Seasonality is a common feature of communicable diseases. Less well understood is whether seasonal patterns occur for non-communicable diseases. The overall effect of seasonal fluctuations on hospital admissions has not been systematically evaluated.This study employed time series methods on a population based retrospective cohort of for the fifty two most common causes of hospital admissions in the province of Ontario from 1988–2001. Seasonal patterns were assessed by spectral analysis and autoregressive methods. Predictive models were fit with regression techniques.The results show that 33 of the 52 most common admission diagnoses are moderately or strongly seasonal in occurrence; 96.5% of the predicted values were within the 95% confidence interval, with 37 series having all values within the 95% confidence interval.The study shows that hospital admissions have systematic patterns that can be understood and predicted with reasonable accuracy. These findings have implications for understanding disease etiology and health care policy and planning. Health care is a complex human endeavor constituted by the interaction of multiple professions, organizations, industries, technologies and the public. Health itself is also a complex concept, with multiple determinants including genetic, socio-cultural, economic and environmental influences . At the Do hospital admissions have consistent patterns? While individual diseases are extensively studied, there is a paucity of systematic approaches to the study of health care events. Epidemiology is not regarded as a science with the predictive accuracy and explanatory power of the physical sciences . Health Using time series analysis, our research program investigates seasonality in the occurrence of health care events. Seasonality is an important aspect of disease manifestation as well as a clue to the etiology of disease. Our initial studies explored seasonality in hospital admissions in discrete disease categories including asthma , falls  and aortConsistent seasonal behavior suggests the possibility of predictable behavior. To the best of our knowledge, there are no studies systematically evaluating the seasonality and predictability of multiple hospital admissions using health services data. We therefore assessed the seasonality and predictability of the most common causes of hospital admission in the province of Ontario, Canada.We conducted a retrospective, population-based study to assess temporal patterns in hospitalisations for the 52 most common admission discharge diagnoses from April 1, 1988 to December 2001. Approximately 14 million residents of Ontario eligible for universal healthcare coverage during this time were included for analysis. The Canadian Institute for Health Information Discharge Abstract Database was used to obtain information on the most responsible diagnosis. This database records discharges from all Ontario acute care hospitals, documenting a scrambled patient identifier, date of admission and discharge, up to 16 diagnoses as coded by the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), and up to 10 procedures.Researchers using these databases have found that diagnoses and surgical procedures are coded with a high degree of accuracy. There is very little missing information in the Ontario databases; other studies have similarly found that less than 1 percent of the basic information on patients is missing in various provincial databases -10.The 52 most common discharges diagnoses over the 10 years were identified by summing all admissions and calculating in rank order the frequencies of admission. Owing to the influence of obstetric related admissions, we limited obstetric codes to the consideration of singleton births. Categories of closely related health conditions  were combined.Numerator data consisted of the total number of discharges for each month for each of the most responsible diagnoses. Denominator data was derived from annual census data for each age group for residents of Ontario provided by Statistics Canada. Monthly population estimates were derived through linear interpolation. All transfers from within one acute care hospital to another within this study group were excluded from the analysis. To take into account the population changes over time we analyzed monthly admission rates per 100,000.This study employed time series methods to assess the presence of statistically significant seasonality, the strength of the seasonal effect and the predictability of the time series. A time series can be decomposed as the sum or product of trend, seasonality, and random components. Trend is the long term movement of the series which is a systematic component that changes over time and generally does not repeat itself within the time range of the available data. If we eliminate the trend then the time series will consist of seasonal and random components.2Autoreg) were calculated. Autoregression uses the coefficient of determination of the autoregressive regression model fitted to the data, and can be used for quantifying the strength of the seasonality within a set of serially correlated observations as occurs with time series data [2Autoreg is interpreted the same way as the coefficient of determination in classic regression: values from 0 to less than 0.4 represent non-existent to weak seasonality, 0.4 to less than 0.7 moderate to strong seasonality, and 0.7 to 1 strong to perfect seasonality. The magnitude of the R2Autoreg shows how well the next value can be predicted when the seasonal component is the only predictor. In other words it shows the contribution of seasonality in the total variation of the data. Thus 1-R2Autoreg would be the variance that remains unexplained [2Autoreg may be underestimated when the seasonal variation is non-stable. To account for this, data transformations were conducted where appropriate, to stabilize the seasonal variations [Analysis of the data involved the use of the following statistical techniques in identical fashion to each series in order to assess statistical significance of seasonal patterns and the consistency and magnitude of seasonal effect. Spectral analyses were conducted to detect statistically significant seasonality. Spectral analysis detects periodicity in time series, by plotting the periodogram or spectral density of the series against the period or frequency . The daties data . The R2Axplained . When thriations . All staOf the 160 monthly observations for each series, the first 148 (April 1988 to December 2000) were used for fitting the model and estimating the parameters. We set aside the last 12 observations (January to December 2001) for assessing the performance of the suggested model and used the rest for fitting the model and estimating the parameters. We applied the first order differencing to eliminate the trend [n monthly observations x1, x2, ..., xn are available and we are interested in predicting the next k unobserved data points xx+1, xx+2,..., xx+k using the n observed data points. Here we will assume that the time series is an additive composition of trend, seasonality, and random components. The multiplicative case can be converted to additive by simply taking the log transformation. The time plot of the series did not indicate large changes in the variations of the amplitude of either seasonal or irregular components of the series whereas the level of the trend increased or decreased. Thus an additive model is appropriate. The first component we should deal with is trend. Visual inspection of the time plots of the 52 series indicate different trend patterns ranging from simple linear to more complex nonlinear patterns. We did not attempt to model the trend component parametrically as estimating the pattern of the trend components globally by a closed mathematical function of time may severely misestimate the true trend beyond the range of fitting period. Instead we decided to use the first order differencing to eliminate the trend component. The first order differencing of a time series xt, t = 1,2, ..., n is the series wt, t = 2,3, ..., n where wt = xt - xt-1 [Suppose t - xt-1 . Visual  for seasonal factors of period 12 and 6. Thus the regression model takes the following formIn the regression model we included βi's can be estimated through linear regression framework. Having fitted the model, one can substitute t = n + 1, n + 2, ..., n + k to estimate the next k differenced observations with their corresponding confidence intervals. The predicted differenced data points can be converted to raw data points by applying the following simple transformation:where xn+j = wn+j + xn+j-1, j = 1,2, ..., kj > 1we can substitute the predicted values for xn+j-1.Confidence intervals can be transferred in a similar manner. For A total of 6,560,210 million admissions were included in the analysis. Figures 2Autoreg test statistics for each diagnosis, rank ordered by R2Autoreg, and the number of predictions that fall outside the 95 percent confidence interval. The R2Autoreg values range from a high of 0.95 (bronchiolitis) to a low of 0.11 (infantile cataract). Fourteen series showed evidence of strong seasonality (R2Autoreg greater than 0.7), nineteen series showed evidence of moderate seasonality (R2Autoreg between 0.4 and 0.69) and eleven showed evidence of weak seasonality (R2Autoreg less than 0.4). Time series with strong seasonal effects by R2Autoreg also showed consistent statistical evidence of seasonality by BKS and Fisher Kappa tests. Those with moderate and weak evidence of seasonality by R2Autoreg showed inconsistent statistical evidence of seasonality by BKS and Fisher Kappa tests.Table In total, 96.5 percent of the predictions fell within the 95 percent confidence interval (602/624). In terms of complete series, the performance of the proposed predictive model is very good. Overall 37 (37/52 = 73 percent) had all 12 observed values falling within 95 percent prediction intervals, 10 series had only 1 observed value outside prediction limits and 4 series had 2 observed values outside 95 percent prediction intervals. For the worst case, only 1 series had 4 out of 12 observed values falling outside the 95% prediction intervals. The standard deviations for the confidence intervals of the predicted values are within 2 admissions per 100,000 for 48 of the 52 series (data not shown).Hospital admissions in the province of Ontario show remarkable consistency and predictability of occurrence. A heterogeneous group of health conditions are represented in the sample including surgical and medical conditions, acute and chronic diseases, communicable and non-communicable diseases. The performance of the proposed model for predicting the one-year ahead number of hospital admissions in the province of Ontario is excellent for the 52 most frequent hospital admissions series considered in this study.Are these results of significance? We believe so. Most health care planning is based on what could be termed the 'invariance principle' that holds that all events are equally likely to happen and therefore hospitals should be staffed and managed accordingly . Our stuOur study is limited to the context of Ontario, and is applicable at a population level. Focusing on the most responsible diagnosis may bias the account of seasonal occurrence, although this bias is likely to be non-differential. In this study we focused on total counts for each most responsible diagnosis, which may obscure significant variation in rates between age and gender.The proposed