Mohammod Mostazir

A multilevel analysis of the determinants of high-risk sexual behaviour in sub-Saharan Africa.

A number of authors have identified multiple concurrent sexual partnerships by both men and women to lie at the root of the HIV/AIDS epidemic in sub-Saharan Africa. This study applies multilevel models to Demographic and Health Survey data collected during 2003-2008 in 20 sub-Saharan African countries to examine the influence of social and cultural context on involvement with multiple sexual partnerships in the region, above and beyond the effects of individual characteristics. The findings provide support for the ecological argument that health behaviours are shaped and determined by societal conditions, in addition to the effects of individual and household characteristics. Involvement with multiple sex partners is most prevalent in societies in which sexual norms are widely permissive and where polygyny is common. Individual autonomy is substantial and attitudes towards sexuality are more liberal among men and women who live in communities in which sexual norms are widely permissive. Men and women who are most likely to have multiple sex partners in the sub-Saharan region are those who initiated sexual activity earlier and those who have the individual attributes (e.g. young age, urban residence, education, media exposure and working for cash and away from home) that bring to them more rights and/or decision-making autonomy, but not necessarily more financial resources and economic security (mostly among women). On the other hand, involvement with multiple partners is determined by cultural norms (i.e. permissive sexual norms) and social change (i.e. mass education, expansion of cash employment). The findings suggest a number of opportunities for more effective policy and programmatic responses to curb the prevalence of multiple partnerships in sub-Saharan Africa.

Childhood obesity: evidence for distinct early and late environmental determinants a 12-year longitudinal cohort study (EarlyBird 62)

Background/objective:The prevalence of childhood obesity continues to rise in most countries, but the exposures responsible remain unclear. The shape of the body mass index (BMI) distribution curve defines how a population responds, and can be described by its three parameters—skew (L), median (M) and variance (S). We used LMS analysis to explore differences in the BMI trajectories of contemporary UK children with those of 25 years ago, and to draw inferences on the exposures responsible.Subjects/methods:We applied Cole’s LMS method to compare the BMI trajectories of 307 UK children (EarlyBird cohort) measured annually from 5–16 years (2000–2012) with those of the BMI data set used to construct the UK 1990 growth centiles, and used group-based trajectory modelling (GBTM) to establish whether categorical trajectories emerged.Results:Gender-specific birth weights were normally distributed and similar between both data sets. The skew and variance established by 5 years in the 1990 children remained stable during the remainder of their childhood, but the pattern was different for children 25 years on. The skew at 5 years among the EarlyBird children was greatly exaggerated, and involved selectively the offspring of obese parents, but returned to 1990 levels by puberty. As the skew diminished, so the variance in BMI rose sharply. The median BMI of the EarlyBird children differed little from that of 1990 before puberty, but diverged from it as the variance rose. GBTM uncovered four groups with distinct trajectories, which were related to parental obesity.Conclusions:There appear to be two distinct environmental interactions with body mass among contemporary children, the one operating selectively according to parental BMI during early childhood, the second more generally in puberty.

Gender‐assortative waist circumference in mother–daughter and father–son pairs, and its implications. An 11‐year longitudinal study in children (EarlyBird 59)

Body mass index (BMI) is gender assortative (mother–daughter, father–son) in contemporary families. The impact of obesity on the metabolic health of contemporary children is nevertheless a correlate of their own weight, not that of their parents. Waist circumference (WC; abdominal fat) is a better predictor of metabolic risk than BMI. Abdominal fat has two components – visceral, which increases metabolic risk, and subcutaneous, which is neutral or even protects.

Exercise to preserve β‐cell function in recent‐onset Type 1 diabetes mellitus (EXTOD) – a randomized controlled pilot trial

Residual β‐cell function is present at the time of diagnosis with Type 1 diabetes. Preserving this β‐cell function reduces complications. We hypothesized that exercise preserves β‐cell function in Type 1 diabetes and undertook a pilot trial to address the key uncertainties in designing a definitive trial to test this hypothesis.

Evidence for energy conservation during pubertal growth. A 10-year longitudinal study (EarlyBird 71)

Background:Diabetes is closely linked to obesity, and obesity rates climb during adolescence for reasons that are not clear. Energy efficiency is important to obesity, and we describe a temporary but substantial fall in absolute energy expenditure, compatible with improved energy efficiency, during the rapid growth phase of puberty.Methods:In a longitudinal cohort study lasting 10 years, we measured voluntary energy expenditure as physical activity (PA) by accelerometry, involuntary energy expenditure as resting energy expenditure (REE) by oxygen consumption, body mass index (BMI) and body composition by dual energy X-ray absorptiometry annually on 10 occasions from 7 to 16 years in the 347 children of the EarlyBird study. We used mixed effects modelling to analyse the trends in REE and their relationship to BMI, lean mass (LM), fat mass (FM), age, PA and pubertal stage.Results:Relative REE and total PA fell during puberty, as previously described, but the longitudinal data and narrow age-range of the cohort (s.d.±4m) revealed for the first time a substantial fall in absolute REE during the period of maximum growth. The fall became clearer still when adjusted for FM and LM. The fall could not be explained by fasting insulin, adiponectin, leptin, luteinising hormone or follicle stimulating hormone.Conclusions:There appears to be a temporary but substantial reduction in energy expenditure during puberty, which is unrelated to changes in body composition. If it means higher energy efficiency, the fall in REE could be advantageous in an evolutionary context to delivering the extra energy needed for pubertal growth, but unfavourable to weight gain in a contemporary environment.

