A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project.

Background: Randomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion. Methods: We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list. Results: Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool. Conclusions: A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. DESIGN: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. DATA SOURCES: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. STUDY SELECTION: Studies that developed or validated a multivariable covid-19 related prediction model. DATA EXTRACTION: At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). RESULTS: 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. CONCLUSION: Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. SYSTEMATIC REVIEW REGISTRATION: Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Difference between body composition of formula- and breastfed infants at birth.

Breastfeeding may reduce obesity risk, but this association could be confounded by breastfeeding families' characteristics. We investigated if body composition differs at birth among infants who were either exclusively breast- or formula-fed. We hypothesized the two groups would differ in body composition, even at birth, prior to their post-natal feeding experience. Healthy primiparous carrying singleton pregnancy were recruited at 15 weeks' gestation. PEA POD® measured body composition within 72 hours of delivery and infant feeding was prospectively captured. Out of the 1,152 infants recruited, 117 (10.2%) and 239 (20.7%) went on to be either exclusively breast- or formula-fed, respectively. Breastfed infants were heavier at birth, but their percentage fat mass (FM) was lower than that of exclusively formula-fed infants (covariate adjusted ß = -1.91 percentage points of FM; 95% CI -2.82 to -1.01). Differences in intra-uterine exposures, irrespective of early diet, may partly explain an infant's obesity risk.

Predicting 1-Year Mortality in Older Hospitalized Patients: External Validation of the HOMR Model.

OBJECTIVES: Accurate prognostic information can enable patients and physicians to make better healthcare decisions. The Hospital-patient One-year Mortality Risk (HOMR) model accurately predicted mortality risk (concordance [C] statistic = .92) in adult hospitalized patients in a recent study in North America. We evaluated the performance of the HOMR model in a population of older inpatients in a large teaching hospital in Ireland. DESIGN: Retrospective cohort study. SETTING: Acute hospital. PARTICIPANTS: Patients aged 65 years or older cared for by inpatient geriatric medicine services from January 1, 2013, to March 6, 2015 (n = 1654). After excluding those who died during the index hospitalization (n = 206) and those with missing data (n = 39), the analytical sample included 1409 patients. MEASUREMENTS: Administrative data and information abstracted from hospital discharge reports were used to determine covariate values for each patient. One-year mortality was determined from the hospital information system, local registries, or by contacting the patient's general practitioner. The linear predictor for each patient was calculated, and performance of the model was evaluated in terms of its overall performance, discrimination, and calibration. Recalibrated and revised models were also estimated and evaluated. RESULTS: One-year mortality rate after hospital discharge in this patient cohort was 18.6%. The unadjusted HOMR model had good discrimination (C statistic = .78; 95% confidence interval = .76-.81) but was poorly calibrated and consistently overestimated mortality prediction. The model's performance was modestly improved by recalibration and revision (optimism corrected C statistic = .8). CONCLUSION: The superior discriminative performance of the HOMR model reported previously was substantially attenuated in its application to our cohort of older hospitalized patients, who represent a specific subset of the original derivation cohort. Updating methods improved its performance in our cohort, but further validation, refinement, and clinical impact studies are required before use in routine clinical practice. J Am Geriatr Soc 1-6, 2019.

Comparative Models of Biological and Social Pathways to Predict Child Growth through Age 2 Years from Birth Cohorts in Brazil, India, the Philippines, and South Africa.

Background: Early growth faltering accounts for one-third of child deaths, and adversely impacts the health and human capital of surviving children. Social as well as biological factors contribute to growth faltering, but their relative strength and interrelations in different contexts have not been fully described. Objective: The aim of this study was to use structural equation modelling to explore social and biological multidetermination of child height at age 2 y in longitudinal data from 4 birth cohort studies in low- and middle-income countries. Methods: We analyzed data from 13,824 participants in birth cohort studies in Brazil, India, the Philippines, and South Africa. We used exploratory structural equation models, with height-for-age at 24 mo as the outcome to derive factors, and path analysis to estimate relations among a wide set of social and biological variables common to the 4 sites. Results: The prevalence of stunting at 24 mo ranged from 14.0% in Brazil to 67.7% in the Philippines. Maternal height and birthweight were strongly predictive of height-for-age at 24 mo in all 4 sites (all P values <0.001). Three social-environmental factors, which we characterized as "child circumstances," "family socioeconomic status," and "community facilities," were identified in all sites. Each social-environmental factor was also strongly predictive of height-for-age at 24 mo (all P values <0.001), with some relations partly mediated through birthweight. The biological pathways accounted for 59% of the total explained variance and the social-environmental pathways accounted for 41%. The resulting path coefficients were broadly similar across the 4 sites. Conclusions: Early child growth faltering is determined by both biological and social factors. Maternal height, itself a marker of intergenerational deprivation, strongly influences child height at 2 y, including indirect effects through birthweight and social factors. However, concurrent social factors, many of which are modifiable, directly and indirectly contribute to child growth. This study highlights opportunities for interventions that address both biological and social determinants over the long and short term.

