Maternal pre-pregnancy body mass index and risk of preterm birth: a collaboration using large routine health datasets.

BACKGROUND: Preterm birth (PTB) is a leading cause of child morbidity and mortality. Evidence suggests an increased risk with both maternal underweight and obesity, with some studies suggesting underweight might be a greater factor in spontaneous PTB (SPTB) and that the relationship might vary by parity. Previous studies have largely explored established body mass index (BMI) categories. Our aim was to compare associations of maternal pre-pregnancy BMI with any PTB, SPTB and medically indicated PTB (MPTB) among nulliparous and parous women across populations with differing characteristics, and to identify the optimal BMI with lowest risk for these outcomes. METHODS: We used three UK datasets, two USA datasets and one each from South Australia, Norway and Denmark, together including just under 29 million pregnancies resulting in a live birth or stillbirth after 24 completed weeks gestation. Fractional polynomial multivariable logistic regression was used to examine the relationship of maternal BMI with any PTB, SPTB and MPTB, among nulliparous and parous women separately. The results were combined using a random effects meta-analysis. The estimated BMI at which risk was lowest was calculated via differentiation and a 95% confidence interval (CI) obtained using bootstrapping. RESULTS: We found non-linear associations between BMI and all three outcomes, across all datasets. The adjusted risk of any PTB and MPTB was elevated at both low and high BMIs, whereas the risk of SPTB was increased at lower levels of BMI but remained low or increased only slightly with higher BMI. In the meta-analysed data, the lowest risk of any PTB was at a BMI of 22.5 kg/m2 (95% CI 21.5, 23.5) among nulliparous women and 25.9 kg/m2 (95% CI 24.1, 31.7) among multiparous women, with values of 20.4 kg/m2 (20.0, 21.1) and 22.2 kg/m2 (21.1, 24.3), respectively, for MPTB; for SPTB, the risk remained roughly largely constant above a BMI of around 25-30 kg/m2 regardless of parity. CONCLUSIONS: Consistency of findings across different populations, despite differences between them in terms of the time period covered, the BMI distribution, missing data and control for key confounders, suggests that severe under- and overweight may play a role in PTB risk.

The dynamic interplay between sleep and mood: an intensive longitudinal study of individuals with bipolar disorder.

BACKGROUND: Sleep disturbances are important symptoms to monitor in people with bipolar disorder (BD) but the precise longitudinal relationships between sleep and mood remain unclear. We aimed to examine associations between stable and dynamic aspects of sleep and mood in people with BD, and assess individual differences in the strength of these associations. METHODS: Participants (N = 649) with BD-I (N = 400) and BD-II (N = 249) provided weekly self-reports of insomnia, depression and (hypo)mania symptoms using the True Colours online monitoring tool for 21 months. Dynamic structural equation models were used to examine the interplay between weekly reports of insomnia and mood. The effects of clinical and demographic characteristics on associations were also assessed. RESULTS: Increased variability in insomnia symptoms was associated with increased mood variability. In the sample as a whole, we found strong evidence of bidirectional relationships between insomnia and depressive symptoms but only weak support for bidirectional relationships between insomnia and (hypo)manic symptoms. We found substantial variability between participants in the strength of prospective associations between insomnia and mood, which depended on age, gender, bipolar subtype, and a history of rapid cycling. CONCLUSIONS: Our results highlight the importance of monitoring sleep in people with BD. However, researchers and clinicians investigating the association between sleep and mood should consider subgroup differences in this relationship. Advances in digital technology mean that intensive longitudinal data on sleep and mood are becoming increasingly available. Novel methods to analyse these data present an exciting opportunity for furthering our understanding of BD.

Improved two-stage estimation to adjust for treatment switching in randomised trials: g-estimation to address time-dependent confounding.