Four biomechanical and anthropometric measures predict tibial stress fracture: A prospective study of 1065 Royal Marines

Background Tibial stress fractures (TSFs) cause a significant burden to Royal Marines recruits. No prospective running gait analyses have previously been performed in military settings. Aim We aimed to identify biomechanical gait factors and anthropometric variables associated with increased risk of TSF. Methods 1065 Royal Marines recruits were assessed in week 2 of training. Bilateral plantar pressure and three-dimensional lower limb kinematics were obtained for barefoot running at 3.6 m/s, providing dynamic arch index, peak heel pressure and lower limb joint angles. Age, bimalleolar breadth, calf girth, passive hip internal/external range of motion and body mass index (BMI) were also recorded. 10 recruits who sustained a TSF during training were compared with 120 recruits who completed training injury-free using a binary logistic regression model to identify injury risk factors. Results 4 variables significantly (p<0.05) predicted increased risk of TSF (ORs and 95% CI): smaller bimalleolar width (0.73, 0.58 to 0.93), lower BMI (0.56, 0.33 to 0.95), greater peak heel pressure (1.25, 1.07 to 1.46) and lower range of tibial rotation (0.78, 0.63 to 0.96). Summary Reduced impact attenuation and ability to withstand load were implicated in tibial stress fracture risk.

Proinsulin is stable at room temperature for 24 hours in EDTA: A clinical laboratory analysis (adAPT 3).

Aims Reference laboratories advise immediate separation and freezing of samples for the assay of proinsulin, which limit its practicability for smaller centres. Following the demonstration that insulin and C-peptide are stable in EDTA at room temperature for at least 24hours, we undertook simple stability studies to establish whether the same might apply to proinsulin. Methods Venous blood samples were drawn from six adult women, some fasting, some not, aliquoted and assayed immediately and after storage at either 4°C or ambient temperature for periods from 2h to 24h. Results There was no significant variation or difference with storage time or storage condition in either individual or group analysis. Conclusion Proinsulin appears to be stable at room temperature in EDTA for at least 24h. Immediate separation and storage on ice of samples for proinsulin assay is not necessary, which will simplify sample transport, particularly for multicentre trials.

Generational change in fasting glucose and insulin among children at ages 5-16y: Modelled on the EarlyBird study (2015) and UK growth standards (1990) (EarlyBird 69)

AIM Pre-diabetes is a state of beta-cell stress caused by excess demand for insulin. Body mass is an important determinant of insulin demand, and BMI has risen substantially over recent time. We sought to model changes in the parameters of glucose control against rising BMI over the past 25years. METHODS Using random coefficient mixed models, we established the correlations between HbA1C, fasting glucose, fasting insulin, HOMA2-IR and BMI in contemporary (2015) children (N=307) at ages 5-16y from the EarlyBird study, and modelled their corresponding values 25years ago according to the distribution of BMI in the UK Growth Standards (1990). RESULTS There was little change in HbA1C or fasting glucose over the 25y period at any age or in either gender. On the other hand, the estimates for fasting insulin and HOMA2-IR were substantially higher in both genders in 2015 compared with 1990. CONCLUSION Insofar as it is determined by body mass, there has been a substantial rise in beta cell demand among children over the past 25years. The change could be detected by fasting insulin and HOMA2-IR, but not by fasting glucose or HbA1C.

Prospective study of biomechanical risk factors for second and third metatarsal stress fractures in military recruits

OBJECTIVES This prospective study investigated anatomical and biomechanical risk factors for second and third metatarsal stress fractures in military recruits during training. DESIGN Prospective cohort study. METHODS Anatomical and biomechanical measures were taken for 1065 Royal Marines recruits at the start of training when injury-free. Data included passive range of ankle dorsi-flexion, dynamic peak ankle dorsi-flexion and plantar pressures during barefoot running. Separate univariate regression models were developed to identify differences between recruits who developed second (n=7) or third (n=14) metatarsal stress fracture and a cohort of recruits completing training with no injury (n=150) (p<0.05). A multinomial logistic regression model was developed to predict the risk of injury for the two sites compared with the no-injury group. Multinomial logistic regression results were back transformed from log scale and presented in Relative Risk Ratios (RRR) with 95% confidence intervals (CI). RESULTS Lower dynamic arch index (high arch) (RRR: 0.75, CI: 0.63-0.89, p<0.01) and lower foot abduction (RRR: 0.87, CI: 0.80-0.96, p<0.01) were identified as increasing risk for second metatarsal stress fracture, while younger age (RRR: 0.78, CI: 0.61-0.99, p<0.05) and later peak pressure at the second metatarsal head area (RRR: 1.19, CI: 1.04-1.35, p<0.01) were identified as risk factors for third metatarsal stress fracture. CONCLUSIONS For second metatarsal stress fracture, aspects of foot type have been identified as influencing injury risk. For third metatarsal stress fracture, a delayed forefoot loading increases injury risk. Identification of these different injury mechanisms can inform development of interventions for treatment and prevention.