatal period; ill-defined conditions; accidents and miscellaneous. The rates for infant, perinatal, neonatal and postneonatal mortalities decreased substantially during the study period. The values for these mortality rates (per 1000 live births or total births in the case of the perinatal mortality rate) or 21.55, 20.43, 13.42 and 8.13 respectively in 1980 contrasted with their values of 9.15, 12.12, 5.51 and 3.64 in 1996. By contrast, the stillbirth rate showed the least change, declining from 8.4 in 1980 to a minimum of 7.79 per 1000 total births in 1996. The ratio of postneonatal to neonatal mortality rates remained broadly constant during the study period. In 1996, the under-5 mortality per 1000 live births was 13.1 in Abu Dhabi Emirate. Accidents formed the leading cause of death in the 1-5 year old children in the whole population from 1980 to 1996. A multiple regression technique was used to evaluate the independent effect of the variables (sex, nationality and region) upon the infant mortality rate. The rate of decline of the infant mortality rate appeared to be changing during the study period, which made the models containing the square of the year more fitting to the data points.

Many empiric and computer-based risk/probability estimation models have been developed, particularly after the discovery of BRCA1/2 genes, for estimating counselee’s probability of being carrier or to predict her risk of developing breast cancer. In this study, the performances of 6 such models have been compared. These are the Claus and Ford programs from Cyrillic3, BOADICEA, Manchester Scoring System, Tyrer-Cuzick, and COS which is a new model and being validated for the first time in this study. Model pedigrees and 172 Grampian families have been used to ascertain models’ performance. In this study the Claus and Ford models have the highest sensitivity but their extremely low specificities make them useless for any clinical or epidemiological use. In contrast COS and MSS have the second highest sensitivity (94% and 90% respectively) at reasonable specificities (53% and 41% respectively) and PPVs (56% and 49% respectively) showing that they are the most useful models for reducing the likelihood of mutations in BRCA1/2 (where the result is negative) and having the lowest false negative rate. From the ROC plots, COS and MSS also have the highest accuracy (within a range of all possible cut-off points) indicating their ability to discriminate between carriers and non-carriers. BOADICEA and T-C generated the most accurate overall predicted prevalence of mutations for all types of family histories and also increased the likelihood of carrying a mutation. BOADICEA and T-C have a sensitivity of 67%, specificity of 76% and 74% respectively and PPV of 64% and 62% respectively. COS and especially MSS can discriminate between BRCA1- and BRCA2-mutation carriers better than other models. These models identified a larger proportion of BRCA1- and BRCA2-mutation carriers correctly. COS and MSS have the higher sensitivity (73% and 64% respectively) at reasonable specificities (76% and 67% respectively) for the families with 3 or fewer cases of breast cancers in comparison with other models, while BOADICEA and COS have the most reasonable combination of sensitivity (80% and 100% respectively) and specificity (56% and 44% respectively) for the families with 6 or more cases of breast and/or ovarian cancer. Interestingly this study has shown that combined use of COS and MSS would significantly increase the specificity to 66% at the expense of few present loss of sensitivity. The single most effective model for clinical use is COS. However mutation prediction could be further improved if different models for different clinical circumstances (e.g. different family histories) were used. However it is practically cumbersome to have all models available in a busy clinic.

<i>Objective</i> - To assess a computer assisted nurse centred model for the measurement and modification of cardiovascular risk factors in general practice. <i>Design</i> - An open prospective study analysed using descriptive and comparative statistics. <i>Subjects</i> - 80504 patients who attended 18 health centres throughout the UK for opportunistic cardiovascular risk factor intervention. <i>Results</i> - The screened population comprised 36751 males (mean age 41.6 years) and 43753 females (mean age 40.7 years). The mean cholestrol level was 5.7 mM in both males and females. 25% of men and 24% of women had cholesterol levels ≥6.5 mM. The mean systolic/diastolic blood pressures were 130/81 mm Hg for men and 124/77 mm Hg for women. The mean body mass index for males was 25.3 kg/m^2 and for females 24.7 kg/m^2. 9% of men and 12% of women were classified as obese (<i>grades II or III</i>). 36% of males smoked compared to 33% of females. 80% of men were current drinkers as were 59% of women. 20% of men were classified as heavy drinkers compared to 4% of women. A composite risk score was used to assess all of the relevant risk factors at screening. 22% of males and 24% of females gave a positive family history in a first degree relative under 55 years of age. 6% of all patients were taking antihypertensive medication compared to 0.1% on lipid lowering drugs. Patterns of recruitment were examined and primary care staff accounted for 56% of referrals, friends and relatives encouraged 23% to attend, and self referrals amounted to 14%. <i>Conclusions</i> - The study succeeded in identifying the prevalence and nature of cardiovascular risk factors in a general practice population. Evidence of worthwhile reductions in risk factors was obtained. Patterns of recruitment and default were elucidated. The model constitutes a useful application of computers in primary care beyond the boundary of the individual practice. Further information from randomised controlled trials of cardiovascular risk factor intervention is awaited.

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The present research aims to study the postnatal care services in Saudi Arabia. It is designed to determine the factors that influence the pattern of immunisation uptake in childhood at immunisation clinics in Primary Health Care Centres (PHCCs) in the Madinah Area. The study covers the Madinah Area (Western Region), which showed, according to published MOH reports, the lowest immunisation coverage by all vaccines (Farag et al., 1995). A survey study of 503 children (1006 Parents), representing 6% of the total study population, was conducted in 24 PHC Centres, which represent 30% of the total number of PHCCs in the study area. These Centres were chosen from all eight regions of the Madinah Area. The sampling method used in this study was Multistage Cluster Sampling, with probability proportional to size technique (PPS). The face-to-face interview survey, using a structured questionnaire, was chosen as the preferred mode of data collection. The survey showed that 67.6% of the total children surveyed were fully immunised, Out of this figure, 46.1% were immunised on time, while 21.5% were fully immunised, but not on time. 25.4% were partially immunised and 7.0% were not immunised. In addition, a variety of factors were shown to have a significant influence on the child's immunisation status. More specifically, place of residence, distance to the PHC Centre, availability of the vaccination card, accommodation type, waiting time at the immunisation clinic and evaluation of the facilities in the clinic are the six major factors that explain why immunisation does not occur. The results also indicated several other demographic, socio-economic, parent-related and clinic-related variables that have a significant influence on the child's immunisation status.

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