methods enjoy simplicity and stability. The prediction approach does not require model selection or any other sophisticated statistical methods. Selecting an appropriate seasonal model can be a challenging task in time series analysis. For example, the Box Jenkins approach is popular for selecting linear time series models. In this approach sometimes the analyst has to select a model subjectively from among several potentially appropriate models. Our proposed regression model does not require model selection.The first order differencing eliminates trend; sin and cosine terms estimate the seasonal factors. The simple regression model works well for highly seasonal to non-seasonal data. Although the seasonal factors of some of the series are changing over time, the simple first order differencing in conjunction with the regression model forecast the future observations within the 95 percent confidence bounds. The confidence intervals around the predicted values are tight, reflecting the accuracy of the projections. This attenuates concerns expressed about the robustness of predictive models in epidemiology .The results of this study demonstrate a simplicity underlying the complexity of hospital admissions. We believe these results are promising and can lead to more rational planning of hospital resources and open up areas of exploration for understanding the determinants of disease causation, specifically in those conditions with moderate to strong seasonality. Further research is necessary to look at whether more complex models have greater predictive power, and whether the analytic approach is robust at different time and space aggregations.The author(s) declare that they have no competing interests.RU conceived the study and wrote the first draft. RM contributed the statistical analysis. MM, LK and EC made substantial contributions to the design and interpretation of the data. All authors contributed to subsequent drafts, have read and approve of the content of the final submitted manuscript.All authors have access to all data in the study and they hold final responsibility for the decision to submit for publication.The pre-publication history for this paper can be accessed here:


R) constitute 5–10% of peripheral CD4+ T cells in naive mice and humans, and play an important role in controlling immune responses. Accumulating evidences show that TR cells are involved in some physiological processes and pathologic conditions such as autoimmune diseases, transplantation tolerance and cancer, and might be a promising therapeutic target for these diseases.CD4+CD25+ regulatory T lymphocytes (TR cells in mouse tumor models, CD4+CD25+ subset in peripheral blood and spleen lymphocytes from normal or C26 colon-carcinoma-bearing BABL/c mice were analyzed by flow cytometry using double staining with CD4 and CD25 antibodies.To evaluate the change of CD4+CD25+ TR in tumor mouse models, and our results provide some information on strategies of antitumor immunotherapy targeting CD4+CD25+ regulatory T lymphocytes.The proportion of CD4+CD25+/CD4+ in spleen lymphocytes was found to be higher than that in peripheral blood lymphocytes in normal mice. No difference was observed in the proportion in peripheral blood lymphocytes between tumor bearing mice and normal mice, while there was a significant increase in the proportion in spleen lymphocytes in tumor bearing mice as compared with normal mice. Moreover, the proportion increased in accordance with the increase in the tumor sizes. The increase in the proportion was due to the decrease in CD4+ in lymphocytes, which is resulted from decreased CD4+CD25- subset in lymphocytes. Our observation suggests the CD4+CD25+/CD4+ proportion in spleen lymphocytes might be a sensitive index to evaluate the T R). TR represents a minor (5–10%) component of peripheral CD4+ T cells but plays an important role in controlling immune responses [R cells possess potent suppressive activity both in vivo and in vitro and are involved in autoimmune diseases, transplantation tolerance and tumor immunity [R cells in total CD4+ T cells was found in peripheral blood of cancer patients [R cells in controlling immune response. The mechanism of how the TR cells control immune response is still unclear. Previous studies show that activated TR cells strongly inhibit proliferative responses of CD4+ or CD8+ T cells in vitro [R cells in immunoregulation makes it be recognized as an attractive therapeutic target for immune-related diseases.Early in 1970s, the concept of suppressor T cells was developed and it was envisioned that this subset of lymphocytes was responsible for the active control, and ultimately the termination, of immune responses . Soon thesponses . Accumulimmunity -5. The timmunity . Similarimmunity , impaireimmunity  and othe minor 5–% componepatients -14 and dpatients ,16. All in vitro ,18, morein vitro , and supin vitro . The impR cells, to our surprise, we did not find an increase of CD4+CD25+/CD4+ in peripheral blood of tumor bearing BALB/c or C57BL/6 mice, this is not in accordance with the increase of the proportion in cancer patients as reported by Wolf et al [R cells in tumor-bearing mice, we analyzed CD4+CD25+ subset in peripheral blood and spleen lymphocytes from normal or C26 colon-carcinoma-bearing mice by flow cytometry.In our animal experiments of antitumor immunotherapy that targeting CD4+CD25+ Tlf et al . In orde5 to 1 × 107 live tumor cells per mouse.6 to 8 weeks BALB/c mice were purchased from the Laboratory Animal Center of Sun Yet-sen University. Mouse C26 colon carcinoma cell line was a gift from Prof. Li-Jian Xian (Cancer Center, Sun Yet-sen University). The C26 Cells were cultured in RPMI 1640 medium (Gibco Invitorogen Corporation) supplemented with 10% fetal calf serum , 100 U/ml of penicillin G and 100 μg/ml of streptomycin, and the medium was renewed every 2 to 3 days. After growing to confluency, the cells were detached with trypsin-EDTA, resuspended in serum-free RPMI 1640 medium and inoculated subcutaneously at right axilla with 1 × 10PE-conjugated anti-mouse CD4, Cychrome-conjugated anti-mouse CD25 antibodies were purchased from eBioscience. Red blood cell lysis buffer is composed of 0.155 M ammonium chloride, 0.01 M potassium bicarbonate, and 0.1 mM EDTA. Fixation solution contains 1% paraformaldehyde in PBS.Mouse peripheral blood was collected from orbital plexus and anticoagulated with 20 U/ml sodium heparin. Single-cell suspensions of splenocytes were prepared by grinding the spleen with the plunger of a disposable syringe, passing the ground spleen through nylon mesh, and suspending the cells in PBS. Mouse peripheral blood or spleen single-cell suspensions were stained with PE-conjugated anti-mouse CD4 and Cychrome-conjugated anti-mouse CD25 antibodies at 4°C for 30 minutes. Then, erythrocytes were lysed by red blood cell lysis buffer. After wash with PBS, the samples were fixed with fixation solution and analyzed on a FACScalibur™ flow cytometer (BD Biosciences) with CELLQuest™ software.t test, statistical significance was accepted at the P < 0.05 level.The data are summarized as the mean ± standard error. Statistical analysis was performed using the Student R cells appear in spleen or peripheral blood in a relative stable percentage manner. The proportion of CD4+CD25+/CD4+ in peripheral blood was 6.19 ± 0.86%, which is in accordance with the results reported by others [P < 0.001). And, the higher level of the proportion in spleen is due to a lower level of the total CD4+ lymphocytes (CD4+CD25+ plus CD4+CD25-) in spleen than that in peripheral blood (37.06 ± 5.76 vs 56.80 ± 6.38, P < 0.001). The representable figures of peripheral blood and spleen lymphocytes double stained with CD4 and CD25 antibodies were shown in Figure To evaluate the normal proportion of CD4+CD25+/CD4+ in mice, 6 to 8 weeks normal BALB/c mice n = 10) were sacrificed to test the proportion in spleen and peripheral blood lymphocytes by flow cytometry using anti-mouse CD4 and CD25 antibodies. The total CD4+ lymphocytes, CD4+CD25+ subset, and CD4+CD25+/CD4+ in spleen or peripheral blood lymphocytes were shown in Table 0 were say others . Otherwi5 to 1 × 107 live C26 colon carcinoma cells were inoculated subcutaneously at right axilla of BALB/c mice respectively (n = 12). 20 days later, tumor nodules were formed at different sizes from 7 to 40 mm in diameters. The mice were sacrificed and peripheral blood and spleen lymphocytes were prepared for double staining with anti-mouse CD4 and CD25 antibodies. In peripheral blood, we did not find an increase in CD4+CD25+/CD4+ in tumor bearing mice, compared with that in normal mice. Otherwise, an increased proportion of CD4+CD25+/CD4+ in spleen lymphocytes was observed in tumor bearing mice, moreover, the proportion increased in accordance with the increase in tumor sizes, as shown in Figure To investigate the possible changes of the proportion in tumor bearing mice, 1 × 10The proportion of CD4+CD25+/CD4+ was determined by two factors: CD4+CD25+ in lymphocytes (numerator) and total CD4+ in lymphocytes (denominator). The increase of the proportion may be due to the increase of CD4+CD25+ subset or decrease of CD4+ subsets, or both. To investigate the possible reason that the proportion increased in spleen lymphocytes of tumor-bearing mice, we analyzed the CD4+CD25+ and total CD4+ cells in spleen lymphocytes. We found there was no obvious change in CD4+CD25+ in spleen lymphocytes from tumor bearing mice, otherwise, a decrease in total CD4+ lymphocytes was found with the increase of the tumor sizes, and the decrease was mainly due to the decrease of CD4+CD25- subset, as shown in Figure R cells provided a new way to study relationship between tumor development and immune suppression. A higher proportion of CD4+CD25+ TR cells was found in peripheral blood of cancer patients and to be related to poor prognosis of the diseases [R cells using anti-CD25 mAb could promote anti-tumor immunity [R cells maybe an attractive target to restore or improve immune function in cancer treatment.The identification of CD4+CD25+ as the phenotype of regulatory T lymphocytes is one of the highlights of recent immunological progress. These cells are proven to be involved in autoimmune diseases, transplantation tolerance and tumor immunity, etc . The reldiseases ,12. Deplimmunity ,16. All R cells, we analyzed the proportion in peripheral blood and spleen lymphocytes in normal or C26 colon-carcinoma-bearing mice by flow cytometry. In present study, the proportion of CD4+CD25+/CD4+ in peripheral blood of normal mice was about 6.19%, which was compatible with the results reported previously (5–10%). But in spleen lymphocytes from normal mice, we found a higher proportion of CD4+CD25+/CD4+ (around 10%), and the higher proportion is due to a lower level of total CD4+ lymphocytes in spleen, compared with that in peripheral blood, whereas the percentages of the CD4+CD25+ cells are similar.In our animal experiments of antitumor immunotherapy, we did not find an increase of CD4+CD25+/CD4+ in peripheral blood in tumor bearing BALB/c mice, this is not in accordance with the results in cancer patients reported previously . To findIn C26-colon-carcinoma bearing BALB/c mice, we found an increase of CD4+CD25+/CD4+ in spleen but not in peripheral blood, furthermore, the proportion in spleen lymphocytes increased with the increase of tumor sizes. The phenomenon that the increase of the proportion in spleen separates with that in peripheral blood may be due to: 