In oncology trials, control group patients often switch onto the experimental treatment during follow-up, usually after disease progression. In this case, an intention-to-treat analysis will not address the policy question of interest - that of whether the new treatment represents an effective and cost-effective use of health care resources, compared to the standard treatment. Rank preserving structural failure time models (RPSFTM), inverse probability of censoring weights (IPCW) and two-stage estimation (TSE) have often been used to adjust for switching to inform treatment reimbursement policy decisions. TSE has been applied using a simple approach (TSEsimp), assuming no time-dependent confounding between the time of disease progression and the time of switch. This is problematic if there is a delay between progression and switch. In this paper we introduce TSEgest, which uses structural nested models and g-estimation to account for time-dependent confounding, and compare it to TSEsimp, RPSFTM and IPCW. We simulated scenarios where control group patients could switch onto the experimental treatment with and without time-dependent confounding being present. We varied switching proportions, treatment effects and censoring proportions. We assessed adjustment methods according to their estimation of control group restricted mean survival times that would have been observed in the absence of switching. All methods performed well in scenarios with no time-dependent confounding. TSEgest and RPSFTM continued to perform well in scenarios with time-dependent confounding, but TSEsimp resulted in substantial bias. IPCW also performed well in scenarios with time-dependent confounding, except when inverse probability weights were high in relation to the size of the group being subjected to weighting, which occurred when there was a combination of modest sample size and high switching proportions. TSEgest represents a useful addition to the collection of methods that may be used to adjust for treatment switching in trials in order to address policy-relevant questions.

Transition to parenthood and mental health at 30 years: a prospective comparison of mothers and fathers in a large Brazilian birth cohort.

Parenthood represents a major biological, social and environmental life change. Mental health disorders are common in parents and impact both the parent and their offspring. However, the relationship between parenthood and mental health and the direction of these effects are poorly understood. Longitudinal data from the Pelotas 1982 birth cohort, Southern Brazil, on 3701 individuals was used to investigate the association between number of children by age 30 years and mental health disorders using DSM-IV diagnoses at age 30 years, suicidal risk and the change in symptoms using repeated measures (using the SRQ-20) from age 19 to 30 years. Mothers, but not fathers, with higher number of children by age 30 years, were at a substantially increased risk of a wide range of mental health disorders compared to women with no children. There was evidence that motherhood was associated with an increase in symptoms over time rather than higher symptoms at baseline. Younger age at first child was also a risk factor for mental health disorders. Mothers, particularly those with multiple children, are at risk of a wide range of mental health disorders. The mechanisms to explain these risks are yet to be elucidated; however, the risk of mental health disorders was not replicated in fathers, which would be expected if residual confounding explained observed associations. Thus, multiparous mothers represent a high-risk group and should be prioritised for supportive interventions.

Frailty in older-age European migrants: Cross-sectional and longitudinal analyses of the Survey of Health, Aging and Retirement in Europe (SHARE).

Frailty correlates with morbidity and is superior to chronological age in predicting mortality. Frailty of older migrants has important implications for the demands placed on healthcare systems. Examining 95,635 Europeans in the Survey of Health, Aging and Retirement in Europe, we investigated cross-sectional and longitudinal associations between migration and frailty at ages >50 years. We examined whether associations differed by countries' level of healthcare coverage and access for migrants and tested mediation by home-ownership and citizenship. Cross-sectionally, first-generation migrants >50 years old were, on average, 16.4% (95% confidence interval [CI]: 14.6, 18.2%) frailer than non-migrants after confounder-adjustment. This decreased to 12.1% (95% CI: 10.1, 14.1%) after adjustment for citizenship. The strength of association between migrant status and frailty was greater in migrants from low-or-middle-income countries, compared with migrants from high-income countries. Migrants into Northern, Western and Eastern Europe were 37.3% (95% CI: 33.2, 41.5%), 12.2% (95% CI: 10.0, 14.6%) and 5.0% (95% CI: 0.5, 9.6%) frailer than non-migrants, respectively, but migrants into Southern Europe were no frailer than non-migrants. The strength of association between migrant status and frailty was greater in countries with lower healthcare coverage and access for migrants. However, citizenship attenuated this difference. Longitudinally, migrants were frailer than non-migrants at 50 years old and trajectories converged over time until migrants and non-migrants were equally frail by 80-90 years. Our work finds no evidence of the 'healthy migrant effect' outside of Southern Europe in older migrants and suggests that acculturation is a key determinant of migrant health.

DNA methylation from birth to late adolescence and development of multiple-risk behaviours.