Associations between maternal lifestyle factors and neonatal body composition in the Screening for Pregnancy Endpoints (Cork) cohort study.

Background: Neonatal body composition likely mediates fetal influences on life long chronic disease risk. A better understanding of how maternal lifestyle is related to newborn body composition could thus inform intervention efforts. Methods: Using Cork participant data (n = 1754) from the Screening for Pregnancy Endpoints (SCOPE) cohort study [ECM5(10)05/02/08], we estimated how pre-pregnancy body size, gestational weight gain, exercise, alcohol, smoking and diet were related to neonatal fat and fat-free mass, as well as length and gestational age at birth, using quantile regression. Maternal factors were measured by a trained research midwife at 15 gestational weeks, in addition to a 3rd trimester weight measurement used to calculate weight gain. Infant body composition was measured using air-displacement plethysmography. Results: Healthy (versus excess) gestational weight gain was associated with lower median fat-free mass [-112 g, 95% confidence interval (CI): -47 to -176) and fat mass (-33 g, 95% CI: -1 to -65) in the offspring; and a 103 g decrease in the 95th centile of fat mass (95% CI: -33 to -174). Maternal normal weight status (versus obesity) was associated with lower median fat mass (-48 g, 95% CI: -12 to -84). At the highest centiles, fat mass was lower among infants of women who engaged in frequent moderate-intensity exercise early in the pregnancy (-92 g at the 95th centile, 95% CI: -168 to -16). Lastly, women who never smoked tended to have longer babies with more fat mass and fat-free mass. No other lifestyle factors were strongly related to infant body composition. Conclusions: These results suggest that supporting healthy maternal lifestyles could reduce the risk of excess fat accumulation in the offspring, without adversely affecting fat-free mass development, length or gestational age.

Positive lifestyle changes around the time of pregnancy: a cross-sectional study.

OBJECTIVES: To examine the prevalence of positive lifestyle behaviours before and during pregnancy in Ireland. DESIGN: Cross-sectional study. SETTING: Population-based study in Ireland. PARTICIPANTS: A total of 718 women of predominantly Caucasian origin from the Pregnancy Risk Assessment Monitoring System (PRAMS), Ireland, were included. PRIMARY AND SECONDARY OUTCOME MEASURES: Positive lifestyle behaviour changes before and during pregnancy in Ireland on alcohol consumption, smoking, folate use and nutrition. RESULTS: Of 1212 women surveyed, 718 (59%) responded. 26% were adherent to all three recommendations on alcohol consumption, smoking and folate use before pregnancy. This increased to 39% for the same three behaviours during pregnancy, with greater increases in adherence observed among women with the lowest adherence before pregnancy. Age, education and ethnicity gaps in adherence before pregnancy appeared to narrow during pregnancy. Adherence to all seven food pyramid guidelines was less than 1% overall, and less than 1% of participants met all four micronutrient guidelines on vitamin D, folate, calcium and iron intake around the time of pregnancy. CONCLUSIONS: Low levels of healthy lifestyle behaviours before pregnancy and low levels of positive lifestyle behaviours during pregnancy demonstrate an urgent need for increased clinical and public health efforts to target deleterious health behaviours before, during and after pregnancy.

A person-centred analysis of the time-use, daily activities and health-related quality of life of Irish school-going late adolescents.

PURPOSE: The health, well-being and quality of life of the world's 1.2 billion adolescents are global priorities. A focus on their patterns or profiles of time-use and how these relate to health-related quality of life (HRQoL) may help to enhance their well-being and address the increasing burden of non-communicable diseases in adulthood. This study sought to establish whether distinct profiles of adolescent 24-h time-use exist and to examine the relationship of any identified profiles to self-reported HRQoL. METHOD: This cross-sectional study gathered data from a random sample of 731 adolescents (response rate 52%) from 28 schools (response rate 76%) across Cork city and county. A person-centred approach, latent profile analysis, was used to examine adolescent 24-h time-use and relate the identified profiles to HRQoL. RESULTS: Three male profiles emerged, namely productive, high leisure and all-rounder. Two female profiles, higher study/lower leisure and moderate study/higher leisure, were identified. The quantitative and qualitative differences in male and female profiles support the gendered nature of adolescent time-use. No unifying trends emerged in the analysis of probable responses in the HRQoL domains across profiles. Females in the moderate study/higher leisure group were twice as likely to have above-average global HRQoL. CONCLUSION: Distinct time-use profiles can be identified amongst adolescents, but their relationship with HRQoL is complex. Rich mixed-method research is required to illuminate our understanding of how quantities and qualities of time-use shape lifestyle patterns and how these can enhance the HRQoL of adolescents in the twenty-first century.