1). Spleen is a professional immune organ, which maybe more sensitive to the changes of immune situation than peripheral blood; 2). In this study, what we used is artificial tumor model, not spontaneous tumor model, and the tumor grew so quickly to cause mice moribund or dead that the increase of the proportion did not appear in peripheral blood. To observe the increase of the proportion in peripheral blood of tumor bearing mice may need a longer observation duration, or had better use spontaneous tumor models. In our experiments, we found the increase of CD4+CD25+/CD4+ is due to the decrease of CD4+ in lymphocytes, which is the result of decreased CD4+CD25- subset in lymphocytes. Our results support the observations reported by Sasada , in whicR cells [The relationship between cancer and immune system has been debated for a long time. Our results provided direct evidence that the tumor might compromise the immune function, since our tumor model was established on BALB/c mice with normal immune function. It is known that tumor cells secrete immunosuppressive cytokines such as IL-10 and TGF-β -27, and R cells ,29. ThesR in tumor mouse models rather than that in peripheral blood lymphocytes, and our results provide some information on strategies of antitumor immunotherapy targeting CD4+CD25+ regulatory T lymphocytes.In normal BALB/c mice, CD4+CD25+/CD4+ proportion in spleen lymphocytes is higher than that in peripheral blood lymphocytes. In C26-colon-carcinoma bearing mice, no difference was found in the proportion in peripheral blood lymphocytes compared with normal mice; Otherwise, the proportion in spleen lymphocytes obviously increased, moreover, the proportion increased in accordance with the increase of tumor sizes. The increase of the proportion is due to the decrease of total CD4+ in lymphocytes, which is resulted from decreased CD4+CD25- subset in lymphocytes. Our observation suggest the CD4+CD25+/CD4+ proportion in spleen lymphocytes might be a sensitive index to evaluate the T


Head injury in England is common. Evidence suggests that socio-economic factors may cause variation in incidence, and this variation may affect planning for services to meet the needs of those who have sustained a head injury.Socio-economic data were obtained from the UK Office for National Statistics and merged with Hospital Episodes Statistics obtained from the Department of Health. All patients admitted for head injury with ICD-10 codes S00.0–S09.9 during 2001–2 and 2002–3 were included and collated at the level of the extant Health Authorities (HA) for 2002, and Primary Care Trust (PCT) for 2003. Incidence was determined, and cluster analysis and multiple regression analysis were used to look at patterns and associations.London, those of the Shire counties, and those of Other Urban authorities. Socio-economic factors were found to account for a high proportion of the variance in incidence for 2001–2. The same pattern emerged for 2002–3 at the PCT level. The use of public transport for travel to work is associated with a decreased incidence and lifestyle indicators, such as the numbers of young unemployed, increase the incidence.112,718 patients were admitted during 2001–2 giving a hospitalised incidence rate for England of 229 per 100,000. This rate varied across the English HA's ranging from 91–419 per 100,000. The rate remained unchanged for 2002–3 with a similar magnitude of variation across PCT's. Three clusters of HA's were identified from the 2001–2 data; those typical of Head injury incidence in England varies by a factor of 4.6 across HA's and PCT's. Planning head injury related services at the local level thus needs to be based on local incidence figures rather than regional or national estimates. Socio-economic factors are shown to be associated with admission, including travel to work patterns and lifestyle indicators, which suggests that incidence is amenable to policy initiatives at the macro level as well as preventive programmes targeted at key groups. It has been estimated that 6.6% of those attending A&E in any given year have a head injury  and overYet, within the UK, evidence upon which to base local service planning is scarce, as recognised in the recent report of the Health Committee of the UK House of Commons . ConsequHospital Episodes Statistics (HES) record all episodes of continuous in-patient care in hospitals in England and can be obtained from the UK Department of Health. For the year 2001–2, statistics are available for the 95 Health Authorities (HA) extant at the time, and for 2002–3 for Primary Care Trusts (PCT's). Concerned with incidence of new cases, data in the current study is based upon the postcode of residence of the patient. 'First episode' was chosen as a filter variable . A second filter identified the relevant primary cause ICD10 codes for head injury (S00.0 to S09.9). There is a long history of debate about the appropriate codes for inclusion in such studies, often surrounding the debate between 'head injury' and 'brain injury' . Much waThe 16–74 year old band was chosen explicitly to match the census key statistics which report on various indicators for the economically active population, deemed to be 16–74 years of age. Census Key Statistics are available from the UK Office of National Statistics and include a range of demographic, social and economic variables that can be presented as percentage indicators. Those chosen for inclusion in the current study are shown in Table In addition, the Townsend Deprivation Index is calculated using the percentage of households with no car, not owner occupied, overcrowded and those economically active who are unemployed . The latThe UK Census key statistics are currently made available at the Primary Care Trust (PCT) level, and thus it was necessary to aggregate these data up to the HA level to match the 2001–2 admission data which was provided at the Health Authority level. The majority of PCT's fit neatly into the 95 Health Authority areas extant in 2002. However, there are some slight variations such that aggregated populations of the HA derived from their respective PCT's match exactly the independent figures (provided separately from the ONS) of 2002 HA populations in 90% of cases, and differ by up to 5% for the rest. For example, a small number of Enumeration Districts (the lowest level census tract) belonging to the Preston PCT, which belongs in North West Lancashire HA, are allocated to East Lancashire. No attempt was made to adjust for these slight variations in boundaries. Key statistic indicators for 2001–2 were thus derived from the aggregated PCT data, based on their aggregated population which, for a few HA's, will differ slightly from the population used to estimate the admission rates for head injury. There was a one-to-one relationship between admission data and census data at the PCT level for the 2002–3 data.Patterns of head injury and socio-economic indicators are determined by Two-Step Cluster Analysis. The procedure is an exploratory tool designed to reveal natural groupings (or clusters) within a data set that would otherwise not be apparent. The association between the various socio-economic factors, and the overall rate for head injury is explored through a multiple regression model using the 2001–2 data at the HA level. This model is validated on the 2002–3 data at the PCT level.The project was funded by the UK Department of Health. The author is independent of the funding body. Ethical approval was not required.A total of 112,718 admissions were recorded for 2001–2. The gives an incidence rate for admission to hospital following a head injury in England in 2001–2, for all ages, of 229.4 per 100,000 Table . The incTaking the overall incidence rate for 2001–2, together with the key statistics in Table The second cluster can be described as the 'Shire' counties, typical of the more rural areas found within England, including Cambridgeshire and Worcestershire. They are characterised by a large proportion of people owning their own home, travelling to work in their own car, and with few of the population born outside of the UK. Although a quarter of the population are without qualifications, the deprivation Index is low at -2.7. The average incidence admission rate for this cluster is 206 per 100,000 all ages.The third cluster can be described as 'Other Urban', and typical of all the Midland and Northern cities of England. They are characterised by a higher proportion of people with limited long standing illness; those of working age who are permanently off sick; of those without qualifications and of those aged 16–24 who are unemployed. The deprivation Index is above average at 1.2, and the admission rate is high at 288 per 100,000 all ages.2 of 0.698, the model explains a large proportion of the variation in admission rates for a head injury . On this occasion the proportion of households without a car was added to the previous set of predictors. Once again, the proportion travelling to work by public transport was the most important variable.The model was then validated upon the 2002–3 data at the PCT level Table . A similHead injury is common; there were 112,718 recorded admissions for English residents during the year April 2001 to March 2002, giving a hospitalised incidence rate of 229.4 per 100,000 all ages. Remaining the same for 2002–3 this incidence is similar to that of stroke although the latter is experienced in a predominately older population . HoweverAdmission rates for England were found to vary by a factor of 4.6 between both health authorities and PCT's. The rates may slightly underestimate the true incidence as those residents of England treated elsewhere are not included. Also, under-reporting may depress incidence to an unknown extent  and, if Half of all health authorities in England, and slightly more PCT's (55%) had an incidence rate which fell below or above the England average by at least 20%. This has important implications for planning local services in response to head injury. Clearly using the overall England incidence rate is unlikely to be helpful. This variation also causes problems in extrapolating the results from research undertaken in a single locality. Estimates of the number of people disabled by head injury, presented as a rate (e.g. 150 per 100000), may have little relation to reality at the local level. The disability rate is conditional upon the local incidence where the study was undertaken. Consequently it is important that research findings should be presented as proportions of the local base incidence if they are to be of any use for planning elsewhere. The extrapolations given above on return to work are based on this approach. Nevertheless such extrapolation assumes equal case mix (e.g. similar mechanisms of injury) which is also unlikely. Case mix will, to a certain extent, be a reflection of local socio-economic factors, particularly associated with sub-populations displaying chronic conditions, including alcohol misuse, shown to have significant impact on outcome ,24,25.The extent of deprivation has also previously been associated with higher incidence of head injury as well as general workload for primary care ,27. The ceteris paribus, we might expect to see the London incidence fall as a consequence of congestion charging and associated increase in the use of public transport. Policies targeted at reducing unemployment amongst the 16–24 year old age group may also be expected to reduce incidence. Also, a continuing emphasis on