BACKGROUND: Risk behaviours in adolescence are linked to poor educational attainment and health and other outcomes in young adulthood. We explored whether there are molecular mechanisms associated with the development, or the result, of multiple risk behaviours (MRBs). METHODS: MRBs (antisocial behaviour and delinquency, traffic-related risk behaviour, risky sexual behaviour, lack of exercise) and their sumscore were characterized based on self-reported questions at age 7 and 17 within the ARIES subsample of the ALSPAC birth cohort, and were linked to DNA methylation at over 485,000 CpG sites at ages 0,7 and 17. Associations were determined for participants with complete data (n = 227-575). RESULTS: There was weak evidence of associations between cumulative MRBs and methylation at cg01783492 and cg16720578 at age 17. DNA methylation at age 17 was associated with risky sexual behaviour (cg22883332), lack of exercise (cg03152353, cg20056908, cg20571116) and substance use (cg02188400, cg13906377). No associations between DNA methylation and individual risk behaviours at age 7 were observed. DNA methylation at age 7 might predispose for traffic-related risk behaviour (cg24683561) and substance use (cg08761410) at age 17. LIMITATIONS: Main limitations are absence of information on directly measured blood cell type proportions and tissue specificity, and a modest sample size. CONCLUSIONS: Cumulative MRB in late adolescence was associated with effects on DNA methylation. More specifically, risky sexual behaviour and sedentary behaviour are associated with changes in DNA methylation, while DNA methylation in childhood may predict later traffic-related risky behaviour. For substance use effects in both temporal directions were observed.

Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study.

BACKGROUND: When an outcome variable is missing not at random (MNAR: probability of missingness depends on outcome values), estimates of the effect of an exposure on this outcome are often biased. We investigated the extent of this bias and examined whether the bias can be reduced through incorporating proxy outcomes obtained through linkage to administrative data as auxiliary variables in multiple imputation (MI). METHODS: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) we estimated the association between breastfeeding and IQ (continuous outcome), incorporating linked attainment data (proxies for IQ) as auxiliary variables in MI models. Simulation studies explored the impact of varying the proportion of missing data (from 20 to 80%), the correlation between the outcome and its proxy (0.1-0.9), the strength of the missing data mechanism, and having a proxy variable that was incomplete. RESULTS: Incorporating a linked proxy for the missing outcome as an auxiliary variable reduced bias and increased efficiency in all scenarios, even when 80% of the outcome was missing. Using an incomplete proxy was similarly beneficial. High correlations (> 0.5) between the outcome and its proxy substantially reduced the missing information. Consistent with this, ALSPAC analysis showed inclusion of a proxy reduced bias and improved efficiency. Gains with additional proxies were modest. CONCLUSIONS: In longitudinal studies with loss to follow-up, incorporating proxies for this study outcome obtained via linkage to external sources of data as auxiliary variables in MI models can give practically important bias reduction and efficiency gains when the study outcome is MNAR.

Body mass index trajectories from 2 to 18 years - exploring differences between European cohorts.

BACKGROUND: In recent decades, there has been an increase in the prevalence of childhood overweight in most high-income countries. Within northern Europe, prevalence tends to be higher in the UK compared with the Scandinavian countries. We aimed to study differences in body mass index (BMI) trajectories between large cohorts of children from UK and Scandinavian populations. METHODS: We compared BMI trajectories in participants from the English Avon Longitudinal Study of Parents and Children born in 1991-1993 (ALSPAC) (N = 6517), the Northern Finland Birth Cohorts born in 1966 (NFBC1966) (N = 3321) and 1986 (NFBC1986) (N = 4764), and the Danish Aarhus Birth Cohort born in 1990-1992 (ABC) (N = 1920). We used multilevel models to estimate BMI trajectories from 2 to 18 years. We explored whether cohort differences were explained by maternal BMI, height, education or smoking during pregnancy and whether differences were attributable to changes in the degree of skew in the BMI distribution. RESULTS: Differences in mean BMI between the cohorts were small but emerged early and persisted in most cases across childhood. Girls in ALSPAC had a higher BMI than all other cohorts throughout childhood, e.g. compared with the NFBC1986 BMI was 2.2-3.5% higher. For boys, the difference emerging over time (comparing the two NFBC's) exceeded the differences across populations (comparing NFBC1986, ABC and ALSPAC). BMI distribution demonstrated increasing right skew with age. CONCLUSION: Population-level differences between cohorts were small, tended to emerge very early, persisted across childhood, and demonstrated an increase in the right-hand tail of the BMI distribution.