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort.

OBJECTIVE: Data-driven approaches to dietary patterns are under-utilized; latent class analyses (LCA) are particularly rare. The present study used an LCA to identify subgroups of people with similar dietary patterns, explore changes in dietary patterns over a 10-year period and relate these dynamics to sociodemographic factors and health outcomes. DESIGN: The 1998 baseline and 2008 follow-up of the Cork and Kerry Diabetes and Heart Disease Study. Diets were assessed with a standard FFQ. LCA, under the assumption of conditional independence, was used to identify mutually exclusive subgroups with different dietary patterns, based on food group consumption. SETTING: Republic of Ireland. SUBJECTS: Men and women aged 50-69 years at baseline (n 923) and at 10-year follow-up (n 320). RESULTS: Three dietary classes emerged: Western, Healthy and Low-Energy. Significant differences in demographic, lifestyle and health outcomes were associated with class membership. Between baseline and follow-up most people remained 'stable' in their dietary class. Most of those who changed class moved to the Healthy class. Higher education was associated with transition to a healthy diet; lower education was associated with stability in an unhealthy pattern. Transition to a healthy diet was associated with higher CVD risk factors at baseline: respondents were significantly more likely to be smokers, centrally obese and to have hypertension (non-significant). CONCLUSIONS: LCA is useful for exploring dietary patterns transitions. Understanding the predictors of longitudinal stability/transitions in dietary patterns will help target public health initiatives by identifying subgroups most/least likely to change and most/least likely to sustain a change.

Associations of linear growth and relative weight gain during early life with adult health and human capital in countries of low and middle income: findings from five birth cohort studies.

BACKGROUND: Fast weight gain and linear growth in children in low-income and middle-income countries are associated with enhanced survival and improved cognitive development, but might increase risk of obesity and related adult cardiometabolic diseases. We investigated how linear growth and relative weight gain during infancy and childhood are related to health and human capital outcomes in young adults. METHODS: We used data from five prospective birth cohort studies from Brazil, Guatemala, India, the Philippines, and South Africa. We investigated body-mass index, systolic and diastolic blood pressure, plasma glucose concentration, height, years of attained schooling, and related categorical indicators of adverse outcomes in young adults. With linear and logistic regression models, we assessed how these outcomes relate to birthweight and to statistically independent measures representing linear growth and weight gain independent of linear growth (relative weight gain) in three age periods: 0-2 years, 2 years to mid-childhood, and mid-childhood to adulthood. FINDINGS: We obtained data for 8362 participants who had at least one adult outcome of interest. A higher birthweight was consistently associated with an adult body-mass index of greater than 25 kg/m(2) (odds ratio 1·28, 95% CI 1·21-1·35) and a reduced likelihood of short adult stature (0·49, 0·44-0·54) and of not completing secondary school (0·82, 0·78-0·87). Faster linear growth was strongly associated with a reduced risk of short adult stature (age 2 years: 0·23, 0·20-0·52; mid-childhood: 0·39, 0·36-0·43) and of not completing secondary school (age 2 years: 0·74, 0·67-0·78; mid-childhood: 0·87, 0·83-0·92), but did raise the likelihood of overweight (age 2 years: 1·24, 1·17-1·31; mid-childhood: 1·12, 1·06-1·18) and elevated blood pressure (age 2 years: 1·12, 1·06-1·19; mid-childhood: 1·07, 1·01-1·13). Faster relative weight gain was associated with an increased risk of adult overweight (age 2 years: 1·51, 1·43-1·60; mid-childhood: 1·76, 1·69-1·91) and elevated blood pressure (age 2 years: 1·07, 1·01-1·13; mid-childhood: 1·22, 1·15-1·30). Linear growth and relative weight gain were not associated with dysglycaemia, but a higher birthweight was associated with decreased risk of the disorder (0·89, 0·81-0·98). INTERPRETATION: Interventions in countries of low and middle income to increase birthweight and linear growth during the first 2 years of life are likely to result in substantial gains in height and schooling and give some protection from adult chronic disease risk factors, with few adverse trade-offs. FUNDING: Wellcome Trust and Bill & Melinda Gates Foundation.

Associations between multiple indicators of socioeconomic status and obesity in young adult Filipinos vary by gender, urbanicity, and indicator used.