prevention is clearly needed, both for the young and the old, to reduce their very high incidence rates.Where public transport is not used for journeys to work, incidence is much higher and combined with higher unemployment rates, and other significant indicators associated with 'lifestyle indicators', high incidence rates are observed in the cities and other urban communities in the Midlands and Northern England, including Teeside and Mersyside. As demographic, social and economic factors appear to account for half the variation observed in hospitalised admission rates, one implication is that incidence can be modified at the macro policy level. For example, Some technical limitations are worth mentioning. The likelihood distance measure used in the two-step cluster analysis assumes that variables in the cluster model are independent. Further, each continuous variable is assumed to have a normal (Gaussian) distribution, although in practice the technique is robust to violation of these assumptions. In fact, reassuringly, the results of the linear regression model do suggest independent main effects for several of the key variables and, importantly, the absence of interaction effects. Also it is unknown how, if at all, the slight variation in population denominators used to calculate incidence and the socio-economic indicators for the 2001–2 data could influence these results. However, replication upon the 2002–3 data at the PCT level suggests a robust model. Due to censoring of data of elderly admissions at the PCT level we were not able to confidently include the proportion of females admitted in our validation model, and thus we do not know if variation in male-female ratios at the local level was also a contributing factor to variance in incidence.It is also worth restating that the accuracy of case ascertainment, and the coding of head injuries upon admission to hospital is known to underestimate the true incidence ,22 but hIncidence of head injury in England is high, similar to stroke if just admissions are considered, and the data show considerable variability at the local level. Given that most of the estimates of the potential impact of head injury rely on studies undertaken in a single locality ,28,29 thTo assist in planning for services, data at the local level can now readily be obtained from on-line data sets from the Department of Health. At the national level they can be downloaded on-line at:While we have as yet little understanding of how case mix is related to, or interacts with socio-economic factors to mediate medium or longer term-outcomes, the association of such factors with incidence suggests that economic and social policies, for example in the development of prevention programmes, and in encouraging the use of public transport for journeys to work, may have a significant impact on reducing the incidence of head injury.The author(s) declare that they have no competing interests.The pre-publication history for this paper can be accessed here:Hospitalised Incidence rate for head injury in England in 2001–2. Estimated rate per 100,000; for those aged 0–15; 16–74; and 75 years and over, and in total. Estimates for England, and extant Regions and Health Authorities at the time.Click here for fileIncidence of admission to hospital for head injury for England, and each Primary Care Trust (PCT) in England 2002–3; Estimated rate per 100,000; for those aged 0–15; 16–74; and 75 years and over, and in total. Estimates for England, and PCT's.Click here for file


The increasing number of available genotypes for genetic studies in humans requires more advanced techniques of analysis. We previously reported significant univariate associations between gene polymorphisms and antidepressant response in mood disorders. However the combined analysis of multiple gene polymorphisms and clinical variables requires the use of non linear methods.In the present study we tested a neural network strategy for a combined analysis of two gene polymorphisms. A Multi Layer Perceptron model showed the best performance and was therefore selected over the other networks. One hundred and twenty one depressed inpatients treated with fluvoxamine in the context of previously reported pharmacogenetic studies were included. The polymorphism in the transcriptional control region upstream of the 5HTT coding sequence (SERTPR) and in the Tryptophan Hydroxylase (TPH) gene were analysed simultaneously.A multi layer perceptron network composed by 1 hidden layer with 7 nodes was chosen. 77.5 % of responders and 51.2% of non responders were correctly classified . Finally, we performed a comparison with traditional techniques. A discriminant function analysis correctly classified 34.1 % of responders and 68.1 % of non responders (F = 8.16 p = 0.0005).Overall, our findings suggest that neural networks may be a valid technique for the analysis of gene polymorphisms in pharmacogenetic studies. The complex interactions modelled through NN may be eventually applied at the clinical level for the individualized therapy. The increasing number of available genotypes for genetic studies in humans requires more advanced techniques of analysis . MoreoveIn particular, psychiatric disorders are characterized by a non mendelian, multifactorial genetic contribution with a number of susceptibility genes interacting with each other ,8. In thSince our initial study  we invesHowever, both the increasing number of genes associated with response and the limitations of traditional methods of analysis are factors requiring the use of new techniques of analysis that more closely resemble to the underlying biological process, i.e. that allows for non-linear interactions.Neural networks (NN) have been proposed for such studies ,23,24. TNN have been used in other fields of medicine, for example to predict cyclosporine dosage in patients after kidney transplantation , perspecIn fact, neural networks proved to outperform single marker association tests, particularly in the case of a complex mode of inheritance or where multiple mutations result in more than one haplotype associated with the disease ,30,31.In the present paper we have re-analysed our sample where polymorphism in the transcriptional control region upstream of the 5HTT coding sequence (SERTPR) and in the Tryptophan Hydroxylase (TPH) gene were analized , in thatThe sample was already described in the original paper . BrieflyPlasma fluvoxamine levels were determined by high-performance liquid chromatography after 2 weeks of stable 300 mg daily dose . Nine paThis is one of the most popular network architecture in use today, though relatively recent . In MLP Originally developed about 60 years ago by Fisher , in clasIn a radial basis function network the response surface of a single radial unit is a Gaussian (bell-shaped) function, peaked at the center, and descending outwards. RBF networks have advantages and disadvantages over MLPs. First, they can model any non-linear function using a single hidden layer, which removes some design-decisions about numbers of layers. Second, the simple linear transformation in the output layer can be optimized fully using traditional linear modelling techniques, which are fast and do not suffer from problems such as local minima which plague MLP training techniques. However the clumpy approach also implies that RBFs are not inclined to extrapolate beyond known data: the response drops off rapidly towards zero if data points far from the training data are used, therefore they are less reliable for clinical samples such our one. Detailed review of the models are reported elsewhere ,37.An "intent-to-treat" analysis was carried out for all patients who had a baseline assessment and at least 1 assessment after randomization, with the last observation carried forward on the HAM-D. For the current application the inputs to the first layer of the neural network consist of SERTPR and TPH genotypes while the target outputs consist of response status. The network is then trained to attempt to predict response from genotypes. Each node of the input layer of the network is set to a value representing the genotype of each polymorphism. For each polymorphism and for each subject this value is set to genotypes aa, ab or bb. If a marker genotype is missing then the input is assigned a value equal to the average of the values for all subjects in the dataset, however no missing data were present in our sample. The target output for the network is set to 1 or 2 depending on whether the subject is responding or not.The best network was selected on the basis of its discriminating error and performance, positive and negative predictive values were also reported for each model. This last was expressed as area under the Receiving Operator Characteristic (ROC) Curve. The area under a ROC curve ranges from zero to one, with values close to unity indicating better predictive power; an area of 0.5 indicates that the model is not predicting better than a random choice.However, one major problem of NN analyses is to establish if the prediction from genotypes is greater than would be expected by chance. If the whole sample is used for training, the network will to some extent "learn to recognise" particular features of each member of the dataset and can use these to predict response in a way which may not reflect any general association between marker genotypes and disease. Generally, this problem is faced by a set of strategies: dividing the dataset (50:50, 80:20...), Jackknife, bootstrapping, cross-validation and so on. However those methods present some disadvantages, in particular if only a part of the data is used to train the network this leads to a loss of power given that subjects in the validating part have different patterns of association between genotypes and drug response.In order to remedy these problems, in the case of MLP, it has been suggested to perform both training and testing on the entire dataset. The statistical significance of any observed association between outputs and affection status can be estimated using a permutation test .Once the network was defined, a statistic, denoted T, is calculated to compare the outputs for responders and non responders in the same way as an unpaired t statistic, although the statistic is not expected to follow a t distribution under the null hypothesis. Instead, in order to estimate statistical significance a permutation procedure is performed. A large number of replicate data sets are generated from the original data and the obtained network model by randomly permuting genotypes with respect to affection status. For each of these replicate data sets we can then train and test the data set as before, each time calculating T. Since each permuted data set will have only random association between genotype and affection status we obtain N values of T which provide a distribution of T under the null hypothesis. We count the number of times any of these values exceeds the value of T we obtained for the real dataset and denote this number R. Then (R + 1)/(N + 1) provides an unbiased estimate of the statistical significance of the association between genotype and affection status in the real dataset.In order to estimate a p-value of alpha, one should carry out approximately 10/alpha replicates. Typically, in order to detect association at a significance of 0.01 one would perform 1000 replicates . In the case of the present paper we performed 10000 replicates.Multiple regression and discriminant function analyses were performed