Joint modelling compared with two stage methods for analysing longitudinal data and prospective outcomes: A simulation study of childhood growth and BP.

There is a growing debate with regards to the appropriate methods of analysis of growth trajectories and their association with prospective dependent outcomes. Using the example of childhood growth and adult BP, we conducted an extensive simulation study to explore four two-stage and two joint modelling methods, and compared their bias and coverage in estimation of the (unconditional) association between birth length and later BP, and the association between growth rate and later BP (conditional on birth length). We show that the two-stage method of using multilevel models to estimate growth parameters and relating these to outcome gives unbiased estimates of the conditional associations between growth and outcome. Using simulations, we demonstrate that the simple methods resulted in bias in the presence of measurement error, as did the two-stage multilevel method when looking at the total (unconditional) association of birth length with outcome. The two joint modelling methods gave unbiased results, but using the re-inflated residuals led to undercoverage of the confidence intervals. We conclude that either joint modelling or the simpler two-stage multilevel approach can be used to estimate conditional associations between growth and later outcomes, but that only joint modelling is unbiased with nominal coverage for unconditional associations.

Challenges and novel approaches for investigating molecular mediation.

Understanding mediation is useful for identifying intermediates lying between an exposure and an outcome which, when intervened upon, will block (some or all of) the causal pathway between the exposure and outcome. Mediation approaches used in conventional epidemiology have been adapted to understanding the role of molecular intermediates in situations of high-dimensional omics data with varying degrees of success. In particular, the limitations of observational epidemiological study including confounding, reverse causation and measurement error can afflict conventional mediation approaches and may lead to incorrect conclusions regarding causal effects. Solutions to analysing mediation which overcome these problems include the use of instrumental variable methods such as Mendelian randomization, which may be applied to evaluate causality in increasingly complex networks of omics data.

Comparison of imputation variance estimators.

Appropriate imputation inference requires both an unbiased imputation estimator and an unbiased variance estimator. The commonly used variance estimator, proposed by Rubin, can be biased when the imputation and analysis models are misspecified and/or incompatible. Robins and Wang proposed an alternative approach, which allows for such misspecification and incompatibility, but it is considerably more complex. It is unknown whether in practice Robins and Wang's multiple imputation procedure is an improvement over Rubin's multiple imputation. We conducted a critical review of these two multiple imputation approaches, a re-sampling method called full mechanism bootstrapping and our modified Rubin's multiple imputation procedure via simulations and an application to data. We explored four common scenarios of misspecification and incompatibility. In general, for a moderate sample size (n = 1000), Robins and Wang's multiple imputation produced the narrowest confidence intervals, with acceptable coverage. For a small sample size (n = 100) Rubin's multiple imputation, overall, outperformed the other methods. Full mechanism bootstrapping was inefficient relative to the other methods and required modelling of the missing data mechanism under the missing at random assumption. Our proposed modification showed an improvement over Rubin's multiple imputation in the presence of misspecification. Overall, Rubin's multiple imputation variance estimator can fail in the presence of incompatibility and/or misspecification. For unavoidable incompatibility and/or misspecification, Robins and Wang's multiple imputation could provide more robust inferences.

Agreement between routine and research measurement of infant height and weight.

UNLABELLED: In many countries, routine data relating to growth of infants are collected as a means of tracking health and illness up to school age. These have potential to be used in research. For health monitoring and research, data should be accurate and reliable. This study aimed to determine the agreement between length/height and weight measurements from routine infant records and researcher-collected data. METHODS: Height/length and weight at ages 6, 12 and 24 months from the longitudinal UK birth cohort (born in Bradford; n=836-1280) were compared with routine data collected by health visitors within 2 months of the research data (n=104-573 for different comparisons). Data were age adjusted and compared using Bland Altman plots. RESULTS: There was agreement between data sources, albeit weaker for height than for weight. Routine data tended to underestimate length/height at 6 months (0.5 cm (95% CI -4.0 to 4.9)) and overestimate it at 12 (-0.3 cm (95% CI -0.5 to 4.0)) and 24 months (0.3 cm (95% CI -4.0 to 3.4)). Routine data slightly overestimated weight at all three ages (range -0.04 kg (95% CI -1.2 to 0.9) to -0.04 (95% CI -0.7 to 0.6)). Limits of agreement were wide, particularly for height. Differences were generally random, although routine data tended to underestimate length in taller infants and underestimate weight in lighter infants. CONCLUSIONS: Routine data can provide an accurate and feasible method of data collection for research, though wide limits of agreement between data sources may be observed. Differences could be due to methodological issues; but may relate to variability in clinical practice. Continued provision of appropriate training and assessment is essential for health professionals responsible for collecting routine data.