More research is needed on the socio-environmental determinants of obesity in lower- and middle-income countries. We used generalized estimating equations to evaluate the cross-sectional effect of urban residence and multiple individual-level indicators of socioeconomic status (SES) on the odds of overweight or central adiposity in a birth cohort of young adult (mean age 21.5 y) Filipino males (n = 987) and females (n = 819) enrolled in the Cebu Longitudinal Health and Nutrition Survey. Overweight was defined as BMI >/=25 kg/m(2) and central adiposity was defined as a waist circumference >85 cm for males or >80 cm for females. Community-level urbanicity was measured on a continuous scale. Multiple indicators of SES included assets, income, education, and marital status. In the final multivariable models, assets and being married were positively related to overweight and central adiposity in males (P < 0.05), but being married was the only predictor of these outcomes in females. However, once the modifying effects of urban residence were accounted for, assets were positively related to overweight and central adiposity among the most rural women, but not in more urban women. Our results are consistent with a growing body of literature that suggests the relationship between SES and obesity is positive in lower-income contexts and inverse in higher-income contexts, particularly in females. The pattern of relationships we observed suggests that as the Philippines continues to develop economically, the public health impact of obesity will increase similarly to what has been observed in countries further along in their economic transition.

Practical application of the vanishing tetrad test for causal indicator measurement models: an example from health-related quality of life.

Researchers are often faced with the task of trying to measure abstract concepts. The most common approach is to use multiple indicators that reflect an underlying latent variable. However, this 'effect indicator' measurement model is not always appropriate; sometimes the indicators instead cause the construct of interest. While the notion of 'causal indicators' has been known for some time, it is still too often ignored. However, there are limited means to determine whether a possible indicator should be treated as a cause or an effect of the latent construct of interest. Perhaps the best empirical way is to use the vanishing tetrad test (VTT), yet this method is still often overlooked. We speculate that one reason for this is the lack of published examples of its use in practice, written for an audience without extensive statistical training. The goal of this paper was to help fill this gap in the literature-to provide a basic example of how to use the VTT. We illustrated the VTT by looking at multiple items from a health related quality of life instrument that seem more likely to cause the latent variable rather than the other way around.

Size at birth, weight gain in infancy and childhood, and adult blood pressure in 5 low- and middle-income-country cohorts: when does weight gain matter?

BACKGROUND: Promoting catch-up growth in malnourished children has health benefits, but recent evidence suggests that accelerated child weight gain increases adult chronic disease risk. OBJECTIVE: We aimed to determine how birth weight (BW) and weight gain to midchildhood relate to blood pressure (BP) in young adults. DESIGN: We pooled data from birth cohorts in Brazil, Guatemala, India, the Philippines, and South Africa. We used conditional weight (CW), a residual of current weight regressed on prior weights, to represent deviations from expected weight gain from 0 to 12, 12 to 24, 24 to 48 mo, and 48 mo to adulthood. Adult BP and risk of prehypertension or hypertension (P/HTN) were modeled before and after adjustment for adult body mass index (BMI) and height. Interactions of CWs with small size-for-gestational age (SGA) at birth were tested. RESULTS: Higher CWs were associated with increased BP and odds of P/HTN, with coefficients proportional to the contribution of each CW to adult BMI. Adjusted for adult height and BMI, no child CW was associated with adult BP, but 1 SD of BW was related to a 0.5-mm Hg lower systolic BP and a 9% lower odds of P/HTN. BW and CW associations with systolic BP and P/HTN were not different between adults born SGA and those with normal BW, but higher CW at 48 mo was associated with higher diastolic BP in those born SGA. CONCLUSIONS: Greater weight gain at any age relates to elevated adult BP, but faster weight gains in infancy and young childhood do not pose a higher risk than do gains at other ages.

Quantifying the urban environment: a scale measure of urbanicity outperforms the urban-rural dichotomy

The rapid urbanization of the developing world has important consequences for human health. Although several authorities have called for better research on the relationships between urbanicity and health, most researchers still use a poor measurement of urbanicity, the urban-rural dichotomy. Our goal was to construct a scale of urbanicity using community level data from the Cebu Longitudinal Health and Nutrition Survey. We used established scale development methods to validate the new measure and tested its performance against the dichotomy. The new scale illustrated communities and across time, that were not apparent before. Furthermore, using a continuous measure of urbanicity allowed for better illustrations of the relationships between urbanicity and health. The new scale is a better measure of urbanicity then the traditionally used urban-rural dichotomy. (AU)

Quantifying the urban environment: a scale measure of urbanicity outperforms the urban-rural dichotomy.

The rapid urbanization of the developing world has important consequences for human health. Although several authorities have called for better research on the relationships between urbanicity and health, most researchers still use a poor measurement of urbanicity, the urban-rural dichotomy. Our goal was to construct a scale of urbanicity using community level data from the Cebu Longitudinal Health and Nutrition Survey. We used established scale development methods to validate the new measure and tested its performance against the dichotomy. The new scale illustrated misclassification by the urban-rural dichotomy, and was able to detect differences in urbanicity, both between communities and across time, that were not apparent before. Furthermore, using a continuous measure of urbanicity allowed for better illustrations of the relationships between urbanicity and health. The new scale is a better measure of urbanicity than the traditionally used urban-rural dichotomy.