to compare the results obtained with the NN strategy with traditional techniques. Responder status was the dependent variable with SERTPR and TPH as independent variables. Genotypes were scored in the following way according to the hypothesis of codominance (SERPR*l/l = 1, SERPR*l/s = 2, SERPR*s/s = 2, TPH*C/C = 1, TPH*C/A = 2, TPH*A/A = 2).Calculations for the NN selection were performed using STATSOFT (Kernel release 5.5 A). Evaluation was performed using the NNPERM package .MLP showed the best performance and was therefore selected over the other networks , after 5000 epochs we reduced it to 0.01 but after 5000 further epochs we observed no improvement and therefore we finished the selection process and retained the network. Both polymorphisms contributed substantially to the model . This was expected since both markers were individually associated with response. In detail single marker significance, calculated as simple allelic chi-square, was p = 0.00058 for SERTPR and p = 0.025 for TPH. The classification of subjects in responders and non responders was 77.5 % for responders and 51.2% for non responders. Classification may vary depending from the selected threshold, therefore the area under the ROC curve is a better indicator of performance, in this case the area was 0.731. We also evaluated the predictive power of the network with the SERTPR polymorphism only, in this case the area under the ROC curve was 0.698. We may therefore observe that the add of TPH polymorphism increases the predictive power of the system.In order to evaluate the significance of the network we applied a permutation test with 10000 replicates. The t statistic for the network was 4.35, it was achieved in 81 out of 10000 simulations yielding a network p-value = (81+1)/(10000+1) = 0.0082.Finally, we performed a comparison with traditional techniques. A multiple regression analysis showed a significant correlation (p = 0.0004) with a variance explained of 12.5%. The discriminant function analysis correctly classified 34.1 % of responders and 68.1 % of non responders (F = 8.16 p = 0.0005).Following, we tested the possible impact of clinical variables on response. We included in the model the following variables: Age, age at onset, sex, education, diagnosis, presence of delusional features, recurrence index (defined as number of episodes per year), pindolol augmentation and baseline HAM-D. With those variables no satisfactory network was identified. They were therefore not considered as possible confounding factors in the genetic analysis.This paper reports the first attempt to use NN in pharmacogenetic analyses. We applied this technique to short term antidepressant response in mood disorders. Our analyses suggest that MLP network is the most appropriate for this kind of data, in according with previous observations . The groFurther developments of this strategy are the inclusion of more detailed information on the phenotypic side. The classification results we obtained are not sufficient in clinical terms were in particular much higher specificities are needed in order to recognize in advance non responders. To reach this target we should consider that we previously observed that some polymorphism influence only part of the whole depressive symptomatology . FurtherThe relatively small sample we used does not guarantee against a possible overfitting phenomenon, therefore enlargement of the sample is a priority. Moreover we used the same sample for testing and validating our result, this is not a standard technique , this prDifferences in allele frequency for different populations have been reported . HoweverOverall, our findings suggest that neural networks may be a valid technique for the analysis of gene polymorphisms in pharmacogenetic studies. The complex interactions modelled through NN may be eventually applied at the clinical level for the individualized therapy .The author(s) declare that they have no competing interests.AS conceived the study, drafted the manuscript and participated in the design of the study and performed the statistical analysis. ES participated in its design and coordination. All authors read and approved the final manuscriptThe pre-publication history for this paper can be accessed here:


Microarray technologies allow the identification of large numbers of expression differences within and between species. Although environmental and physiological stimuli are clearly responsible for changes in the expression levels of many genes, it is not known whether the majority of changes of gene expression fixed during evolution between species and between various tissues within a species are caused by Darwinian selection or by stochastic processes. We find the following: (1) expression differences between species accumulate approximately linearly with time; (2) gene expression variation among individuals within a species correlates positively with expression divergence between species; (3) rates of expression divergence between species do not differ significantly between intact genes and expressed pseudogenes; (4) expression differences between brain regions within a species have accumulated approximately linearly with time since these regions emerged during evolution. These results suggest that the majority of expression differences observed between species are selectively neutral or nearly neutral and likely to be of little or no functional significance. Therefore, the identification of gene expression differences between species fixed by selection should be based on null hypotheses assuming functional neutrality. Furthermore, it may be possible to apply a molecular clock based on expression differences to infer the evolutionary history of tissues. Analysis of differences in gene expression between primate species suggests that the majority of them are selectively neutral and likely to have little or no functional consequences Advances in microarray technology have made the systematic study of expression levels of thousands of transcripts possible. This has been heralded as a major step forward in understanding the function of genomes, since transcript expression levels are expected to correlate with biological functions. Although this is clearly the case for many genes that change their expression in response to environmental stimuli e.g., , it is nTo test whether this may be the case, we have investigated whether a neutral model can describe transcriptome differences observed among primate and mouse species as well as among various brain regions within a species.(Pan trogodytes), one orangutan (Pongo pygmaea), and one rhesus macaque (Macaca mulatta) using oligonucleotide microarrays. To exclude the influence of DNA sequence differences on the hybridization results, at least between humans and chimpanzees, only oligonucleotide probes that matched perfectly to the chimpanzee DNA sequences were used in the analysis . Due to the greater probe length, these arrays are much less sensitive to DNA sequence differences and therefore can be used to compare gene expression in humans and macaques  as gauged by a permutation test (p = 0.028, n = 76), the vast majority of which are noncoding (We further considered the correlation between the average diversity within humans and chimpanzees and the divergence between the species for the 2,926 genes. This correlation is highly significant (ion test . Since aoncoding . Thus, aMus musculus, three outbred M. spretus, and one M. caroli. As shown in M. musculus, respectively, as was done in the primates. M. musculus diverged faster among mouse species than genes that vary less. As in the case of primate species, imperfect matches of M. spretus and M. caroli mRNAs to the array oligonucleotides may partly influence the observed expression differences between species. Nonetheless, as for primates, the difference in divergence rates between genes with high and low expression variation within species is unlikely to be explained by hybridization differences since there is no indication that genes that vary more in expression within species diverge faster between species with respect to their DNA sequence. The correlation between diversity and divergence for M. musculus and M. spretus for genes detected in both species is highly significant (τ = 0.29, p < 0.001, n = 3,139), although in this case we cannot correct for DNA sequence differences. A correlation between gene expression differences within and between species was recently demonstrated also in teleost fish  in at least one of four brain regions in either the chimpanzees or the humans after masking all probes carrying DNA sequence differences between the species. Of these, 28 contained at least one mutation that leads to a loss of function in both humans and chimpanzees. We therefore assumed that these pseudogenes were nonfunctional in the common ancestor of humans and chimpanzees. Finally, we checked whether these probe sets may crosshybridize with any intact genes by aligning them to the human genome. This left us with 23 expressed pseudogenes.To test this, we considered the expression patterns in four regions of the brain in three humans and three chimpanzees using the Affymetrix U95 array set interrogating approximately 40,000 genes (Philipp Khaitovich, unpublished data). In order to identify all probe sets on these arrays that interrogate expressed pseudogenes, we aligned the probe sequences, as well as published lists of human pseudogenes, to the human genome . In totap = 0.16 and p = 0.69, respectively)  of the genes had a distribution radically different from that of the pseudogenes. When the data for four brain regions were combined, no visual difference between the two distributions was apparent (ctively) A.Thus, we failed to detect any significant excess of intact genes that diverged faster in expression than pseudogenes. This indicates that the fraction of gene expression differences between the species that are fixed by positive selection is small. Interestingly, there was also no detectable excess of intact genes that diverged slower than pseudogenes. This may seem unexpected, since the expression of many intact genes might be thought to be stabilized by negative selection and therefore to change more slowly than pseudogenes. This may indicate that purifying selection as well is a weak force affecting gene expression. However, it should be noted that the small number of expressed pseudogenes analyzed limits the power to detect positive and negative selection. A targeted effort to study expressed pseudogenes in closely related species would be a worthwhile undertaking.The fact that the overall accumulation of expression differences conforms to a selectively neutral model does not mean, of course, that all expression differences between species are selectively neutral. As for nucleotide changes, some changes in gene expression will have had phenotypic consequences and some of these will have become fixed due to positive selection. To identify such gene expression differences, we propose to use the ratio of divergence between species to diversity within species, akin to the tests suggested for quantitative genetic traits  and in ap = 0.388; Wilcoxon rank sum test, p = 0.134), and both distributions appeared to center around roughly the same values  is very similar to that of the prefrontal cortex in both humans and chimpanzees, although it is known to be involved in speech processing in humans while it must have another function in chimpanzees . This isA noteworthy finding is that