Breast-feeding and health consequences in early childhood: is there an impact of time-dependent confounding?

BACKGROUND: Estimated effects of breast-feeding on childhood health vary between studies, possibly due to confounding by baseline maternal and child characteristics. Possible time-dependent confounding has received little consideration. Our aim was to evaluate the impact of such confounding. METHODS: We estimated the relationship between cumulative exclusive breast-feeding up to 6 months and wheezing, rash and body mass index (BMI) at 12 months [in the Whistler cohort (n = 494) and PROBIT (n = 11,463)], and wheezing, rash, asthma, hay fever, eczema, allergy and BMI at age 6.5 years (PROBIT). We adjusted for time-dependent confounding by weight, length, rash, respiratory illness and day care attendance using marginal structural models (MSMs). RESULTS: Weight and day care attendance appeared potential time-dependent confounders, since these predicted breast-feeding status and were influenced by previous breast-feeding. However, adjustment for time-dependent confounders did not markedly change the estimated associations. For example, in PROBIT the adjusted increase in BMI at 12 months per 1-month increase in exclusive breast-feeding was 0.04 (95% CI -0.09 to 0.01) using logistic regression and -0.06 (95% CI -0.11 to -0.01) using MSM. In Whistler, these estimates were each -0.05 (95% CI -0.10 to 0.00). CONCLUSIONS: In two cohort studies, there was little evidence of time-dependent confounding by weight, length, rash, respiratory illness or day care attendance of the effects of breast-feeding on early childhood health.

Identification of a dietary pattern prospectively associated with increased adiposity during childhood and adolescence.

BACKGROUND: Specific dietary risk factors for excess adiposity in young people are poorly understood. However, studies in adults suggest dietary energy density, fat and fibre are critical dietary factors. OBJECTIVE: To examine longitudinal relationships between a dietary pattern (DP) characterised by dietary energy density, % total energy from fat and fibre density and fat mass (FM) in children from 7 to 15 years of age. DESIGN: Subjects were 6772 children from the UK Avon Longitudinal Study of Parents and Children. Dietary intake was assessed using a 3-day food diary at 7, 10 and 13 years of age. An energy-dense, high-fat, low-fibre DP was identified using reduced rank regression and subjects scored for the DP at each age. FM was measured at 11, 13 and 15 years and FM index (FMI) calculated as FM/height((x)). Longitudinal models were adjusted for dietary misreporting, physical activity and maternal factors. RESULTS: DP z-scores at all ages were positively associated with later FMI. A 1 s.d. unit increase in DP z-score was longitudinally associated with an average increase in FMI z-score of 0.04 s.d. units (95% confidence interval (CI), 0.01-0.07). For each 1 s.d. unit increase in DP z-score, the odds of being in the highest quintile for FMI (as a marker of excess adiposity) increased by 13% (95% CI, 1-27%). CONCLUSIONS: Dietary habits during childhood are associated with increased adiposity in adolescence, with specific implications for dietary energy density, fat and fibre intake. Improving diet quality may reduce the risk of obesity in young people.

Patient-specific recovery patterns over time measured by dependence in activities of daily living after stroke and post-stroke care: the South London Stroke Register (SLSR).

BACKGROUND AND PURPOSE: Data on patient-specific recovery after stroke are lacking and the effects of complex healthcare interventions on the course of recovery were not reported. To quantify the recovery pattern up to 1 year post-stroke and assess effects of evidence-based treatments on the patient-specific course of recovery allowing its prediction. METHODS: A total of 355 patients after first-ever stroke from the population-based South London Stroke Register (source population >270,000) participated in a substudy between August 2002 and October 2004. At 1, 2, 3, 4, 6, 8, 12, 26, and 52 weeks post-stroke, Barthel Index (BI; ranging from 0 to 20) was documented. Multilevel growth models allowing predictions for patients with specific characteristics were calculated. RESULTS: Mean age was 70 years, 48% were male and 23% died within the first year. The age-, gender- and stroke subtype-adjusted BI curve sharply increased until week 8 to 24 depending on patient characteristics and subsequently plateaued. Multivariable analysis identified stroke unit care, appropriate secondary prevention and physiotherapy for those with disabilities as independent predictors of improved functional ability over time (P < 0.05). Patients receiving stroke unit care additionally gained 4 BI points within 6 months compared with their counterparts (P = 0.004). CONCLUSIONS: Functional outcome in the general population showed an increase followed by a plateau. Care parameters reflecting guideline treatment independently improved recovery illustrating the beneficial effects of evidence-based interventions on recovery in an unbiased population.

Accuracy of height and weight data from child health records.

BACKGROUND: There is limited knowledge of the accuracy of height and weight measurements from child health records, despite widespread use for research and clinical care. We assess the accuracy of such measurements, using research measurements as the gold standard. METHODS: We compare height/length and weight measurements from clinics of the Avon Longitudinal Study of Parents and Children with routinely collected child health records within 2 months of the clinic date at age 4 (n = 345), 8 (n = 1051), 12 (n = 139), 18 (n = 649), 25 (n = 183), and 43 months (n = 123). To adjust for age differences at measurement, growth data were converted into standard deviation scores using the UK 1990 growth reference. RESULTS: Mean weight standard deviation score (SDS) differences were < or =0.08, with mean predicted differences < or =0.1 kg (eg, mean predicted difference at 8 months -0.011 kg, 95% level of agreement -0.64 to 0.62 kg). Mean height SDS differences were < or =0.45, with mean predicted differences < or =0.9 cm (eg, mean predicted difference at 8 months -0.59 cm, 95% level of agreement -3.84 to 2.66 cm). There was indication of lower accuracy at 4 months old (mean predicted height difference at 4 months -0.91 cm, 95% level of agreement -4.61 to 2.79 cm), but this decreased when the age difference between measurements was reduced. Routine measurements slightly overestimated heights of tall children and underestimated those of short children, but otherwise differences were not associated with sex, social class, birth weight, birth length, or maternal anthropometry. CONCLUSION: Routinely collected child health record height/length and weight data are compatible with no systematic bias, at least in children over 8 months old, supporting their use in clinical practice and research.

Current strategies for monitoring men with localised prostate cancer lack a strong evidence base: observational longitudinal study.

BACKGROUND: The UK National Institute for Health and Clinical Excellence (NICE) guidance recommends conservative management of men with 'low-risk' localised prostate cancer, monitoring the disease using prostate-specific antigen (PSA) kinetics and re-biopsy. However, there is little evidence of the changes in PSA level that should alert to the need for clinical re-assessment. METHODS: This study compares the alerts resulting from PSA kinetics and a novel longitudinal reference range approach, which incorporates age-related changes, during the monitoring of 408 men with localised prostate cancer. Men were monitored by regular PSA tests over a mean of 2.9 years, recording when a man's PSA doubling time fell below 2 years, PSA velocity exceeded 2 ng ml(-1) per year, or when his upper 10% reference range was exceeded. RESULTS: Prostate-specific antigen doubling time and PSA velocity alerted a high proportion of men initially but became unresponsive to changes with successive tests. Calculating doubling time using recent PSA measurements reduced the decline in response. The reference range method maintained responsiveness to changes in PSA level throughout the monitoring. CONCLUSION: The increasing unresponsiveness of PSA kinetics is a consequence of the underlying regression model. Novel methods are needed for evaluation in cohorts currently being managed by monitoring. Meanwhile, the NICE guidance should be cautious.

Early life growth and hemostatic factors: the Barry Caerphilly Growth study.