the accumulation of expression differences between brain regions within a species is much slower than the accumulation of expression differences within a brain region between species. In fact, the expression differences that have accumulated among the primate species over 20 million years see A are appA possible alternative explanation for the correlation between differences in gene expression and evolutionary divergence time among brain regions could be that differences in gene expression do not correlate with evolutionary divergence time, but instead with divergence time during fetal development. Our observations would then result from the fact that both developmental divergence times and expression differences correlate with evolutionary divergence. A correlation between developmental and evolutionary divergence times has been hypothesized before  according to manufacturer's instructions and purified with Quiagen RNeasy kit  following the “RNA cleanup” protocol. RNAs were of high and comparable quality as gauged by the ratio of 28S to 18S ribosomal RNAs visualized on agarose gels and by the signal ratios between the probes for the 3′ and 5′ ends of the mRNAs of GAPDH and β-actin genes used as quality controls on Affymetrix microarrays .For the primate samples, approximately 200 mg of gray matter was collected from post mortem brain samples from prefrontal cortex region corresponding to Brodmann's area 9 in the left hemisphere from six male humans who were 45, 45, 63, 65, 70, and 70 years old; five male chimpanzees that were 7, 12, 12, 12, and approximately 40 years old; one 16-year-old male orangutan; five approximately 10-year-old male rhesus macaques; and five approximately 15-year-old male crab-eating macaques. All individuals had no history of brain-related diseases and suffered sudden deaths without associated brain damage. For the mouse samples, approximately 50 mg of gray matter was collected from the frontal cortex regions of six For Affymetrix microarrays, labeling of 5 μg of the RNA, hybridization, staining, washing steps, and array scanning were carried out following Affymetrix protocols. Expression data were collected using Affymetrix HG U95Av2 arrays for the primate samples and Affymetrix MG U74Av2 arrays for the mice samples. The Affymetrix CEL files containing expression data for the different regions of the mouse brain, including amygdala, cerebral cortex, hippocampus, hypothalamus, cerebellum, olfactory bulb, and two regions of spinal cord were provided by John Hogenesch.http://www.ebi.ac.uk/arrayexpress/).Arrays containing 51,000 cDNAs corresponding to approximately 40,000 UniGene clusters were manufactured in the laboratory of W.A. as described elsewhere (Anonymous 2003). Labeling, hybridization, staining, washing, and array scanning were carried out as described by http://www.affymetrix.com/analysis/index.affx) first to the human genome (build 33) and then to a draft version of the chimpanzee genome (the assembly was given courtesy of David Jaffe in June 2003). Using BLAT  in gene expression between humans and chimpanzees if the real divergence is zero. Then using this distribution and the observed distribution of differences (Z), we generated a distribution (Y) that-added to values from X-would give Z. In order to underestimate the divergence, we generated Y assuming that the correlation of X and Y is one. We then generated random samples in the following way: For each gene (g), we chose a random difference of expression (d) from our generated distribution. We then drew six samples from a normal distribution whose mean is zero and whose variance is the diversity in humans for gene g, and three samples from a normal distribution whose mean is d and whose variance is the diversity of chimps for gene g. For these expression values we then calculated the correlation between diversity and divergence. We repeated the whole procedure 1,000 times. None of these randomizations generated a correlation that is as strong as the observed one. To make sure that the whole test is conservative, we generated 100 datasets of three types, all of which had a similar diversity, but had a “real” divergence distribution of (1) zero, (2) the underestimated divergence, or (3) the measured divergence, and had uncorrelated diversity and divergence. We then performed the whole test described above, doing just one randomization test. If the test was not conservative, one would expect the correlation in the dataset to be higher than the correlation after randomization in 50% of the cases. Instead, the correlation after randomization was higher in 98, 98, and 99 cases respectively-showing that our test is indeed conservative.http://vega.sanger.ac.uk). These sequences, as well as the Affymetrix target sequences, were mapped to the human genome (build 34) using BLAT (http://genome.ucsc.edu). Thus, we identified 889 probe sets that overlapped with a pseudogene, but not with a known gene. Combined with gene expression data collected in four brain regions  in three humans and three chimpanzees, 33 of these probe sets had detectable expression levels in at least one brain region in either three chimpanzees or three humans. For these probe sets, we checked whether at least one of the identified interruptions of the human pseudogene was also present in the chimpanzee, indicating that the pseudogene was already nonfunctional at the time of the chimpanzee–human divergence. This left us with 28 probe sets that were checked for crosshybridization with other genes by aligning oligonucleotide probes from these probe sets to the human genome. Finally, we were left with 23 expressed pseudogenes that did not match perfectly to any other gene by more than seven out of 16 probes in the probe set.We retrieved sequences of all pseudogenes as determined by ing BLAT , and the


Malnutrition in children can be a consequence of unfavourable socioeconomic conditions. However, some families maintain adequate nutritional status in their children despite living in poverty. The aim of this study was to ascertain whether family-related factors are determinants of stunting in young Mexican children living in extreme poverty, and whether these factors differ between rural or urban contexts.A case-control study was conducted in one rural and one urban extreme poverty level areas in Mexico. Cases comprised stunted children aged between 6 and 23 months. Controls were well-nourished children. Independent variables were defined in five dimensions: family characteristics; family income; household allocation of resources and family organisation; social networks; and child health care. Information was collected from 108 cases and 139 controls in the rural area and from 198 cases and 211 controls in the urban area. Statistical analysis was carried out separately for each area; unconditional multiple logistic regression analyses were performed to obtain the best explanatory model for stunting.In the rural area, a greater risk of stunting was associated with father's occupation as farmer and the presence of family networks for child care. The greatest protective effect was found in children cared for exclusively by their mothers. In the urban area, risk factors for stunting were father with unstable job, presence of small social networks, low rate of attendance to the Well Child Program activities, breast-feeding longer than six months, and two variables within the family characteristics dimension .This study suggests the influence of the family on the nutritional status of children under two years of age living in extreme poverty areas. Factors associated with stunting were different in rural and urban communities.Therefore, developing and implementing health programs to tackle malnutrition should take into account such differences that are consequence of the social, economic, and cultural contexts in which the family lives. Despite improvements in the health of children under five years of age, malnutrition remains as an important public health problem in Mexico  and in oPrevious reports have stated that malnutrition occurs mainly in rural areas and worsens under conditions of extreme poverty ,14,15. IPoverty is not confined to rural areas, nor is malnutrition; they are also present in urban environments . UncontrMalnutrition is an outcome of various factors resulting from unfavourable socioeconomic circumstances such as difficulties in obtaining food, unemployment -which determines an irregular income for the family's breadwinner-, limited access to education and health services, or illness caused by unsanitary conditions ,14,20-24A case-control study was conducted from August through December 1998. Two extreme poverty level areas  were selected. Each area was analysed separately.The study took place in the south-western State of Guerrero, one of the poorest in Mexico, with a population of nearly three million.The rural area, named Alto Balsas, is located next to the Balsas River; the urban area, named El Sinai, is a poor neighbourhood on the outskirts of the port of Acapulco, which has half a million inhabitants. For the rural area, four villages with a combined population of 4,638 were included in the study. The closest city is approximately 45 miles away. The principal language spoken in these villages is Náhuatl, and agriculture is the main economic activity. Because of seasonal conditions there is a high rate of cyclic migration each year. This migration occurs during harvest season, where farmers migrate from the State of Guerrero to another states. There is one medical doctor and one primary care centre per approximately 2300 people.El Sinai is located in the outskirts of Acapulco and has 6,860 inhabitants, most people speak Spanish and they work in the local industry as unskilled manual workers. In this area, there is one medical doctor and one clinic per 3400 people. In both study areas, sanitation and public services are deficient. Table The units of study were children between 6 and 23 months of age. Children older than 6 months were included on the assumption that this is the minimum amount of time the child is exposed to family-related factors; also, this is the average age in which children are weaning (this is defined as the time when mothers begin to introduce food other than milk into the child's diet). Thus infants become more exposed to environmental causes of under-nutrition. The family was defined as next of kin, or persons sharing the same household and food expenses . Only onCases were stunted children. This was ascertained by using the height-for-age indicator . The criControls were children without stunting: equal to or above -2.00 SDs below the median in families that had no stunted children.The sample size was calculated by using the case-control study formula in accordance with the following assumptions [umptions : α = 0.0A five-dimension framework to identify family-related factors that might have influence on the child's nutritional status was constructed. Each dimension comprises several variables selected to build up a comprehensive scenario.The dimensions are the following:1. Family characteristics: parents' age and literacy, type and duration of parents' union; family structure (nuclear or extended); presence of both parents (complete or incomplete family); number of members of the family and mother's use of contraceptives.per capita family income), unemployment and migration during the past two years.2. Family income: parents' employment ;4. Social networks: type of networks (within or