Associations between early life growth trajectories and a range of adult (aged approximately 25 years) hemostatic factors were assessed in the Barry Caerphilly Growth study (N = 517) in South Wales, 1974-1999. Associations of birth weight, birth length, and weight and height velocities during three periods ("immediate": 0-<5 months, "infant": 5 months-<1 year 9 months, and "childhood": 1 year 9 months-5 years) with adult levels of hemostatic factors were assessed. Birth weight was inversely associated with fibrinogen (beta per 1-unit change in z score = -0.08, 95% confidence interval (CI): -0.15, -0.02). Immediate weight velocity was inversely associated with factor VII (beta = -1.88, 95% CI: -3.84, 0.09), factor VIII (beta = -2.58, 95% CI: -4.07, -0.45), and von Willebrand factor antigen (beta = -4.07, 95% CI: -7.25, -0.89). Birth length was inversely associated with fibrinogen (beta = -0.07, 95% CI: -0.14, -0.01). Evidence was weaker for an inverse association of immediate height velocity with factor VIII (beta = -2.16, 95% CI: -4.62, 0.29) and von Willebrand factor antigen (beta = -2.85, 95% CI: -6.52, 0.81). Childhood height velocity was positively associated with D-dimer (ratio of geometric means = 1.11, 95% CI: 1.01, 1.23). Results support the view that the immediate postnatal period may be particularly important, possibly through impaired liver development and/or infection in early life, in determining cardiovascular disease risk.

Establishing normal reference ranges for prostate volume change with age in the population-based Krimpen-study: prediction of future prostate volume in individual men.

BACKGROUND: We aim to establish the normal pattern of prostate volume change with age to provide a baseline from which accelerated prostate growth might be identified in patients with lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH). METHODS: In a community-based study, prostate volume was determined at baseline and after 2.1 and 4.2 years in men without prostate cancer. A bivariate multilevel growth curve model was used to estimate the pattern of change of prostate volume with age. RESULTS: The average percentage increase of total prostate volume and transition zone volume per year of follow-up was 2.2% and 3.5%, respectively. The final model showed that prostate volume was related to age only. The future prostate volume of an individual can be predicted based on his age and known history of prostate volume. The model was also used to calculate time needed for the prostate volume to increase with a certain percentage, for men with different baseline prostate volume values at different ages. CONCLUSIONS: This method establishes normal prostate volume values by age using prostate volume history in men without prostate cancer. The model provides baseline data from which disease progression might be detected.

Relationships between long-term stroke disability, handicap and health-related quality of life.

OBJECTIVES: To estimate levels of disability, handicap and health-related quality of life (HRQOL) up to 3 years after stroke and examine the relationships between these domains. DESIGN: A longitudinal, observational study SETTING: Population-based register of first-ever strokes METHODS: Subjects, registered between 1 January 1995 and 31 December 1997, were assessed at 1 year (n = 490) and 3 years (n = 342) post-stroke for disability [Barthel index (BI)], handicap [Frenchay activity index (FAI)] and HRQOL (SF-36). BI was categorised as severe, moderate, mild and independent (0-9, 10-14, 15-19 and 20); FAI was categorised as inactive, moderately active and very active (0-15, 16-30 and 31-45). SF-36 domains include: Physical Functioning (PF), Role Physical (RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Functioning (SF), Role Emotional (RE) and Mental Health (MH). Physical (PHSS) and Mental Health (MHSS) Summary Scores were computed. RESULTS: at 1 and 3 years, 26.1 and 26.3%, respectively, were disabled (BI < 15); 55 and 51%, respectively, were handicapped (FAI = 0-15); and survivors had low mean PHSS (37.1 and 37.9), but satisfactory mean MHSS (46.6 and 47.7). There was a graded positive relationship between all SF-36 domains and the categories of BI and FAI. Spearman rank correlations were significant between BI and all SF-36 domains at both time points: strong (r > 0.70) with PF, moderate (r = 0.31-0.70) with RP, SF and PHSS, but weak (r < 0.30) with other domains. Correlations between FAI and SF-36 domains were strong with PF, weak with BP, RE and MHSS, and moderate with other domains. CONCLUSIONS: Disability and handicap remain highly prevalent up to 3 years after stroke. Patients' perception of physical health is persistently low, but mental health perception is satisfactory up to 3 years. Due to variable correlations between different HRQOL domains with disability and handicap, it is suggested that disability, handicap and HRQOL should all be assessed to acquire a broader measure of stroke outcome.