outside the family), size of networks, frequency of interactions and type of support (economic, child care, etc.).5. Child health care: patterns of breast-feeding and health-care-seeking for preventive care (immunisations and Well Child Program visits) or curative care.In addition, the following variables were included: child characteristics (age, sex, birth order and birth weight); and housing characteristics (type of construction, crowding conditions, indoor plumbing, sewerage system, and whether the kitchen was in a separate room).In each study area, a local health worker able to communicate in Náhuatl and Spanish was trained to carry out a census to identify children fulfilling inclusion criteria, to interview the mother and to obtain the anthropometric measurements. Data were collected by using a pro-forma. The mother or caregiver was personally interviewed. During the visit, the interviewer measured and recorded the height and weight of each child aged between 6 and 23 months. The weight was measured using a digital scale with a precision error of ± 1 oz. The mother helped to measure the recumbent length of her child and this was done by using a portable calibrated board. To assure accuracy and reliability, one of the researchers (HR or RC) visited 10% of the households within the following week to confirm the data. There were no inconsistencies in data or anthropometric measures that could affect the results.Mexican Institute of Social Security IRB and Ministry of Health authorities of the State of Guerrero approved the study. Local community leaders accepted and collaborated in the study and each family head as well as child's mother gave their informed consent.Analysis was carried out separately for each area. Firstly, a bivariate analysis was run; crude odds ratios (OR) and 95% confidence intervals (95%CI) were calculated for each variable in every dimension. The analysis included estimates of correlation and interaction among variables. Secondly, to obtain the best predictive model for stunting, all statistically or conceptually significant variables within each dimension were included in an unconditional multiple logistic regression analysis; the method selected for modelling started from a saturated model until finding the best explanatory model, after assessing the significance of each covariate and adjusting for major potential confounders such as age and sex of the child, literacy of the mother and household income. Once the best explanatory model was found, goodness of fit assessment was performed. The statistical analysis was carried out using SPSS  and STATA .Through the census, 326 eligible children aged between 6 and 23 months living in the rural area and 448 in the urban area were identified. Two hundred and forty-seven children (75.8%) from the rural area and 409 (91.3%) from the urban area who fulfilled the inclusion criteria were located. Because of the harvest season, some families living in the rural area migrated temporarily, so the remaining 24.2% of children could not be located.Regarding the children living in the rural area 43.7% were stunted. Therefore, the group was divided into 108 cases and 139 controls; as to the urban area, 48.4% of children were stunted, resulting into 198 cases and 211 controls.Table In the rural area, the proportion of first birth order children in the group of cases was lower than in the control group. Housing conditions were similar in both groups. Regarding urban children, cases had poorer housing conditions than controls; also, cases were older than controls in both study areas.Table per capita family income, parents' migration from rural areas, size of social networks and frequency of attendance to the Well Child Program activities, were statistically significant variables.In the rural area, the following variables showed statistically significant differences when comparing cases and controls: parents' illiteracy, parents' civil status, duration of parental union, mother's use of contraceptive method, father engaged in farming activities, exclusive provision of care by the mother, social networks for child care, and age at weaning. At the urban area, mother's illiteracy, duration of parental union longer than two years, father's occupation, Table Additionally, two of the child's characteristics showed significance (data not presented in the table): child's age , and child's sex Table per capita family income did not change the significance of the model when adjusted.The explanatory model for the urban area included several covariates as risk factors in most dimensions. Dimension 1: migration of parents from rural to urban area, and duration of the parents' union longer than two years. Dimension 2: the father being in the same employment for two years or less. Dimension 4: having small family networks. Dimension 5: child having fewer than two visits to the Well Child Program activities during the past 6 months, and breast-feeding longer than six months. Age showed to be a significant confounder, and other characteristics of the child such as sex or birth weight, or those characteristics related to the parents such as literacy or The role of the family as an important influence for nutritional status of children has been increasingly emphasized during the past few years,  and reinNutritional status is an indicator of well being and malnutrition is the result of a complex process within which coexist a number of variables. The results in this study showed that the family related factors for stunting were different in each context -urban or rural-. The model highlighted the importance of identifying, [rather arbitrarily] a number of conceptually grounded dimensions that could be associated with stunting.As mentioned earlier, rural and urban environments are different. Regarding the results of the rural area, within the family income dimension, the variable father's occupation (farming) was found to be a risk factor for child's stunting. In this area, availability of food depends upon local production, which in turn is related to father's occupation. Maize is the staple, and there is lack of food variability or inability to produce sufficient food for the family's nutritional requirements .per capita family income, which was statistically significant in the bivariate analysis, did not show significance in the multivariate analysis. This finding could be interpreted as the ability of the family to cope with a difficult environment. Analysis of microeconomic variables shows the need of further studies to confirm plausibility of our findings and its association with malnutrition.In the urban area the instability of the father's employment (working in the same place for less than 2 years) was found to be a risk factor. Lack of stable employment is a common problem among unskilled workers; their income is low and irregular, thus affecting their capacity to purchase goods and food, which in turn affects child nutrition . NeverthThe dimension of family structure, which included socio-demographic characteristics of the parents, migration, and literacy attainment, has been repeatedly associated with the nutritional status of children. ,23,34,35An interesting finding in this study was the relationship between social networks and children's nutritional status. It is often assumed that extended families have extensive social networks, and that this can be advantageous for the care of young children. However, we found quite the opposite in the rural area: the presence of family networks was associated with stunting, while exclusive provision of child-care by the mother showed a protective effect. These findings stress the role of the mother as primary caregiver, at least for young children; such findings also suggest that when a mother is present to care for the child, some of the effects of living in a poor community can be ameliorated.In the urban area, conditions seem to be different, and the sizes of social networks influenced the nutritional status of the children positively. Urban families living in a more aggressive environment might be more likely to obtain health benefits if they have greater family or social support.Use of health services, based on preventive measures from the Well Child Program, was also analyzed. Few visits to the Well Child Program activities were associated with stunting in the urban area. Restricted access to health care services in deprived areas is an important shortcoming with regard to monitoring child's growth and health . Based oMigration was also explored. In the final explanatory model addressing the urban area, parents' migration from rural to urban area was found to be a risk factor for stunting. Migration from rural to urban settings is frequent among young people looking for improving their living conditions. However, families' adaptation to the new situation is a long process, given that such families live in a hostile environment and they have limited access to information regarding how to care for the child. In contrast, migration of one member of the family from one urban setting to another did not show a relationship with nutritional status of children. Adult male family members, mainly the heads of household, migrate to other states in Mexico or to the U.S. in search of better income. Perhaps the influence of this variable could be identified by a qualitative approach. Therefore, further research on this aspect is necessary.The study has some limitations. Firstly, the study groups were of unequal size; this is a consequence of including all children aged from 6 to 23 months of age identified by the census. Additionally, since children of the control group were significantly younger than cases, some of them could have become stunted by the time they were of comparable age to the cases. To solve this limitation, the covariate age was adjusted in the multivariate analysis. However, it is possible that an age-matched cases-control design would have been preferable.Secondly, the fact that almost 25% of eligible children in the rural area were not included due to migration of their families could have led to selection bias.Another limitation is the lack of precise information regarding food practices among participating families. The interview allowed identifying general aspects such as duration of breast-feeding and age of weaning. Breast-feeding beyond 6 months of age entailed a risk of stunting, but only in the urban area. This issue has been controversial; some authors suggest that the relationship between prolonged breast-feeding and malnutrition may indicate a maternal decision to continue breast-feeding to a nutritionally disadvantaged child -39, rathThis study suggests the influence of the family on the nutritional status of children under two years of age living in extreme poverty areas. Factors associated with stunting were different in rural and urban communities.Therefore, developing and implementing health programs to tackle malnutrition should take into account such differences that are consequence of the social, economic, and cultural contexts in which the family lives.The author(s) declare that they have no competing interests.HR and AS conceived, designed and co-ordinated the study. RPC participated in the design of the study, statistical analysis and interpretation of data, and drafted the manuscript. RC co-ordinated the acquisition of data and participated in the statistical analysis. SD collaborated in the data analysis and drafted the manuscript. JIS and GG participated in the conception and design of the study, interpretation of data and critical revision for important intellectual content. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Individual patient meta-analysis to determine the analgesic efficacy and adverse effects of single-dose rofecoxib in primary dysmenorrhoea.Individual patient information was available from three randomised, double blind, placebo and active controlled trials of rofecoxib. Data were combined through meta-analysis. Number-needed-to-treat (NNT) for at least 50% pain relief and the proportion of patients who had taken rescue medication over 12 hours were calculated. Information was collected on adverse effects.For single-dose rofecoxib 50 mg compared with placebo, the NNTs (with 95% CI) for at least 50% pain relief were 3.2 (2.4 to 4.5) at six, 3.1 (2.4 to 9.0) at eight, and 3.7 (2.8 to 5.6) at 12 hours. For naproxen sodium 550 mg they were 3.1 (2.4 to 4.4) at six, 3.0 (2.3 to 4.2) at eight, and 3.8 (2.7 to 6.1) at 12 hours. The proportion of patients who needed rescue medication within 12 hours was 27% with rofecoxib 50 mg, 29% with naproxen sodium 550 mg, and 50% with placebo. In the single-dose trial, the proportion of patients reporting any adverse effect was 8% (4/49) with rofecoxib 50 mg, 12% (6/49) with ibuprofen 400 mg, and 6% (3/49) with placebo. In the other two multiple dose trials, the proportion of patients reporting any adverse effect was 23% (42/179) with rofecoxib 50 mg, 24% (45/181) with naproxen sodium 550 mg, and 18% (33/178) with placebo.Single dose rofecoxib 50 mg provided similar pain relief to naproxen sodium 550 mg over 12 hours. The duration of analgesia with rofecoxib 50 mg was similar to that of naproxen sodium 550 mg. Adverse effects were uncommon suggesting safety in short-term use of rofecoxib and naproxen sodium. Future research should include restriction on daily life and absence from work or school as outcomes. Dysmenorrhoea is associated with painful cramping of the lower abdominal or back muscles, with or without other symptoms such as nausea, vomiting, and diarrhoea. Onset of dysmenorrhoea is common during adolescence, and up to 50% of women of reproductive age may be affected , and 10%Raised concentrations of uterine prostaglandins are thought to cause the pain and cramping associated with dysmenorrhoea -6. NonstSystematic reviews have shown NSAIDs to be effective in the treatment of primary dysmenorrhoea ,8 While At least moderate pain relief over a cycle was reported in 14 comparisons between NSAID (any NSAID, any dose) and placebo in 599 women, with an NNT of 2.1 (1.9 to 2.5). The most studied NSAID was naproxen, with 287 women in seven trials, with an NNT of 2.5 (2.0 to 3.3) for this outcome. An earlier review [Cox-2 selective inhibitors (coxibs) provide an alternative to conventional NSAIDs, with a potential advantage of once daily dosing -11. ThisQUOROM guidelines  for qualMerck Research Laboratories, Rahway, New Jersey provided individual patient data from three Phase III trials of rofecoxib in dysmenorrhoea (studies 38, 55 and 56), with the guarantee that all relevant studies completed by July 2002 had been made available. One of the trials has been published in full . SearchiOur intention was to use two pain outcomes (pain relief over the first dose, and pain relief over the whole cycle) with the outcome being that closest to at least half pain relief. Over the first dose, this might be a measure of total pain relief (TOTPAR), while over a whole cycle it may be a patient global evaluation of good or excellent, rather than mild, fair, no improvement, or worse. Analyses for comparator treatments were based on information available only from the trials of rofecoxib in this report. Outcome data were pooled in an intention to treat (number of patients randomised) analysis. Neither heterogeneity tests nor funnel plots were used ,17. InstRelative benefit (or risk) was calculated using a fixed effects model  with no The mean age of women in the trials was 31 years, and at baseline pain was moderate in 66% of women and severe in 34%. All trials were randomised, double blind, and compared oral doses of rofecoxib with an active control and placebo in women with moderate to severe pain due to dysmenorrhoea. One trial was a single dose crossover (study 38), and two were multiple dose crossovers (studies 55 and 56), where the crossover was between single doses in different menstrual cycles. Single dose efficacy data were available for the first 12 hours of treatment in all trials, but not summary estimates over a cycle. Study designs and quality and validity scores are shown in Table The single dose trial (study 38) was conducted over three cycles. Each of 49 women received three of four treatments (rofecoxib 25 mg, rofecoxib 50 mg, ibuprofen 400 mg, or placebo). For the two multiple dose studies, one (study 55) compared a single dose of rofecoxib 50 mg followed by 25 mg daily as required, naproxen sodium 550 mg every 12 hours, or placebo in 60 women over three menstrual cycles. The other (study 56) compared rofecoxib 50 mg as required, rofecoxib 50 mg followed by 25 mg daily as required, naproxen sodium 550 mg every 12 hours, or placebo in 122 women over four menstrual cycles. Both trials reported multiple dose adverse effects. In the multiple dose trials, all women received each treatment regimen for one cycle.Pain intensity and pain relief were measured using the standard 4-point categorical pain intensity scale (0 none, 1 mild, 2 moderate, 3 severe) and a 5-point point pain relief scale (0 none, 1 a little, 2 some, 3 a lot, 4 complete). Pain measurements were collected using patient diaries. Patients were assessed at baseline, then at least hourly for eight hours, and again at 12 hours for single dose efficacy data. The exact time at which a patient requested remedication , if required, was recorded. Adverse effects were recorded as the number of patients with any adverse effect(s), or particular adverse effects.Full efficacy results over six, eight and 12 hours are shown in Table Rofecoxib 25 mg was tested in a single trial, rofecoxib 50 mg in three, ibuprofen 400 mg in one and naproxen sodium 550 mg in two. For all the active analgesics the proportion of patients with at least 50% pain relief was about 60% at all time points, and with placebo it was about 30% at all time points (Table There was no significant difference between NNTs for single doses of study treatments at six, eight or 12 hours. For instance, no significant difference at the 12 hour comparison was seen between the NNTs of rofecoxib 25 mg and rofecoxib 50 mg (z score 1.19, p = 0.23), ibuprofen 400 mg (z score 0.28, p = 0.78), or naproxen sodium 550 mg(z score 1.09, p = 0.28), or between NNTs of rofecoxib 50 mg and ibuprofen 400 mg (z score 0.26, p = 0.79), or naproxen sodium 550 mg (z score 0.096, p = 0.60).The proportion of patients who remedicated at different time points over 12 hours is shown in Figure Few adverse effects of a particular type were reported, and none were serious in any trial. The most commonly reported adverse effects were nausea and somnolence, but these occurred infrequently. A single dose in one trial (study 38) gave the proportion of patients reporting any adverse effect(s) as 10% (5/49 patients) with rofecoxib 25 mg, 8% (4/49) with rofecoxib 50 mg, 12% (6/49) with ibuprofen 400 mg, and 6% (3/49) with placebo. With multiple doses over a cycle, the proportion of patients reporting any adverse effect(s) was 23% (42/179 patients) with rofecoxib 50 mg, 24% (45/181) with naproxen sodium 550 mg, and 18% (33/178) with placebo.Pain with dysmenorrhoea usually lasts for about three days, though with considerable individual variation. Trials of analgesics can have various forms. The simplest might be to give the same analgesic for the whole of the painful cycle, and ask a global question concerning efficacy at the end. Women might then be crossed over to a different treatment at the next cycle. A variation would be to use the same basic structure, but make more detailed evaluations of pain or pain relief over a limited time during the first day, though a global question could always be added. A more complicated design would use a cross-over within a single cycle.The three trials described here used a cross-over between cycles, with detailed pain measurements over 12–24 hours in the first painful day. Twelve-hour and 24-hour outcomes have also been reported in two other recent studies of coxibs in dysmenorrhoea ,11. WithAll three trials were of the highest reporting quality, and had high validity scores, indicating that known sources of bias are unlikely to occur ,8. We knIndividual patient information from three trials of high quality showed that for the outcome of at least half pain relief over 12 hours, rofecoxib, naproxen sodium and ibuprofen were similarly effective in the treatment of pain associated with dysmenorrhoea. This confirms what was known from previous meta-analysis , in whicRofecoxib 50 mg was statistically indistinguishable from naproxen sodium 550 mg Table  at all tPain relief and duration of analgesia are not the only issues of importance in dysmenorrhoea. The impact of dysmenorrhoea on activities of daily living, disability or function, and absence from work or school are additional factors to be considered. These outcomes were not addressed by the trials for rofecoxib, which were conducted for regulatory purposes. This limits the utility of the information, but trials of other coxibs  have also concentrated on pain relief and duration of analgesia ,11.Future trials should examine a range of short-term analgesia and longer outcomes like interference with daily living or absence from work or school. The analysis by Zhang and colleagues  did examFuture individual patient analysis of trials in dysmenorrhoea would have the potential to examine issues around the efficacy of analgesics in women with heavy menstrual loss, or who use combined oral contraceptive pills. In this analysis information was not available for these analyses, and in any event any sub-groups would probably have been too small for any definitive answer.In the trials for rofecoxib, information on adverse effects was collected using diaries. Few adverse effects were reported to have occurred and none were serious. The most common adverse effects were nausea and somnolence. These and headache have been frequently reported with other coxibs ,11 and NBased on information from three trials, a single dose of rofecoxib 50 mg is as effective as a single dose of naproxen sodium 500 mg in controlling the pain associated with dysmenorrhoea, and causes relatively few adverse effects.RAM has been a consultant for Merck, Sharpe and Dohme Ltd, UK. RAM, JE and HJM have received lecture fees from pharmaceutical companies. The authors have received research support from charities and government sources at various times, but no such support was received for this work. Neither author has any direct stock holding in any pharmaceutical company. The terms of the financial support from MSD included freedom for authors to reach their own conclusions, and an absolute right to publish the results of their research, irrespective of any conclusions reached. MSD did have the right to view the final manuscript before publication, and did so.JE conducted the analyses, which were checked by RAM. All authors contributed equally to the design, writing and reviewing of the paper.The pre-publication history for this paper can be accessed here: